AI & Technology

Less Talk More Action on Scale Ups

The House of Lords recently debated the conclusions and recommendations of the Report from the Communications and Digital Committee AI and creative technology scaleups: less talk, more action

This is an edited version what I said in winding up the debate or the Liberal Democrats

The noble Baroness, Lady Kidron, mentioned the holistic nature of the report—the fact that it was both AI and creative tech. That is really powerful and has enabled us to have an excellent debate today. I agree that this debate should be required reading. We have covered a huge amount of ground.

The phrase “incubator economy” really has stuck. It has helped to guide us through today’s debate and made the contributions that much sharper and more relevant. We are great at hatching ideas but also at watching them fly away to mature elsewhere. We can illustrate this with a number of examples, as noble Lords have done. When ARM chose to list in New York rather than London, we lost what would now be Britain’s fifth-biggest company. When companies such as Wise follow the same path, which it recently has done, the pattern becomes clear. This was epitomised by a City AM headline on Tuesday:

“Ouch: Three tech firms bail out of the UK in a single day”.

Many noble Lords have of course mentioned Alphawave, Spectris and Oxford Ionics—at the beginning of London Tech Week too; what an appalling time to have that news. This is of long standing, in terms of DeepMind and Solexa as well. The consequences of this failure are significant: decreased global competitiveness, weaker economic prospects and a potential brain drain of talent..

The Government are putting great faith into AI adoption with the AI opportunities action plan and an industrial strategy with plans for eight growth-driving sectors, but, at the same time, we must break down a number of barriers that are holding us back. First, as we have heard from across the House, we have a significant funding gap for later-stage rounds compared to the US, which was called, very graphically, the “valley of death” by Lady Wheatcroft. As we have heard, UK pension funds manage over £3 trillion of assets yet invest barely a fraction of that in growing domestic companies.

We do have initiatives, such as the Long-term Investment for Technology and Science programme, and the British Business Bank has supported many UK unicorns. UKI2S, a public/private seed fund, has a proven track record, but the size of the funding gap remains immense. There is also a recognised lack of technology expertise among institutional investors and, probably among pension funds as well.

We are in a global technology race. Some 62% of UK AI firms identify skills shortages as a growth barrier. We are in fierce global competition for AI talent and our visa system is slow, laborious and costly. SMEs often cannot match big tech salaries and, although the scale-up visa exists, industry leaders say that it is not yet fast or cheap enough to meet the needs of rapidly growing businesses, especially in highly competitive fields like AI.

We have infrastructure issues too. As we heard from the committee, the withdrawal by this Government at the outset of £1.3 billion for AI infrastructure, including the Edinburgh supercomputer, sent exactly the wrong signal. As one witness to the committee put it, we have

“some really big gaps in infrastructure, compute and power”.

We also have the issue of regulation and procurement. Government procurement rules prevent smaller companies competing for government contracts despite government procurement being a potential driver of innovation. The committee heard that the Competition and Markets Authority is alleged to be harsh on internal roll-ups, where one British company proposes acquiring another British company.

What needs to happen now? Again, I thought the phrase “a manageable challenge” from Lord Willetts, was very useful. I also rather liked his "Hamiltonian" versus "Jeffersonian" approach. On capital, the National Wealth Fund’s £7.3 billion commitment is a start, but we need those resources deployed quickly and strategically. The Government are, it seems, taking action to unlock £75 billion through the Mansion House accord and have introduced pension fund reforms, but these will take several years to have meaningful impact.

I know that the Government listen to the Tony Blair Institute. Its recent report recommends giving the British Business Bank and the National Wealth Fund

“clear, complementary mandates to deliver on the … government’s industrial strategy”.

Specifically, it says that the British Business Bank should focus on crowding in capital for the scale-up phase—series B to C—with its maximum investment cap raised to £25 million. Meanwhile, the NWF should act as a more capital-intensive direct investor, with a minimum investment of £25 million for late-stage—series D+—strategic assets. Can the Minister comment on the progress being made in defining the roles of those two institutions? The discussion from Lord Massey, about capital gains tax in terms of AIM stocks was a very interesting suggestion.

The AI Opportunities Action Plan also stresses investment in talent. It explicitly recommends that the Government explore how best to address wider barriers, such as the cost and complexity of visas, which create obstacles for start-ups and deter overseas talent from relocating to the UK. We need a fast-track visa system for scale-ups now, not after another consultation. However, I accept the concerns of the Lord Tarassenko, that there is a falling number of UK entrants to courses.

On infrastructure, I welcome the £2 billion commitment in the spending review, and the Government’s promise to immediately double AI research capacity and launch AI growth zones for data centres. The compute strategy, promised for spring 2025, is already overdue and must deliver accessible resources to our universities, start-ups and scale-ups as soon as possible. However, I also accept the reservations of the noble Lord, Lord Tarassenko: we do not want to find ourselves investing in infrastructure when we can deliver what we need without the extent of that infrastructure, as DeepSeek demonstrated.

AI growth zones are being launched to accelerate data centre construction and infrastructure, with formal selection processes opening this spring, we understand. However, we need to tackle the environmental issues around them too. The noble Lord, Lord Hamilton—who is in his place, I notice—was absolutely right to raise that issue.

In order to scale up, start-ups need to overcome the diffusion problem, which refers to the challenge of achieving widespread adoption and market penetration for their innovations. This is impacted by a lack of access to digital platforms, which have quasi-monopoly positions. I am glad to say that Google and Apple are now under investigation by the CMA, and the outcome will be the acid test for whether the new digital markets regime results in access remedies that allow our start-ups to scale more easily.

On regulation, the Regulatory Innovation Office, under its very welcome new chair, the noble Lord, Lord Willetts, is promising, as part of its mission, to reduce red tape and help companies bring new products to market faster, but it must have teeth. Given that the AI Opportunities Action Plan aims to accelerate the adoption of safe and trustworthy AI across the economy, clarity, certainty and consistency of AI regulation for business is crucial. The Government have kicked a future AI Bill into longer, if not wholly long, grass. They talk of a sector-led, outcomes-based approach to AI regulation, but many of us have seen no detail of any proposals and believe that the minimalist approach being adopted is simply inadequate in the face of AI risks and the need for public trust. Good, outcome-based regulation is not the enemy of innovation. In fact, it can be the creator of interoperability and the driver of innovation.

We have discussed constantly, for what seems like several months, a significant issue for creatives: the use of copyright content for training AI models. I do not intend to say too much about this, but the Minister is only too well aware of the arguments being made. Given the Government’s recent failure to deliver clarity to the creative industries, the consultation on AI and copyright, the associated economic impact assessment and the technology report must provide clarity quickly, as must the working parties. Our creative industries must have the transparency they need to ensure that they can thrive alongside the tech industries without being their victim. Where is the creative industries sector plan? Everything seems to be promised for late spring—I think we have a traffic jam somewhere in Whitehall. It will identify growth barriers, we understand, and outline commitments from the Government and industry to overcome them.

I have little time left. I share the reservations about the National Data Library, but also the promise associated with it, expressed by Lord Tarassenko, and the noble Baroness, Lady Kidron. It could be a good sovereign asset vehicle, if it takes the right shape.

The committee’s report is entitled AI and Creative Technology Scaleups: Less Talk, More Action. It is not just a good title; it is an urgent instruction. Are the Government ready to match ambition with action? I very much look forward to the Minister’s reply but, as Lord Holmes, said, she has been given much to think about.

by Tim Clement-Jones

AI regulation does not stifle innovation

This is a piece I wrote recently published in the New Statesman's Spotlight on Technology Supplement

Achieving balance between human potential and machines isn’t just possible – it’s necessary.

Ever since co-founding the All-Party Parliamentary Group on AI nine years ago, still ably administered by the Big Innovation Centre, I’ve been deeply involved in debating and advising on the implications of artificial intelligence. My optimism about AI’s potential remains strong – from helping identify new Parkinson’s treatments to DeepMind’s protein structure predictions that could transform drug discovery and personalised medicine.

Yet this technology is unlike anything we’ve seen before. It’s potentially more autonomous, with greater impact on human creativity and employment, and more opaque in its decision-making processes.

The conventional wisdom that regulation stifles innovation needs turning on its head. As AI becomes more powerful and pervasive, appropriate regulation isn’t just about restricting harmful practices – it’s key to driving widespread adoption and sustainable growth. Many potential AI adopters are hesitating not due to technological limitations but to uncertainties about liability, ethical boundaries and public acceptance. Clear regulatory frameworks addressing algorithmic bias, data privacy and decision transparency can actually accelerate adoption by providing clarity and confidence.

Different jurisdictions are adopting varied approaches. The European Union’s AI Act, with its risk-based framework, started coming into effect this year. Singapore has established comprehensive AI governance through its model AI governance framework. Even China regulates public-facing generative AI models with fairly heavy inspection regimes.

The UK’s approach has been more cautious. The previous government held the AI Safety Summit at Bletchley Park and established the AI Safety Institute (now inexplicably renamed the AI Security Institute), but with no regulatory teeth. The current government has committed to binding regulation for companies developing the most powerful AI models, though progress remains slower than hoped. Notably, 60 countries – including Saudi Arabia and the UAE, but not Britain or the US – signed the Paris AI Action Summit declaration in February this year, committing to ensuring AI is “open, inclusive, transparent, ethical, safe, secure and trustworthy”.

Several critical issues demand urgent attention.

Intellectual property: the use of copyrighted material for training large language models without licensing has sparked substantial litigation and, in the UK, unprecedented parliamentary debate. Governments need to act decisively to ensure creative works aren’t ingested into generative AI models without return to rights-holders, with transparency duties on developers.

Digital citizenship: we must equip citizens for the AI age, ensuring they understand how their data is used and AI’s ethical implications. Beyond the UAE, Finland and Estonia, few governments are taking this seriously enough.

International convergence: despite differing regulatory regimes, we need developers to collaborate and commercialise innovations globally while ensuring consumer trust in common international ethical and safety standards.

Well-designed regulation can be a catalyst for AI adoption and innovation. Just as environmental regulations spurred cleaner technologies, AI regulations focusing on explainability and fairness could push developers toward more sophisticated, responsible systems.

The goal isn’t whether to regulate AI, but how to regulate it promoting both innovation and responsibility. We need principles-based rather than overly prescriptive regulation, assessing risk and emphasising transparency and accountability without stifling creativity.

Achieving the balance between human potential and machine innovation isn’t just possible – it’s necessary as we step into an increasingly AI-driven world. That’s what we must make a reality.

by Tim Clement-Jones

The new Council of Europe AI Framework Convention demonstrates that the principles of the European Convention on Human Rights are still highly relevant after 75 years

I recently took part in a debate in the House of Lords celebrating the 75th Anniversary of the European Convention on Human Right. This is what I said about the importance of the new Council of Europe Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law and how it links to the principles and objectives original Convention.

The new Council of Europe framework convention on artificial intelligence is another living demonstration that the principles of the European Convention on Human Rights are still highly relevant after 75 years. The AI framework convention does not seek to replace the ECHR but rather to extend its protections into the digital age. AI now permeates our daily lives, making decisions that affect our privacy, liberty and dignity. These systems can perpetuate discrimination, erode privacy and challenge fundamental freedoms in a way that demands new protections. Open for signature in September 2024, the AI framework convention is the first legally binding international instrument on AI, setting clear standards for risk assessment and impact management throughout the life cycle of AI systems.

The framework convention’s principles require transparency and oversight, ensuring that AI systems cannot operate as black boxes, making decisions that affect people’s lives without accountability. They require parties to adopt specific measures for identifying, assessing, preventing and mitigating risks posed by AI systems, and a specific human rights impact assessment has been developed. The convention recognises that, in the age of AI, protecting human rights requires more than individual remedies; it demands accessible and effective remedies for human rights violations resulting from AI systems. Rather than merely reacting to harms after they occur, the framework mandates consideration of society-scale effects before AI systems are deployed. I only wish, having heard what its director had to say on Tuesday, that our AI Security Institute had the same approach.

The framework convention was achieved through unprecedented consultation, involving not just the 46 member states of the Council of Europe but observer states, civil society, academia and industry representatives. Beyond European nations, it has attracted signatories including Israel, the United States—albeit under the previous Administration—and, most recently, Japan and Canada, in February this year.

However, a framework is only as good as its implementation, and this brings me to my central question to the Government. What is their plan? The Ministry of Justice’s Report to the Joint Committee on Human Rights on the Government’s Response to Human Rights Judgments 2023-24 said:

“Once the treaty is ratified and brought into effect in the UK, existing laws and measures to safeguard human rights from the risks of AI will be enhanced”.

How will existing UK law be amended to align with the framework convention? What additional resources and powers will be given to our regulatory bodies? What mechanisms will be put in place to monitor and assess the impact of AI systems on vulnerable groups? The convention offers us tools to prevent such problems, but only if we implement it effectively.

As we mark 75 years of the European Convention on Human Rights, we should remember that its enduring strength lies not just in its principles but in how nations have given those principles practical effect through domestic law and institutions. The UK has long been a leader in both human rights and technological innovation. I urge the Government to present a comprehensive implementation plan for the AI framework convention. Our response to this challenge will determine whether the digital age enhances or erodes our fundamental rights. I do not need to emphasise the immense power of big tech currently. We need to see this as a time when we are rising to meet new challenges with the same vision and commitment that created the European Convention on Human Rights, 75 years ago.

by Tim Clement-Jones

Empowering Our Communities with Data Intermediaries

I recently responded to the Government's Call for Evidence on Data Intermediaries. I welcome the opportunity to contribute to this important call for evidence which centres around unlocking the value of data whilst exploring mechanisms that facilitate responsible data sharing and at the same time empowering individuals.

Data is increasingly integral to people's lives and fuels most modern business. Citizen data holds tremendous potential for economic and societal benefit through innovative products, improved public services, and research advancements. However, cumulative failures, such as the backlash to both Care.Data and subsequently the General Practice Data for Planning and Research programme, and the response to the Cambridge Analytica scandal, have resulted in tenuous public trust in data sharing. Data misuses, breaches, and sharing scandals highlight the need for models of data stewardship that safeguard privacy while enabling innovation guided by public input. Increased legitimacy and trustworthiness of data and AI use are needed to reverse this trend.

Data intermediaries are broadly defined as entities facilitating data sharing or access between data holders (including individuals exercising their rights) and data users. They act on behalf of or for the benefit of data subjects when dealing with personal data. They can potentially empower individuals to exercise their data subject rights more easily and enable responsible and straightforward sharing of quality data. Data Communities represent a specific proposed model within this landscape, focused on empowering individuals by enabling them to collectively exercise their data rights.

Defining Data Communities and Their Purpose

Attempts were made during the passage of the Data (Use and Access) Bill to define a "data community" as an entity established to activate data subjects’ data rights under Chapters III and VIII of the UK GDPR on their behalf. This concept was part of a proposed set of amendments intended to establish the ability for data subjects to assign their personal data rights to a third party. This would have expressly enabled data subjects to mandate a community to exercise specific rights over designated data, for defined purposes and durations, with respect to specified data controllers—all while retaining ultimate control.

Relationship to Other Data Intermediary Models

Data Communities need to be understood as a specific type of data intermediary or data institution. While related to concepts like data trusts and data cooperatives, Data Communities need to be specifically defined by their function of exercising the individual data subject rights granted under the UK GDPR on behalf of their members They are distinct from, for example, a data trust that might hold legal rights over data assets themselves, or a data cooperative focused on collective ownership or bargaining. The OECD's concept of 'community-based data sharing agreements' appears conceptually related to the aims of Data Communities.

Potential Benefits of Data Communities

The establishment and effective operation of Data Communities will in my view yield many benefits:

•Empowering Data Subjects: Data intermediaries, including Data Communities, have the potential to empower individuals to exercise their data subject rights more easily. This is particularly relevant for rights like data portability, which are currently under-exercised. The collective exercise of rights can provide greater leverage in the data ecosystem.

•Rebalancing Power Asymmetries: By enabling collective action and representation, Data Communities can help rebalance asymmetries of power between individuals and large data controllers, and between technology companies, government and the public.

•Increasing Public Confidence: Involving people through mechanisms like Data Communities can contribute towards increased public confidence in the use of data. This is crucial given the current low levels of public trust.

•Facilitating Responsible Data Sharing: They can facilitate responsible and straightforward sharing of quality data, potentially enabling data use for wider societal gains or public benefit as specified by the community members. Data communities can enable analysis through data access and sharing, supporting areas like public health, innovation in commercially sensitive environments, quality assurance of data/AI, matching skills to jobs, and achieving Net Zero targets. They can absorb some of the costs and risks associated with data processing activities and provide assurances around data quality. Data communities may also go beyond legal requirements around data protection and apply additional measures to protect against unethical use of data and ensure it is only used for agreed purposes.

•Supporting Collective Action: The Data Communities model allows for collective action on data issues, as seen in the example of UK Uber drivers attempting to establish a data trust (related concept) for collective bargaining purposes. This is a practical application for achieving economic benefit that is difficult for an individual data subject to achieve alone.

•Enhancing Transparency and Accountability: Regulatory requirements can ensure that Data Communities operate transparently and are subject to regulatory oversight.

Key Considerations and Regulatory Framework

Implementing Data Communities effectively requires careful consideration of practical challenges and a robust regulatory framework:

•Establishing and Operating Data Communities: There is a need for practical guidance on how individuals can establish, operate, and join Data Communities. Making complex issues transparent and understandable requires considerable time, resources, and skills.

•Interaction with Data Controllers/Processors: Clear guidance is needed for data controllers and processors on how to respond to requests made by Data Communities exercising rights on behalf of their members. This includes defining "good practice" in engaging with Data Communities

•Transparency and Oversight: The proposed requirement for the Information Commissioner to maintain a public register and establish complaints mechanisms for both data subjects and Data Community controllers is essential for ensuring accountability and addressing potential issues.

•Effective Data Portability: The viability of Data Communities heavily relies on the effective and technically feasible portability of data. Challenges in exercising the right to data portability need to be addressed. There is a need to monitor reasons for refusal of portability requests. Technical infrastructure can enhance interoperability and data portability. Users might prefer controller-to-controller transfer, which should be made simple.

•Ensuring Inclusivity and Uptake: Careful consideration is needed to encourage uptake beyond the most engaged or digitally literate groups. A bottom-up approach relying solely on citizen demand might be skewed. Achieving a viable market requires a sufficient number of participants.

•Avoiding Risks: Mechanisms must be in place to mitigate risks associated with data intermediaries generally, such as distrust, the creation of dominant entities or new data monopolies, conflicts of interest, and increased demands on regulatory oversight.

Crucial Role of Appropriate Legal Frameworks

The identification and clarification of appropriate legal frameworks are fundamental for the effective operation and trustworthiness of Data Communities, regardless of their specific scope. Regulatory and legal opacity and uncertainty are significant barriers for data intermediaries generally.

•Building Trust and Accountability: A clear legal framework is a necessary foundation for building trust and accountability around data intermediation models like Data Communities It ensures that these entities operate transparently and are subject to regulatory oversight.

•Clarifying Roles and Obligations: Legal frameworks need to define the roles and obligations of Data Communities (e.g., whether they act as controllers or processors) and their relationship with data holders, data users, and regulators. This clarity is essential for the legal certainty needed by all parties involved.

•Enabling the Exercise of Rights: we need to clarify explicitly the ability of data subjects to legally mandate a Data Community to exercise their data rights on their behalf and address current legal ambiguities that hinder intermediaries from acting effectively on behalf of an individual.

•Ensuring Responsible Stewardship: Legal frameworks can incorporate requirements for good practice and responsible data management. This should go beyond mere compliance with existing data protection laws and could help ensure data is used only for agreed and ethical purposes.

•Providing Regulatory Oversight and Complaints Mechanisms: There should be a requirement for the Information Commissioner to maintain a public register of Data Communities and establish complaints mechanisms.

•Interfacing with Existing Law: Data Communities need to operate within the existing legal landscape, including comprehensive frameworks like the UK GDPR. The legal framework for Data Communities needs to clearly articulate how they interact with and build upon these existing frameworks.

Conclusion

In summary, Data Communities, represent a promising mechanism for empowering individuals and fostering more responsible data stewardship by enabling collective exercise of data subject rights. This model aligns with the broader goals of increasing participation and rebalancing power in the data landscape. Integrating the Data Community concept into the broader data intermediary landscape, supported by the proposed regulatory measures, is a valuable step towards a more trustworthy and equitable data ecosystem in the UK. Realizing the potential of Data Communities will depend on developing clear practical guidance and ensuring robust regulatory oversight. Addressing challenges related to effective data portability and ensuring inclusive access will be key to their success. Further exploration and piloting of this model, alongside other forms of data intermediaries, should be encouraged and facilitated to understand their full potential and identify contexts where they are most impactful.

by Tim Clement-Jones

Digital Inclusion Action Plan: No One Should Be Left Behind in Digital Britain

I recently responded to a Call for Evidence on the government's Digital Inclusion Action Plan: First Steps. It represents a tentative first step, but we need transformative action to ensure no one is left behind in our increasingly digital society. As Liberal Democrat spokesperson for Science, Innovation and Technology, I've responded to the government with concrete proposals for systemic change.

Digital Access is a Fundamental Right

In modern Britain, digital inclusion isn't optional - it's essential for full participation in society. Whether accessing Universal Credit, booking GP appointments, or helping children with homework, being online has become as vital as having running water or electricity. Yet millions remain excluded from our digital society.

The economic case is compelling. Research by CEBR shows £9.48 return for every £1 invested in digital inclusion. The Local Government Association found a 4% increase in economic activity per 10% broadband increase. Digital exclusion deepens inequalities, reduces productivity, and increases pressure on public services.

Beyond the Usual Suspects

While the government identifies five priority groups - low-income households, older people, disabled people, unemployed and young people - this framework needs expansion. Digital exclusion affects social housing tenants, benefits recipients, people with health conditions, single parents, those with English as second language, and geographically isolated communities.

Research by Stockport Homes demonstrates how these characteristics intersect - tenants who don't use the internet are more likely to be over 55, have disabilities, and rely on pensions, with 30% having no devices at all.

Learning from Success

We have excellent models to build upon. 100% Digital Leeds provides a council-led blueprint focusing on third-sector capacity building. Greater Manchester's evidence-based approach targets specific demographic needs with affordable connectivity solutions. Digital Unite's Digital Champions Network offers scalable peer support across multiple settings.

Four Pillars - But We Need More

The government's four focus areas - skills, tackling poverty, breaking barriers, and building confidence - provide a foundation but need strengthening:

Digital Rights and Citizenship must be added as a fifth pillar. We need comprehensive online safety education, privacy protection frameworks, and digital citizenship understanding.

For Skills, we must establish digital literacy as a statutory right with clear progression pathways integrated into essential public services.

For Data and Device Poverty, internet access should be an essential utility with legal rights to data access, mandatory social tariff provision, and sustainable device recycling infrastructure.

For Breaking Barriers, we need universal design standards, digital "right-of-way" for public services, multi-language support, and guaranteed offline alternatives.

For Building Confidence, comprehensive scam awareness programs, peer learning networks, and addressing cultural barriers are essential.

Practical Solutions Now

Several immediate actions could transform digital inclusion:

Auto-enrollment for social tariffs through DWP systems would ensure eligible households automatically receive affordable connectivity
VAT reform on broadband - using the 15% differential to create a social inclusion fund
National device donation scheme - government departments and businesses donating refurbished equipment
Digital champions in every community - trained volunteers providing local support
Emergency connectivity support - for those in crisis situations

Sustainable Funding Essential

The Digital Inclusion Innovation Fund needs minimum 3-5 year commitments, ring-fenced allocation for deprived areas, and support for both grassroots innovation and proven programs. We should remove early termination charges for benefits recipients and simplify social tariff applications.

Working Together

Success requires partnership across government, industry, charities and communities. We need a National Digital Inclusion Forum, regional partnerships, and statutory requirements for public service digital access. Employers must actively promote digital upskilling - as FutureDotNow argues, businesses across all sectors need incentives to train their workforce in essential digital skills.

The Cost of Inaction

Digital exclusion isn't just about technology - it's about social justice. Every day offline means missed opportunities for education, employment, healthcare, and social connection. The pandemic showed us the devastating impact of digital exclusion. We cannot return to treating it as an afterthought.

Time for Transformation

The government's plan provides a foundation, but we need greater ambition and systemic change. By treating digital inclusion as fundamental infrastructure backed by appropriate resources and statutory requirements, we can ensure no one is left behind.

Change starts with ideas and is achieved by actions. Digital inclusion is one of the defining challenges of our time. Together, we can build a digitally inclusive Britain where everyone has the skills, access, and confidence to thrive in our digital world.

by Tim Clement-Jones

Lord C-J: We need more women in the STEM Workforce

The House of Lords recently celebrated International Women's Day with a debate to "take note of International Women's Day and the steps being taken to promote women's participation and leadership in science and technology in the UK and internationally"

This is what I said in the debate:

It is a great privilege to take part in this debate. We have heard a brilliant and insightful set of maiden speeches today. I particularly valued the weight of the Welsh and Scottish representation here. It is not always present in the force that it should be. I declare an interest as chair of Queen Mary University, which, relevant to this debate, has a very distinguished biomedical engineer at the helm of our School of Engineering and Materials Science, Professor Hazel Screen. I envy the noble Lord, Lord Davies, for having an engineer daughter to consult with on his speech today. I also thank the Minister, the noble Baroness, Lady Smith, for her introduction today and for moving the Motion. I congratulate her on her new appointment. I do wonder how many hours in the day there are, as I know the weight of her current post.

I was chair of the House of Lords Artificial Intelligence Committee, whose 2018 findings revealed a deeply troubling picture. Globally, over three-quarters of AI and data science professionals were male. In the UK, women’s representation was even lower at just 20%. Seven years later, despite numerous initiatives, the needle has barely moved. I am not surprised that the noble Baroness, Lady Lane-Fox, is angry—we all should be. This is not just about fairness, crucial though that may be. This is not to undervalue the importance of the humanities and the arts. As we have heard from the noble Baroness, Lady Morrissey, and others, it is about the quality and safety of the AI systems being developed.

As the noble Viscount, Lord Stansgate, said, when teams lack diversity, the technology they create reflects those limitations. We are in danger of building tomorrow’s world with yesterday’s biases. The implications are profound—from facial recognition systems that fail to properly identify women and ethnic minorities to recruitment algorithms that perpetuate gender bias or medical diagnostic systems trained predominantly on male data, as well as the proliferation of deepfake pornography, misogyny, threats of violence and trolling online, as illustrated by the noble Baronesses, Lady Hazarika, Lady O’Grady and Lady Owen.

The wider picture of STEM is equally concerning. As we have heard, women comprise only 29% of the UK’s tech workforce. In engineering and technology apprenticeships, women account for just 17% of starts. Only 8.5% of active spin-outs had all-female founding teams, and just 16% had mixed founding teams. At leadership level, as the noble Baroness, Lady Lane-Fox, said, women make up a mere 6% of STEM leaders. These statistics represent not just inequality but a massive waste of talent at a time when these skills are crucial to our economic future and medical research, as the noble Baroness, Lady Smith of Llanfaes, pointed out.

The digital divide compounds these challenges. Women are 40% less likely than men to adopt technologies and there is a striking gap of 21 percentage points between junior men and women in adopting AI tools at work. This creates a vicious cycle—underrepresentation leads to technology designed without women’s input, which in turn makes technology less accessible to women, as the Minister said.

We have seen some laudable initiatives. The previous Government’s investment in AI and data science conversion degrees with scholarships for underrepresented groups was welcome. Organisations such as WISE, the Tech Talent Charter, which sadly closed down last year, and Women in AI have done valuable work. The Tech She Can charter, with more than 170 companies committed to increasing women in technology roles, shows industry recognition of the problem.

We must ask why, despite all these efforts, progress is so slow. The education pipeline remains a critical challenge and, although we have seen some improvement, with an almost 30% increase in girls starting STEM A-levels between 2009 and 2020, this has not translated into proportional workforce representation. Something is clearly going wrong in the transition from education to career and in career progression thereafter.

The persistence of the leaky pipeline in STEM education and careers, mentioned by the noble Baroness, Lady Bottomley, remains deeply concerning. While we see encouraging numbers of young women taking STEM A-levels and entering undergraduate programmes, the sharp decline at postgraduate level and into academic careers suggests systemic issues beyond mere time lag effects. I was very interested to hear what the noble Baroness, Lady Bousted, said about the culture in schools.

It is particularly striking that many capable female students report never having considered advanced STEM careers, not because of active discouragement but because they simply had not envisioned themselves in these roles. I was very interested to hear the noble Baroness, Lady Greenfield, set out a number of really interesting suggestions for action in this area. I would suggest another few areas where government action could make a real difference.

First, we need a comprehensive review of the effectiveness of current initiatives. While individual programmes show promise, they often operate in silos. We need a coherent national strategy that co-ordinates efforts across education, industry and government. This should include early intervention in schools, support through higher education and workplace initiatives.

Secondly, we should consider mandatory reporting on gender diversity in STEM roles for larger companies, similar to gender pay gap reporting. What gets measured gets managed. This would provide crucial data to inform policy and hold organisations accountable. Companies should report not just on overall numbers but on recruitment, retention and progression.

Thirdly, we need targeted support for critical transition points, particularly in returning to STEM careers after career breaks. What happened to the pilot returners programme in the Midlands and the north of England, known as STEM ReCharge? This should include expanded training opportunities, flexible working arrangements and structured return-to-work programmes.

Fourthly, we must address the persistent barriers in workplace culture. This means tackling unconscious bias, mentioned by the noble Lord, Lord Davies, ensuring fair promotion processes and creating inclusive environments. The Government should lead by example in their own STEM workforce and require diversity initiatives as part of public procurement, as mentioned by the noble Baroness, Lady O’Grady.

Fifthly, we need specific focus on emerging technologies. With AI and quantum computing shaping our future, we cannot afford to repeat past patterns of exclusion. This means ensuring women’s participation in this field from the ground up.

More fundamentally, as mentioned by the noble Baroness, Lady Lane-Fox, the noble Lord, Lord Parekh, and many others in this debate, we need to address the cultural barriers that persist in STEM fields. We should celebrate the prominent women in STEM, as we were asked to by the noble Baronesses, Lady Moyo and Lady Bottomley, but the very fact that we can name all these individuals—as role models who show what is possible—and their very exceptionalism, highlights the systemic problem we must address. That surely is self-evident.

This underscores the critical importance of visible role models and intentional mentorship. We need to move beyond passive representation to active engagement, ensuring that young women not only see themselves succeeding in STEM fields but are actively encouraged to see themselves in these roles. It is not just about technical skills; it is about creating an environment where girls see themselves as natural problem-solvers and innovators. Too often, this fundamental confidence-building is missing from young girls’ experiences, creating invisible barriers long before career choices come into play.

Time is short, but I want to mention the international dimension, which was raised particularly by the noble Lords, Lord Loomba and Lord McConnell. Our leadership in science and technology gives us both the opportunity and the responsibility to set global standards for inclusion. In this context, the announced cuts to the UK aid budget cast a huge and unwanted shadow over STEM development globally, particularly for women and girls. Are the Government still committed to the international women and girls strategy of 2023-30, launched only two years ago on International Women’s Day? It set important goals. Given the Government’s commitment to STEM education and gender equality, will efforts be made to protect these areas from the worst impacts of these cuts?

Looking ahead in the UK, we see that the stakes could not be higher. AI and other emerging technologies will reshape our society. If women remain underrepresented in the development of such technologies, we risk embedding gender bias into the architecture of our digital future. This is not just about equality; it is about ensuring that our technological development serves our entire society and not just half of it.

by Tim Clement-Jones

AI and Copyright Lord C-J " The Government need to take this option off the table"

With huge thanks to Christian Gordon-Pullar for all his work here is our response to the Government's consultation on IP and Copyright. We are clear that there is no lack of clarity in UK copyright law that should allow technology companies to scrape the internet and use copyright material for training their AI models without any recompense to creators and that we need to introduce clear rules requiring transparency of use and a better enforcement mechanism for. breaches of copyright.

I and my Liberal Democrat colleagues fully support the major campaign by the media, artists and the creative industries to demand that the government take their preferred option, of a text and data mining exeception requiring an opt-out, off the table and make sure that they ensure that one of the most valuable sectors in the British economy survives and thrives alongside AI.

Here is a link to the Consultation

https://www.gov.uk/government/consultations/copyright-and-artificial-intelligence/copyright-and-artificial-intelligence

And here is our response

Response to Consultation: AI and Copyright on behalf of Lord Clement-Jones and Christian Gordon-Pullar

Context for Response to Consultation

Use of AI clearly offers significant opportunities across the broad canvas of the United Kingdom’s creative industries, and abroad. Creators and associated creative businesses are using AI technology to support creativity, the process of content production or to help personalise content. AI clearly has many creative uses, as Sir Paul McCartney has emphasised. It is one thing, however, to use the technology but another to be at the mercy of it.

The Government consultation[3] itself begins with the sentence :

“Two major strengths of the UK economy are its creative industries and AI sector. Both are essential to drive economic growth and deliver the government’s Plan for Change.”

We support the policy objectives within the consultation and in particular, at a high level, the three objectives set out in the Government consultation, in relation to AI and Copyright, namely:

Supporting right holders’ controlof their content and ability to be remunerated for its use.
Supporting the development of world-leading AI models in the UKby ensuring wide and lawful access to high-quality data.
Promoting greater trust and transparencybetween the sectors.

It is incumbent on any Government to find a true and fair balance for authors, musicians, artists and all creative content creators and owners, not just for foreign and domestic tech and AI companies and tech entrepreneurs, at the expense of the giants on whose creative and historical works their success relies and on whose shoulders their business and technology stands.

The Ministerial foreword reinforces this:

“This consultation sets out our plan to deliver a copyright and AI framework that rewards human creativity, incentivises innovation and provides the legal certainty required for long-term growth in both sectors.”

It is unclear and remains unexplained - in the Consultation - why the Government states:

“AI firms have raised concerns that the lack of clarity over how they can legally access training data creates legal risks, stunts AI innovation in the UK and holds back AI adoption”

It is entirely unclear where or what lack of clarity is being referenced? There is currently clarity and certainty in the Copyright regime in the United Kingdom and additionally the UK recognises Computer Generated Works (See para 51 of the Consultation). In relation to copyright and Intellectual Property (IP), under the current law in relation to content ingestion by AI developers, consent must be secured for the use of rightsholders’’ content. The Consultation appears to be creating the distinct impression that copyright owners should be concerned and this is creating uncertainty.

The Consultation also states:

The creative industries drive our economy, including TV and film, advertising, the performing arts, music, publishing, and video games. They contribute £124.8 billion GVA to our economy annually, they employ many thousands of people, they help define our national identity and they fly the flag for our values across the globe. They are intrinsic to our success as a nation and the intellectual property they create is essential to our economic strength

It is unclear however if, and to what extent, the Government has carried out any serious investigation into the financial impact on the creative industries in the preparation of this Consultation, or since its publication. It is however clear that the impact will be significant and very likely greater than the proposed benefits of the data centres and investments offered by Big Tech.

The estimate of benefits to the UK economy use by the AI Opportunities Plan is built on shaky foundations,. It is derived from Google's UK Economic Impact Report which highlighted that "AI-powered innovation could create over £400 billion in economic value for the UK economy by 2030. The £400 billion figure cited by Google comes from a report commissioned by Google and compiled by the consultancy firm Public First. This economic impact report was designed to analyse the potential effects of AI adoption on the UK economy by 2030.Public First conducted the research using several methods:

Polling of over 4,000 individuals across every region in the UK
Polling of 1,000 senior business leaders from small, medium, and large businesses across various industries
Traditional economic modelling to measure the economic activity driven by Google products.

The report estimates that AI-powered innovation could create over £400 billion in economic value for the UK economy by 2030, which is equivalent to an annual growth rate of 2.6%.

This figure is based on projections of how AI technologies could boost productivity, create new job opportunities, and drive innovation across various sectors of the economy. It is important to note that this is a projection based on economic modelling and assumptions about future AI adoption and impact. As with any such forecast, it should be viewed as an estimate rather than a guaranteed outcome.

We remain convinced that the current copyright regime is clear and no evidence has been produced to warrant a new and more permissive exception regime to existing copyright laws in the United Kingdom. It is our preferred option that the Government makes a clear statement that the use and/or ‘ingestion’ of content, without consent, to train an AI model capable of being used beyond non-commercial research, constitutes copyright infringement.

Foreword/Summary

Questions surrounding the balance between copyright and data mining (text and data mining or TDM) is a major issue for content owners and creatives in the literary, musical and visual arts and not just in the UK, but around the world.

Getty and the New York Times are suing in the United States, so too many writers, artists and musicians and it was at the root of the Hollywood Actor and Writers strike last year .

Here in the United Kingdom, as the Government’s intentions have become clearer the temperature has risen. We have seen the creation of a new campaign -Creative Rights in AI Coalition (CRAIC) across the creative and news industries and Ed Newton-Rex six[4] raising over 30,000 signatories from creators and creative organisations. But with the current Consultation, we are now faced with a proposal regarding text and data mining exception which we thought was settled under the last Government. It starts from the false premise of legal uncertainty.

As the News Media Association says:

The government’s consultation is based on the mistaken idea—promoted by tech lobbyists and echoed in the consultation—that there is a lack of clarity in existing copyright law. This is completely untrue: the use of copyrighted content by Gen AI firms without a license is theft on a mass scale, and there is no objective case for a new text and data mining exception.

There is no lack of clarity over how AI developers can legally access training data. The applicable law in England and Wales is absolutely clear that commercial organisations – including Gen AI developers – must license the data they use to train their Large Language Models (“LLMs”). Merely because AI platforms such as Stability AI are resisting claims doesn’t mean the law in the UK is uncertain. There is no clear reason for – and no need for developers to - find ‘it difficult to navigate copyright law in the UK’.

AI developers have already, in a number of cases, reached agreement with between news publishers. OpenAI has signed deals with publishers like News Corp, Axel Springer, The Atlantic, and Reuters, offering annual payments between $1 million and $5 million, with News Corp’s deal reportedly worth $250 million over five years.

More recently, it is clear that the US fair use defence questions have not been settled despite the ruling in Thomson Reuters v. ROSS Intelligence, which involved Thomson Reuters suing ROSS Intelligence for using its copyrighted Westlaw headnotes to train an AI-powered legal research tool. On February 11, 2025, Judge Stephanos Bibas of the Delaware federal district court ruled against ROSS, rejecting its fair use defence and granting partial summary judgment in favour of Thomson Reuters. It is notable, however, that the court emphasised that ROSS’s use was commercial and non-transformative, as it created a competing product using the copyrighted material. This decision is significant as it sets a precedent for AI copyright cases, though it does not address generative AI specifically.

There can be no excuse of market failure. There are well established licensing solutions administered by a variety of well-established mechanisms and collecting societies. There should be no uncertainty around the existing law and the surrounding legal framework. We have some of the most effective collective rights organisations in the world.

The Consultation says that “The government believes that the best way to achieve these objectives is through a package of interventions that can balance the needs of the two sectors” The government appears to believe we need to achieve a balance between the creative industries and the tech industries. But the Consultation raises the fundamental question as to what kind of balance the government’s preferred option will deliver.

The government’s preferred option is to change the UK’s copyright framework by creating a text and data mining exception where rights holders have not expressly reserved their rights—in other words, an ‘opt-out’ system, where content is free to use unless a rights holder proactively withholds consent. To complement this, the government is proposing: (a) transparency provisions; and (b) provisions to ensure that rights reservation mechanisms are effective.

The government has stated that it will only move ahead with its preferred ‘rights reservation’ option if the transparency and rights reservation provisions are ‘effective, accessible, and widely adopted’. However, it will be up to Ministers to decide what provisions meet this standard, and it is clear that the government wishes to move ahead with this option regardless of workability, without knowing if their own standards for implementation can be met.

A few key overarching points to note:

Although it is absolutely clear that that use of copyright works to train AI models is contrary to UK copyright law, the laws around transparency of these activities haven’t caught up. As well as using pirated e-books in their training data, AI developers scrape the internet for valuable professional journalism (even where such articles are protected by © Copyright notices and terms and conditions) and other media, in breach of both the terms of service of websites and copyright law, for use in training commercial AI models.
At present, developers can do this without declaring their identity, or they may use IP scraped to appear in a search index for the completely different commercial purpose of training AI models.
How can rights owners agree – in principle or in practice - to opt-out of something they don’t know full understand or even know about? AI developers will often scrape websites, or access other pirated material before they launch an LLM in public. This means there is no way for IP owners to opt-out of their material being taken before its inclusion in these models. Once used to train these models, the commercial value has already been extracted from the third party IP scraped, without permission, with no practical way to find or delete data from those models.
The next wave of AI models responds to user queries by browsing the web to extract valuable news and information from professional news websites. This is known as Retrieval Augmented Generation-RAG. Without payment for extracting this commercial value, AI agents built by companies such as Perplexity, Google and Meta, will effectively free ride on the professional hard work of journalists, authors and creators. At present such crawlers are hard to block.

This is incredibly concerning, given that no effective ‘rights reservation’ system for the use of content by Gen AI models has been proposed or implemented anywhere in the world, making the government proposals entirely speculative.

As the NMA also say :

“What the government is proposing is an incredibly unfair trade-off—giving the creative industries a vague commitment to transparency, whilst giving the rights of hundreds of thousands of creators to Gen AI firms. While creators are desperate for a solution after years of copyright theft by Gen AI firms, making a crime legal cannot be the solution to mass theft.[5]”

We need transparency and clear statement about copyright. We absolutely should not expect artists to have to opt out. AI developers must: be transparent about the identity of their crawlers; be transparent about the purposes of their crawlers; and have separate crawlers for distinct purposes. Unless news publishers and the broader creative industries can retain control over their data – making UK copyright law enforceable – AI firms will be free to scrape the web without remunerating creators. This will not only reduce investment in trusted journalism, but it will ultimately harm innovation in the AI sector. If less and less human-authored IP is produced, tech developers will lack the high-quality data that is the essential fuel in generative AI.

Amending the applicable Law to address the challenges posed by AI development, particularly in relation to copyright and transparency, is essential to protect the rights of creators, foster responsible innovation, and ensure a sustainable future for the creative industries.

This should apply regardless of which country the scraping of copyright material takes place if developers market their product in the UK, regardless of where the training takes place.

It will also ensure that AI start-ups based in the UK are not put at a competitive disadvantage due to the ability of international firms to conduct training in a different jurisdiction. It is clear that AI developers have used their lobbying clout to persuade the government that a new exemption from copyright - in their favour - is required.

In response we will be vigorously opposing the preferred option for a new text and data mining exemption with an opt-out and will be seeking to ensure that the government answers the following key questions before proceeding further

What led the government to do a u-turn on the previous government’s decision to drop the text and data mining exemption it proposed?
What estimate of the damage to the creative industries it has made of implementing its clearly favoured option of a TDM plus opt out given there is no robust economic assessment currently in existence
Is damaging the most successful UK economic sector for the benefit of US AI developers what it means by balance?
Why it has not included the possibility of an opt in to a TDM in its consultation paper options?
What examples of successful workable opt outs or rights reservation from TDM’s can it draw on particularly for small rights holders? What research has it done? the paper essentially admits that effective technology is not there yet. Isn’t it clear that the EU opt out system under the Copyright Directive has not delivered clarity?
What regulatory mechanism if any does the government envisage if its proposal for a TDM with rights reservation/opt out is adopted? How are creators going to be sure any new system would work in the first place?

Detailed Response below

Response to Consultation

Copyright – Text and Data Mining

The three stated objectives in the Consultation[6] are set out in para / section 54 of the Consultation:

Supporting right holders’ controlof their content and ability to be remunerated for its use.
Supporting the development of world-leading AI models in the UKby ensuring wide and lawful access to high-quality data.
Promoting greater trust and transparencybetween the sectors.

The Government rightly believe that there is a need to promote and further enable AI development. This must however be balanced with a commensurate and proportionate recognition of the critical importance and value of data as raw material. AI developers rely on high-quality data to develop reliable and innovative AI-driven inventions and applications. Licensing regimes under existing IP law are designed to cater for the needs of AI developers.

By the same token content and data-driven businesses themselves have seen a rapid increase in the use of AI technology and machine-learning, either for news summaries, data gathering efforts, translations for research and journalistic purposes or to assist organisations to save time by processing large amounts of text and other data at scale and speed. Digital technologies, including AI, are and will continue to be of critical importance to these industries, helping create content, new products and value-added services to deliver to a broad range of corporate and retail clients. Whether in news media or cross-industry research, publishers are themselves investing in AI; continued collaboration with start-ups and academia are creating tailored materials for wide populations of beneficiaries (students, academia, research organisations, and even marketers of consumer publishing products).

It is of paramount importance to balance the needs of future AI development with the legal, commercial and economic rights of copyright and data-owners and the need to incentivize new AI adoption with recognition of the rights of – and remuneration for - existing content owners.

We have however seen no evidence the existing copyright legislative framework fails to adequately address the current needs of AI developers. Moreover it is particularly important, in our view, to ensure that the development of AI is not enabled at the expense of the underlying investment by copyright and data-owners. (see endnote 1).

If the content owners of underlying data materials withhold the licensing of, or access to, such materials or attempt to price them at a level that is unfair, the answer is for Government via the Competition and Markets Authority/the new Digital Markets Unit (or indeed other regulators who form part of the Digital Regulation Cooperation Forum) to put in place competition measures to ensure there is a clear legal recourse in such situations.

In summary we do not believe that current copyright law creates a disparity between the interests of AI developers and investors and content owners. The existing copyright regime under the CDPA reflects a balance that fairly protects those investing in data creation without giving an unfair advantage to technology companies offering AI-enabled content creation services. In particular the current framework provides a balanced regime for data and text mining and we believe no changes are required at present.

At the very least, if AI Operators and providers must be able to demonstrate transparency and provide users and regulators with access to clear records of the inputs that the AI technology has used (e.g. sources of content includes copyrighted content), it will be impossible to satisfy the UK regime as well as basic international standards on cybersecurity standards, let alone copyright infringement or applicable parallel imports laws, to satisfy UK sovereignty principles.

In order, RESPONSES below.

Section C1

Question 1.Do you agree that option 3 is most likely to meet the objectives set out above?

NO, we do not agree.

Creating a more permissive system of copyright is unlikely to incentivise AI developers to obtain consent or license content from rightsholders.
AI developers have shown little appetite to license content at scale and there have been no signals, from what we have seen, that that position would change under any new regime. In the EU, which introduced a new Text and Data Mining (TDM) Exception with an Opt-Out (before the explosion in AI development) there has been no material increase in licensing of content, demonstrating that it is not the law which is preventing such licensing.
As currently drafted, the Consultation contains a new exception would also be available to all users, not simply AI developers for training. This would mean any user could copy works and reproduce them for commercial gain unless those rights were reserved. This presents the distinct opportunity for some unscrupulous users to deliberately look for works that are not rights reserved to exploit them commercially which is not possible under the existing copyright system

Question 2.Which option do you prefer and why?

Ranking Options in order:

We would therefore urge the Government to elect Option 0 – Make no legal change. No other option is currently justifiable given the lack of evidence of an adverse commercial environment preventing access to data or text by AI-enabled content creators. Should the Government or IPO consider that there needs to be increased access to data at lower cost, it should look at otherpolicy levers to stimulate such uptake, such as providing tax incentives for content owners to license content, rather than reducing copyright protection.
We also concur with industry leads who consider that forcing rightsholders to opt in to protection, or opt out of a data mining exception - as suggested in Option 3 – would be complicated and costly for many businesses and industries who own literally millions of works, when licensing is far simpler, and would be against the spirit of international treaties on copyright
Further such changes would impact the rights of copyright owners, as enshrined in Article 1 of the Human Rights Act . The Human Rights Act 1998 incorporates rights contained in the European Convention on Human Rights (ECHR) into UK national law. This means that they can be used to challenge the actions and decisions of governments and public bodies in the UK courts. Under the UK Human Rights Act 1998, intellectual property rights are protected as part of the broader “right to property” enshrined in Article 1 of the First Protocol, meaning that public authorities cannot interfere with your intellectual property without a legitimate legal reason and in the public interest; this includes patents, trademarks, copyrights, and other forms of intellectual property you may own

Article 1 of the First Protocol states:.

“Every natural or legal person is entitled to the peaceful enjoyment of his possessions. No one shall be deprived of his possessions except in the public interest and subject to the conditions provided for by law and by the general principles of international law.

The preceding provisions shall not, however, in any way impair the right of a State to enforce such laws as it deems necessary to control the use of property in accordance with the general interest or to secure the payment of taxes or other contributions or penalties.”

Possessions include any tangible and intangible property

While the Act protects intellectual property, it does allow for limitations in the public interest, meaning that the government can restrict intellectual property rights under certain circumstances if it is deemed necessary for the greater good. This is clearly for the benefit of tech and AI companies, not the greater good of content owners and creative industries across the fields of literary, musical and visual arts, inter alia.

Section C1 (cont.)

Question 3. Do you support the introduction of an exception along the lines outlined above?

RESPONSE: No, this is not necessary under UK law as the copyright owner already holds such rights, and such an exception would not be effective.

Absent a licence, or consent in writing, such rights to control his/her/its copyright are reserved for the copyright owner and no use of that copyright is permitted (except under existing non-commercial research exceptions for academic research, inter alia). Any such unauthorised use would constitute copyright infringement.

Question 4. If so, what aspects do you consider to be the most important? If not, what other approach do you propose and how would that achieve the intended balance of objectives?

RESPONSE: Only applicable if Option 3 is the eventual outcome. If such an approach for Option 3 were in fact the outcome at the end of the consultation, a presumption (as per existing UK law) should exist that no content is automatically permitted for TDM use by AI/Tech companies or other third parties, and that would be the case even in case where content available publicly or otherwise does not have a text of machine readable opt-out language. The presumption must be in favour of the content and copyright owner (else risks creating costly litigation for SMEs and individuals who cannot reasonably be expected to allocate funds to litigate foreign and domestic tech companies and other well-funded tech start-ups seeking to use content without consent.

Any new exception would also have to be narrowly drafted to ensure it is limited to AI training, to ensure ill-intentioned users do not exploit the new system to reproduce works for commercial gain outside of the AI environment.

Question 5. What influence, positive or negative, would the introduction of an exception along these lines have on you or your organisation? Please provide quantitative information where possible.

RESPONSE: Any new exceptions would adversely impact creative industries both operationally and financially – as seen from feedback and publications and statements made by the Performing Rights Society [7](PRS)[8], Anti-Copying in Design (ACID[9]) and others. (See footnotes for references).

Content owners would have to spend time and money on legal advice, potentially, to:

Embed Metadata and Watermarks - Add metadata to digital files to indicate copyright ownership and usage restrictions. Watermarks could deter unauthorised use if a robust and easily useable form was readily available. Embedding metadata could be relatively simple and could be done using file properties, specialised software or programming methods (e.g., EXIF for images, or custom fields in JSON or XML) See Appendix 1
Monitor and Enforce Their Rights
Content owners would have to regularly check for unauthorised use of their copyright work online. If an owner identifies infringements, they would need to contact the offending party to request removal or seek legal advice. However, identifying the offending party remains a significant challenge without a proper system in place in terms of transparency requirements..

For example, A photographer would have to retrospectively opt-out thousands of individual works to gain protection which is currently automatic, time that they can ill-afford to spend which detracts from their valuable time, better spent generating new revenue-generating copyright-protected works. Legal costs would like increase – to challenge infringement - but under a new regime there would have to be a dual track for action, one under the new regime and another under the existing regime, potentially doubling legal costs.

Question 6. What action should a developer take when a reservation has been applied to a copy of a work?

RESPONSE: The developer must seek consent and pay for the content before training AI or technology systems on the content and without such consent would not / should not train its AI or technology on such content . This applies equally today under the existing law – and most companies ignore such rights because they are not enforced and the consequences are too financially burdensome for content owners – hence the rights should be bolstered not diluted.

Question 7. What should be the legal consequences if a reservation is ignored?

RESPONSE: Any new system for rights reservation must have the same legal standing as Technical Protection Measures. That is sub-optimal in any event. We propose that a statutory strict liability should be imposed and a presumption of copyright infringement should apply in case where use is without consent/licence.

Question 8. Do you agree that rights should be reserved in machine-readable formats? Where possible, please indicate what you anticipate the cost of introducing and/or complying with a rights reservation in machine-readable format would be.

RESPONSE: No: any such system should be sufficiently flexible to enable different content owners to opt out for types of works. While machine readable formats would most likely be required, these must be simple and low cost enough for all rightsholders to access; without this, such measures place the burden on the content owners to spend money to defend copyright and IP protection, rights that are fundamentally embodied in existing law and rights already held under the Human Rights Act 1998.

Section C2: Technical Standards

Question 9. Is there a need for greater standardisation of rights reservation protocols?

RESPONSE: If required at all, standardisation of protocols and standards for such protocols would seem helpful.

Question 10. How can compliance with standards be encouraged?

RESPONSE: Infringement or breach of any such protocols would need to be clearly stated to constitute copyright infringement with deterrents in place to create a compliant legislative regime. In the absence of such protocols, a statutory strict liability should be imposed or a presumption of copyright infringement should apply

Question 11. Should the government have a role in ensuring this and, if so, what should that be?

RESPONSE: Establish a Government regulator or unit to enforce such rights, to be paid for by the tech industry – which is demanding additional rights, which derogate from the rights of copyright and IP owners, which already exist under existing UK Copyright legislation and under the Human Rights Act 1998.

Section C3 – Licensing and contracts

Question 12. Does current practice relating to the licensing of copyright works for AI training meet the needs of creators and performers?

RESPONSE: Currently the licensing regime does not expressly address licensing for AI training but if AI training entities should apply the existing legal principles under the existing Law and therefore actually check copyright notices and apply for licensing /consent where no other approach is available.

Question 13. Where possible, please indicate the revenue/cost that you or your organisation receives/pays per year for this licensing under current practice.

RESPONSE: n/a from the authors

Question 14. Should measures be introduced to support good licensing practice?

RESPONSE: There is no presumption that commercial AI training or use of inputs is permitted under UK copyright law and rights-management societies and professional bodies including PRS and other licensing organisations already provide for such good licensing practices and may therefore need to update those for use by AI etc -

See https://www.prsformusic.com/ and also https://www.gov.uk/licence-to-play-live-or-recorded-music and ICO for film licensing – at https://www.independentcinemaoffice.org.uk/advice-support/what-licences-do-i-need/film-copyright-licensing/ and ICMP for Contemporary Music https://www.icmp.ac.uk/blog/understanding-music-copyrights-and-licenses

Question 15. Should the government have a role in encouraging collective licensing and/or data aggregation services? If so, what role should it play?

RESPONSE: No - this should be left to professional collection societies and licensing bodies authorised by each industry but the Government could, as an alternative to the preferred approach of robust enforcement, assist content owners by making any unauthorised use enforceable as a statutory liability, or create a presumption of infringement if that is not already clear (it seems clear to the authors)

Question 16. Are you aware of any individuals or bodies with specific licensing needs that should be taken into account?

RESPONSE: n/a

Section C4 – Transparency

Question 17. Do you agree that AI developers should disclose the sources of their training material?

RESPONSE YES. Transparency is vital to the AI eco-system. We advocate for transparency, by which we intend that AI developers must maintain records of the individual works that their AI systems etc. have ingested at a granular level.

Question 18. If so, what level of granularity is sufficient and necessary for AI firms when providing transparency over the inputs to generative models?

RESPONSE : As with current Law – the source, author and detail of data / content used and whether it is used under licence or not. Granularity is crucial – a general statement would not be sufficient to protect the principles of transparency nor to protect creator’s rights under the Law.

Question 19. What transparency should be required in relation to web crawlers?

RESPONSE: We should retain the amendments to the Data Use and Access Bill in this respect proposed by Baroness Kidron and passed by the House of Lords on the 28th of January 2025 which provide inter alia for regulations to require disclosure by AI models of

the name of the crawler,
the legal entity responsible for the crawler,
the specific purposes for which each crawler is used,
the legal entities to which operators provide data scraped by the crawlers they operate, and
a single point of contact to enable copyright owners to communicate with them and to lodge complaints about the use of their copyrighted works.
the URLs accessed by crawlers deployed by them or by third parties on their behalf or from whom they have obtained text or data,
the text and data used for the pre-training, training and fine-tuning, including the type and provenance of the text and data and the means by which it was obtained,
information that can be used to identify individual works, and
the timeframe of data collection.

Question 20.What is a proportionate approach to ensuring appropriate transparency?

RESPONSE: Unclear but it must at least involve an equal or greater effort by AI and tech developers using AI to scrape content as is being considered for content owners who have to add tech measures to their content e.g. watermarks etc and notices in machine readable format for opt outs and/or further technical, legal and operational costs to craft disclaimers or text for assertion of their (already existing) rights.

Question 21. Where possible, please indicate what you anticipate the costs of introducing transparency measures on AI developers would be.

RESPONSE: Unclear at this stage but perhaps the Government can broker – as part of its incentive deals– a framework to resolve past copyright infringement issues, to obviate the need for class actions by creative content owners or individuals, a one-off settlement/payment for past copyright infringement

Question 22. How can compliance with transparency requirements be encouraged, and does this require regulatory underpinning?

RESPONSE: If Option 3 is adopted then it must be a condition for tech developers and AI companies, at least, to take all reasonable operational measures to ensure that copyright and content is licensed or its input and output use is authorised (under license or written consent), such efforts to be at least equal or greater than the efforts being likely considered for content owners (who have to add tech measures to their content e.g. watermarks etc and notices in machine readable format for opt outs and/or further technical, legal and operational costs to craft disclaimers or text for assertion of their (already existing) rights)

Question 23. What are your views on the EU’s approach to transparency?

RESPONSE: It is very questionable, to say the least, how effective or workable the Working Groups implementing the EU AI ACT have found the opt out provisions; in the meantime, the transparency provisions is a clear benchmark for the UK and it should take note, given that until recently UK was bound by such rules. The law in UK should at least equally protect UK citizens and content and creative owners - – but not impose unworkable opt out mechanisms based on an as-yet-untested EU comparison - to promote consistency and to avoid a mass migration of creatives.

Section C5 : Clarification of Copyright Law

Question 24. What steps can the government take to encourage AI developers to train their models in the UK and in accordance with UK law to ensure that the rights of right holders are respected?

RESPONSE: See above responses to Q20 and Q22 – and reiterated here. A statutory strict liability should be imposed or a presumption of copyright infringement should apply, failing which, the Government should make a clear statement, in the form of a Copyright Notice, that the current exception regime does not allow for the use of works, covered by copyright, for commercial purposes, without the consent of the owner of those works.

Section C6

Question 25. To what extent does the copyright status of AI models trained outside the UK require clarification to ensure fairness for AI developers and right holders?

RESPONSE: If an AI company has trained its AI on content that is covered by copyright in the United Kingdom, then making the output or service provided by that company in the United Kingdom would still constitute copyright infringement.

At the very least, if AI Operators and providers are unable to demonstrate transparency and provide users and regulators with access to clear records of the inputs that the AI technology has used (e.g. sources of content includes copyrighted content), it will be impossible to satisfy the UK regime as well as basic international standards on cybersecurity standards, let alone copyright infringement or applicable parallel imports laws, in order to satisfy UK sovereignty principles.

Question 26. Does the temporary copies exception require clarification in relation to AI training?

RESPONSE: No, this is no defence; it is also no different to existing approach taken by any computer (an AI is just a software programme and no different to existing technologies, for now)

Question 27. If so, how could this be done in a way that does not undermine the intended purpose of this exception?

RESPONSE: We are not in favour of any exception but if such an exception were to be considered, then clear guardrails would need to be implemented – to ensure that any such temporary copies create no economic value or advantage.

Section C6 - Encouraging Research and Innovation

Question 28. Does the existing data mining exception for non-commercial research remain fit for purpose?

RESPONSE: YES, it is sufficient and fit for purpose, as it currently stands[10] The Exception received significant Parliamentary scrutiny before being implemented in 2014 and we believe any reform would significantly change the careful balance agreed upon then. Any such reform of the Exception would require significant and separate analysis, as opposed to being mixed in with this consultation.

Question 29. Should copyright rules relating to AI consider factors such as the purpose of an AI model, or the size of an AI firm?

RESPONSE: No. All such instances and use of copyright content are still governed by the existing UK Copyright legislation and the size of purpose of the firm is irrelevant (unless perhaps it is a true charity not a charitable front designed by and for a commercial purpose).

Section D - Computer-generated works: protection for the outputs of generative AI

Option 0: No legal change, maintain the current provisions

RESPONSE: Maintain the status quo.

Computer Generated Works (CGWs) distinguish the UK from other countries and prevents the argument that AI needs to ‘own’ IP outside of the existence of a ‘human author’ for creativity – it does not. AI is a tool in the hands of a company or individual.
CGWs protection is necessary to encourage the production of outputs by generative AI or other tools, and any legal ambiguity is likely to be resolved or of little effect. The Courts will resolve any ambiguity as they have done in England and Wales for centuries.
The exception in s9(3) CDPA works. “If a work is computer-generated – that is, not authored by a human – then copyright ought to be vested in the person who made the 'arrangements necessary for the creation of work”
AI does not require or deserve any special rights or considerations and such rights are adequately covered in the relevant S.9(3) of the CDPA: .

Section D2 - Outputs

Question 30. Are you in favour of maintaining current protection for computer-generated works? If yes, please explain whether and how you currently rely on this provision.

RESPONSE : YES: See above re Computer Generated Works expressly that these distinguish the UK from other countries where such a regime does not exist.

Question 31. Do you have views on how the provision should be interpreted?

RESPONSE: It has been clearly interpreted in case law. The Advocate General in Painer[11] took this view, noting that only human creations can be copyright- protected (although the human can employ a “technical aid” like a camera). A similar position has also been taken by the U.S. Copyright Office, which determined that images created using the generative AI model, Midjourney, were not original works of authorship protected by U.S. copyright law because this excludes works produced by non-humans[12]. Caselaw from other countries also reflects this understanding[13]. It is right and proper that the facts of each case should determine the outcome, as was Parliament’s intention[14].

RESPONSE: No changes to CGWs are required

Question 32. Would computer-generated works legislation benefit from greater legal clarity, for example to clarify the originality requirement? If so, how should it be clarified?

RESPONSE: No.

Question 33. Should other changes be made to the scope of computer-generated protection?

RESPONSE: No

Question 34. Would reforming the computer-generated works provision have an impact on you or your organisation? If so, how? Please provide quantitative information where possible.

RESPONSE: unknown until details are provided of what the changes would be in a legislative context and the authors consider this unnecessary

Question 35. Are you in favour of removing copyright protection for computer-generated works without a human author?

RESPONSE: NO, for reasons given above. UK is fortunate to have a CGW right which is absent in many legislative frameworks

Question 36. What would be the economic impact of doing this? Please provide quantitative information where possible.

RESPONSE: Unknown at yet

Question 37. Would the removal of the current CGW provision affect you or your organisation? Please provide quantitative information where possible.

RESPONSE: Almost certainly given the licensing arrangements and revenue based on existing legislation. Quantum unknown.

Section D4

Question 38. Does the current approach to liability in AI-generated outputs allow effective enforcement of copyright?

RESPONSE: The law is clear in relation to AI-generated outputs. If a service is being provided in the UK which has been trained on the use of UK material, without permission, then the service is infringing and operating illegally. The enforcement of the law is clearly challenging given the lack of transparency by AI developers of the works they have used to train their models and for what purpose. See above proposals on strict liability regime for AI companies infringing copyright and alternative enforcement mechanisms mentioned in previous responses, above.

Question 39. What steps should AI providers take to avoid copyright infringing outputs?

RESPONSE: comply with the law –

check copyright notices (which is easy with AI tools) and
obtain consent under licence or written permission to use substantial elements of content in which copyright subsists and is claimed and/or owned by a third party under a simple © Notice.

Section D5 - AI Output Labelling

Question 40. Do you agree that generative AI outputs should be labelled as AI generated? If so, what is a proportionate approach, and is regulation required?

RESPONSE: YES and YES

Question 41. How can government support development of emerging tools and standards, reflecting the technical challenges associated with labelling tools?

RESPONSE: Unclear, the labelling is easy with AI and tech tools

Question 42. What are your views on the EU’s approach to AI output labelling?

RESPONSE: n/a No comment. The EU AI Act, formally adopted by the EU in March 2024, requires providers of AI systems to mark their output as AI-generated content. This labelling requirement is meant to allow users to detect when they are interacting with content generated by AI systems to address concerns like deepfakes and misinformation. Unfortunately, implementing one of the AI Act’s suggested methods for meeting this requirement—watermarking—may not be feasible or effective for some types of media. As the EU’s AI Office begins to enforce the AI Act’s requirements, the Government should closely evaluate the practicalities of AI watermarking.

Section D6: Digital Replicas and other issues

Question 43. To what extent would the approach(es) outlined in the first part of this consultation, in relation to transparency and text and data mining, provide individuals with sufficient control over the use of their image and voice in AI outputs?

RESPONSE: This is an important area that requires a more detailed review of the effectiveness of UK laws. Moral rights and personality image rights such as exist in EU would help protect individuals to have adequate control over their image/reputation and performance. This is an area that needs further review and potentially, legislation. Ratification of international treaties on this topic such as the Beijing Treaty would be an important first step towards international cooperation on standards and enforcement frameworks.

There are significant limits on the control people have over their image and voice in the UK. To the extent image (or personality) rights are protected at all, it is via a mix of privacy law, data protection, contract law, moral rights and the common law tort of ‘passing off’. The approaches outlined in the first part of the consultation do not materially improve individuals’ position in relation to use of their image and voice in AI outputs. It is directed to the use of copyright works. It does not follow that a copyright work is directly probative of a person’s image and/or voice. Further, it does not follow that the owner of that copyright work is the person in question.

Question 44. Could you share your experience or evidence of AI and digital replicas to date?

RESPONSE: The ability of digital replicas in real time can cause and have caused irreparable damage to many including people we know who have been fooled by sophisticated AI scams and with real-time artificial intelligence replicas of real people, actors well then personalities and even family members, easily cloned from information available on social media and images shared on the Internet, can cause irreparable damage to individuals who may be ill prepared or ill-equipped to address these – and those in the public arena (including actors and artists or politicians, even) may suffer financial harm as well as reputational damage.

There have also been examples of deepfake videos of politicians in recent times in the UK- for example of Sadiq Khan and Sir Keir Starmer. A change in the law to explicitly cover acts like these, rather than leaving recourse only to adjacent rights such as defamation or passing off would, in our view, be advisable.

Section D7 – Emerging Issues

Question 45. Is the legal framework that applies to AI products that interact with copyright works at the point of inference clear? If it is not, what could the government do to make it clearer?

RESPONSE: No comment – question unclear

Question 46. What are the implications of the use of synthetic data to train AI models and how could this develop over time, and how should the government respond?

RESPONSE: It is likely the outputs and quality of AI tools trained on synthetic data models will be degraded as compared to original/real data models

Question 47. What other developments are driving emerging questions for the UK’s copyright framework, and how should the government respond to them?

RESPONSE: None, at present.

Section E

End notes

Lord Clement-Jones CBE[15] is a Liberal Democrat Life peer and the Liberal Democrat DSIT Spokesperson in the House of Lords, and inter alia, the Co-Chair of the All-Party Parliamentary Group on Artificial Intelligence. He was chair of the House of Lords Select Committee on Artificial Intelligence (2017–2018) and is a former member of the Select Committees on Communications and Digital (2011–2015)) as well as a former Lib Dem Lords spokesperson on the Creative Industries (2004-10). He is an officer and active member of the All-Party Parliamentary Group on Intellectual Property.
Christian Gordon-Pullar is an IP specialist and an experienced intellectual asset manager with more than 30 years’ experience, ranked in the IAM Top 300 Global IP Strategists in 2020- 2024 (inclusive). He has a proven track record in IP in the fields of financial services, pharmaceuticals and life sciences, fintech and e-commerce, working at a C level with venture capital and private equity firms across portfolios. Until August 2024, Christian was Chairman of Fox Robotics Ltd, a UK Agritech AI start up. He has led IP licensing efforts in multinationals across Europe and Asia. Based in Singapore from 2001 to 2019, he also has significant Asia experience where he was head of Tech, Intellectual Property and Corporate Functions Legal, AsiaPac at JPMorgan. Before that, he was global head of intellectual property at Standard Chartered Bank and CEO of Standard Chartered’s global IP licensing entity. [16] Christian was formerly a solicitor in the IP Group (TMT) at Lovell White Durrant, now Hogan Lovells, from 1993-1999.

Consent. The individuals named above would be agreeable to being contacted by the Intellectual Property Office (UK IPO) in relation to this consultation.

APPENDICES

Watermarking

Watermarking of copyright content for LLMs is an active area of research and discussion, with several approaches being explored to address copyright concerns in AI training and generation. While watermarking shows promise, its practicality for preventing copyright theft is still strongly debated.

Embedding Watermarks: Researchers have proposed methods to implant backdoors on embeddings, such as the Embedding Watermark method3. This technique aims to protect the copyright of LLMs used for Embedding as a Service (EaaS) by inserting watermarks into the embeddings of texts containing trigger words.
Output Watermarking: Some techniques focus on watermarking the text generated by LLMs. These methods can significantly reduce the probability of generating copyrighted content, potentially by tens of orders of magnitude4.
Model-Level Watermarking: A novel approach involves embedding signals directly into LLM weights, which can be detected by a paired detector. This method allows for watermarked model open-sourcing and can be more adaptable to new attacks.
Reinforcement Learning-Based Watermarking: A co-training framework using reinforcement learning has been proposed to iteratively train a detector and tune the LLM to generate easily detectable watermarked text while maintaining normal utility[17].

While watermarking shows potential, several factors affect its practicality in preventing copyright theft:

Effectiveness: Some studies demonstrate that watermarking can significantly reduce the likelihood of generating copyrighted content4. However, the effectiveness varies depending on the specific method and implementation.
Detection Challenges: Detecting watermarks in fully black-box models remains difficult. Some methods, like DE-COP, have shown promise in detecting copyrighted content in training data, even for black-box models6.
Trade-offs: There's an inherent trade-off between watermark transparency and effectiveness. Increased transparency may make watermarks more detectable and modifiable9.
Implementation Constraints: Watermarking during the LLM training phase cannot be applied to already trained models, limiting its applicability to existing LLMs[18].
Legal and Ethical Considerations: The use of copyrighted material in training datasets remains a contentious issue, with ongoing legal debates and lawsuits.

In conclusion, while watermarking techniques for LLMs are advancing rapidly, their practicality in preventing copyright theft is still uncertain. These methods show promise in reducing the generation of copyrighted content and potentially tracking its use, but challenges remain in implementation, detection, and legal frameworks. As the field evolves, a combination of technical solutions, legal guidelines, and ethical considerations will likely be necessary to address copyright concerns in AI effectively.

EU Transparency requirements

The EU AI Act requires a “sufficiently detailed summary” of training data for General-Purpose AI (GPAI) models to ensure transparency and protect stakeholders’ rights, such as copyright holders. The required level of granularity includes:

Data Sources and Types: Providers must disclose the origins of datasets (e.g., public or private databases, web data, user-generated content) and specify the types of data used (e.g., text, images, audio) across all training stages, from pre-training to fine-tuning.
Content Description: Summaries must detail dataset size, filtering processes (e.g., removal of harmful content), augmentation methods, and whether copyrighted or personal data is included. This also involves specifying licensing terms for the data.
Narrative Explanations: Clear, non-technical descriptions must accompany technical details to ensure accessibility for both experts and laypersons.

This level of detail is designed to balance transparency with the protection of trade secrets while enabling stakeholders to exercise their rights effectively

[1] See Section C for details.

[2] See Section C for details.

[3] https://www.gov.uk/government/consultations/copyright-and-artificial-intelligence

[4] https://ed.newtonrex.com/

[5] https://www.lordclementjones.org/2024/12/21/governments-ai-copyright-consultation-is-selling-out-to-the-techbros/

[6] https://www.gov.uk/government/consultations/copyright-and-artificial-intelligence/copyright-and-artificial-intelligence

[7] https://www.prsformusic.com/m-magazine/news/prs-for-music-announces-ai-principles

[8] https://www.prsformusic.com/press/2024/creative-rights-in-ai-coalition-calls-on-government-to-protect-copyright

[9] https://m.facebook.com/100063658326152/photos/1084206480377953/

[10] The Post Implementation Review Process, published in 2020 found (in relation to the series of exceptions introduced in 2014), the review has not identified any improvements in the assumptions which would change the original assessment. Based on the largely positive responses from the call for evidence that the original objectives remain valid, and evidence to suggest the exceptions are operating as intended, we find that it would therefore be appropriate for the exceptions to remain in their current form. See https://www.legislation.gov.uk/uksi/2014/1372/pdfs/uksiod_20141372_en_002.pdf

[11] Eva-Maria Painer v Standard Verlags GmbH (C-145/10) C:2011:798 at [89]–[94] at [121]

[12] Second Request for Reconsideration for Refusal to Register Théâtre D’opéra Spatial (Copyright Review Board September 5, 2023). U.S. Copyright Office, Library of Congress. Copyright Registration Guidance: Works Containing Material Generated by Artificial Intelligence, 16 March 2023 88 FR 16190.

[13] Australia: it is necessary to identify a human author in order for there to be an original literary work (Telstra Corporation Limited v Phone Directories Company Pty Ltd (2010) FCA 44); Singapore: copyright only arises when a work is created by a human author (Asia Pacific Publishing Pte Ltd v Pioneers & Leaders (Publishers) Pte Ltd [2011] SGCA 37

[14] Bently et al, Intellectual Property Law, 6th Edn at [138].

UK Intellectual Property Office, "Consultation outcome—Artificial Intelligence and Intellectual Property: copyright and patents: Government response to consultation" (GOV.UK, updated 28 June 2022)

[15] https://www.libdems.org.uk/tim_clement_jones

[16] https://www.iam-media.com/strategy300/individuals/christian-gordon-pullar

[17] https://openreview.net/forum?id=r6aX67YhD9

[18] https://arxiv.org/html/2501.02446v1

by Tim Clement-Jones

Government's AI Copyright Consultation is Selling out to the Techbros

We have recently seen the publication of the Government's Copyright and AI Consultation paper. This my take on it.

I co-chair the All Party Parliamentary Group for AI and chaired the AI select Committee committee and wrote a book earlier this year on AI regulation. Before that I had a career as an lawyer defending copyright and creativity and in the House of Lords, I’ve have been my Party’s creative industry spokesperson. The question of IP and AI absolutely for me is the key issue which has arisen in relation to Generative AI models. It is one thing to use tech, another to be at the mercy of it.

It is a major issue not just in the UK, but around the world. Getty and the New York Times are suing in the United States, so too many writers, artists and musicians and it was at the root of the Hollywood Actor and Writers strike last year .

Here in the UK, as the Government’s intentions have become clearer the temperature has risen. We have seen the creation of a new campaign -Creative Rights in AI Coalition (CRAIC) across the creative and news industries and Ed Newton-Rex raising over 30,000 signatories from creators and creative organisations.

But with the new government consultation which came out a few days ago we are now faced with a proposal regarding text and data mining exception which we thought was settled under the last Government. It starts from the false premise of legal uncertainty.

As the News Media Association say:

There is no lack of clarity over how AI developers can legally access training data. UK law is absolutely clear that commercial organisations – including Gen AI developers – must license the data they use to train their Large Language Models (“LLMs”).

Merely because AI platforms such as Stability AI are resisting claims doesn’t mean the law in the UK is uncertain. There is no need for developers to find ‘it difficult to navigate copyright law in the UK’.

AI developers have already in a number of cases reached agreement with between news publishers. OpenAI has signed deals with publishers like News Corp, Axel Springer, The Atlantic, and Reuters, offering annual payments between $1 million and $5 million, with News Corp’s deal reportedly worth $250 million over five years.

There can be no excuse of market failure. There are well established licensing solutions administered by a variety of well-established mechanisms and collecting societies. There should be no uncertainty around the existing law. We have some of the most effective collective rights organisations in the world. Licensing is their bread and butter.

The Consultation paper says that “The government believes that the best way to achieve these objectives is through a package of interventions that can balance the needs of the two sectors” Ministers Lord Vallance, and Feryal Clark MP seem to think we need a balance between the creative industries and the tech industries. But what kind of balance is this?

The government is proposing to change the UK’s copyright framework by creating a text and data mining exception where rights holders have not expressly reserved their rights—in other words, an ‘opt-out’ system, where content is free to use unless a rights holder proactively withholds consent. To complement this, the government is proposing: (a) transparency provisions; and (b) provisions to ensure that rights reservation mechanisms are effective.

Although it is absolutely clear that we know that use of copyright works to train AI models is contrary to UK copyright law, the laws around transparency of these activities haven’t caught up. As well as using pirated e-books in their training data, AI developers scrape the internet for valuable professional journalism and other media in breach of both the terms of service of websites and copyright law, for use in training commercial AI models.

At present, developers can do this without declaring their identity, or they may use IP scraped to appear in a search index for the completely different commercial purpose of training AI models.

How can rights owners opt-out of something they don’t know about? AI developers will often scrape websites, or access other pirated material before they launch an LLM in public. This means there is no way for IP owners to opt-out of their material being taken before its inclusion in these models. And once used to train these models, the commercial value has already been extracted from IP scraped without permission with no way to delete data from those models.

The next wave of AI models responds to user queries by browsing the web to extract valuable news and information from professional news websites. This is known as Retrieval Augmented Generation-RAG. Without payment for extracting this commercial value, AI agents built by companies such as Perplexity, Google and Meta, will effectively free ride on the professional hard work of journalists, authors and creators. At present such crawlers are hard to block.

As the NMA also say What the government is proposing is an incredibly unfair trade-off—giving the creative industries a vague commitment to transparency, whilst giving the rights of hundreds of thousands of creators to Gen AI firms. While creators are desperate for a solution after years of copyright theft by Gen AI firms, making a crime legal cannot be the solution to mass theft.

Unless news publishers and the broader creative industries can retain control over their data – making UK copyright law enforceable – AI firms will be free to scrape the web without remunerating creators. This will not only reduce investment in trusted journalism, but it will ultimately harm innovation in the AI sector. If less and less human-authored IP is produced, tech developers will lack the high-quality data that is the essential fuel in generative AI.

Amending UK law to address the challenges posed by AI development, particularly in relation to copyright and transparency, is essential to protect the rights of creators, foster responsible innovation, and ensure a sustainable future for the creative industries.

This should apply regardless of which country the scraping of copyright material takes place if developers market their product in the UK, regardless of where the training takes place.

It will also ensure that AI start-ups based in the UK are not put at a competitive disadvantage due to the ability of international firms to conduct training in a different jurisdiction

It is clear that AI developers have used their lobbying clout to persuade the government that a new exemption from copyright in their favour is required. As a result, the government seem to have sold out to the tech bros.

In response the creative industries and supporters such as myself will be vigorously opposing government plans for a new text and data mining exemption and ensuring we get answers to our questions:

What led the government to do a u-turn on the previous government’s decision to drop the text and data mining exemption it proposed?

What estimate of the damage to the creative industries it has made of implementing its clearly favoured option of a TDM plus opt out?

Is damaging the most successful UK economic sector for the benefit of US AI developers what it means by balance?

Why it has not included the possibility of an opt in to a TDM in its consultation paper options?

What is the difference between rights reservation and opting out? Isn’t this pure semantics?

What examples of successful workable opt outs or rights reservation from TDM’s can it draw on particularly for small rights holders? What research has it done? the paper essentially admits that effective technology is not there yet. Isn’t it clear that the EU opt out system under the Copyright Directive has not delivered clarity?

What regulatory mechanism if any does the government envisage if its proposal for a TDM with rights reservation/opt out is adopted? How are creators going to be sure any new system would work in the first place?

by Tim Clement-Jones

We Need Better Protection for Citizens in the Face of Automated Decision Making

The second Reading of my Private Members Bill tool place recently. It is designed to give greater rights to all of us who are subject to AI and Automated decision making in government which is becoming increasingly prevalent with the enthusiasm of the new Labour government to "digitally transform" our public services.

I thank Big Brother Watch, the Public Law Project and the Ada Lovelace Institute, which, each in their own way, have provided the evidence and underpinned my resolve to ensure that we regulate the adoption of algorithmic and AI tools in the public sector, which are increasingly being used across it to make and support many of the highest-impact decisions affecting individuals, families and communities across healthcare, welfare, education, policing, immigration and many other sensitive areas of an individual’s life. I also thank the Public Bill Office, the Library and other members of staff for all their assistance in bringing this Bill forward and communicating its intent and contents, and I thank all noble Lords who have taken the trouble to come to take part in this debate this afternoon.

The speed and volume of decision-making that new technologies will deliver is unprecedented. They have the potential to offer significant benefits, including improved efficiency and cost effectiveness in government operations, enhanced service delivery and resource allocation, better prediction and support for vulnerable people and increased transparency in public engagement. However, the rapid adoption of AI in the public sector also presents significant risks and challenges, with the potential for unfairness, discrimination and misuse through algorithmic bias and the need for human oversight, a lack of transparency and accountability in automated decision-making processes and privacy and data protection concerns.

Incidents such as the 2020 A-level and GCSE grading fiasco, where an algorithmic approach saw students, particularly those from lower-income areas, unfairly miss out on university places when an algorithm was used to estimate grades from exams that were cancelled because of Covid-19, have starkly illustrated the dangers of unchecked algorithmic systems in public administration disproportionately affecting those from lower-income backgrounds. That led to widespread public outcry and a loss of trust in government use of technology.

Big Brother Watch’s investigations have revealed that councils across the UK are conducting mass profiling and citizen scoring of welfare and social care recipients. Its report, entitled Poverty Panopticon [The Hidden Algorithms Shaping Britain’s Welfare State], uncovered alarming statistics. Some 540,000 benefits applicants are secretly assigned fraud risk scores by councils’ algorithms before accessing housing benefit or council tax support. Personal data from 1.6 million people living in social housing is processed by commercial algorithms to predict rent non-payers. Over 250,000 people’s data is processed by secretive automated tools to predict the likelihood of abuse, homelessness or unemployment.

Big Brother Watch criticises the nature of these algorithms, stating that most are secretive, unevidenced, incredibly invasive and likely discriminatory. It argues that these tools are being used without residents’ knowledge, effectively creating tools of automated suspicion. The organisation rightly expressed deep concern that these risk-scoring algorithms could be disadvantaging and discriminating against Britain’s poor. It warns of potential violations of privacy and equality rights, drawing parallels to controversial systems like the Metropolitan Police’s gangs matrix database, which was found to be operating unlawfully. From a series of freedom of information requests last June, Big Brother Watch found that a flawed DWP algorithm wrongly flagged 200,000 housing benefit claimants for possible fraud and error, which meant that thousands of UK households every month had their housing benefit claims unnecessarily investigated.

In August 2020, the Home Office agreed to stop using an algorithm to help sort visa applications after it was discovered that the algorithm contained entrenched racism and bias, and following a challenge from the Joint Council for the Welfare of Immigrants and the digital rights group Foxglove. The algorithm essentially created a three-tier system for immigration, with a speedy boarding lane for white people from the countries most favoured by the system. Privacy International has raised concerns about the Home Office's use of a current tool called Identify and Prioritise Immigration Cases—IPIC—which uses personal data, including biometric and criminal records to prioritise deportation cases, arguing that it lacks transparency and may encourage officials to accept recommended decisions without proper scrutiny.

Automated decision-making has been proven to lead to harms in privacy and equality contexts, such as in the Harm Assessment Risk Tool, which was used by Durham Police until 2021, and which predicted reoffending risks partly based on an individual’s postcode in order to inform charging decisions. All these cases illustrate how ADM can perpetuate discrimination. The Horizon saga illustrates how difficult it is to secure proper redress once the computer says no.

There is no doubt that our new Government are enthusiastic about the adoption of AI in the public sector. Both the DSIT Secretary of State and Feryal Clark, the AI Minister, are on the record about the adoption of AI in public services. They have ambitious plans to use AI and other technologies to transform public service delivery. Peter Kyle has said:

“We’re putting AI at the heart of the government’s agenda to boost growth and improve our public services”,

and

“bringing together digital, data and technology experts from across Government under one roof, my Department will drive forward the transformation of the state”.—[Official Report, Commons, 2/9/24; col. 89.]

Feryal Clarke has emphasised the Administration’s desire to “completely transform digital Government” with DSIT. As the Government continue to adopt AI technologies, it is crucial to balance the potential benefits with the need for responsible and ethical implementation to ensure fairness, transparency and public trust.

The Ada Lovelace Institute warns of the unintended consequences of AI in the public sector, including the risk of entrenching existing practices, instead of fostering innovation and systemic solutions. As it says, the safeguards around automated decision-making, which exist only in data protection law, are therefore more critical than ever in ensuring people understand when a significant decision about them is being automated, why that decision is made, and have routes to challenge it, or ask for it to be decided by a human.

Our citizens need greater, not less, protection, but rather than accepting the need for these, we see the Government following in the footsteps of their predecessor by watering down such rights as there are under GDPR Article 22 not to be subject to automated decision-making. We will, of course, be discussing these aspects of the Data (Use and Access) Bill in Committee next week.

ADM safeguards are critical to public trust in AI, but progress has been glacial. Take the Algorithmic Transparency Recording Standard, which was created in 2022 and is intended to offer a consistent framework for public bodies to publish details of the algorithms used in making these decisions. Six records were published at launch, and only three more seem to have been published since then. The previous Government announced earlier this year that the implementation of the Algorithmic Transparency Recording Standard will be mandatory for departments. Minister Clark in the new Government has said,

“multiple records are expected to be published soon”,

but when will this be consistent across government departments? What teeth do the Central Digital and Data Office and the Responsible Technology Adoption Unit, now both within DSIT, have to ensure the adoption of the standard, especially in view of the planned watering down of the Article 22 GDPR safeguards? Where is the promised repository for ATRS records? What about the other public services in local government too?

The Public Law Project, which maintains a register called Tracking Automated Government, believes that in October last year there were more than 55 examples of public ADM systems use. Where is the transparency on those? The fact is that the Government’s Algorithmic Transparency Recording Standard, while a step in the right direction, remains voluntary and lacks comprehensive adoption or indeed a compliance mechanism or opportunity for redress. The current regulatory landscape is clearly inadequate to address these challenges. Despite the existing guidance and framework, there is no legally enforceable obligation on public authorities to be transparent about their use of ADM and algorithmic systems, or to rigorously assess their impact.

To address these challenges, several measures are needed. We need to see the creation of and adherence to ethical guidelines and accountability mechanisms for AI implementation; a clear regulatory framework and standards for use in the public sector; increased transparency and explainability of the adoption and use of AI systems; investment in AI education; and workforce development for public sector employees. We also need to see the right of redress, with a strengthened right for the individuals to challenge automated decisions.

My Bill aims to establish a clear mandatory framework for the responsible use of algorithmic and automated decision-making systems in the public sector. It will help to prevent the embedding of bias and discrimination in administrative decision-making, protect individual rights and foster public trust in government use of new technologies.

I will not adumbrate all the elements of the Bill. In an era when AI and algorithmic systems are becoming increasingly central to government ambitions for greater productivity and public service delivery, this Bill, I hope noble Lords agree, is crucial to ensuring that the benefits of these technologies are realised while safeguarding democratic values and individual rights. By ensuring that ADM systems are used responsibly and ethically, the Bill facilitates their role in improving public service delivery, making government operations more efficient and responsive.

The Bill is not merely a response to past failures but a proactive measure to guide the future use of technology within government and empower our citizens in the face of these powerful new technologies. I hope that the House and the Government will agree that this is the way forward.

by Tim Clement-Jones

Lord C-J Commentary on the new Government's Science and Technology Programme

Sadly we only had 5 minutes speaking time in the recent Kings Speech debate . Here is an an extended version of my speech which goes into greater depth as to what I believe the Government should be doing in this area if it is to fulfill its growth through innovation agenda and expresses some caveats about how they plan to do this.

When we debated the New government’s proposals in the Kings speech recently the House of Lords gave a particularly warm welcome to Lord Vallance of Balham-formerly Sir Patrick Vallance- as the new Minister of State in the Department. While the Government’s Chief Scientific Adviser we know from the book “the Long Shot” how he played an critical role in the establishment of the UK Vaccine Taskforce, which was set up in April 2020 in response to the COVID-19 pandemic. He was pivotal in the recruitment of Dame Kate Bingham to chair the Vaccine Taskforce and in organizing the overall strategy for the UK development and distribution of COVID-19 vaccines. For that we should be eternally grateful.

I welcome the Government’s growth through innovation agenda and mission to enhance public services through the deployment of new technology and also the concentration of digital functions in DSIT and that it will become the centre for “digital expertise and delivery in government,improving how the government and public services interact with citizens.” in the words of the new Secretary of State, Peter Kyle.

The Government is expanding the department’s scope and size by bringing in experts in data, digital, and AI from the Government Digital Service, the Incubator for AI (i.AI), and the Central Digital Data Office to unite efforts to implement digital transformation of public services under one roof. There is great potential in justice, education, healthcare to name but three areas.

This is crucial particularly in the adoption of innovative technologies and tools in our healthcare for which Liberal Democrats believe there should be ring-fenced budgets. We need to be ensuring interoperability of IT systems too.

They government have committed too to modernising public sector procurement frameworks to enable start-ups and SMEs to drive public sector innovation and better public services. Will , however, clear, transparent framework of standards incorporating ethical principles be established? Public sector adoption is very desirable but requires trust on the part of the public/ and the citizen For instance we need to ensure that citizens can assert their rights when faced with automated decision making or live facial recognition

It has felt, under the previous regime, that universities have been under continual threat from government rather than valued as the engines of knowledge and growth and we need to be far more internationally outward looking, in particular fixing our relationship with the EU- using science and technology to address societal challenges for a more resilient and prosperous future in the words of the Royal Society.

I welcome the new Industrial Strategy Council. Does this mean we can plan for 10 years of stability and opportunity creation in science and tech sector? Successive policy changes to the R&D tax regime over the past several years have created uncertainty and additional red-tape for SMEs, putting at risk the UK’s reputation as a location for innovative businesses.We need to give businesses certainty and incentivise them to invest in new technologies to grow the economy, create good jobs and tackle the climate crisis.

Opening up what can be a blocked pipeline all the way from R & D to commercialisation, from university spinout through start up to scale up and IPO, and crowding in and derisking private investment through the National Wealth Fund, the British Business Bank and post Mansion House pension reforms, are crucial with all the local, regional, national and UK wide aspects, recognizing the importance of innovation clusters and centres of excellence. We need to tackle regional disparities and develop the innovation clusters with greater devolution to combined authorities

Digital Skills and Digital literacy are also crucial but to deploy digital tools successfully we also need a pipeline of creative collaborative and critical thinking skills. A massive skills and upskilling agenda is needed in the face of technology advances. The focus in training should be on lifelong skills grants, reforming the apprenticeship levy, and boosting vocational training and apprenticeships and many of the governments proposals in this respect are welcome.

In this context, as the the chair of a university governing council I very much welcome the Government’s new tone on the value of universities, of long term settlements, and of resetting relations with Europe and international research collaboration.

The role of university research and spinouts is crucial . The Research Excellence Framework has the perverse incentive of discouraging cooperation. We should be encouraging strategic partnerships in research especially internationally. We need to be full throated members of Horizon -the uncertainty has been extremely damaging to collaboration. I hope the government will now commit to joining the European Innovation Council as well

Last year Labour set out its plan for the life sciences.It committed to the investment of £10bn into R&D. Further, the plan said that Labour would see the creation of 100,000 jobs in the life sciences sector by 2030. The document contains a range of further welcome pledges including strengthening the Office for Life Sciences and the Life Sciences Council, and to bring laboratory clusters within the scope of the ‘Nationally significant infrastructure regime’ in England.

We need to ensure Government spending on R&D keeps pace with other nations, and establish a long-term strategy for science, research and innovation that commands cross party support.Research, development and innovation are crucial to driving productivity growth, yet our current levels of R&D investment and productivity lag the G7. I hope this means that we will soon see whether spending plans for government R & D expenditure by 2030 and 2035 match their words.

And disproportionately high overseas researcher visa costs MUST be lowered as Lord Vallance recommended in his Digital Technology Review. UK visa costs are up to 17 times higher than other leading science nations.The Royal Society have called this a “punitive tax on talent”.

But support for innovation should not be unconditional or at any cost. I hope this government will not fall into the trap of viewing regulation as necessarily the enemy of innovation. We need guardrails to ensure that, for example, AI adoption leads to public benefit.

I hope therefore that the reference to AI regulation in the King's Speech, but failure to announce a bill, is only a timing issue. What IS the Government’s intention especially given an AI bill was heavily trailed in the media?

With AI technologies continuing to develop at an exponential rate, clarity on regulation is needed by developers and adopters.There is the question too as to what extent the new government will depart from the current sectoral approach to regulating AI and adopt a cross-sectoral approach. What does the King's Speech reference to regulating "the most powerful artificial intelligence models" actually refer to? Will the government be launching yet another consultation on AI regulation?

There is no doubt we need to seize the opportunities of AI, whilst making sure we mitigate the risks of AI, ensuring ethical standards for AI development and use are adopted.

Liberal Democrats believe we need to create a clear, workable and well-resourced cross-sectoral regulatory framework for artificial intelligence that:

Promotes innovation while creating certainty for AI users, developers and investors.
Establishes transparency and accountability for AI systems in the public sector.
Ensures the use of personal data and AI is unbiased, transparent and accurate, and respects the privacy of innocent people

The government in particular should lead the way in ensuring that there is a high level of transparency and opportunity for redress when Algorithmic and automated systems are used in government. I commend my new private members bill (the Public Authority Algorithmic and Automated Decision-Making Systems Bill) to it!

The government should also negotiate the UK’s participation in the Trade and Technology Council with the US and the EU, so we can play a leading role in global AI regulation, and we should work with international partners in agreeing common global standards for AI risk and impact assessment, testing, training monitoring and audit.

As regards AI regulation in the Kings Speech itself we are promised a Product Safety and Metrology bill which could require alignment of AI driven products with the EU AI Act which seems to be putting the cart well in front of the AI regulatory horse.

We do need however to ensure that high risk systems are mandated to adopt international ethical and safety standards.At the same time in In this age of IOT we should require all suppliers to provide a short, clear version of their terms and conditions, setting out the key facts as they relate to individuals’ data and privacy.

As regards the creative industries there are clearly great opportunities in relation to the use of AI but there are also challenges and big questions over authorship and intellectual property and many artists feel threatened-the root cause of the recent Hollywood writers and actors strike. What is the government’s approach?

We need to establish very clearly that Generative AI systems need a licence to ingest copyright material for training purposes-just as Mumsnet and the New York Times are asserting- and that there is an obligation of transparency in the use of data sets and original content.

Lord Vallance is on record as wanting certainty in the relationship between IP rights and generative AI for innovator and investor confidence. And this should be the case for for creatives too. Copyright content needs to be properly remunerated by the tech platforms. The bill needs to make clear that platforms profit from content and need to pay properly and fairly, on benchmarked terms and with reference to value for end users when content is use for training Large Language Models.

And when will the government set up the promised new Regulatory Innovation Office? This was promised as an organisation to help “regulators to update regulation, speed up approval timelines and co-ordinate issues that span existing boundaries”. and as a “pro-innovation body” designed to “set targets for tech regulators, end uncertainty for businesses, turbocharge output, and boost economic growth”. We need in particular to know whether it will replace the Digital Regulators Cooperation Forum.

We must also ensure we have the right climate for FDI. The Harrington Report called for a new Business investment Strategy for the Office for Investment. Despite the previous government’s Life Sciences Vision we have seen pharma company Eli Lilley pulling investment on laboratory space in London because the UK “does not invite inward investment at this time”. Astra Zeneca decided to build its next plant in Ireland because of the U.K.’s “discouraging” tax rate.

We also need to modernise employment rights to make them fit for the age of the gig economy,including by establishing a new ‘dependent contractor’ employment status in between employment and self-employment, with entitlements to basic rights such as minimum earnings levels, sick pay and holiday entitlement.

There is a great need for need for greater diversity and inclusion in the AI workforce and science and technology more broadly. Only one in four senior tech employees in the UK are women, and only 14% from ethnic minorities.

I hope the Government too is fully committed despite its growth agenda to a full hearted support for the Competition and Markets Authority in the use of its powers under the new Digital Markets Act. I welcome the CMA’s market investigation into Cloud Services and its reassurance that it is looking broadly at the anti-competitive practices of the service providers such as vendor lock-in tactics and non-competitive procurement.

Then again how will the government kickstart better progress on Project Gigabit? Given the competitive model for rollout of broadband services that has been chosen, investors in alternative providers to the incumbents need reassurance that their investment is going onto a level playing field and not one tilted in favour of the incumbents.

Also in terms of vital cross departmental working, joining up government on Science and Technology policy we need to know what the role will be of the National Science and Technology Council and what are its key priorities.

There no mention in Labour’s manifesto on the potential impact of AI on the workplace.The TUC and Institute for the Future of Work are among those who have called for new legislation to create further legal protections for workers and employers in relation to the use of AI. The government should introduce safeguards against the invasion of privacy through surveillance technology and discriminatory algorithmic decision-making in the workplace along the lines of the TUC draft bill and algorithmic impact assessment along the lines of IFOW’s proposals.

The Government’s will also need to decide how to follow up on the recommendations of recent key Reports such as

Professor Dame Angela McLean’s Review of Life Sciences
The Vallance Review of Pro-innovation Regulation of Digital Technologies
The Independent Review of Research Bureaucracy by Professor Adam Tickell
The Independent Review of the UKRI by Sir David Grant
The Independent Review of the UK’s Research, Development and Innovation Landscape by Sir Paul Nurse
The O’Shaughnessy Report on Clinical Trials
The Independent Review of the Future of Compute by Professor Zoubin Ghahramani FRS and
The Independent Review of University Spin-out Companies by Professor Irene Tracey and Dr. Andrew Williamson

More broadly it will need to set out its approach to the science and technology framework for DSIT set out by the previous government in 2023 with its 10 priority areas Will this be revised? If so they need to set measurable targets and key outcomes in the priority areas. The government will also need to take a clear view on the key technologies we should be assisting in developing and commercialising

Then there are the pre existing financial commitments in the science and technology field. The Chancellor has said she will be checking all the previous government’s commitments for affordability. Which of the previous Government’s financial commitments will she confirm? For instance

The £7.4 million upskilling fund pilot to help SMEs develop AI skills.

Investing up to £100 million in the Alan Turing Institute over the next five years (up from £50 million)

The £100 million investment by the British Business Bank into ICG,in respect of the Long-term Investment for Technology and Science (LIFTS) initiative

The £1.1 billion funding for 65 Centres for Doctoral Training (CDTs) through the Engineering and Physical Sciences Research Council (EPSRC), covering key technologies like AI and engineering biology.

As regards the bills in the Kings Speech I look forward to seeing the details but the Digital Information and Smart Data bill does seem to be heading in the right direction in the areas being reinstated. The retention and enhancement of public trust in data use and sharing is the overriding need so that the potential of data can be unleashed through better trusted sharing of data. It is really important that we do more to educate the public about how and where our data is used and what powers individuals have to find out this information

I hope other than a few clarifications, especially in the research area, and in terms of the constitution of the ICO we are not going exhume some of the worst areas of the old DPDI bill and we have ditched the idea of a Brexit EU divergence Dividend by the watering down of so many data subject rights.

Will the Government give a firm commitment to safeguard our data adequacy with the EU? Will the bill introduce the promised ban on the creation of sexually explicit deepfakes?

I also hope that the Government will confirm that the intent of the reinstated Digital Verification provisions is not compulsory national Digital ID but the creation of a market in digital ID providers that give choice to the citizen.

Given that LinesearchbeforeUdig, or LSBUD is claimed to already achieve the aims of NAUR, to be more widely used than the National Underground Assert Register NUAR and be more cost-effective, I hope also that Ministers will meet LSBUD and provide us all with much greater clarity around these proposals.

I hope that we can include other positive spects of the late unlamented DPDI Bill in the bill: More action on online fraud, digital identity theft, deepfakes in elections Misinformation and disinformation, misogyny as a hate crime, there is quite a list of possibilities. Together with new models of personal data control which were advocated as long ago as 2017 with the Hall Pesenti review, especially through new data communities and institutions and an enhanced ability to exercise our right to data portability, especially in real-time and more regulatory oversight over use of biometrics and biometric technologies.

I of course welcome the pledge to give coroners more powers to access information held by technology companies after a child’s death AND to banning the creation of sexually explicit deepfakes.

As regards the Cyber Security and Resilience Bill, events of recent days have made it clear we are not just talking about threats from bad actors. It reminds us how dependent we are on just a few overly dominant major tech companies. With Microsoft and AWS enjoying a combined UK market share of around 70-90%, according to the Competition and Markets Authority’s own research, the lack of competition presents a serious concerns for our nation's security and resilience. There needs to to be a rethink on critical national infrastructure such as cloud services and business software which are now essential public utilities and also how we are wholesale replacing reliable analogue communication with digital systems without backup.

In the bill I hope will we see the long awaited amendment of the Computer Misuse Act to include a statutory public interest defence, as called for by Cyber Up, to allow white hat research into computer systems as the Vallance report recommended. The rules for computer evidence must be changed too. We must have no more Horizon scandals!

by Tim Clement-Jones

This is a piece I wrote recently published in the New Statesman's Spotlight on Technology Supplement

Achieving balance between human potential and machines isn’t just possible – it’s necessary.

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