Between December 2024 and February 2025, the UK’s Intellectual Property Office (IPO) ran a public consultation on how to achieve a balance between the rights of human copyright holders, whose works, often taken from the internet, feed the training of Artificial Intelligence (AI)  models, and the right of the AI developers to develop their industry.

The IPO set out the problem by describing the issues faced by the two sides as:

1. the problem for the copyright holders is that they are ‘are finding it difficult to control the use of their works in training AI models and seek to be remunerated for its use’;
2. the problem for the AI developers is that they are ‘finding it difficult to navigate copyright law in the UK’.

Hence, the IPO sought views on ensuring that a set of twin Intellectual Property (IP) objectives is met. The first of these is providing sufficient ‘control’ of copyright holders on their material so that they may be fairly compensated for the use of their IP when used for training AI; the second is ensuring that the ‘access’ of AI developers to large, often copyrighted, datasets is not hampered so that ‘investment’ and ‘innovation’ in the AI industry are also protected. The IPO acknowledged that the debate on copyright and AI ‘has concentrated on large, commercial, generative AI models’ (IPO 2024), which are most likely to affect the creative industries.

However, such a framing of this complex and contentious issue, though commonsensical,  stands in danger of overlooking inequities developing towards another group of stakeholders – those users of the internet who provide, what the IPO has termed, ‘low-value data’ (IPO 2024). The economic interests of this group do not seem a significant part of this IPO consultation as they generally are not in most IP-centred debates on the issue. Yet these Users provide a significant amount of the revenue flowing to AI developers from their daily activities on the internet and on other digital media (Image 1).

Image 1: Algorithms surveille Users even as they provide free services. From collecting data to improve User experience, they move to utilising this data for influencing behaviour so that the AI owners may sell advertisement space by matching advertisers with Users and assuring success for advertisers.

Image © 2025 by Sasmita Sinha. All rights reserved

Changing uses of IP in the AI landscape

The reasons may have to do with the traditional concerns of IP protection as they have evolved over the past 350 years. The development of intellectual property protection in its modern form is mostly traced back to England’s Statute of Anne of 1710. The statute recognised the need to protect the rights of creators of intellectual products, such as books, to profit from their originality, skill and labour (Deazley 2008). The books were deemed to be the property of their authors due to being ‘the Product of their Learning and Labour’ (The statute of Anne, 1710, as cited in Deazley 2008, italics added).

This view of intellectual property is important because until the rise of certain kinds of AI, this ‘internal’ quality in the creation of one’s intellectual property was precisely what gave an individual the right to profit from it. Intellectual property emanates from within the mental processes of its creator(s) and becomes recognisable as private property in law once it is inscribed in a tangible medium, such as on paper or a canvas.

Currently, however, there are AI whose development and functioning is more akin to traditional industrial processes as shown in Image 2, which describes both the creation and functioning of an algorithm at Facebook. Both these processes utilise intellectual and behavioural input from the Users of Facebook in order to create Intellectual Property owned by the company, bringing it substantial growth and profits.

Image 2: One of Facebook’s algorithm that develops from collecting and analysing User data in order to then
direct feeds to the individual that are beneficial for the company’s growth though not always beneficial for the User

Image © 2025 by Sasmita Sinha is licensed under CC BY 4.0

In such cases, it would seem that AI development uses individual User’s data more like a traditional industrial activity. For example, house-building uses raw materials like clay that are baked into the bricks, which are ultimately transformed into a final product that does not retain any immediately identifiable trace of the clay in its original form. Despite their lack of visibility, however, such raw materials have to be paid for in a way that the Users’ data feeding the Facebook algorithm does not.

Using a post-Marxist approach, Morreale et al (2024) have discussed such daily activities by Internet Users as the creation of surplus value, which is finally harvested by platforms like Google and Facebook. According to the authors, the Users perform tasks like those shown in Image 1 above in the form of  ‘micro-tasks … [acting like] … unwitting labourers: individuals who are unaware‘ that their seemingly innocuous activities like creating playlists and rating books are then harnessed and utilised for AI training by these companies. The authors call these practices ‘labour exploitation’ because, they argue, that the ‘technology companies unilaterally extract surplus value from individuals to train AI’.

From ‘productivity’ to distributive justice

These ruminations on the nature of what constitutes intellectual property worthy of protection and financial rewards become significant in the context of AI discussions like the IPO’s consultation since, in the past decade, governments around the world have intervened actively to facilitate the AI industry’s access to large datasets for free or at relatively low cost. The primary driver of such interventions has been an almost non-negotiable emphasis on productivity gains.

However, in the context of the IPO consultation, it is notable that the consultation text cites the Global AI Index 2024, which shows the UK in the 4th position globally and as a world-leading power in AI development and innovation. As Hilty et al. (2021) elaborate, governments are expected to use policy initiatives to drive forward innovation in sectors where there is a clear identified need for innovation to solve an identified social problem. Going by the data cited by IPO, there is no such need in the UK at the moment in the AI development industry. Writing more generally, Hilty et al (2021) also agree that ‘on a general level one can presently observe that AI innovation appears to be thriving’ (p. 62).

Instead, the volume of concern is rising at the helpless exposure of individuals to, what essentially amounts to, a mining of the human individual for corporate profit. The increasing power- and economic inequalities ushered in by AI deployment are a cause for concern too. Placed in the context of the phenomenal per capita economic growth that has taken place globally in the past 50 years or so (Data Page: GDP per capita 2023), in spite of a significant jump in the world’s population at the same time (which has more than doubled to its current 8 billion people in the same period [PM 2025]), the emphasising of productivity and competitiveness seems misplaced.

It is, therefore, suggested in this series of blogs that reframing the issue as one primarily involving distributive justice within society rather than one centred on promoting productivity captures the current problems to be solved in a much more meaningful manner. Of course, IP law has traditionally been more concerned with rewarding innovation than matters of justice. However, by exploring the definition of ‘intellectual’ in IP laws, I propose that a widening of this definition, particularly via the lens of distributive justice, may be a much more effective approach to a just balancing of the rights of all the stakeholders in the current AI-development scenario, than staying within established ideological parameters, which may erase the contributions of the most vulnerable group and deny them their valid economic share of the AI pie.

 

References

Deazley, R. (2008) ‘Commentary on the Statute of Anne 1710', in Primary Sources on Copyright (1450-1900), eds 
L. Bently & M. Kretschmer, www.copyrighthistory.org [online resource].

Intellectual Property Office (IPO), 'Copyright and AI: Consultation', December 2024, https://www.gov.uk/government/consultations/copyright-and-artificial-intelligence/copyright-and-artificial-intelligence#c-our-proposed-approach
[online resource] (accessed 20.9.2025). Contains public sector information licensed under the Open Government Licence v3.0.

Morreale, F. et al. (2024) 'The unwitting labourer: extracting humanness in AI training', AI & Soc, 39, 2389–2399,  
https://doi.org/10.1007/s00146-023-01692-3 [online resource].

Population Matters (PM), https://populationmatters.org/the-facts-numbers/ [online resource] (accessed 20.9.2025).

'Data Page: GDP per capita', part of the following publication: Max Roser, Bertha Rohenkohl, Pablo Arriagada, 
Joe Hasell, Hannah Ritchie, and Esteban Ortiz-Ospina (2023), 'Economic Growth'. Data adapted from Bolt and 
van Zanden. Retrieved from
 https://archive.ourworldindata.org/20250915-110645/grapher/gdp-per-capita-maddison-project-database.html 
[online resource] (archived on September 15, 2025).

 

Does public perception of the innovator as a human individual promote corporate oligopolies?

 

Innovation is a term that has been increasingly popular and even ‘fashionable’ in social sciences since the 1970s (Mohr 1976, p.1). With the establishment of the World Intellectual Property Organization (WIPO), and especially since the globalization associated with the rise of digital economy, its use and importance have entered the popular parlance too. Mohr (1976) points out that innovation as a term is ‘associated with improvement’ and the ‘act of innovation’ is highly ‘laden with positive value’ (1976, p. 1).

This positive association is hugely important for driving policies in a certain direction, where benefitting the innovator is considered an indisputable public good. Significantly, then, the image of the ‘innovator’ is of utmost importance in garnering public support behind these policies. A simple collocation check for the word ‘innovator’ yields 40 sentences, of which the majority, shown in the table below in the column on the right, suggest a meaning that conjures up a human individual rather than a corporate entity. Yet in policy and academic literature and debates on the subject, the meaning more readily conjured up is that of a commercial entity. Edler et al. (2015) write in a review of academic literature on the link between IPRs and innovation policy that ‘ Intellectual property rights are major means for firms to appropriate the value of their inventions’ (p. 6, emphasis added).

Table showing collocation for the word ‘innovator’–suggesting corporate v individual as its meaning

(Click on the link above to download and view the table)

Throughout their discussion of the link between IPRs and innovation policy, the meaning of the innovator as corporate entities predominates. As IPRs are a crucial instrument for allocating benefits of innovation, this meaning becomes utterly crucial in navigating the tension that the authors identify between ‘the monopoly function and the diffusion function’ (p. ) that the IPR regimes contain. While the public support for allowing the benefits of innovation to go to innovators reflects an understanding of rewarding creative or problem-solving individuals or small enterprises, it often fails to fully appreciate the huge policy tilt being created in favour of large corporate bodies.

Economically perhaps the most significant, but also the most controversial of the IPR instruments is the patent. Edler et al. (2015) summarise that in policy research, design and evaluation IPRs are taken as a barometer of the innovative capacities of companies, regions and countries even though ‘patents as indicators of innovation are highly contested’ (p. 6). This is because patent registration often reflects strategic considerations rather than only ‘the protection of essential invention (Blind et al 2005)’ (Edler et al. 2015, p. 6). The question, therefore, arises as to whether the exclusive protections offered to companies by patents and the benefits accruing from them, converting into a substantial increase of their economic power, are really rewarding a human capacity that the original IPR system set out to protect and which the public view of an innovator applauds protection for.

Similarly, the word innovation’s ‘positive value’ that Mohr (1976, p. 1) pointed to derives from its underlying association with ideas of ‘improvement’. What is significant to emphasise is that in the public imagination the meanings of ‘improvement’ still relate to a betterment of the fundamental human condition. Innovations, across board, are taken to make better those essential needs that apply to all humans and hence cannot be denied on the basis of power, politics or other contentious issues. Innovation, the implication is, binds us together across divisions and its value cannot be questioned. For example, the article at the WIPO site here https://www.wipo.int/en/web/ipday/2017/ten_innovations     discusses 10 innovations that better human lives by making them ‘healthier, safer, and more comfortable’. Health, safety and comfort are fundamental human needs and anything that is said to improve them carries a visceral appeal.

Some of the ideas listed in the WIPO article fill one with admiration like the one about the “auto-exploration bra”, created by a young man, motivated  by his mother’s late cancer diagnosis, to provide a better equipment that women can use on a regular basis to improve the chances of breast cancer detection early. In fact, the medical technology field has been a burgeoning field of research with ‘Medical-related patents [seeing]… a 76.3% increase in granted patents, from 30,429 in 2023 to 53,648 in 2024‘ but it is difficult to determine how many of these are by individuals when the field is dominated by big companies like Medtronic, Johnson & Johnson, Cilag AG, Becton, Dickinson and Company, and Boston Scientific. Under the circumstances, innovations like the “auto-exploration bra” get headlines and create a warm emotional envelope of positive public sentiment that benefits all medical changes listed as innovation. All these innovations, however, are not only improvements in a certain medical field but are also, if not primarily, economic instruments that shift economic and other power equations between the patient/customer and the manufacturer/professional involved in prescribing their use. The respect for innovation and scientific research can often obscure the societal, economic and environmental impacts of new products and evade deeper scrutiny balancing the magnitude of betterment promised with that of the shift in control of human and natural resources that organised corporate innovation puts in the hands of the large companies.

Writing in 2020, in the context of digitisation, Veale pointed out that ‘considerations of whether ‘computing’ was useful in a given context’ were often not given adequate space in deliberations on increasing use of technologies. Instead, simply ‘increasing the availability or intensity of digital use’ was considered as ‘improvement’. Hence there is a process of collectivization at work here whereby all ‘innovators’ are generally perceived as individuals and the rewards they received through IPRs and other policies are considered fair compensation for a valuable human capacity contributing to a desirable meeting of basic human need. For large scale adoption of a product or service, its innovative value itself should not be reason enough. Some of the other questions that might be asked are:

1. What is the process in place right now for serving this need?
2. What will be the percentage of improvement? Will it be the same in all contexts? If not, are there thresholds that may be devised below which the adoption of the product may not be of much value?
3. What will be the environmental cost of producing this article?
4. How does the improvement in numbers compare with the environmental cost?
5. Will data from large numbers of people be collected? If so, who will be in the best position to create further marketable ‘innovations’ from it at the fastest speed? Will it be the same patent owner? If, yes, how will it affect the power balance in that field of enterprise? Will it create monopolies or oligopolies?

The vital importance of this last question cannot be stressed enough because this is where the collectivization of meaning of ‘innovator’ interacts materially with power distribution in society. In capitalist societies, which would currently encompass almost the whole world, the discourse of innovation validates swelling inequalities. By triggering human sympathies reserved for remarkable human achievement, the discourse of innovation supports a rolling back of the State in order to incentivize innovative individuals to solve human problems and be rewarded economically for it without cumbersome bureaucratic processes.

However, the result has often been that it has proved increasingly difficult to challenge the power shift to big business that this discourse facilitates. Complex factors in modern capitalism dictate the need for constant innovation of new products by businesses to keep making profits (Figure 1 below). Since business profits provide jobs, welfare, infrastructure and defence money through taxation, national governments are increasingly hobbled in their role of providing societal checks on the power of big business. The larger the government spend, the more the governments must rely on businesses, in effect, creating a power nexus that leaves little freedom for any interests that may diverge from those desired by parties to this nexus.

Figure 1: Modern capitalism and the power of organised innovation

The resulting decimation of effective State power, when coupled with this discourse, places inordinate control over vital natural and societal resources in the hands of larger private multinational corporations, which, in reality, dominate patent grants. Innovation is no longer only, or even primarily, rewarding individuals. Moreover, the logic of an urban industrial society denies most individuals any direct production relationship with nature because natural resources are viewed primarily as ‘standing resources’ (Heidegger 1953) to feed industrial needs.

Inevitably, this logic places governments and ordinary citizens in the power of commercial organisations working for their own private profit rather than for public welfare, but still becoming intrinsically linked to it. Industrialised innovation in the hands of organisations, which include some of the richer universities, that can devote entire departments and large chunks of corporate budgets simply to pursuit of innovating for the market disadvantages individual innovators, who find it hard to compete with this mighty machine.

Edler et al (2015) point out that government measures are often aimed to lead directly to ‘subsequent innovation’ (p. 7), further reducing the spontaneous element in innovation activities and putting large organised innovation at an advantage that grows cumulatively with each successful innovation. Both within and between nations power relations become concentrated on feeding increasing amounts of natural and other resources to organisations that can churn out products faster and faster. In a majority of cases these happen to be large multinationals, relying on increasing automation that further adds to their capacity to innovate. The snowballing of economic rewards for these companies that occurs from this process leaves few challengers to their power in an international governance space that increasingly resembles a Hobbesian state of nature.

Particularly in the case of developing countries, the importance of Foreign Direct Investment (FDI) being promoted by both theorists and practitioners, means that national governments have to agree to skewed agreements to attract FDI. Under Bilateral Investment Treaties (BIT) mostly Western investors are privileged because the BITs, in a majority of cases, do not include issues of importance for the local populace ‘such as labour, migration, environment and human rights clauses‘. Further, the State–Investor dispute mechanisms operate away from the public gaze and scrutiny in ways that most often allow ‘foreign investors [to]… elude the justice systems of host countries and challenge host states before arbitral tribunals‘.

Changing public perception of the terms innovator and innovation, therefore, to reveal their close links to issues of power at both national and international levels is of crucial importance. The public ought to be able to choose between forcing a change of direction between the two options of reverting the reality back to the original meaning of benefitting more individual-centred innovation or erecting power centres in society that effectively check and balance the ill effects of the currently over-weaning powers of the corporates in the name of supporting innovation. The IPR regime can be amended to facilitate these changes too.

References

 

ANAQUA (2025) ‘Anaqua analysis of USPTO patenting statistics 2024,’ Patent Management, 30 January 2025, available online (accessed 20.7.2025).

Downs, Jr., G. W. and Mohr, L. B. (1976) ‘Conceptual issues in the study of innovation,’ Administrative Science Quarterly, vol. 21, no. 4, Dec., pp. 700–715.

Edler, J., Cameron, H. and Hajhashem, M. (2015) The intersection of intellectual property rights and innovation policy making – a literature review. World Intellectual Property Organisation: Department for Transition and Developed Countries of the World Intellectual Property Organization, World Intellectual Property Organization, Geneva.

Marchini, J., Morales, J. and Roffinelli, G., ‘Conflicts between Latin American countries and transnational corporations : The challenges of the region in the face of asymmetrical investment treaties,’ Investment Treaty News, 30 July 2018, IISD, available online (accessed 20.7.2025).

Veale, M. and Borgesius, F. Z. (2021) ‘Demystifying the Draft EU Artificial Intelligence Act,’  SocArXiv. July 6. doi:10.9785/cri-2021-220402.

WIPO (2017) ’10 innovations that are improving lives,’ World Intellectual Property Organization website, available online (accessed 20.7.2025).

 

Image courtesy Photo by Jason Goodman on Unsplash

 

Riots, bias, IPR and questions on AI technology

Politics this week, in both US and the UK, has featured prominently some of the issues touched on in earlier blogs about AI technology. As always, things move so fast with this technology that politicians and, to a far greater extent, the public are left reacting haphazardly to its effects and uses. The lack of coherence and the serious issues at the heart of using this technology, therefore, demand constant thought and clarity lest we walk into an era of new norms that none of us remember choosing, far less agreeing with.

Social media and public information

With reference to the riots that took place in the aftermath of stabbings in Southport on 29 July 2024, Professor Andrew Chadwick, professor of political communication at Loughborough University, and an expert in the spread of online misinformation, has been quoted as saying that a ‘complicated mix‘ of ingredients converges to bring about the kind of heightened passions and public disorder seen in the wake of the stabbings. He was being asked about the role played by social media rumours that had spread the notion that the stabbings had been carried out by a migrant, possibly a Muslim or Syrian person.

Professor Chadwick emphasised, however, that it was not just the false name or the rumour around it but

the way these are used by public figures and interested parties that is equally important in causing the kind of surprising scenes of disorder witnessed this week.

This issue has been simmering for nearly a decade since information began to come to light about social media algorithms that promote controversial or emotive content much more aggressively than normal material, for commercial reasons. In March 2021, Karen Hao reported in MIT Technology Review that even after the fierce Cambridge Analytica scandal of 2018, in which personal data had been ‘surreptitiously siphoned‘ from millions of Facebook users to sway the 2016 US elections in Donald Trump’s favour, Facebook efforts at mitigation had not targeted the spread of misinformation via their platform.

Instead their efforts had been focussed much more on addressing bias against disadvantaged groups on their platform. While in itself a laudable objective, the better-targeting of marginalised groups actually serves to promote the business aims of social media platforms so it is difficult to attribute this initiative to pure altruism. Hao quotes Professor Hany Farid of University of California, Berkeley to make the point that the aim of business growth at all costs means ‘maximizing engagement’ trumps considerations of veracity and truth. In fact, Professor Farid suggests that ‘harm, divisiveness, conspiracy’ tend to become the friends of businesses in these circumstances by bringing them more subscribers.

With this information in their hands, and social media becoming the major source of socio-political communications, politicians of dubious intent have revelled in placing incendiary gossip, innuendo and out-of-context diatribe on their accounts to gain political traction. The early promise of the internet giving a voice to the people, and thus promoting democracy, has become a far more mixed proposition in light of these developments. Ethical certainties of the past and the role of various players in their upkeep are often exhaustingly complicated now.

Ethical confusion and the need for a new business model

Ironically, while the rumours and misinformation regarding the Southport incidents in the UK spread through X, formerly Twitter, the owner of the platform was accusing Google algorithms in the US of obstructing the flow of information on Donald Trump, though other reporters did not always have the same search experience that he did.

With serious and frivolous, true and false, pleasant and atrocious all jumbled up in the same digital space, and competing for the individual’s attention at lightening speeds and voracious volumes, the ease with which misinformation can be unleashed amongst the public is alarming for supporters of democracy. In his 2016 book Homo Deus, Professor Yuval Noah Harari had pointed out how our private data is the most valuable asset in the digital universe which we end up giving away for free to Big Tech algorithms.

All those thousands of likes and shares on social media, as well as information about our relationships and interests, feeds the algorithms that enable large platforms to attract advertisers. What is more, this information helps build profiles that can potentially be used to exert subliminal control of users by ‘nudging’ them to buy more of what they like or, alternately, to help politicians understand ‘what each candidate needs to say [to each user] in order to tip the balance’ in their favour (Harari 2016, p. 397). This level of control of individual views and choices is pernicious to democratic societies because it subverts popular will, through unaccountable power and influence, for commercial or political gain.

A business model that prioritises economic growth alone, even at the expense of weightier, but often intangible, human imperatives poses a grave risk to societies valuing human freedom and well-being as non-negotiable values.

Facial recognition, bias and shifting boundaries of police authority

At the same time, the ethical dilemmas are deepened by the need of the authorities to gain control of the situation. Reacting to the riots in the wake of the Southport incident, the prime minister indicated that the government ‘might use these riots to sanction greater use of facial recognition cameras‘. This use of fire to fight fire, or technology to combat technology, may seem inevitable, however, much caution has been urged with regard to the use of facial recognition technology for law enforcement.

The use of this technology involves real-time comparison of facial biometrics of members of the public with facial biometrics of people on a police watchlist. Images of people captured through CCTV cameras are converted to numerical data and the data is then compared with similar numerical data for the images on the watchlist. Images that do not match are deleted instantaneously while those matched are then checked by a human operative before action is taken. In the case of Bridges v The South Wales Police in 2020, the judges noted that the South Wales Police had not failed in its efforts to ‘to equip itself with information on possible or potential disparate impacts, based on the information reasonably available at that time’, yet their judgement was that

‘too much discretion is currently left to individual police officers. It is not clear who can be placed on the watchlist nor is it clear that there are any criteria for determining where AFR [facial recognition technology] can be deployed.’

Thus, it is easy, even with the best intentions, for this technology, which one of the experts in the trial testified was often found to contain ‘bias on grounds of race or sex’, to be misused. Facial biometrics form part of a person’s private data and are thus protected under various legal provisions. Even ‘the Information Commissioners [have] advised there must be a “very high bar” for its use‘. Once again, the neutrality of the technology is only as good as the datasets that the underlying AI that does the work is trained on. Due to historic bias against certain minorities in particular, any datasets from historical policing records, have a good chance of passing on that bias to the AI technology.

Yet, as an expert witness to the Court noted ‘the precise makeup, scale and sources of the training data [for AI] used are commercially sensitive and cannot be released’. It is in this manner that intellectual property rules often make it difficult to ensure adequate transparency if bias is to be ruled out with complete certainty. The balance between profit-needs of commercial enterprises and public good seems tilted too far in favour of technology companies at the moment and is justified in the name of constant need for economic growth.

As we inch our way into a human environment clogged with AI applications – from those controlling Google searches, to those controlling our ‘user experiences’ of social media, or banking, or healthcare, or self-driving cars, or legal needs, or predicting our chances of getting cancer, or writing our essays, or drawing our pictures – the convenience and surface excitement often hide from view the impact of this exchange of breadth of information for depth, on human cognition and judgement.

As Henrik Skaug Sætra, Mark Coeckelbergh & John Danaher have warned,

‘…the challenges in question are non-trivial … the system … refers not just to individual AI companies, but to the larger eco-system of companies, social structures, and political arrangements that generate the negative impacts in question … You have to change the entire business model and the supporting legal–political infrastructure.’

Each time a government gives in to using AI technologies that further erode the privacy of the individual that has been hard-won after centuries of struggle, they strengthen that legal–political infrastructure that Sætra et al. are arguing against. The most vital challenge of our times is to stem this tide and then hope to turn it back.

Photo by The 77 Human Needs System on Unsplash