Artificial Intelligence: UK policy and global concerns.

A recent document described UK policy on the use of artificial intelligence in the reduction of carbon emissions (BEIS, 2022). This involves co-funding a ‘virtual centre of excellence on AI innovation and decarbonisation’ and funding projects ‘which further the development of AI technologies to support decarbonisation’. Comment on the document noted the increasing use of AI tools to ‘solve some of society’s current and future challenges’, and referred to the UK’s National AI Strategy. It also noted that while ‘AI has great potential, it can also cause harm’, and referenced the ‘AI Bill of Rights’ proposed for the USA (E&T, 2022). The two themes of UK AI strategy and global concern over the use of AI will be developed below.

The UK’s National AI Strategy outlined a ‘ten-year plan to make Britain a global AI superpower’ and foresaw a profound impact by AI on the UK and the wider world during that period (BEIS 2021). The document referred to earlier initiatives such as the 2017 Industrial Strategy ‘which set out the government’s vision to make the UK a global centre for AI innovation’ and the 2018 AI Sector Deal designed to ‘boost the UK’s global position as a leader in developing AI technologies.’ The National AI Strategy set out to build on existing strengths and recognised the power of AI to ‘increase resilience, productivity, growth and innovation across the private and public sectors.’

The UK Government is advised on such matters by the AI Council, set up in 2019. It describes itself as focussing on three main areas: developing the public understanding of AI, tackling negative perceptions and boosting confidence in AI among businesses and society; increasing skills in AI and the diversity of people working in the field AI; and ‘exploring how to develop and deploy safe, fair, legal and ethical data-sharing frameworks’ (AI Council, 2023).

The AI Roadmap published by the AI Council lists sixteen ‘recommendations to help the government develop a UK National AI Strategy’. These include two topics related to carbon emissions, and the document also has a short section on climate change (AI Roadmap, 2021). Carbon emissions and AI are mentioned in relation to developing smart materials for energy storage, and in the general sense of access to data, governance, and the development of cleaner systems, products and services. The section on climate change contains a number of general statements on the essential part that AI technologies can play in areas such as reducing greenhouse gases in the atmosphere and ‘the environmental impacts of goods, services and human activities’ and mentions more specific applications in forecasting supply and demand in real time, combating illegal deforestation and understanding Arctic sea ice loss. However it is perhaps fair to say that much of the section is merely aspirational. Elsewhere the document addresses the place of AI in areas such as supporting high growth AI startups, enabling public sector adoption, health and social care, and defence and security. It also notes public scepticism towards AI, and the need for a stronger governing environment: there is an emphasis on reassuring the public ‘that the use of AI is safe, secure, fair, ethical and duly overseen by independent entities’ and on giving confidence to business. Some readers may feel that public scepticism towards AI is seen primarily as an unfortunate obstacle in the way of economic opportunity, rather than an expression of well-grounded fears.

A rather different attitude to the dangers of AI is shown by the Blueprint for an AI Bill of Rights, which opens with the statement that ‘among the great challenges posed to democracy today is the use of technology, data, and automated systems in ways that threaten the rights of the American public.’ There follow examples in which automated systems can be unsafe, biased, discriminatory, or undermining of privacy (White House, 2022). Five principles are identified ‘that should guide the design, use, and deployment of automated systems’. They are protection from unsafe or ineffective systems; protection from discrimination by algorithms and systems; protection from abusive data practices; notice that an automated system is being used and an explanation of how this may affect outcomes; and the option not to use the automated systems but to have access to a human alternative where appropriate. The discussion of the five principles is supported by examples, possible actions to implement good practice, and a range of citations.

A further approach to the future of AI is outlined in an open letter published by the Association for Mathematical Consciousness Science which addresses the question of consciousness in AI systems (AMCS, 2023). The letter describes itself as ‘a wakeup call for the tech sector, the scientific community and society in general to take seriously the need to accelerate research in the field of consciousness science’ since the ‘increasing computing power and capabilities of the new AI systems are accelerating at a pace that far exceeds our progress in understanding their capabilities and their “alignment” with human values.’ The authors of the letter cite the Large Language Models such as ChatGPT and Bard, and consider it inevitable that such systems will soon ‘be constructed to reproduce aspects of higher-level brain architecture and functioning’, and may possibly go on to have ‘feelings and even human-level consciousness.’ They note that AI systems ‘have already been observed to exhibit unanticipated emergent properties’ and their future development may change ‘what society can do to control, align and use such systems.’ (Emergent properties in the context of the future of AI form part of an online discussion (AI Revolution, 2023) and in the context of Large Language Models they are the subject of a paper by O’Connor, 2023).The emergence of consciousness in AI systems would raise ethical, legal, and political concerns beyond those presently recognised, and the writers call for accelerated research in consciousness ‘in order to ensure that AI development delivers positive outcomes for humanity’. Reference is made to a previous open letter, calling for an immediate pause of at least 6 months in the training of AI systems more powerful than the language model created by OpenAI and numbered GPT-4 (FoL, 2023).

Problems increase as AI systems approach Artificial General Intelligence, where they equal or surpass human capabilities in most tasks, or go beyond this to Artificial Super Intelligence (ASI), possibly becoming self-aware and significantly surpassing human intelligence. Tzimas (2021) speculates that ‘ASI systems could very well decide to restructure our political and social systems, eventually even suppressing humans, with the best of intentions, as for example to reverse climate change or secure human welfare.’ Benekova et al.  (2022) warns that ‘we should by no means be looking for an AI that is too similar to human intelligence’, given that ‘science has created or contributed to causing a number of global problems that  are  not  just  a  menace  but  even  present  a  real  existential  threat  to  mankind, such as weapons of mass destruction or climate change’.

In the context of climate change, even if we limit discussion to present AI systems, it is not difficult to see how just one of the ills to which AI systems are prone, namely unconscious bias, could affect the decisions made by them. Such bias could be on the grounds of race, religion or politics, favouring one group over another on matters such as the allocation of resources. At a broader level, bias could exist regarding species, affecting decisions on whether or not to provide protection to a given organism.

References

AI Council, 2023, AI Council, online, accessed 9 May 2023

https://www.gov.uk/government/groups/ai-council

AI Revolution, 2023, The AI revolution: Google’s developers on the future of artificial intelligence: https://www.youtube.com/watch?v=880TBXMuzmk

AI Roadmap, 2021, UK AI Council, online, accessed 9 May 2023

https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/949539/AI_Council_AI_Roadmap.pdf

AMCS, 2023, The Responsible Development of AI Agenda Needs to Include Consciousness Research, Association for Mathematical Consciousness Science, online, accessed 10 May 2023

https://amcs-community.org/open-letters/

BEIS, 2021, National AI Strategy, online, accessed 8 May 2023

https://www.gov.uk/government/publications/national-ai-strategy

BEIS, 2022, Government launches £1.5 million AI programme for reducing carbon emissions, BEIS, press release, online, accessed 8 May 2023

https://www.gov.uk/government/news/government-launches-15-million-ai-programme-for-reducing-carbon-emissions

Benekova, Z., et al., 2022, Artificial Intelligence, Value Alignment and Rationality, Sciendo, online, accessed 8 May 2023

https://sciendo.com/article/10.2478/bjes-2022-0004

E&T, 2022, UK launches £1.5m AI green innovation programme, Engineering and Technology, Nov. 2022, online, accessed 8 May 2023

https://eandt.theiet.org/content/articles/2022/11/uk-launches-15m-ai-green-innovation-programme/

FoL, 2023, Pause Giant AI Experiments: An Open Letter, Future of Life institute, online, accessed 10 May 2023

https://futureoflife.org/open-letter/pause-giant-ai-experiments/

O’Connor, 2023, Emergent Abilities of Large Language Models, AssemblyAI, online, accessed 10 May 2023

https://www.assemblyai.com/blog/emergent-abilities-of-large-language-models/

 Tzimas, T., 2021, Artificial Intelligence and Human Rights: Their Role in the Evolution of AI, Heidelberg Journal of International Law, online, accessed 10 May 2023

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3947615

White House, 2022, Blueprint for an AI Bill of Rights, online, accessed 8 May 2023, online, accessed 8 May 2023

https://www.whitehouse.gov/ostp/ai-bill-of-rights/


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