Engage Digital

Discussion

Artificial Intelligence (AI) is the science of using computers to do things that to-date have required the human mind. It is the science of programming a computer to learn how to do, rather than to just do.

Certain AI functionality has been around for decades. However, the progress of AI has accelerated in recent years due to the rise of big data, the proliferation of connected sensors and actuators (the Internet of Things), and access to vastly increased processing power; especially through the cloud. AI, including its application in robotics, is now commonly referred to as the "Fourth Industrial Revolution". This revolution will see brands and governments engage digital to drive economic growth in our increasingly connected world.

For Artificial Intelligence to deliver fully on its promise, the technology will require predictability and trust. The two are interconnected: predictable legal treatment facilitates trust. Additionally, the successful use of AI will also require a robust ethical code to deal with issues that are too complex or fast changing to be adequately addressed by legislation.

What’s also clear is that with such a wide range of stakeholders with an interest in AI, the government will need to support the development of a thriving ecosystem around the technology. In this role, government would facilitate communication between stakeholders and encourage the sharing of best practice, as well as support research into AI techniques and help small businesses get off the ground.

Opportunities and Challenges

There are several opportunities for the UK in this space:

• The UK could champion the ambition to become the global centre of developments in Artificial Intelligence technologies. To do this, there must be collaboration between private enterprise, finance and researchers.
• The UK already has many of the key foundations in place for a thriving AI ecosystem: good infrastructure, access to finance, an entrepreneurial culture, a skilled workforce and a fast-growing digital economy. Each of these can improve even further, as is set out in other areas of this site, but that does not take away from the fact that the UK is in a strong position to take a global leadership position in the development of AI.
• The UK is already one of the main centres for creative scientific research and development, with many world class universities and research institutions.
• Significant AI start-ups have already risen out of the UK (the main example, DeepMind, being one of the world's leading AI companies). To ensure this continues, the UK will wish to retain top talent and promote small businesses so that they continue to contribute to the UK’s digital economy.
• New companies need space to thrive, with lower regulatory hurdles and support to help them grow. This requires pro-active lending policies from the world of finance, the understanding of regulators and appropriate approaches to working visas to allow for the recruitment of necessary talent.

But these opportunities also come with associated challenges:

• Cooperation - How to get thought leaders from different sectors to cooperate and communicate where they have varying aims and values. For example, academics looking to expand knowledge on the subject and businesses looking to maximise profits.
• Competition - other countries and cities are starting to build up their capabilities for AI, particularly in Fintech. Research funding is also competitive and there are new AI hubs developing around the world (in places such as Montreal in Canada and Singapore). It is important to maintain the UK’s lead to continue to attract the right people and companies to invest in the country.
• Talent - securing the right talent to work in new AI companies is a crucial part of developing a strong ecosystem for tech companies. Government can act to aid the inflow of the highly skilled talent where it’s required to make these companies a success.

Our view

We welcome steps already being taken in this space, including the £400 million Digital Infrastructure Investment Fund; and the funding boost of £17.3m from the Engineering and Physical Sciences Research Council (EPSRC) to support the development of new Robotics and Artificial Intelligence (RAI) technologies in universities across the UK.

None of this is for government alone and it is important for the UK – government, business, academia and society more widely – to collaborate and build on its existing position of strength so that we can engage AI further to differentiate and boost growth. These opportunities include:

Setting up broad-based AI Forums in strategic locations, bringing in members of private enterprise, academia, finance and policy makers to encourage dialogue between sectors on AI issues. The focus should be on regions with strong research institutions, as this is where the best new AI talent will most likely congregate.

Maintaining and increasing funding for research into AI. Investment is needed in universities to encourage graduates and post-graduates to continue research into AI techniques. There is currently a global skills shortage in this area. The UK is well placed to be the centre for the training of the next wave of AI specialists if the right investment is made. Partnerships with technology companies should be enhanced and encouraged as a way to gain further funding for this important area of research.

Continuing to promote policies and existing mechanisms for entrepreneurial businesses in the AI space. Providing incentives for the public sector to start adopting AI technologies. Support must be in place to help start-ups and small businesses set up and start trading.

Providing world class opportunities and open doors for the talented individuals in this field. This includes supporting educational establishments so that we can bring forward a new generation of talent ready for the future. Reskilling workers who may have lost out due to the introduction of AI technologies will also be important.

Steps to Implementation

• Create and promote AI Forums in targeted regions to bring in significant parties from all sectors, including finance, academia, private enterprise and public policy. Open a dialogue with these stakeholders to encourage further cooperation.
• Review support for small businesses and ensure that it is suitable for AI start-ups. Ensure that high-tech players in the space are given regulatory space and support from the tax system so that they can grow. Consider also the support given to universities and start-ups coming out of top universities.
• Assess current funding levels for AI research and increase grants to aid research in this area.
• Support the roll out of 5G. Infrastructure is vital for a thriving AI ecosystem in what is an increasingly connected world. Now that cloud computing can provide the processing power needed for this, connectivity will be key to getting these technologies to market. Support for infrastructure is vital.

Discussion

Artificial Intelligence (AI) is the science of using computers to do things that traditionally required the human mind. It is a technology that will accelerate the digital transformation of industry, and will prove essential to the success of our digital economy in what is an increasingly connected world.

For AI to deliver on its promise, however, it will require predictability and trust. These two are interrelated. Predictable treatment of the complex issues AI will throw up, such as accountability and permitted data uses, will encourage investment in and use of AI. Similarly, progress with AI requires consumers to trust the technology and the fairness of how they are affected by it and how their data is used; predictable and transparent treatment facilitates this trust.

A robust legal framework will be needed to deal with those issues too complex or fast changing to be addressed adequately by legislation. But the political and legal process alone will not be enough. For trust to flourish, an ethical code will be equally important.

The government should therefore encourage discussion on the ethics of AI, and ensure all relevant parties are involved; bringing together the private sector, consumer groups and academia to develop an ethical code that keeps up with all relevant technological, social and political developments. Government efforts should be collaborative with existing efforts to research and discuss ethics in AI. There are many existing initiatives which could be encouraged, including the Alan Turing Institute, the Leverhulme Centre for the Future of Intelligence, the WEF Centre for the Fourth Industrial Revolution, work being done by the Royal Society, and the Partnership on Artificial Intelligence to Benefit People and Society. There are industry bodies, such as the Institute of Electrical and Electronics Engineers, working on developing standards and certification systems for Ethically Aligned Design of AI and autonomous systems. Where possible making those efforts inclusive rather than not exclusive or isolated is desirable.

Opportunities and Challenges

As Artificial Intelligence becomes more sophisticated, it will start to make or assist decisions that have a greater impact on individual lives. This will raise ethical challenges as people adjust to the larger and more prominent role of automated decision making in society.

In the UK, AI has exciting implications in the consumer, healthcare, transport, professional services and defence industries. It promises to deliver learning and evolving systems that are more efficient and safer, smarter, and better able to operate at scale. For example:

• Big data analytics - applying AI across massive data sets enables functionality such as autonomous vehicles, remote healthcare and advanced network management.
• Liquid work force - use of AI in certain workforce processes will enable the separation of specific tasks and the exploration of new disaggregated resourcing models.
• Automation - the entrance of AI to industries including professional services will allow the automation of tasks previously reserved to humans, enabling them to be done faster and at greater scale.

But these opportunities come with associated ethical challenges:

• Decision making and liability - as AI use increases, it will become more difficult to apportion responsibility for decisions. If mistakes are made which cause harm, who should bear the risk?
• Transparency - when complex machine learning systems have been used to make significant decisions, it may be difficult to unpick the causes behind a specific course of action. The clear explanation of machine reasoning is necessary to determine accountability.
• Bias - machine learning systems can entrench existing bias in decision making systems. Care must be taken to ensure that AI evolves to be non-discriminatory.
• Human values - Without programming, AI systems have no default values or 'common sense'. The British Standards Institute BS 8611 standard on the 'ethical design and application of robots and robotic systems' provides some useful guidance: 'robots should not be designed solely or primarily to kill or harm humans; humans, not robots, are the responsible agents; it should be possible to find out who is responsible for any robot and its behaviour.
• Data protection and IP - The potential of AI is rooted in access to large data sets. What happens when an AI system is trained on one data set then applies learnings to a new data set? Could this infringe data protection and privacy rights? Who, if anyone, should own the output of AI thought processes?
• Social dislocation - extensive deployments of AI could lead to social dislocation.
• Cybersecurity - as more reliance is placed on AI, the importance of cybersecurity will increase. Security must be a top priority for all actors if trust is to be maintained.

Our view

We welcome steps already being taken in this space, including its commitment to undertake a major review on the development of artificial intelligence. As such, the UK already enjoys strong foundations in AI. But more can always be done.

None of this is for government alone and it is important for the UK – government, business, academia and society more widely – to collaborate and build on its existing position of strength so that we can engage AI further to differentiate and boost growth. These opportunities include fostering a public discussion to build a set of fundamental ethical principles for Artificial Intelligence development. Flexibility is necessary to allow for private bodies to develop and commit to more specific codes in certain sectors, building on these fundamental principles.

Such codes should focus on:

• Responsibility for mistakes - it must be clear where liability lies when systems make mistakes. General principles should guide accountability.
• Transparency in decision making - it must be clear when AI systems must explain their actions to humans, showing why a decision was made, and when, if ever, such transparency is not necessary.
• Avoiding bias - steps must be made to stop systemic bias. Core values such as equality, diversity and lack of discrimination must be promoted.
• Core ethical values - what are the core ethical values of AI to be?
• Data protection and IP - the importance of data protection, IP ownership and cyber security must be recognised and balanced against the need to use data to promote innovation.
• Mitigating social dislocation - the codes should confront what obligations rest on actors who deploy AI to mitigate the social dislocation that results.
• Cybersecurity - the need for strong protection against hacking will increase as AI systems take a heightened role in society.

Sectors where specific codes may need to be developed include:

• Autonomous Vehicles
• Healthcare
• Finance
• Energy
• Defence

Steps to Implementation

• Set up an AI Advisory Body to consider ethical issues, foster discussion forums and publish resulting guidance to the industry and regulators. Communicate developments to the public to show initiative.
• Gather intelligence on and participate actively in the development of such codes internationally. The 'Asilomar AI Principles' and the 'Partnership on AI' codes should be considered among others to pick up on the latest thinking.
• Develop core ethical principles - engage with stakeholders to put together and publish fundamental ethical principles.
• Encourage the development of sector specific codes particularly in fast moving areas, as mentioned above.