Evidence Meeting 6 – Inequality, Education, Skills and Jobs – Overview

 In Evidence, Evidence Meeting Overview

Evidence Meeting 6 | Monday, 16 October 2017 | 5:30 – 7:00pm
Committee Room 1, House of Lords

Main Focus:

How can AI reduce inequality and not be a creator of it? Ideas
  • Social exclusion and living – standards
  • Skills
  • Education and training
  • The future of work

Evidence:

Speakers:

  • Professor Margaret Ann Boden, OBE, ScD, FBA –  Research Professor of Cognitive Science at the Department of Informatics, University of Sussex
  • Azeem Azhar – VP, Head of Venture & Foresight and Chief, Exponential View, Schibsted Media Group
  • Olly Buston – CEO, Future Advocacy
  • Calum Chace – Book Author, “The Economic Singularity” & “Surviving AI”
  • John Hawksworth – Chief UK Economist, PwC
  • Laura James – Technical Principal, Doteveryone
  • Professor Peter McOwan – Professor of Computer Science, School of Electronic Engineering and Computer Science, Queen Mary University
  • Shamus Rae – Partner, Head of Innovation and Investments, KPMG

Overview

In the previous five APPG AI meetings, the unprecedented impact AI is having – and will continue to have – on society has been made clear. The evidence gathered thus far has mirrored the recent Hall/Pesenti review of AI, urging the UK to seize the opportunities of these disruptive technologies and deliver on their economic potential. However, the community has simultaneously shed light on a set of risks accompanying these opportunities. A common worry amongst the group has been that the benefits of AI might not be distributed across all members of society in a fair and inclusive way.

Hence, Chairs Stephen Metcalfe and Lord Tim Clement Jones asked 8 panellists and a wider audience of 131 government, academia, and industry representatives to join them in the sixth APPG AI meeting in discussing AI implications on inequality, education, skills and jobs.

Professor Margaret Boden was first to provide evidence. Highlighting the growing dependence on AI technologies, she recommended a restructure of education/training at all levels, and for all ages. From primary school onwards, people will need to be alerted both to its potential and to its limitations, she advised. Some tangible constructs can include: specialty courses in data management, retraining of school teachers, and MSc degrees for knowledge transfer.

Azeem Azhar spoke next, presenting the group graphs illustrating the growth in inequality and decline in labour share of value in the UK. He proposed two potential scenarios: one of mass technological unemployment and another of job creation. Both scenarios suggest that our transition period (over the next 5-15 years) will levy mental and financial stresses on millions of people. To mitigate this distress, companies should realise their responsibility to their workforce, lifelong education must become available, and the job transition dialogue must be reframed.

Laura James took the microphone next. She reminded the group that AI doesn’t decrease or increase inequality; it is only a tool that humans must decide how to use. Laura emphasised the importance for government and the public sector to get contract negotiation right. Access to data should be granted in ways that ensure public benefit reflecting the future value which can be realised from the unlocking of insights and intelligence, and positive public outcomes. Government must think strategically to make sure AI doesn’t increase inequality gaps and although this might require notable investment, the long-term benefits will make the process worthwhile.

The fourth speaker was KPMG’s Shamus Rae. He agreed with Azeem that there are two likely scenarios and noted that it is up to us for the utopian version to prove the right one. According to Shamus, in the long-term, AI will impact all jobs, regardless of whether they belong to the low-skilled or high-skilled categories. We need to rethink how we measure inequality, so that we can include capacity and capability in the assessment. We also need to be thinking of how we can educate citizens to be adaptable to the job disruption that will likely take place.

John Hawksowrth shared some of PwC’s recent findings showing the economic opportunities (it is estimated that AI will boost the UK economy by 10% by 2030) but also the disruption that is anticipated to take place (30% of UK jobs are in risk of being automated). He recognised that disruption will not affect all social groups and/or regions equally, and we need to realise that AI will create clear winners and losers. He recommended: vocational training for young people, investment in life-long learning, and the rethinking of a welfare system with a stronger safer net. John also pushed government to work fast to build the evidence now so we can make the right decisions tomorrow.

Calum Chase took the floor, warning the community that technological unemployment is a real prospect. Unlike the past, the technologies of today are able to displace cognitive skills and, hence, it is unlikely that more jobs will be created then lost. He asked for the UK government to invest in think tanks to research the risks and opportunities of AI, and use this evidence to pave the path for how society can overcome a likely period of transition and panic.

Olly Buston emphasised the scale and scope of disruption in job markets as a result of today’s automation. He announced a new report that Future Advocacy would publish the following day, illustrating the impact of automation in individual parliamentary constituencies. The report concluded that he highest levels of future automation are predicted in Britain’s former industrial heartlands in the Midlands and the North of England, as well as the industrial centres of Scotland. Olly hopes that this regional analysis will make the issue of technological unemployment more relatable to individuals and society will consequently engage more with the topic.

Professor Peter was last to give evidence, highlighting much of what was already said in the importance of policy making to seize opportunities and mitigate risks. He focused on the need for educational reform in order for citizens to be empowered with the skills needed to benefit from AI technologies. He asked for academics and the rest of the stakeholders to work together to demystify AI and make it more accessible to all. He also urged the need to train career teachers, and other relevant figures, in order for them to be equipped with the right knowledge to guide youth towards job demands of the future.

The Chairs thanked the panel and asked the MPs, Lords, and other key stakeholders to pose their questions. An engaging discussion soon flourished, brainstorming a political economy model that will seize AI benefits and, simultaneously, bring about inclusive growth – regional, social, and sectoral.

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