This report from UK think tank the Adam Smith Institute presents an optimistic vision for artificial intelligence, automation and the future of work.
The Adam Smith Institute’s latest paper, by Fellow James Lawson, makes the optimistic case for the future of artificial intelligence and employment. Machine learning is the most important area advancing artificial intelligence (AI). It allows more complex problems to be solved than traditional coding and work to be automated more easily. AI is real and increasingly used all around us in a wide range of applications, from entertainment to transport, healthcare and office work. There have been widespread concerns about the impact of AI on jobs even before the economic crisis caused by COVID-19. These concerns will only intensify in the challenging period ahead. There have been similar concerns about the impact of new technology on jobs for centuries. These worries are often driven by the Luddite fallacy: assuming that robots and workers are competing for a fixed number of jobs in a static economy. Automation has historically been a force for good and doomsday scenarios have not transpired. Some jobs are highly vulnerable to automation from AI. An estimated 30-40 per cent of UK work is at high risk. These studies provide a useful directional guide about the scope of automation but are subjective, may not translate into actual job losses, and are unclear on timelines or the net impact on employment. The net impact of AI on jobs and the flexibility of the labour market will determine the future outcome. This paper uses a Technological Unemployment Matrix as a framework to guide policymakers. The most likely scenario is that AI will support greater prosperity. There is no trend so far towards the doomsday scenarios, and the UK labour market is flexible, with a strong record of delivering high employment. AI will create new jobs, boost productivity and increase purchasing power. There will be some losses to mitigate, with temporary displacement and pockets of unemployment.Read Full Report