The choices we make now will determine how AI affects our jobs and future prosperity.
In this year’s Sanjaya Lall Memorial Lecture, Visiting Professor Daron Acemoglu urges us not to fall for the myth that technological advancements lead naturally to greater prosperity and better lives.
Techno-optimism, particularly strong in the US, would have us believe that time and the market will miraculously smooth out the rough edges and short-term problems of technologies such as AI (artificial intelligence), and create benefits for us all. Acemoglu calls this the ‘productivity bandwagon’: the narrative that as technology improves, productivity increases and results in higher wages for workers.
Drawing on arguments in his recent book, Power and Progress: Our Thousand Year Struggle Over Technology and Prosperity, Acemoglu shows how the automation of processes such as weaving during the Industrial Revolution in Britain led not only to depressed wages (the real earnings of textiles workers declined by about 50 per cent over 90 years) but also to greater surveillance, poor living conditions, overcrowding, squalor, and disease. Things only started improving after about 1840 as institutions changed and trade unions became stronger.
If firms today continue to fixate on the ability of AI to automate existing jobs and do not consider how to use technology to create new tasks and better jobs, there is no incentive for them to raise wages or otherwise share productivity gains with workers. Economic inequality and power differentials will only rise.
But all is not lost. Indeed, there is all to play for, he says, if governments regulate appropriately and labour movements and civil society act to redress power imbalances and reshape the direction of technology. AI should be used to help humans, not replace them. For example, he suggests that AI could help combat the current shortage of electricians and others trades by providing better information and training.
The post-lecture discussion covers topics as varied as Universal Basic Income, the thin line between concern and fear-mongering, and global inequality. He concludes: ‘It's going to be the next decade or so where we're going to see how much AI, what type of AI and who's going to benefit from it, so I think being realistic about where we are and what we can do is very important.’