AI was expected to revolutionize the way we do just about everything, but the changes that were promised haven’t materialized as quickly as expected. What’s holding AI back?
On this episode of Disruptors, an RBC podcast, host John Stackhouse sits down with Ajay Agrawal to dig into this question and more. Ajay is a professor at the University of Toronto’s Rotman School of Management; he was named to The Order of Canada this year for his contributions to enhance Canada's productivity, competitiveness, and prosperity through innovation and entrepreneurship, and he’s the founder of the Creative Destruction Lab, an early proponent of AI ingenuity.
Ajay is also the author of two books about AI. His latest, Power and Prediction: The Disruptive Economics of Artificial Intelligence, co-written with fellow Rotman professors Joshua Gans and Avi Goldfarb, focuses on the fact that AI hasn’t lived up to the excitement that he himself helped create. When he looked back at the predictions made in his 2018 bestseller, Prediction Machines: The Simple Economics of Artificial Intelligence, he realized it was time to shift focus away from AI as a technology and instead look at the economics of the systems in which it operates.
This episode also features an exciting new AI technology called GPT-3, which uses deep learning to produce text that reads like it was written by a human. It was created by Open AI, an organization founded in San Francisco in 2015. Ilya Sutskever, their chief scientist, is Canadian and a U of T alum.
GPT-3 even provided a brief summary of John and Ajay’s conversation:
“Creative Destruction Lab was designed to address the market failure of commercializing early stage science. The program helps entrepreneurs with the judgment they need to turn their scientific innovation into a business. AI is characterized as a drop in the cost of prediction.
AI is not going to figure out the complexities of health care. There are many barriers to deploying AI in health care, including system frictions that are not aligned with the incentives of hospitals, doctors, and insurers. It is difficult to experiment with AI in health care because of the need for a system-level overhaul.
AI has the potential to help reduce discrimination by making it easier to detect and then fix. However, too much regulation of AI has the potential to stifle innovation. Canada is doing well on the research side of AI, but there is room for improvement on the application side.”
Amazingly concise! This episode also features an AI-generated John Stackhouse, so listen in and see if you can tell the difference.
To read Ajay Agrawal’s newest book, “Power and Prediction: The Disruptive Economics of Artificial Intelligence”, co-written with fellow Rotman School of Management professors Joshua Gans and Avi Goldfarb click here. Follow this link to the University of Toronto’s article about testing out GPT-3 and this one for more about Open AI, GPT-3 and Dall-E2. Some background on IBM Watson can be found here.