Service science offers a very broad set of tools and theoretical models for fitting all those pieces together. And it also makes me realize not only is AI policy sort of very fast developing and a newish space, but I would imagine just to research subfield on AI governance is probably fairly new. So there are still obviously issues by kind of soaking all this properly and analyzing yet and figuring out which interactions which path to focus on as opposed to others. But service science is helpful for that because it approaches this big problem with a big set of tools. That makes it easier to point towards the most kind of significant challenges and the most viable solutions.
In episode 57 of The Gradient Podcast, Andrey Kurenkov speaks to Blair Attard-Frost.
Note: this interview was recorded 8 months ago, and some aspects of Canada’s AI strategy have changed since then. It is still a good overview of AI governance and other topics, however.
Blair is a PhD Candidate at the University of Toronto’s Faculty of Information who researches the governance and management of artificial intelligence. More specifically, they are interested in the social construction of intelligence, unintelligence, and artificial intelligence, the relationship between organizational values and AI use, and the political economy, governance, and ethics of AI value chains. They integrate perspectives from service sciences, cognitive sciences, public policy, information management, and queer studies for their research.
Have suggestions for future podcast guests (or other feedback)? Let us know here!
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Outline:
* Intro
* Getting into AI research
* What is AI governance
* Canada’s AI strategy
* Other interests
Links:
* Once a promising leader, Canada’s artificial-intelligence strategy is now a fragmented laggard
* The Ethics of AI Business Practices: A Review of 47 Guidelines
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