The fear of algorithmic decision-making and surveillance capitalism dominate today's tech policy discussions. But instead of simply criticizing big data and automation, we can harness technology to correct discrimination, historical exclusions, and subvert long-standing stereotypes.

Orly Lobel is the author of “The Equality Machine: Harnessing Digital Technology for a Brighter, More Inclusive Future” and Warren Distinguished Professor of Law at the University of San Diego School of Law. Lobel is one of the nation's foremost legal experts on labor and employment law. She is also one of the nation's top-cited young legal scholars.

Orly and Greg discuss how collecting more data and adding more inputs into decision algorithms may be beneficial to expose disparities in current frameworks in the real world, and help us to right past injustices and ongoing inequities.

*unSILOed Podcast is produced by University FM.*

The idea of data minimization

22:24: At the EU level, there's this term that is now coming into the federal policy and legislation before Congress, which is "data minimization." This idea that the default needs to be that we need to collect as little as possible and use the data that we collect to a very narrow channel of predefined use because that will protect our privacy. And the assumption also kind of the next step in this fallacy analysis that's really flawed is that when we collect more information, we're actually going to be harming the more vulnerable.

Is the law counterproductive?

15:21: I think that we've designed our laws in ways that are counterproductive by restricting the inputs into decision-making rather than checking on the outputs.

Rethinking the role of public investment

37:21: We're at a moment where there's going to be acceleration. There's always been a lot of changes. But right now, for sure, there's going to be a leap in speed in which some jobs are going to be annihilated and others are going to be available. So there's very much a role for public investment there for digital literacy and re-skilling that will not necessarily be provided by the market.

What makes an employee do their job well?

31:56: When they think about their careers and their human capital as their own, even from time zero, employees will invest much more in doing the job well.

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• The Equality Machine: Harnessing Digital Technology for a Brighter, More Inclusive Future
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