Google and Facebook are monopolies. Does it matter? Feat. Sally Hubbard

In this episode of Innovation For All, Sheana Ahlqvist speaks with Sally Hubbard, antitrust expert and investigative journalist at The Capitol Forum. Learn whether giant tech companies are building monopolies (spoiler alert: they are) and why that unfair advantage matters.

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In this episode, you’ll learn:

  • What is Antitrust law?
  • Is fake news an antitrust problem?
  • How monopolies amplify inequality
  • What would it look like to unmonopolize big tech companies?

As an antitrust expert and investigative journalist, Sally Hubbard has forged a successful career specializing in tech platforms, competition and regulatory risk. Currently leading The Capitol Forum’s coverage of monopolization issues, Sally’s expertise in antitrust and tech giants, including Google, Apple, Facebook, and Amazon, yields predictive analysis of regulatory outcomes. Sally founded and hosts Women Killing It!, a podcast series that interviews career rockstars to find out what has worked for them, how they got where they are today, and what they wish they knew sooner.

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When Are “Fair” Algorithms Better Than Accurate Ones? with Osonde Osoba

Artificial Intelligence continues to penetrate our lives. As it does so, we should be wary of its ethical and social implications.

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Osonde Osoba, an engineer at the RAND Corporation and a professor at the Pardee RAND Graduate School, joins Sheana Ahlqvist in today’s episode of Innovation For All Podcast to talk about fairness in Artificial Intelligence and Machine Learning. AI has the ability to seriously impact our lives, which is why Osonde is pushing for systems that are accurate, unbiased, and flexible.

Discover what areas we should be wary when handing over the decision-making to AI’s, why this isn’t just a technical issue, but also political, and who should we put in charge of these systems. Learn also the importance of accountability, ethics, privacy, and regulation in AI systems.

IN THIS EPISODE YOU’LL LEARN:

  • The difference between Machine Learning and Artificial Intelligence
  • Should AI systems intentionally be made to ‘align with our comfort’?
  • What roles do the legislators, policy makers, etc. do?
  • Strategies to protect Data Privacy in AI and ML models
  • Regulatory rules between the developers and the users
  • If technology changes so rapidly, how can regulators keep up?
  • How can we build accountability into AI & ML?

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