Episode description

Joining us at Arthur HQ in this episode is Dr. Rachel Cummings, an Associate Professor of Industrial Engineering & Operations Research at Columbia University who is known for her principled and practical work in differential and data privacy, crossing machine learning and public policy. She sat down for a chat with our Chief Scientist John Dickerson about:

• Her work in differential privacy, which is at the intersection of academia, industry, and policy
• How she got into the field of differential privacy, what she likes about it, and what she would change
• Her advice for people interested in academia, policy, or differential privacy in general
• What she’d say to present-day policymakers
• What areas of tech she thinks are overhyped and risky, and her predictions for the next decade
• Considerations around the tradeoff between privacy and accuracy

Watch the video, including Rachel's research presentation prior to the Q&A, on Youtube: https://bit.ly/3Ki7lHc 

Learn more about Arthur: https://bit.ly/40JXiC5

Learn more about Rachel: https://bit.ly/40Ml6oE  

[2:48] Tell us more about yourself, what led you to Columbia and to economics/ML/differential privacy?

[5:11] What advice do you have for someone who wants to move into differential privacy and privacy research writ large, whether it’s an academic/research focus or a policy/communications focus?

[7:15] Do you have any advice for present-day policymakers?

[8:52] If you could change one thing about the field, what would it be?

[11:00] What are your predictions for the next 1-3 years? What’s overhyped right now? Do you have some hope for breakthroughs? Where can we see business impact or policy impact immediately?

[12:42] What are your predictions for the next 10 years? What are the biggest opportunities or things you would focus on if you were just getting into the field? 

[14:57] What are some risks or things to look out for?

Audience Q&A

[16:21] Differential privacy’s goal is to not have to reason about background knowledge or prior belief, but people think about privacy in a manner that requires reasoning about priors. Is it possible that differential privacy is just not compatible with what people want from privacy? 

[20:39] How do you see the areas of cryptography and differential privacy cooperating in the future?

[22:48] When you were structuring your research with your collaborators, were there particular industry verticals or companies that you had in mind as potential adopters or that you would be interested in partnering with as the research progresses further?