Heather Zheng on Privacy and AIHow Machine Learning (and manila folders) can protect your personal data
What if you had a way to upload as many selfies as you wanted to instagram or facebook, and still protect yourself from facial recognition software? Turns out, that’s not a pipe dream! In fact, the SAND Lab (Security, Algorithms,Networking and Data) at the University of Chicago is developing all sorts of tools and techniques to help us protect our digital privacy.
Joining us in this episode, Heather Zheng, PhD from the SAND lab, walks us through both examples of current data privacy concerns, as well as new potential threats to privacy. But don’t worry, for each concern, Heather is able to provide a solution to keep your data private.
Find our transcript here: LINK
Curious to learn more? Check out these additional links:
(Guy) Fawkes image/photo masking: http://sandlab.cs.uchicago.edu/fawkes/
Research about tracking you through your home with wi-fi: http://sandlab.cs.uchicago.edu/adversarialwifi/
Research on recovering your key strokes: https://sandlab.cs.uchicago.edu/keystroke/
Hidden Markov models explained: https://brilliant.org/wiki/hidden-markov-models/
Allyson’s episode about GPT-3: [LINK]
Follow Heather Zheng: https://people.cs.uchicago.edu/~htzheng/
This episode was audio engineered by Tyler Damme.
Music by Blue Dot Sessions.
The Institute for Mathematical and Statistical Innovation (IMSI) is funded by NSF grant DMS-1929348.