We are joined by Anthony Katsur, the CEO of IAB Tech Lab. Anthony discusses standards within the ad tech industry. He explained how IAB Tech Lab set and propagates global standards, actions to ensure compliance from advertisers, and industry trends for a more privacy-centric ad tech space.

When we navigate a webpage, it is fairly easy for our mouse movement to be tracked and collected. Today, Luis Leiva, a Professor of Computer Science discusses how these mouse tracking data can be used to predict age, gender and user attention. He also discusses the privacy concerns with mouse tracking data and possible ways it can be curtailed.

On the show, Aleksandra Urman and Mykola Makhortykh join us to discuss their work on the comparative analysis of web search behavior using web tracking data. They shared interesting results from their analysis, bordering around the user preferences for search engines, demographic patterns, and differences between how men and women surf the net.

Did Aristotle Use a Laptop? That's a question from the StrategyQA benchmark which highlights the stretch goals for current artificial intelligence systems. Answering a question like that requires several cognitive steps and reasoning. Constructing a dataset of similarly challenging questions is a major undertaking. On today's episode, Mor Geva returns to share details about the creation of StrategyQA and the larger Big Bench dataset it has been included in.

While at first glance, the use of ad blockers drops the revenue of news publishers, this may not be completely true. On the show today, Shunyao Yan, an Assistant Professor in Marketing at Leavey School of Business, Santa Clara University, discussed the effect of ad blockers on news consumption and how ad blockers can potentially be helpful for news publishers.

People who do not want their data tracked and shared online can pay a token for a cookie paywall. But are the websites keeping to their side of the bargain? Victor Morel, a Postdoc candidate at the Chalmers University of Technology joins us to discuss his work around auditing the activities of cookie paywalls. He discussed the findings from his analysis and proffers some solutions to making cookie paywalls more transparent.

The advancement of generative language models has been a force for good, but also for evil. On the show, Avisha Das, a post-doctoral scholar at the University of Texas Health Center, joins us to discuss how attackers use machine learning to create unsuspecting phishing emails. She also discussed how she used RNN for automated email generation, with the goal of defeating statistical detectors.

Peter Gloor, a Research Scientist at the MIT Center for Collective Intelligence, takes us on a new world of tribe classification. He extensively discussed the need for such classification on the internet and how he built a machine learning model that does it. Listen to find out more!

We hear about the impeccable achievements of GPT-3 models, but such large generative models come with their bias. On the show today, Conrad Borchers, a Ph.D. student in Human-Computer Interaction, joins us to discuss the bias in GPT-3 for job ads and how such large models can be de-biased. Listen to learn more!