Big Data, Advertising and the Phenomenon of Ad Blockers
A series of podcasts exploring the issues
The phenomenon of ad blocking hits on issues at the intersection of data science, user experience, privacy and advertising and publishing business models. To explore these issues, I recently talked with three experts for the NYC Media Lab podcast to try to understand what’s driving consumer demand for ad blockers, how the media and technology ecosystem will react, and what the future will hold for advertising technology.
In the first installment in the series we hear from Doc Searls, the influential blogger and author of The Intention Economy: When Customers Take Charge, co-author of The Cluetrain Manifesto and Director of Project VRM at Harvard’s Berkman Center for Internet and Society, where he served as a fellow from 2006 to 2010. Check out his related posts on ad blocking here.
In the second episode in the series, we hear from Claudia Perlich, who is Chief Scientist at Dstillery, where she develops the machine learning that drives digital advertising. Perlich is also a professor at NYU’s Stern School of Business, where she teaches a course on data mining for business intelligence. Check out recent pieces on O’Reilly and PSFK that feature Perlich.
Finally, in the last episode in the series we hear from Dave Carroll, associate professor of media design in the MFA Design and Technology graduate program at Parsons The New School for Design, who has written about a variety of issues in digital media, including recently about the rise of ad blocking technologies. You can read his pieces on Medium here.
I hope you’ll listen to these podcasts and engage in the discussion on these issues both here and on Twitter. Follow @nycmedialab, @justinhendrix, @profcarroll, @dsearls, and @claudia_perlich for more.