Time Machines Are Selling Potato Chips

Veronica Ahern guests. We anticipate adtech's influence on the quantification of consumers, while considering how algorithms continue to expand & exploit the gaps in our perceived reality.

(1:44) Mitch introduces Veronica Ahern, fresh off her career move at Oracle. We compress a hundred years of advertising into one brief recap -- revealing how the industry progressed from transporting their ads to physical destinations all over the built environment, to now focusing primarily on one tiny screen and the manipulative factors that dictate whether showing an ad will provide a return on investment. (6:52) We rag on the old-school industry performance metric of "circulation", a hilariously uninformed and illogical method of quantifying efficacy. Veronica offers up some of the new-age, creepily-precise ROI metrics by comparison. (8:54) Mitch asks Veronica whether advertising has incidentally become the most well-funded psychological study in human history. We point to research conducted by Stanford University and the University of Cambridge, wherein an algorithm fueled only by a subject's Facebook likes was able to gauge that person's personality more accurately than their close friends and family. (14:47) Veronica walks us through the adtech "time machine": programmatic real-time bidding auctions. We look towards a potential future where such technologies could squeeze entire algorithmic lifetimes into the millisecond-long window between a real-world event and a human's perception of that event. (25:15) Mitch's hot take: privacy is the enemy of progress. The argument primarily stems from the nature of data as something that only has value when it is shared; Veronica riffs on it by emphasizing the need for advertisers, consumers and policymakers to become better-educated and transparent about the value exchange that data as a currency creates. (35:15) We address the farce of personally identifiable information (PII) as a red herring in the grand scheme of consumer data, and wishful thinking that the average person could simply peek under the hood of adtech programs (or any algorithm-driven technologies) in order to decide how they should work or what's malfunctioning.