Online targeted advertising is a primary source of revenue in the internet economy, and while we know that personal data collection for targeted advertising violates privacy, we know little about how targeted advertising affects us. Recent research shows that online targeted advertising divides and isolates us by preventing us from collectively flagging ads we object to, unlike in the physical world where regulators can be alerted to harmful content. Machine learning algorithms used to screen ads for harmful content can be biased and only ban the clearest violations, while contextual harms associated with targeted ads can amplify biases. Regulators traditionally take a reactive approach to regulating advertising, relying on consumer complaints, which raises questions about the ads that go unchallenged. To address these challenges, consumers should be restored as active participants in the regulation of online advertising. This could be achieved by blunting the precision of targeting categories, instituting targeting quotas, or banning targeting altogether.
Authors: Silvia Milano, Brent Mittelstadt, and Sandra Wachter
Original Publication in The Conversation