Data Tug of War: Personalize the Experience Versus the Demand for Greater Control

Popularized in 2008, the Nudge theory gained greater notoriety as tech companies sought to use machine learning algorithms to scale specific user behavior. Social media platforms notwithstanding, nudge interventions are often developed to influence behavior to the benefit of society as whole; however, there are often unintended consequences to the individual.  

Recent research explores two ways nudges can be personalized: through choice or through delivery. In the context of the world of work, the former could consist of automating a nudge based on point in the candidate journey – for job seekers who have been to the career site but not yet started the application process, a message about coming back to learn more, and for those who have started the application process, but not finished, a message about completing the application. Delivery nudges focuses on how someone is incentivized (default or social norms) – a reminder to complete an application versus creating urgency by providing a nudge about the deadline or the volume of applicants. 

The key to successfully building out these interventions (and the difficulty) is understanding the nudge specific segments of candidates would be more receptive to, which requires personal data (e.g., social media, personality data, etc.) appropriate for the context. 

Read more: https://behavioralscientist.org/the-future-of-nudging-will-be-personal/ [Behavioral Scientist]

User data has long been a commodity. As news about Google’s decision to kill off the third-party tracking cookie brings palpitations to the ad tech market, the full effect of this decision remains to be seen; my money is on necessity continuing to be the mother of invention. 

While Google’s decision is not directly correlated, this past year has brought a heightened level of skepticism and distrust in many institutions. The public, now increasingly aware of big tech’s consumption and use of their data, is being encouraged to “poison” their data. Beyond ad blockers, researchers have proposed three tactics:

• Data strikes, inspired by the idea of labor strikes, which involve withholding or deleting your data so a tech firm cannot use it – leaving a platform or installing privacy tools, for instance.
• Data poisoning, which involves contributing meaningless or harmful data. AdNauseam, for example, is a browser extension that clicks on every single ad served to you, thus confusing Google’s ad-targeting algorithms.
• Conscious data contribution, which involves giving meaningful data to the competitor of a platform you want to protest, such as by uploading your Facebook photos to Tumblr instead.

Building on the momentum of the past year’s collective resistance, the move is in recognition that one-off actions may not create change, but the power of a critical mass just might. 

Read more: https://www.technologyreview.com/2021/03/05/1020376/resist-big-tech-surveillance-data/ [MIT Technology Review] 

The downstream implications could suggest a more complicated market for employers at a moment when most are focused on automated targeted marketing strategies. The cost structure for obtaining user-specific insights may look as it has in the past, incentivizing individuals to share their preferences. However, candidates may be more likely and willing to provide insights into their preferences as there is a long-term benefit (i.e., a job) in it for them.