"I Don't Know If We're Doing Good. I Don't Know If We're Doing Bad": Investigating How Practitioners Scope, Motivate, and Conduct Privacy Work When Developing AI Products


Hao-Ping (Hank) Lee, Carnegie Mellon University; Lan Gao and Stephanie Yang, Georgia Institute of Technology; Jodi Forlizzi and Sauvik Das, Carnegie Mellon University


How do practitioners who develop consumer AI products scope, motivate, and conduct privacy work? Respecting privacy is a key principle for developing ethical, human-centered AI systems, but we cannot hope to better support practitioners without answers to that question. We interviewed 35 industry AI practitioners to bridge that gap. We found that practitioners viewed privacy as actions taken against pre-defined intrusions that can be exacerbated by the capabilities and requirements of AI, but few were aware of AI-specific privacy intrusions documented in prior literature. We found that their privacy work was rigidly defined and situated, guided by compliance with privacy regulations and policies, and generally demotivated beyond meeting minimum requirements. Finally, we found that the methods, tools, and resources they used in their privacy work generally did not help address the unique privacy risks introduced or exacerbated by their use of AI in their products. Collectively, these findings reveal the need and opportunity to create tools, resources, and support structures to improve practitioners' awareness of AI-specific privacy risks, motivations to do AI privacy work, and ability to address privacy harms introduced or exacerbated by their use of AI in consumer products.

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