If AI is addictive, where does the responsibility lie? With big tech or its users?

Datasets used to train AI algorithms may underrepresent older people. Credit: Pixabay/CC0 Public Domain

When I talk to my son, an engineering student, and we have a question or disagreement, he immediately turns to ChatGPT as his primary source of information and confirmation.

He is not alone in this. The use of generative AI tools has exploded across different demographic groups. For many people, these tools can be entertaining, informative and beneficial. However, they also have a dark side.

Generative AI is not formally recognized as addictive right now—the medical evidence is still being gathered. But there is a significant amount of data showing heavy use of chatbots and other systems that produce text, images and video leading to neural patterns and behavior that are associated with addiction.

In light of Meta's and YouTube's recent legal defeat in a landmark social media addiction trial, I believe it's time to ask whether a similar logic applies to generative AI—and how it could be addressed. The starting point would be to identify who carries responsibility for overuse of generative AI.