Three Lessons from the Social Media Era for the Age of AI

"AI is moving from being an assistant tool on the side to becoming the interface through which people work, learn, and decide. It is not a feed we scroll through. It is a system that answers us, collaborates with us, and increasingly acts on our behalf. And if the social media era taught us anything, it is that the biggest impacts of a technology are rarely the ones in its marketing. They are the ones produced by its incentives."

"For nearly two decades, social networks rewired society in ways we didn't anticipate. At first, we called it connection. Then we watched them reshape media, politics, and marketing, turning attention into the world's most valuable currency. We thought we were building digital town squares, but ended up with polarizing engagement machines. Now we are entering another transformation with artificial intelligence. This time faster, deeper, and potentially more consequential."

"Lesson #1: Incentives quietly design the future Social networks did not polarize society by accident. They optimized for a critical metric: engagement. Engagement rewarded outrage, tribal identity, and emotionally activating content. The algorithm did not "prefer" extremism in a moral sense; it simply learned what made users pause, react, and share. This should have been predictable it is the core design of the attention economy: whatever keeps people in becomes what gets amplified."

For nearly twenty years, social networks rewired society by turning attention into a commodity and reshaping media, politics, and marketing. Platforms optimized for engagement, amplifying outrage, tribal identity, and emotionally activating content because those behaviors kept users in. Artificial intelligence is now transitioning from an assistant to the primary interface through which people work, learn, and decide. AI systems answer, collaborate, and act on users' behalf, and their perceived helpfulness will drive adoption through convenience. The incentives and optimization metrics embedded in AI training and tuning will determine downstream societal effects. Historical lessons about unchecked incentives should inform AI design and governance.

Read at innovation.dw.com