The rise of taste, human authenticity and judgment in an AI world | Adam Mosseri (Head of IG)

AI will not produce useful strategic plans unless humans steer it with rich constraints because out-of-the-box models default to predictable, shallow options unless you feed them context like team capabilities, incentives, and regulatory bounds and iterate in a back-and-forth.

Labeling camera-captured (non-AI) content may be more practical than reliably detecting AI-generated media because generative models will blur the line as they improve, while tagging verified camera origin avoids an arms race and supports confidence reporting.

Good strategy must be controversial because a debatable, opinionated path differentiates you from competitors and forces commitment, whereas an uncontroversial plan just turns into a race on execution.

Great product leaders act as curators because no one person can invent everything, so they pick complementary people and ideas, combine the best options, and manage trade-offs to create a coherent direction.

Token consumption for AI will be treated like a finite resource, so organizations will cap or ration usage based on team trust and expected ROI to control compute costs and capacity.

Platforms should label AI-generated content for user agency but judge posts mainly on quality and provenance because account signals let users decide trust while moderation should focus on personalization and safety rather than tool origin.

Exploration-based algorithmic ranking helps niche creators break out because it deliberately tests and surfaces relevant but less-popular items, exposing them to audiences that popularity signals would miss.

Purely chronological feeds reward volume because frequent posters always appear at the top, which allows high-rate publishers to crowd out friends and low-volume creators as the system scales.