When AI optimizes for the wrong thing — with Nicole Alexander, former Meta executive

What happens when marketing AI stops finding the right customer and starts finding the right moment of weakness? Nicole Alexander, former Global Head of Marketing at Meta and author of "Ethical AI in Marketing," takes us inside one of the most uncomfortable truths about modern marketing technology.

Nicole reveals how optimization algorithms don't just target demographics anymore — they identify emotional vulnerability. We explore the distinction between growth as a physics problem and responsibility as a human problem, and why the assumption that efficiency equals ethics is fundamentally broken.

Nicole shares her framework for building AI systems that scale without exploitation, explaining why the question isn't "Is this ethical?" but rather "What constraints would make this sustainable?" She offers a provocative reframe: the conversion that destroys trust isn't a win — it's technical debt on your customer lifetime value.

This conversation challenges marketers to rethink how they measure success, engineers to redesign how they optimize, and leaders to consider what it means to build AI that serves people rather than simply converting them.

Key Takeaways:

• Why AI-driven systems ask "What vulnerability is the most profitable lever to pull?"
• How algorithms engineered for time spent inevitably reward outrage
• The business case for treating trust as a technical constraint, not a review step
• Why guardrails should be part of optimization itself, not added later

Nicole Alexander is a Professor at NYU, author of "Ethical AI in Marketing," and former Global Head of Marketing at Meta, where she led teams building some of the world's most sophisticated marketing systems.

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