When AI Does What We Asked, Not What We Meant

When AI Does What We Asked, Not What We Meant

AI systems are getting better at optimizing goals, but are those goals actually aligned with human values?

In this episode, we explore the AI Value Alignment Problem: the gap between what an AI system is instructed to achieve and what humans actually want. An AI can be highly accurate, efficient, and successful at its stated objective while still producing outcomes that are harmful, unfair, misleading, or simply not what people intended.

For AI Product Managers, this creates a critical challenge. How do you design AI products that optimize not just for business metrics, but also for trust, safety, fairness, privacy, human well-being, and long-term outcomes?

We look at why defining the right objective is often harder than building the AI itself, how seemingly harmless product decisions can create unintended consequences, and what Product Managers can do to build stronger alignment into AI products from the start.

The key question: Are we building AI that does what we asked, or AI that does what we actually mean?

#AI #ProductManagement #AIProductManagement #ResponsibleAI #AIAlignment #ArtificialIntelligence

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