Stanford CS329Z lays out agent challenges: reliability gaps, interaction failures, privacy risks
stanfordnlp · x · 2026-11-12
In Stanford's CS329Z "Engineering AI Agents," Prof. Diyi Yang argues more powerful agents bring significant technical and safety hurdles:
- Reliability & evaluation: a large gap between raw capability (benchmark scores) and real-world reliability; standard metrics miss consistency, robustness to distractions (e.g., website pop-ups), and predictability.
- Interaction failures: agents often fail to collaborate — e.g., a grocery-ordering agent that never asked for location or preferences and made harmful assumptions.
- Privacy & security: agents need access to highly sensitive user data to function, amplifying risk.
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