Robo-Psychology 22 - Toward a Cognitive Susceptibility Taxonomy in Human-AI Interaction
Technical “alignment” work asks whether an AI will do what we want it to do. Real‑world harms show that a complementary question is just as urgent: What will people do when an AI talks back? What happens when the AI conversation drifts into dangerous territory as a result of echo feedback?
Case studies underscore that AI “alignment” in the technical sense is not enough; we must also understand the human susceptibilities in these interactions.
Each of the Cognitive Suceptibility (CST) entries we discuss can amplify failures on the AI’s side, turning what might be minor model issues into major incidents. This human-AI interplay is why CST is not merely a catalogue of user quirks, but a map of risk multipliers in AI systems
Human susceptibilities are force multipliers for AI faults. This is why AI safety cannot be solved by technical alignment alone; the socio-cognitive alignment between humans and AI is equally critical.
By identifying patterns like those in CST, we can start to devise holistic mitigations that treat the human-AI system as a whole.
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