Executive summary: Psychology research could make important contributions to AI safety in areas like anticipating societal responses to AI developments, improving forecasting techniques, describing human values, assessing AI decision-making biases, and modeling risks related to institutional stability and AI development.
Key points:
Human-AI interaction research could explore AI persuasiveness, human-AI capability differences, trust in AI, and more.
Foundational work on forecasting biases, aggregation techniques, and interpreting probability estimates could be applied to predicting AI development trajectories.
Understanding human values, both in general and in the context of AI alignment, is crucial. This includes research on well-being, value spread, moral uncertainty, and fanaticism.
Modeling institutional stability issues like AI arms race dynamics, risks from malevolent actors, identifying ethical decision-makers, and AI cooperation/conflict scenarios is important.
Anticipating societal responses to AI developments in areas like AI sentience, takeoff scenarios, risk aversion, and post-TAI well-being could inform AI strategy.
Applying cognitive science methods to understand the nature of AI cognition and its similarities/differences with human cognition is a promising area for interdisciplinary research.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, andcontact us if you have feedback.
Executive summary: Psychology research could make important contributions to AI safety in areas like anticipating societal responses to AI developments, improving forecasting techniques, describing human values, assessing AI decision-making biases, and modeling risks related to institutional stability and AI development.
Key points:
Human-AI interaction research could explore AI persuasiveness, human-AI capability differences, trust in AI, and more.
Foundational work on forecasting biases, aggregation techniques, and interpreting probability estimates could be applied to predicting AI development trajectories.
Understanding human values, both in general and in the context of AI alignment, is crucial. This includes research on well-being, value spread, moral uncertainty, and fanaticism.
Modeling institutional stability issues like AI arms race dynamics, risks from malevolent actors, identifying ethical decision-makers, and AI cooperation/conflict scenarios is important.
Anticipating societal responses to AI developments in areas like AI sentience, takeoff scenarios, risk aversion, and post-TAI well-being could inform AI strategy.
Applying cognitive science methods to understand the nature of AI cognition and its similarities/differences with human cognition is a promising area for interdisciplinary research.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.