Yampolskiy, Roman V.

The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation

Brundage, M., Avin, S., Clark, J., Toner, H., Eckersley, P., Garfinkel, B., Dafoe, A., Scharre, P., Zeitzoff, T., Filar, B., et al. (2018) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 849

The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation

Brundage, M., Avin, S., Clark, J., Toner, H., Eckersley, P., Garfinkel, B., Dafoe, A., Scharre, P., Zeitzoff, T., Filar, B., et al. (2018) · Apollo - University of Cambridge Repository

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 849

Responses to catastrophic AGI risk: a survey

Sotala, K., & Yampolskiy, R. V. (2015) · Physica Scripta

Ethics and Social Impacts of AIPsychiatry, Mental Health, Neuroscience

Cited by 121

Artificial Superintelligence

Yampolskiy, R. V. (2015) · Chapman & Hall/CRC eBooks

Ethics and Social Impacts of AIPsychiatry, Mental Health, Neuroscience

Cited by 75

Unpredictability of AI: On the Impossibility of Accurately Predicting All Actions of a Smarter Agent

Yampolskiy, R. V. (2020) · Journal of Artificial Intelligence and Consciousness

Ethics and Social Impacts of AIPsychiatry, Mental Health, Neuroscience

Cited by 42

On the Limits of Recursively Self-Improving AGI

Yampolskiy, R. V. (2015) · Lecture Notes in Computer Science

Computability, Logic, AI AlgorithmsPsychiatry, Mental Health, Neuroscience

Cited by 23

Building Safer AGI by introducing Artificial Stupidity

Trazzi, M., & Yampolskiy, R. V. (2018) · arXiv

Psychiatry, Mental Health, NeuroscienceEthics and Social Impacts of AI

Cited by 15

AI Risk Skepticism, A Comprehensive Survey

Ambartsoumean, V. M., & Yampolskiy, R. V. (2023) · arXiv

Ethics and Social Impacts of AIRisk Perception and Management

Cited by 10