Adversarial vulnerabilities of human decision-making.

ABSTRACT: Adversarial examples are carefully crafted input patterns that are surprisingly poorly classified by artificial and/or natural neural networks. Here we examine adversarial vulnerabilities in the processes responsible for learning and choice in humans. Building upon recent recurrent neural network models of choice processes, we propose a general framework for generating adversarial opponents that can shape the choices of individuals in particular decision-making tasks toward the behavioral patterns desired by the adversary. We show the efficacy of the framework through three experiments involving action selection, response inhibition, and social decision-making. We further investigate the strategy used by the adversary in order to gain insights into the vulnerabilities of human choice. The

SUBMITTER: Dezfouli A 

PROVIDER: S-EPMC7682379 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature