JOURNAL ARTICLE

Causal Learning for Socially Responsible AI

Abstract

There have been increasing concerns about Artificial Intelligence (AI) due to its unfathomable potential power. To make AI address ethical challenges and shun undesirable outcomes, researchers proposed to develop socially responsible AI (SRAI). One of these approaches is causal learning (CL). We survey state-of-the-art methods of CL for SRAI. We begin by examining the seven CL tools to enhance the social responsibility of AI, then review how existing works have succeeded using these tools to tackle issues in developing SRAI such as fairness. The goal of this survey is to bring forefront the potentials and promises of CL for SRAI.

Keywords:
Social responsibility Computer science Artificial intelligence Power (physics) State (computer science) Data science Engineering ethics Engineering Political science Public relations

Metrics

13
Cited By
1.27
FWCI (Field Weighted Citation Impact)
51
Refs
0.83
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Adversarial Robustness in Machine Learning
Physical Sciences →  Computer Science →  Artificial Intelligence
Ethics and Social Impacts of AI
Social Sciences →  Social Sciences →  Safety Research
Domain Adaptation and Few-Shot Learning
Physical Sciences →  Computer Science →  Artificial Intelligence

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