In the current era, people and society have grown increasingly reliant on
artificial intelligence (AI) technologies. AI has the potential to drive us
towards a future in which all of humanity flourishes. It also comes with
substantial risks for oppression and calamity. Discussions about whether we
should (re)trust AI have repeatedly emerged in recent years and in many
quarters, including industry, academia, healthcare, services, and so on.
Technologists and AI researchers have a responsibility to develop trustworthy
AI systems. They have responded with great effort to design more responsible AI
algorithms. However, existing technical solutions are narrow in scope and have
been primarily directed towards algorithms for scoring or classification tasks,
with an emphasis on fairness and unwanted bias. To build long-lasting trust
between AI and human beings, we argue that the key is to think beyond
algorithmic fairness and connect major aspects of AI that potentially cause
AI's indifferent behavior. In this survey, we provide a systematic framework of
Socially Responsible AI Algorithms that aims to examine the subjects of AI
indifference and the need for socially responsible AI algorithms, define the
objectives, and introduce the means by which we may achieve these objectives.
We further discuss how to leverage this framework to improve societal
well-being through protection, information, and prevention/mitigation.

本文介绍了开发 Socially Responsible AI Algorithms 框架的意义和方法来实现人工智能的可信赖，从而提高人类社会的福祉。