Challenges of Human-Aware AI Systems

TL;DR

This paper discusses the challenges and progress in developing human-aware AI systems that effectively collaborate with humans by understanding social intelligence, mental states, and ethical considerations.

Contribution

It provides a comprehensive survey of research challenges, progress, and future directions in designing AI systems that are socially aware and ethically responsible.

Findings

Progress in modeling human mental states

Advances in explainability and trust-building

Identification of ethical issues in human-aware AI

Abstract

From its inception, AI has had a rather ambivalent relationship to humans---swinging between their augmentation and replacement. Now, as AI technologies enter our everyday lives at an ever increasing pace, there is a greater need for AI systems to work synergistically with humans. To do this effectively, AI systems must pay more attention to aspects of intelligence that helped humans work with each other---including social intelligence. I will discuss the research challenges in designing such human-aware AI systems, including modeling the mental states of humans in the loop, recognizing their desires and intentions, providing proactive support, exhibiting explicable behavior, giving cogent explanations on demand, and engendering trust. I will survey the progress made so far on these challenges, and highlight some promising directions. I will also touch on the additional ethical quandaries that such systems pose. I will end by arguing that the quest for human-aware AI systems broadens the scope of AI enterprise, necessitates and facilitates true inter-disciplinary collaborations, and can go a long way towards increasing public acceptance of AI technologies.