  Human computation is an approach to solving problems that prove difficult
using AI only, and involves the cooperation of many humans. Because human
computation requires close engagement with both "human populations as users"
and "human populations as driving forces," establishing mutual trust between AI
and humans is an important issue to further the development of human
computation. This survey lays the groundwork for the realization of trustworthy
human computation. First, the trustworthiness of human computation as computing
systems, that is, trust offered by humans to AI, is examined using the RAS
(Reliability, Availability, and Serviceability) analogy, which define measures
of trustworthiness in conventional computer systems. Next, the social
trustworthiness provided by human computation systems to users or participants
is discussed from the perspective of AI ethics, including fairness, privacy,
and transparency. Then, we consider human--AI collaboration based on two-way
trust, in which humans and AI build mutual trust and accomplish difficult tasks
through reciprocal collaboration. Finally, future challenges and research
directions for realizing trustworthy human computation are discussed.
