Visible to the public Biblio

Filters: Author is Beaton, Brian  [Clear All Filters]
2018-12-10
Beaton, Brian.  2018.  Crucial Answers About Humanoid Capital. Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction. :5–12.

Inside AI research and engineering communities, explainable artificial intelligence (XAI) is one of the most provocative and promising lines of AI research and development today. XAI has the potential to make expressible the context and domain-specific benefits of particular AI applications to a diverse and inclusive array of stakeholders and audiences. In addition, XAI has the potential to make AI benefit claims more deeply evidenced. Outside AI research and engineering communities, one of the most provocative and promising lines of research happening today is the work on "humanoid capital" at the edges of the social, behavioral, and economic sciences. Humanoid capital theorists renovate older discussions of "human capital" as part of trying to make calculable and provable the domain-specific capital value, value-adding potential, or relative worth (i.e., advantages and benefits) of different humanoid models over time. Bringing these two exciting streams of research into direct conversation for the first time is the larger goal of this landmark paper. The primary research contribution of the paper is to detail some of the key requirements for making humanoid robots explainable in capital terms using XAI approaches. In this regard, the paper not only brings two streams of provocative research into much-needed conversation but also advances both streams.