AI support for Ethical AI Design

(Diary of an Old AI Researcher who is still Programming)

7 March 2019

We have published a paper titled

`Organic and dynamic tool for use with knowledge base of AI ethics for promoting engineers’ practice of ethical AI design'.

Kaira Sekiguchi and Koichi Hori: Organic and dynamic tool for use with knowledge base of AI ethics for promoting engineers’ practice of ethical AI design', AI & Society, Springer (2018). https://doi.org/10.1007/s00146-018-0867-z

As I mentioned in "Toward AI-embedded Society where AI is Not Recognized as AI" , we should develop AI systems to solve the problems caused by AI systems. The paper shows the first step in this direction.

You can download the full paper from https://doi.org/10.1007/s00146-018-0867-z.
Following is the abstract of the paper.

In recent years, ethical questions related to the development of artificial intelligence (AI) are being increasingly discussed. However, there has not been enough corresponding increase in the research and development associated with AI technology that incorporates with ethical discussion. We therefore implemented an organic and dynamic tool for use with knowledge base of AI ethics for engineers to promote engineers’ practice of ethical AI design to realize further social values. Here, “organic” means that the tool deals with complex relationships among different AI ethics. “Dynamic” means that the tool dynamically adopts new issues and helps engineers think in their own contexts. Data in the knowledge base of the tool is standardized based on the ethical design theory that consists of an extension of the hierarchical representation of artifacts to understand ethical considerations from the perspective of engineering, and a description method to express the design ideas. In addition, we apply the dynamic knowledge management model called knowledge liquidization and crystallization. To discuss the effects, we introduce three cases: a case for the clarification of differences in the structures among AI ethics and design ideas, a case for the presentation of semantic distance among them, and a case for the recommendation of the scenario paths that allow engineers to seamlessly use AI ethics in their own contexts. We discuss the effectiveness of the tool. We also show the probability that engineers can reconstruct AI ethics as a more practical one with professional ethicists.