Implementations in Machine Ethics: A Survey
This survey addresses the problem of machine ethics implementation for researchers and practitioners in AI and robotics, but it is incremental as it synthesizes existing work rather than proposing new methods.
The paper tackles the challenge of selecting and implementing ethical theories in autonomous systems by introducing a trimorphic taxonomy to analyze implementations, presenting a comprehensive survey of relevant works, and identifying research patterns and future directions.
Increasingly complex and autonomous systems require machine ethics to maximize the benefits and minimize the risks to society arising from the new technology. It is challenging to decide which type of ethical theory to employ and how to implement it effectively. This survey provides a threefold contribution. First, it introduces a trimorphic taxonomy to analyze machine ethics implementations with respect to their object (ethical theories), as well as their nontechnical and technical aspects. Second, an exhaustive selection and description of relevant works is presented. Third, applying the new taxonomy to the selected works, dominant research patterns, and lessons for the field are identified, and future directions for research are suggested.