The AAAI’s Twenty-Ninth Conference on Artificial Intelligence was held January 25–30, 2015 in Austin, Texas. Machine cognition was an important focal area covered in two workshops on AI and Ethics, and Beyond the Turing Test, and in a special track on Cognitive Systems.
Some of the most interesting emergent themes are discussed in this article.
Computational Ethics Systems
One main research activity in machine ethics is developing computational ethics systems. The status is that there are several such systems; however, a paucity of overall standards bodies, general ethics modules, and an articulation of universal principles that might be included like human dignity, informed consent, privacy, and benefit-harm analysis.
One required feature of computational ethics systems could be the ability to flexibly apply different systems of ethics to more accurately reflect the ways that human intelligent agents approach real-life situations. For example, it is known from early programming efforts that simple models like Bentham and Mill’s utilitarianism are not robust enough ethics models. They do not incorporate comprehensive human notions of justice that extend beyond the immediate situation in decision-making.
What is helpful is that machine systems on their own have evolved more expansive models than utilitarianism such as a prima facie duty approach. In the prima facie duty approach, there is a more complex conceptualization of intuitive duties, reputation, and the goal of increasing benefit and decreasing harm in the world. This is more analogous to real-life situations where there are multiple ethical obligations competing to determine the right action. GenEth is a machine ethics sandbox that is available to explore these kinds of systems for Mac OS, with details discussed in this conference paper.
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