Abstract
According to Hume’s guillotine, one cannot derive values from facts. Since intelligent systems are fact processors, one can ask how ethical machines can be possible. However, ethics is a real-life process. People analyze actions and situations emotionally and cognitively. Thus they learn rules, such as “this situation feels good/bad.” The cognitive analysis of actions is associated with emotional analysis. The association of action, emotion and cognition can be termed a primary ethical schema. Through an ethical information process in which emotions and cognitions interact in social discourse, primary ethical schemas are refined into ethical norms. Each component of the process is different, but they cooperate to construct an ethical approach to thinking.
Hume’s guillotine mistakenly breaks down primary ethical schemas and juxtaposes emotions and cognitions. There is no ethics without coordinated emotional, cognitive and social analysis. Therefore, his theory can be seen as a pseudo problem.
In the future, ethical processes will involve intelligent systems that can make ethical choices. Weak ethical artificial intelligence (AI) systems can apply given ethical rules to data, while strong ethical AI systems can derive their own rules from data and knowledge about human emotions. Resolving Hume’s guillotine introduces new ways to develop stronger forms of ethical AI.
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Saariluoma, P. (2020). Hume’s Guillotine Resolved. In: Rauterberg, M. (eds) Culture and Computing. HCII 2020. Lecture Notes in Computer Science(), vol 12215. Springer, Cham. https://doi.org/10.1007/978-3-030-50267-6_10
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DOI: https://doi.org/10.1007/978-3-030-50267-6_10
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