Moral Decision Making in Autonomous Systems: Enforcement, Moral Emotions, Dignity, Trust, and Deception

By R. Arkin, Patrick Ulam, Alan R. Wagner. 2012

170 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Safety Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Tero Karppi
2. H. Baayen
3. Michael Ramscar
4. L. Janda
5. Harald Baayen

In Safety Research

1. Tero Karppi
2. John V. Guttag
3. Harini Suresh
4. Ella Glikson
5. Anita Williams Woolley

Citations in the corpus

• Algorithmic Bias in Autonomous Systems (2017, background): “The processing of the algorithm is statistically biased in the sense that its judgments or decisions deviate from what a “neutral” algorithm might have done, but it helps ensure the system conforms to important moral norms [Arkin et al., 2012].”
• Ethical governance is essential to building trust in robotics and artificial intelligence systems (2018, unknown): “The training approach is developed for an assistive robot in [55], while examples of constraint-based approaches are explored in [56,57].”
• “The Computer Said So”: On the Ethics, Effectiveness, and Cultural Techniques of Predictive Policing (2018, methodology): “…these techniques could be used not only in the context of military technology but also in other fields of our culture where automation and computational power has an important role and ethical governance is needed and demanded (see Arkin, Ulam, & Wagner, 2012; Böhlen & Karppi, 2017, p. 13).”