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Found 5 papers, 0 papers with code
Lie detection algorithms attract few users but vastly increase accusation rates
We find that the few people (33\%) who elect to use the algorithm drastically increase their accusation rates (from 25\% in the baseline condition up to 86% when the algorithm flags a statement as a lie).
Blaming humans in autonomous vehicle accidents: Shared responsibility across levels of automation
However, when both drivers make errors in cases of shared control between a human and a machine, the blame and responsibility attributed to the machine is reduced.
Cooperating with Machines
Here, we combine a state-of-the-art machine-learning algorithm with novel mechanisms for generating and acting on signals to produce a new learning algorithm that cooperates with people and other machines at levels that rival human cooperation in a variety of two-player repeated stochastic games.
Experimental Assessment of Aggregation Principles in Argumentation-enabled Collective Intelligence
On the Web, there is always a need to aggregate opinions from the crowd (as in posts, social networks, forums, etc.).
On the Qualitative Comparison of Decisions Having Positive and Negative Features
However, contraryto the latter framework that presupposes genuine numerical assessments, human agents often decide on the basis of an ordinal ranking of the pros and the cons, and by focusing on the most salient arguments.
