Artificial Intelligence (AI) increasingly becomes an indispensable advisor. New ethical concerns arise if AI persuades people to behave dishonestly. In an experiment, we study how AI advice (generated by a Natural-Language-processing algorithm) affects (dis)honesty, compare it to equivalent...

Fairness is a crucial concept in the context of artificial intelligence (AI) ethics and policy. It is an incremental component in existing ethical principle frameworks, especially for algorithm-enabled decision systems. Yet, unwanted biases in algorithms persist due to the failure of...

We study a differential Riccati equation (DRE) with indefinite matrix coefficients, which arises in a wide class of practical problems. We show that the DRE solves an associated control problem, which is key to provide existence and uniqueness of a solution. As an application, we solve two...

People sometimes exhibit a costly preference for humans relative to algorithms, which is often defined as a domain-general algorithm aversion. I propose it is instead driven by biased evaluations of self and other humans, which occurs more narrowly in domains where identity is threatened and...

This paper proposes a branch-and-bound algorithm (B&B) for the proactive scheduling problem, which incorporates a degree of anticipation for variability in practical projects. First, the resource-constrained proactive scheduling model is formulated. Second, solving its resource-unconstrained...