This paper addresses the steep learning curve in Machine Learning faced by noncomputer scientists, particularly social scientists, stemming from the absence of a primer on its fundamental principles. I adopt a pedagogical strategy inspired by the adage "once you understand OLS, you can work your...

We audit the job recommender algorithms used by four Chinese job boards by creating fictitious applicant profiles that differ only in their gender. Jobs recommended uniquely to the male and female profiles in a pair differ modestly in their observed characteristics, with female jobs advertising...

This paper analyzes 12,596 wagering decisions of 6,064 contestants in the US game show Jeopardy!, focusing on the anchoring phenomenon in financial decision-making. We find that contestants anchor heavily on the initial dollar value of a clue in their wagering decision, even though there exists...

We investigate whether short-term everyday stressors leads to unhealthier dietary choices among low socioeconomic status mothers. We propose a novel stress protocol that aims to mimic everyday stressors experienced by this population, involving time and financial pressure. We evaluate the impact...

Most definitions of algorithmic bias and fairness encode decisionmaker interests, such as profits, rather than the interests of disadvantaged groups (e.g., racial minorities): Bias is defined as a deviation from profit maximization. Future research should instead focus on the causal effect of...