When algorithms use data generated by human beings, they inherit the errors stemming from human biases which likely diminishes their performance. We examine the design and value of a bias-aware linear classification algorithm that accounts for bias in input data, using breast cancer diagnosis as...

We consider the effects of "precision" screening policies for cancer guided by algorithms. We first show that complex machine learning models can indeed predict cancer better than simpler models that use established risk factors. We then tackle the evaluation challenge: an algorithm that can...

In traditional models, votes are an expression of preferences and beliefs. Psychological theories of cognitive dissonance suggest, however, that behavior may shape preferences. In this view, the very act of voting may influence political attitudes. A vote for a candidate may lead to more...

In traditional models, votes are an expression of preferences and beliefs. Psychological theories of cognitive dissonance suggest, however, that behavior may shape preferences. In this view, the very act of voting may influence political attitudes. A vote for a candidate may lead to more...

In traditional models, votes are an expression of preferences and beliefs. Psychological theories of cognitive dissonance suggest, however, that behavior may shape preferences. In this view, the very act of voting may influence political attitudes. A vote for a candidate may lead to more...