algorithm's implied costs of learning …What do machines learn, and why? To answer these questions we import models of human cognition into machine learning …. We propose two ways of modeling machine learners based on this join: feasibility-based and cost-based machine learning …

We examine how machine learning can be used to improve and understand human decision-making. In particular, we focus on … released. This is a promising machine learning application because it is a concrete prediction task for which there is a large … volume of data available. Yet comparing the algorithm to the judge proves complicated. First, the data are themselves …

compare the prices generated by AIAs that use different learning protocols when there is market interaction. Asynchronous … learning occurs when the AIA only learns about the return from the action it took. Synchronous learning occurs when the AIA …

We study the early adoption and diffusion of five AI-related technologies (automated-guided vehicles, machine learning …

a quality upgrade one of these inputs requires a period of learning before it can be used effectively, then in general … wasteful to tie up funds in the other inputs which will be underutilized until the date learning is over. We provide evidence …

represent an understudied channel for this type of social learning. We study an environmentally-focused law in the shale gas …

, endogenous learning here eliminates that effect …

We estimate the impact of district-level schooling mode (in-person versus hybrid or distance learning) on test scores …