Machine learning (ML) is a novel method that has applications in asset pricing and that fits well within the problem of measurement in economics. Unlike econometrics, ML models are not designed for parameter estimation and inference, but similar to econometrics, they address, and may be better...

We investigate the data-driven newsvendor problem when one has n observations of p features related to the demand as well as historical demand data. Rather than a two-step process of first estimating a demand distribution then optimizing for the optimal order quantity, we propose solving the...

Where should better learning technology (such as machine learning or AI) improve decisions? I develop a model of decision-making in which better learning technology is complementary with experimentation. Noisy, inconsistent decision-making introduces quasi-experimental variation into training...

Aim/purpose - This research presents a conceptual stakeholder accountability model for mapping the project actors to the conduct for which they should be held accountable in artificial intelligence (AI) projects. AI projects differ from other projects in important ways, including in their...

Part I. Artificial intelligence : present and future -- 1. Human intelligence (HI) versus artificial intelligence (AI) and intelligence augmentation (IA) -- 2. Expecting the future: How AI's potential performance will shape current behavior -- Part II. The status of machine learning methods for...