As Stores Reopen, Which Customers Are Most Likely to Return? New research in MIT Sloan Review reveals how consumer preferences have changed and how retailers can adapt.

As Stores Reopen, Which Customers Are Most Likely to Return? New research reveals how consumer preferences have changed and how retailers can adapt. https://sloanreview-mit-edu.cdn.ampproject.org/c/s/sloanreview.mit.edu/article/as-stores-reopen-which-customers-are-most-likely-to-return/amp Professors Patrick Lynch and Richard Ettenson available for commentary, analysis, and interviews. The COVID-19 pandemic and…

HU facial recognition software predicts criminality

A group of Harrisburg University of Science and Technology students and professors have developed an automated computer classifier capable of predicting with 80% accuracy and no racial bias whether someone is likely to be a criminal based solely on a picture of their face.
Jonathan W. Korn, a PhD student in Harrisburg University of Science and Technology’s Data Science program and a NYPD veteran; Prof. Nathaniel J.S. Ashby, and Prof. Roozbeh Sadeghian’s research titled “A Deep Neural Network Model to Predict Criminality Using Image Processing” will appear in the forthcoming Springer Nature – Research Book Series: Transactions on Computational Science & Computational Intelligence

Consumer Stockpiling During COVID-19 Crisis Can Look Panicky, But It Has Its Rational Side

Consumers are clearing store shelves. Some observers call it “panic buying.” But a Johns Hopkins University expert on consumer behavior, while acknowledging that panic is an element of the phenomenon, says stockpiling can be seen as a rational approach to shopping during a pandemic.