During the past couple of weeks, two new BEHAVE-research manuscripts have been published. The first is a Chapter about the moral dimension of regret, and its implications for choice set design. The design, or architecture, of choice sets is an increasingly established marketing tool to steer choices towards products with, e.g., a particularly high profit margin, in a subtle wat that is often not detectable by consumers. This manuscript shows, using the random regret minimization model which has been developed at TU Delft, how some of these choice architectures generate disproportional levels of regret and hence should be considered morally problematic. Food for thought for marketing professionals! The Chapter has appeared in the book The Moral Psychology of Regret, published by Rowman International.
Another manuscript, of which Ahmad Alwosheel is first author and Sander van Cranenburgh second author, was published in the Journal of Choice Modelling. It reconceptualizes techniques from the computer vision field to develop a procedure to build trust in the use of so-called Artificial Neural Networks (ANNs) for choice behavior analysis. ANNs are increasingly used to analyze and predict choice behavior, but their ‘black box’ nature causes problems in terms of explainability and interpretability. Especially in morally sensitive choice situations, this hampers the use of these models, as it precludes learning what moral values and trade-offs were at stake. The idea of having the trained neural network generate so-called prototypical examples helps gain trust, among analysts, that a particular neural network has learned intuitive relations and behavioral processes underlying the observed choice data. This in turn will help pave the way towards using these machine learning approaches for the analysis of moral decision making.