Russ McBride

A Framework for Error Correction Under Prediction

Clark describes a budding trend in neuroscience toward what he calls a “predictive processing” model, the core idea of which is pretty simple. The brain is a prediction machine. It generates top-down predictions about expected sensory input. These collide with actual bottom-up sensory input, canceling out the matches, and leaving only the prediction errors to propagate forward. This model nicely explains a variety of otherwise anomalous experimental results and dovetails cleanly with Bayesian modeling formalisms. As such it is a wonderfully concise model that gets at a critical and under-appreciated component of brain activity – error correction under prediction.

Management in the Age of Machine Intelligence

The purpose of this panel symposium is to explore the implications of machine learning and algorithmic organization on management theory. We have gathered together a diverse collection of scholars ...

In Search of the “Entrepreneurial Mindset”:Insights from Neuroscience

The way in which cognitive abilities – affective as well as intellectual – influence the development of the entrepreneurial mindset has been topic of academic discussion for quite some years (Cardon et al, 2005; Grégoire et al, 2010; Krueger & Day 2010). For example, Baron (2007) argued that cognitive abilities in the form of experience are an explanatory factor for why some people identify business opportunities successfully.