Informational Appetites + (un)Natural Statistics = “Screen Addiction”

Seminar | May 15 | 12-1:30 p.m. | 560 Evans Hall

 William Softky, Visiting scholar, Bioengineering Department, Stanford University

 Neuroscience Institute, Helen Wills

It is a truth not yet universally acknowledged that a self-regulating system which is stable in one environment can become unstable when the environment changes. This truth is called homeostatic fragility. Mathematically, the key mechanism is sign-reversal, which converts a negative-feedback loop into a positive-feedback loop. Sign-reversal explains all sorts of self-regulatory malfunctions in biological systems: energy and salt balance, opioid analgesia, chemical dependencies, behavioral addictions like gambling, and now “screen addiction” and its brethren. A second truth is that an active learning or self-calibrating system mathematically requires “informational appetites” (Sommer) for rare but useful inputs, inputs the system thus finds interesting. Humans, uniquely among species, can artificially copy or synthesize such interesting inputs, e.g. bright colors, shiny things, pictures, or news from afar. Unfortunately, because of homeostatic fragility, over-exposure to formerly rare inputs often converts a stable and functional information-foraging instinct into compulsive over-use, for example by compelling people already made lonely and depressed by screen-based socializing to seek solace online rather than in person. While this vicious circle is rooted in the abstract mathematics of information theory, the results are all too real: worldwide, the use of artificial entertainment and communication channels, most especially interactive digital ones, is tightly correlated with rising mental misery, self-harm, and violence. It is not clear whether or how humans can learn to avoid these enticingly decalibrating channels, but it is clear that human cognition and social function will collapse otherwise. (Based on work with Criscillia Benford, e.g. Sensory Metrics of Neuromechanical Trust, Neural Computation 29, 2293–2351, 2017).

We conclude that we humans are the victims of our own success, our hands so skilled they fill the world with captivating things, our eyes so innocent they follow eagerly.

 nterranova@berkeley.edu