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Monday, March 29, 2021

The problem with prediction

Joseph Fridman
aeon.com
Originally published 25 Jan 21

Here is an excerpt:

Today, many neuroscientists exploring the predictive brain deploy contemporary economics as a similar sort of explanatory heuristic. Scientists have come a long way in understanding how ‘spending metabolic money to build complex brains pays dividends in the search for adaptive success’, remarks the philosopher Andy Clark, in a notable review of the predictive brain. The idea of the predictive brain makes sense because it is profitable, metabolically speaking. Similarly, the psychologist Lisa Feldman Barrett describes the primary role of the predictive brain as managing a ‘body budget’. In this view, she says, ‘your brain is kind of like the financial sector of a company’, predictively allocating resources, spending energy, speculating, and seeking returns on its investments. For Barrett and her colleagues, stress is like a ‘deficit’ or ‘withdrawal’ from the body budget, while depression is bankruptcy. In Blackmore’s day, the brain was made up of sentries and soldiers, whose collective melancholy became the sadness of the human being they inhabited. Today, instead of soldiers, we imagine the brain as composed of predictive statisticians, whose errors become our neuroses. As the neuroscientist Karl Friston said: ‘[I]f the brain is an inference machine, an organ of statistics, then when it goes wrong, it’ll make the same sorts of mistakes a statistician will make.’

The strength of this association between predictive economics and brain sciences matters, because – if we aren’t careful – it can encourage us to reduce our fellow humans to mere pieces of machinery. Our brains were never computer processors, as useful as it might have been to imagine them that way every now and then. Nor are they literally prediction engines now and, should it come to pass, they will not be quantum computers. Our bodies aren’t empires that shuttle around sentrymen, nor are they corporations that need to make good on their investments. We aren’t fundamentally consumers to be tricked, enemies to be tracked, or subjects to be predicted and controlled. Whether the arena be scientific research or corporate intelligence, it becomes all too easy for us to slip into adversarial and exploitative framings of the human; as Galison wrote, ‘the associations of cybernetics (and the cyborg) with weapons, oppositional tactics, and the black-box conception of human nature do not so simply melt away.’