AI is frequently used by people in positions of power on people who have less power. And as AI diffuses across more and more users, this power imbalance may concentrate even more. An effective way to understand how power is enacted in an AI system is to start with a power mapping exercise - and to think more about "studying up" - looking up at those who have the most agency and autonomy.
Not only is this good ethical practice but it can be used to improve the accuracy of predictions from an AI. This is because of what researchers call a "theory of agency," which says that prediction accuracy is a by-product of agency.
We can use performance management scoring as an example. Any proxy for performance is most directly a by-product of a manager's decision rather than the employee's actual performance. It's the manager's decision that becomes directly datafied, before other measures of employee performance. This means that an AI to predict how a manager will score an employee will...
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