A Closer Collaboration Between Artificial and Human Intelligence

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By David Lobina | 1Q 2022 | IN-6419


Training AI Systems with Real-Time Human Input


Artificial Intelligence (AI), in the guise of Deep Neural Networks (DNNs), is ever more present in industry, with myriad AI systems applied to all sorts of problems and to all kinds of situations. As pattern-recognition algorithms, though—and this is what DNNs effectively effect (no pun intended)—AI systems can run into many problems. The well-publicized instances in which AI algorithms return clearly biased outcomes just one example, but it is a unmistakable one. When such outcomes take part in a decision-making process of some kind—e.g., in deciding whether to award a loan to an applicant—it is not hard to conclude that biased outcomes are manifestly unfair; unfair decisions can easily produce harmful states of affairs. Moreover, the underlying algorithms that put inputs and outputs together are typically not explainable as it is usually not possible to know how the algorithm reached the decision it has returned. In many cases, AI vendors often find themselves between the proverbial rock and a hard place. AI systems may yield many benefits, but o…

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