Originally posted November 26, 2018
Here is an excerpt:
Perhaps as a result of this misguided impression, public debates continue today about what value, if any, the social sciences could bring to artificial-intelligence research. In Simon’s view, AI itself was born in social science.
David Runciman, a political scientist at the University of Cambridge, has argued that to understand AI, we must first understand how it operates within the capitalist system in which it is embedded. “Corporations are another form of artificial thinking-machine in that they are designed to be capable of taking decisions for themselves,” he explains.
“Many of the fears that people now have about the coming age of intelligent robots are the same ones they have had about corporations for hundreds of years,” says Mr Runciman. The worry is, these are systems we “never really learned how to control.”
After the 2010 BP oil spill, for example, which killed 11 people and devastated the Gulf of Mexico, no one went to jail. The threat that Mr Runciman cautions against is that AI techniques, like playbooks for escaping corporate liability, will be used with impunity.
Today, pioneering researchers such as Julia Angwin, Virginia Eubanks and Cathy O’Neil reveal how various algorithmic systems calcify oppression, erode human dignity and undermine basic democratic mechanisms like accountability when engineered irresponsibly. Harm need not be deliberate; biased data-sets used to train predictive models also wreak havoc. It may be, given the costly labour required to identify and address these harms, that something akin to “ethics as a service” will emerge as a new cottage industry. Ms O’Neil, for example, now runs her own service that audits algorithms.
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