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AI for Good?
In focusing on the outcomes of AI, rather than on the legislation designed to condition its use, we believe AI for Good can be transformed from a vague promise to effective practice.
Technology has always been pitched on a promise of value. This rings particularly true for information technology, where each new generation of IT has been hinged on promising consumers to go faster, better, and more economically. If the vision of “AI for Good” embodies this promise, where does this pledge lead us? How are we defining artificial intelligence, what are we measuring, and how is it being applied for the common good? In this contribution, we would like to explore the context and the challenges of harnessing AI for Good.
After proposing an operational definition of both AI and AI for Good, we will address four different levels of concern: personal privacy, human agency, managerial responsibility, and implicit bias. In each instance, we will explore the various facets of the challenge and propose elements of an operational framework in leveraging AI to improve human intelligence.
Artificial Intelligence
Any discussion of AI for Good hinges on the goals set for artificial intelligence
Artificial intelligence (AI) can be defined as the application of computer algorithms in data-driven decision-making to simulate human intelligence…
