As I listened to the speaker celebrate this technical progress, my experience as a historian and occasional practicing statesman gave me pause. What would be the impact on history of self-learning machines—machines that acquired knowledge by processes particular to themselves, and applied that knowledge to ends for which there may be no category of human understanding? Would these machines learn to communicate with one another? How would choices be made among emerging options? Was it possible that human history might go the way of the Incas, faced with a Spanish culture incomprehensible and even awe-inspiring to them? Were we at the edge of a new phase of human history? [...]
This goes far beyond automation as we have known it. Automation deals with means; it achieves prescribed objectives by rationalizing or mechanizing instruments for reaching them. AI, by contrast, deals with ends; it establishes its own objectives. To the extent that its achievements are in part shaped by itself, AI is inherently unstable. AI systems, through their very operations, are in constant flux as they acquire and instantly analyze new data, then seek to improve themselves on the basis of that analysis. Through this process, artificial intelligence develops an ability previously thought to be reserved for human beings. It makes strategic judgments about the future, some based on data received as code (for example, the rules of a game), and some based on data it gathers itself (for example, by playing 1 million iterations of a game). [...]
First, that AI may achieve unintended results. Science fiction has imagined scenarios of AI turning on its creators. More likely is the danger that AI will misinterpret human instructions due to its inherent lack of context. A famous recent example was the AI chatbot called Tay, designed to generate friendly conversation in the language patterns of a 19-year-old girl. But the machine proved unable to define the imperatives of “friendly” and “reasonable” language installed by its instructors and instead became racist, sexist, and otherwise inflammatory in its responses. Some in the technology world claim that the experiment was ill-conceived and poorly executed, but it illustrates an underlying ambiguity: To what extent is it possible to enable AI to comprehend the context that informs its instructions? What medium could have helped Tay define for itself offensive, a word upon whose meaning humans do not universally agree? Can we, at an early stage, detect and correct an AI program that is acting outside our framework of expectation? Or will AI, left to its own devices, inevitably develop slight deviations that could, over time, cascade into catastrophic departures?
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