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Human minds simply cannot reconstruct highly complex natural phenomena efficiently enough in the age of big data. A modern Baconian method that incorporates reductionist ideas through data-mining, but then analyses this information through inductive computational models, could transform our understanding of the natural world. Such an approach would enable us to generate novel hypotheses that have higher chances of turning out to be true, to test those hypotheses, and to fill gaps in our knowledge. It would also provide a much-needed reminder of what science is supposed to be: truth-seeking, anti-authoritarian, and limitlessly free.

Intelligent machines will be our intellectual children, our progeny. They will start off inheriting many of our moral norms, because we will not allow anything else. But they will come to reflect on their nature, including their relationships with us and with each other. If we are wise and benevolent, we will have prepared the way for them to make their own choices – just as we do with our adolescent children.What does this mean in practice? It means being ready to accept that machines might eventually make moral decisions that none of us find acceptable. The only condition is that they must be able to give intelligible reasons for what they’re doing. An intelligible reason is one you can at least see why someone might find morally motivating, even if you don’t necessarily agree.