AI is machine learning, and you need ever updated data sets to match reality

The hope is that all this data-related faff will be a one-off, and that, once trained, a machine-learning model will repay the effort over millions of automated decisions.

There is no AI, just computers that can try to get it right over and over, but quickly. Little wonder: that’s what humans do, just much slower. And humans architect and write that code. All we know how to do is bang our head against the wall until the wall bends to our will.

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Firms in other industries woud love that kind of efficiency. Yet the magic is proving elusive. A survey carried out by Boston Consulting Group and mit polled almost 2,500 bosses and found that seven out of ten said their ai projects had generated little impact so far. Two-fifths of those with “significant investments” in ai had yet to report any benefits at all.


Perhaps as a result, bosses seem to be cooling on the idea more generally. Another survey, this one by pwc, found that the number of bosses planning to deploy ai across their firms was 4% in 2020, down from 20% the year before. The number saying they had already implemented ai in “multiple areas” fell from 27% to 18%. Euan Cameron at pwc says that rushed trials may have been abandoned or rethought, and that the “irrational exuberance” that has dominated boardrooms for the past few years is fading.

Original source: For AI, data are harder to come by than you think