Machine-learning is a boon, but it still needs a human hand
We should remember that devices only compute what has been programmed by people
Advances in computer power, machine-learning and predictive algorithms are creating paradigm shifts in many industries. For example, when an algorithm outperformed six radiologists in reading mammograms and accurately diagnosing breast cancer, this raised questions around the role of machine-learning in medicine and whether it will replace, or enhance, the work being done by doctors.
Similarly, when Google’s AI software AlphaGo beat the world’s top Go master in what is described as humankind’s most complicated board game, The New York Times declared “it isn’t looking good for humanity” when an algorithm can outperform a human in a highly complex task...
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