Effective machine learning starts with considered human thinking – IAPA

Once technology is released into the world, it can be incredibly difficult to control. I suspect if you asked Tim Burners-Lee whether he is happy that his invention has become the most effective tool for the distribution of pornography ever invented, he’ll tell you that he isn’t. The Law of Unintended Consequences tells us it is impossible to foresee the full ramifications of any new technology from the point of its inception, but in an era where companies (and particularly startups) push to get new ideas out the door and into the hands of custoemrs as quickly as possible, the chance for measured reflection is limited.

The same of course is true with AI and data analytics moire generally. In my latest post ahead of next weeks IAPA Advancing Analytics conference I asked the speakers about the potential for negative consquences, and whether sufficient thought has gone into the ethical considerations of what AI might enable.

As healthcare data scientist Halim Abbas says: “We have built something, and it is turning out to be a very powerful driver in society, and we are not really sure how to best use it. It is like we have built a hot air balloon, and now we are in the air, asking how do we steer.”

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