Beyond buzzwords: why A.I. isn’t always the best solution (video)

Some people listen to the sales pitch for a new tool, hear the words ‘machine learning’, ‘neural networks’ and ‘predictive analysis’, and immediately think: this is what we need! Wim Schmitz is not one of those people…

Wim is an Exellyst working as a Business Analyst (in RPA & Data Science) at Umicore, and one of the people in charge of finding new and improved ways of managing repetitive administrative tasks such as logging worked hours. They need a better, more user-friendly tool than the one they currently use, which was around since before Wim was even born. So they got in touch with a scale-up launching a new time management tool and scheduled a meeting.

Where others were over the moon by the promises of this new app – effectively blinded by buzzwords – Wim looked at these claims more critically. Where the scale-up pitched Internet of Things and Web 3.0 compatibility as an asset, Wim saw security risks. Deep learning was flagged in his mind as an untransparent machine learning model. And for neural networks, he immediately thought of privacy concerns. He said to his manager: if we start using this tool, I will no longer feel comfortable working for Umicore. And so they didn’t.

In short: while A.I. holds a lot of promise and can absolutely be an asset in the workplace of tomorrow, the first question you should always ask when presented with these fancy tools, is: where is the value? Asserting the value of what you’re trying to do holds a much more reliable guarantee for success than a fancy tool with lots of buzzing A.I. application terms.

Want to learn more about this critical view of artificial intelligence? Watch Wim’s full presentation in the video right here.

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