Our behavior in this pandemic has seriously confused AI machine learning systems

The chaos and uncertainty surrounding the coronavirus pandemic have made an unlikely victim: machine learning systems programmed to make sense of our online behavior.

The algorithms that recommend products on Amazon, for example, find it difficult to interpret our new lifestyles, MIT technology review reports.

And while machine learning tools are designed to incorporate new data, they are generally not so robust

For example, MIT Tech reports that a company that detects credit card fraud needed to step in and modify its algorithm to accommodate the surge in interest in gardening equipment and tools electric.

An online retailer discovered that his AI was ordering inventory that no longer matched what was sold. And a company that uses AI to recommend investments based on a sentiment sentiment analysis has been misled by the generally negative tone in the media.

"The situation is very volatile," Rael Cline, CEO of algorithmic marketing consultancy Nozzle, told MIT Tech.

"You are trying to optimize toilet paper last week, and this week everyone wants to buy puzzles or gym equipment."

While some companies spend more time and resources manually running their algorithms, others see it as an opportunity to improve.

"A pandemic like this is a perfect trigger for building better machine learning models," said Sharma.

READ MORE: Our strange behavior during the pandemic plays with AI models

This article was originally published by Futurism