Massey University’s Teo Susnjak on how Covid-19 broke machine

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Massey University’s Teo Susnjak on how Covid-19 broke machine learning, extreme data patterns, wealth and income inequality, bots and propaganda and being primed to believe bad predictions

5th Jun 20, 10:00am

This week’s Top 5 comes from Teo Susnjak a computer scientist specialising in machine learning. He is a Senior Lecturer in Information Technology at Massey University and is the developer behind GDPLive.

As always, we welcome your additions in the comments below or via email to david.chaston@interest.co.nz.

And if you’re interested in contributing the occasional Top 5 yourself, contact gareth.vaughan@interest.co.nz.

1. Covid-19 broke machine learning.

As the Covid-19 crisis started to unfold, we started to change our buying patterns. All of a sudden, some of the top purchasing items became: antibacterial soap, sanitiser, face masks, yeast and of course, toilet paper. As the demand for these unexpected items exploded, retail supply chains were disrupted. But they weren’t the only ones affected.

Artificial intelligence systems began to break too. The MIT Technology Review reports:

Machine-learning models that run behind the scenes in inventory management, fraud detection, and marketing rely on a cycle of normal human behavior. But what counts as normal has changed, and now …

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