Why poor AI is skewing representation

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AI is a great tool for lifting the burden of repeatable, predictable tasks off humans. Until it isn’t. The fact is, a lot of AI is biased and even unconsciously discriminatory. It’s trained on poor, skewed datasets as the result of traditional biases in the tech industry. That means in the real world,  unrepresented groups such as women are losing out on opportunities as a result of decisions being made by AI in finance, HR, healthcare, and more. So what can we do to solve this issue? We’re joined by Professor Anjana Susarla from Michigan State University to find out.


This is Technology Now, a weekly show from Hewlett Packard Enterprise. Every week we look at a story that's been making headlines, take a look at the technology behind it, and explain why it matters to organisations and what we can learn from it.


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About the expert: https://broad.msu.edu/profile/asusarla/
Anjana's book recommendation: Algorithms of Oppression: How Search Engines Reinforce Racism (https://en.wikipedia.org/wiki/Algorithms_of_Oppression#:~:text=Algorithms%20of%20Oppression%3A%20How%20Search,%2C%20and%20human%2Dcomputer%20interaction.)
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Hewlett Packard Enterprise
Tags
HPE, artificial intelligence, edge to cloud
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