Information and digital literacy in education via the digital path

From Google searches and dating sites to detecting credit card fraud, artificial intelligence (AI) keeps finding new ways to creep into our lives. But can we trust the algorithms that drive it?

As humans, we make errors. We can have attention lapses and misinterpret information. Yet when we reassess, we can pick out our errors and correct them.

But when an AI system makes an error, it will be repeated again and again no matter how many times it looks at the same data under the same circumstances.

AI systems are trained using data that inevitably reflect the past. If a training data set contains inherent biases from past human decisions, these biases are codified and amplified by the system.

The private and public sectors are increasingly turning to artificial intelligence (AI) systems and machine learning algorithms to automate simple and complex decision-making processes.[1] The mass-scale digitization of data and the emerging technologies that use them are disrupting most economic sectors, including transportation, retail, advertising, and energy, and other areas. AI is also having an impact on democracy and governance as computerized systems are being deployed to improve accuracy and drive objectivity in government functions.

MIT grad student Joy Buolamwini was working with facial analysis software when she noticed a problem: the software didn't detect her face -- because the people who coded the algorithm hadn't taught it to identify a broad range of skin tones and facial structures. Now she's on a mission to fight bias in machine learning, a phenomenon she calls the "coded gaze." It's an eye-opening talk about the need for accountability in coding ... as algorithms take over more and more aspects of our lives.