Mind Matters News and Analysis on Natural and Artificial Intelligence


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Gary Smith: The AI Delusion

“When I Nod My Head, Hit It!” And Other Commands that Confuse AI.

Pablo Picasso said “Computers Are Useless. They Can Only Give You Answers.”  Picasso didn’t go far enough. The answers that computers give must themselves be questioned. This is especially true of AI. Questioning AI is the topic today on Mind Matters. Show Notes 01:27 | Introduction to Gary Smith 02:40 | The AI Delusion 04:50 | Stocks and Data 07:00 Read More ›

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1: IBM’s Watson Is NOT Our New Computer Overlord

AI help, not hype: It won at Jeopardy (with specially chosen “softball” questions) but is not the hoped-for aid to cancer specialists
One problem that has dogged Watson has nothing to do with AI or medicine. The journalism around the introduction of projects like Watson is long on the Gee Whiz! An Electronic Brain! It Won at Jeopardy! And it is short on systematic inquiry as to outcomes versus goals. Read More ›
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AI Winter Is Coming

Roughly every decade since the late 1960s has experienced a promising wave of AI that later crashed on real-world problems, leading to collapses in research funding.
Nearly all of AI’s recent gains have been realized due to massive increases in data and computing power that enable old algorithms to suddenly become useful. For example, researchers first conceived neural networks—the core idea powering much machine learning and AI’s notable advances—in the late 1950s. The worries of an impending winter arise because we’re approaching the limits of what massive data combined with hordes of computers can do. Read More ›

GIGO alert: AI can be racist and sexist, researchers complain

Can the bias problem be addressed? Yes, but usually after someone gets upset about a specific instance.

From James Zou and Londa Ziebinger at Nature: When Google Translate converts news articles written in Spanish into English, phrases referring to women often become ‘he said’ or ‘he wrote’. Software designed to warn people using Nikon cameras when the person they are photographing seems to be blinking tends to interpret Asians as always blinking. Word embedding, a popular algorithm used to process and analyse large amounts of natural-language data, characterizes European American names as pleasant and African American ones as unpleasant. Now where, we wonder, would a mathematical formula have learned that? Maybe it was listening to the wrong instructions back when it was just a tiny bit? Seriously, machine learning, we are told, depends on  absorbing datasets of Read More ›