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What They Don’t Tell You: 4 Ways Humans Still Vastly Outperform AI
Media coverage often portrays AI as more intelligent than it is.
AI systems seem so intelligent because they give more exposure to achievements that reflect it. Reality tells us otherwise.
Every time there’s a notable breakthrough in AI, we only hear how intelligent and skilled the systems are getting. In 2012 Hinton’s team got 63% top-1 accuracy on the ImageNet challenge. A few years later, a system topped human performance by achieving a striking +90% top-1 accuracy. The news: “AI can recognize objects better than humans.” Well, no. When they tested this exact model on a real-world object dataset its performance dropped 40–45%.
Last year people went nuts over GPT-3. The New York Times, The Guardian, Wired, TechCrunch, DigitalTrends, and many other prestigious news magazines spread the word about its astonishing capabilities. The hype went so over the top that Sam Altman, OpenAI’s CEO, had to reduce the tone:
“[GPT-3 is] impressive […] but it still has serious weaknesses and sometimes makes very silly mistakes. AI is going to change the world, but GPT-3 is just a very early glimpse.”
In contrast, almost no one talks about all the tasks at which AI is still very dumb. AI not being very intelligent doesn’t make for a catchy headline. Despite all the successes of deep learning systems, there are still crucial ways in which AI is the opposite of “superhuman.” Gary Marcus, a professor of psychology at New York University and leading AI expert, mentions some examples in his book Rebooting AI. In this article, I’ll explain in which ways we still vastly outperform AI — and will still do in the foreseeable future.
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