The Challenges of Defining and Measuring AI Intelligence

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Artificial Intelligence News

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The lack of a widely accepted definition of intelligence in AI systems poses challenges in accurately measuring their capabilities. The obsession with human-centric yardsticks may hinder the exploration of non-human ways in which machines can meet human needs. Conflicting timelines and predictions about AI's advancement further complicate the issue.

If we obsess over this fuzzy human-centric yardstick for AI's abilities, we could miss out on promising — but decidedly non-human — ways machines could meet actual human needs.

These consistent ways of benchmarking allow comparisons to performances by people, he says. And "there are many such objective evaluation measures where the best software meets or exceeds people." Lipton points to the calculator. It's "much 'smarter' than humans at performing arithmetic calculations, and yet much less capable at higher math," he says."People make optimal decisions based on their circumstances," says Songyee Yoon, president and chief strategy officer at NCSOFT, one of the world's largest online game developers.

"When young, we tend to explore more and take risks. As we age, we exploit what we've learned or accumulated, paving the way for future prosperity," she says. "Deciding when to transition between these phases gradually is also a trait of 'smartness.'"

 

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