Mind Matters Natural and Artificial Intelligence News and Analysis

TagMeaningless correlations

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Blockchain Network, Data Stream

Define Information Before You Talk About It: Egnor Interviews Marks

Has anyone ever given you some useless information? What does it even mean for information to be meaningful? This week, on Mind Matters News, guest host Dr. Michael Egnor interviews our own Robert J. Marks about information, as well as the creative limits of artificial intelligence, and why evolutionary algorithms aren’t the magic bullet they’re often presented to be. Show Read More ›

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Code on computer monitor

Robert J. Marks on Information and AI (Part I)

What is information? How is information created? Will artificial intelligence ever be creative? Dr. Michael Egnor discusses information theory, correlations, and creative artificial intelligence with Dr. Robert J. Marks. Show Notes Additional Resources

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Worried doctors and medical researchers on conference meeting, discussing possible solutions for resolving a world health crisis. Health and medical care concept. Selective focus.

Computers Excel at Finding Temporary Patterns

Which contributes to the replication crisis in science

The scientific method calls for the rigorous testing of plausible theories, ideally through randomized controlled trials. For example, a study of a COVID-19 vaccine might give the vaccine to 10,000 randomly selected people and a placebo to another 10,000, and compare the infection rates for the two groups. If the difference in the infection rates is too improbable to be explained by chance, then the difference is deemed statistically significant. How improbable? In the 1920s, the great British statistician, Sir Ronald Fisher , said that he favored a 5 percent threshold. So 5 percent became the Holy Grail. Unfortunately, the establishment of a 5 percent hurdle for statistical significance has had the perverse effect of encouraging researchers to do whatever Read More ›

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Serious Investors Should Embrace the Stock Market Algos!

We can use computers’ inability to distinguish meaning from noise in data to our advantage

Computer algorithms are much, much better than humans at discovering statistical patterns but much, much worse than humans at discerning whether the patterns are meaningful. Wise investors can use the resulting blips to their advantage.

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Computers’ Stupidity Makes Them Dangerous

The real danger today is not that computers are smarter than us, but that we think computers are smarter than us

Many marketing decisions, medical diagnoses, and stock trades, loan and job applications, and election strategies are evaluated by computers. But, as my little experiment shows, the computer does not know whether a pattern is information or noise.

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