How can business intelligence and data analytics help medical centers in countries like Uganda care for patients and operate more efficiently? Robert J. Marks discusses data analytics, inefficiency, and medicine with Dr. Peter Kulaba. Show Notes 00:54 | Introducing Dr. Peter Kulaba 02:13 | Medical challenges facing Uganda 03:54 | Wasting the money used for healthcare 05:09 | Run-down medical…
The explosion of data has vastly increased the number of coincidental patterns that can be discovered by tenacious researchers. If there are a relatively fixed number of useful patterns and the number of coincidental patterns is growing exponentially, then the ratio of useful patterns to useless patterns must necessarily be getting closer to zero every day.
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Media often co-operate with researchers’ inflated claims about machine learning’s powers of discovery. An ingenious “creative” approach to accuracy enables the misrepresentation, says data analyst Eric Siegel.
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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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Gary N. Smith and Robert J. Marks discuss the inability of AI to understand puns, lyrics, context, or anything at all. From trading futures, predicting political outcomes, and parsing lyrics, the fundamental incomprehension of artificial intelligence is a key to understanding its limitations. Show Notes 02:30 | The AI Delusion by Oxford University Press 03:00 | The importance of knowing…
Contrary to the dogma of hypothesis testing, it is possible to do after-the-fact pattern analysis while limiting the probability of false positives.
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