Is AI fundamentally flawed? Can Elon Musk merge man with machines? Will there ever be self-driving cars? Join us as we revisit the top 12 most over-hyped stories in artificial intelligence from 2020 with Robert J. Marks, Jonathan Bartlett, and Eric Holloway. Show Notes 00:01:10 | Introducing Jonathan Bartlett 00:01:37 | Introducing Dr. Eric Holloway 00:02:00 | #12: “The way Read More ›
Merry Christmas! Our Walter Bradley Center director Robert J. Marks has been interviewing fellow computer nerds (our Brain Trust) Jonathan Bartlett and Eric Holloway about 12 overhyped AI concepts of the year. From AI Dirty Dozen 2020 Part II. Now here’s #8. Sick of paying for health care insurance? Guess what? AI is better! Or maybe, wait… “Is AI really better than physicians at diagnosis?” starts at 01:25 Here’s a partial transcript. Show Notes and Additional Resources follow, along with a link to the complete transcript. Robert J. Marks: We’re told AI is going to replace lawyers and doctors and accountants and all sorts of people. So, let’s look at a case of the physicians. This was a piece on Read More ›
There are many forces that shape the hyped AI stories we read. Media is everywhere and competition is fierce. Articles with provocative headlines and content are clickbait for the browsing consumer. We’re going to count down the AI Dirty Dozen: the top twelve AI hyped stories for 2020. Join Dr. Robert J. Marks as he discusses some of these stories with Read More ›
William Dembski created quite a stir in the world of information theory with his book The Design Inference. For the first time, he outlined a rigorous method for identifying design, which he called the explanatory filter. Since then many critics have claimed that Dembski’s proposed filter is without merit due to the lack of application in the couple of decades since its invention. But, are the critics right, or are they wrong—wrong in the way that a fish doesn’t recognize water because water is the very atmosphere of the fish’s existence? Let us first remind ourselves of Dembski’s explanatory filter. His filter proceeds in three main steps. Eliminate events of large probability (necessity) Eliminate events of medium probability (chance) Specify Read More ›
Those dealing with data must always remember “If you torture data long enough, it will confess to anything.” The answers that computers give must themselves be questioned. Robert J. Marks and Gary Smith address artificial intelligence, spurious correlations, and data research on Mind Matters. Show Notes 01:34 | Introduction to Gary Smith, the Fletcher Jones Professor of Economics at Pomona Read More ›
In this week’s podcast, Pomona College’s Gary Smith, author of The AI Delusion, talks with Walter Bradley Center director Robert J. Marks about why so many bad research papers are accepted in the science establishment and in media.
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