As Jeffrey Shallit claims? That is, does intelligent intervention increase information? Is that intervention detectable by science methods? With 2 DVDs of the same storage capacity — one random noise and the other a film (BraveHeart, for example), how do we detect a difference? Robert J. Marks, one of the authors of Introduction to Evolutionary Informatics<,/em> thinks so:
In Define information before you talk about it, neurosurgeon Michael Egnor interviewed engineering prof Robert J. Marks on the way information, not matter, shapes our world (October 28, 2021). In the first portion, Egnor and Marks discussed questions like: Why do two identical snowflakes seem more meaningful “https://mindmatters.ai/2021/11/how-information-becomes-everything-including-life/” target=”another”>more meaningful than one snowflake. Then they turned to the relationship between information and creativity. Is creativity a function of more information? Or is there more to it? Now, they ask, does human intervention make any difference? Does Mount Rushmore have no more information than Mount Fuji?News, “Does Mt Rushmore contain no more information than Mt Fuji?” at Mind Matters News
Michael Egnor: Dr. Jeffrey Shallit, a mathematician at the University of Waterloo near Toronto, claims that Mount Rushmore doesn’t have any more information than Mount Fuji. I’d like to ask my guest today Dr. Robert Marks to answer that question.
Robert J. Marks: In terms of meaningful information I think it’s obvious. Michael, they used to say that it doesn’t take a brain surgeon to answer this or it doesn’t take a rocket scientist. Well, it turns out you’re a brain surgeon. And I’ve done work for NASA. And I got a NASA tech brief award. I guess that makes me a rocket scientist. So I think for both of us, the answer is obvious. Mount Rushmore contains more information than does Mount Fuji.
There’s more meaningful information on Mount Rushmore. There’s Lincoln and Roosevelt and Washington. And yeah, what do we get with Mount Fuji? We just get a big chocolate gumdrop.
Michael Egnor: Can we say what type of information the additional information on Mount Rushmore is?
Robert J. Marks: Yeah, this is an interesting question. I’m going to give an explanation, then dovetail into the answer. We can ask ourself the definition of two DVDs, both of which have the same storage capacity. One has the movie Braveheart. One has just random noise. And both of them take out the same amount of bytes.
Robert J. Marks: Can we say that the DVD of Mel Gibson’s Braveheart has more information than the noise? Yes, absolutely. If you talk about meaningful information, and as we talked about before, it depends on your definition of information. Certainly in the case of Shannon information, or possibly Kolmogorov information yeah, they’re the same. But neither one of those measures meaning. And so one has to go to specified complexity, the mathematics of specified complexity, specifically algorithmic specified complexity.
And I’ll give a little pitch here, in case people want to read more about it. It’s in Chapter Seven, of the book that I co-authored with design theorist William Dembski and Winston Ewert called Introduction to Evolutionary Informatics.
And the cool part about the book is that it references a lot more nerdy papers that have been published in archival prestigious journals and conferences. So you can read it there at kind of a layperson’s level, or you can dig deeper and go into the papers.
Here are the previous episodes in the series:
- How information becomes everything, including life. Without the information that holds us together, we would just be dust floating around the room. As computer engineer Robert J. Marks explains, our DNA is fundamentally digital, not analog, in how it keeps us being what we are.
- Does creativity just mean Bigger Data? Or something else? Michael Egnor and Robert J. Marks look at claims that artificial intelligence can somehow be taught to be creative. The problem with getting AI to understand causation, as opposed to correlation, has led to many spurious correlations in data driven papers.
You may also wish to read:
Jeffrey Shallit, a computer scientist, doesn’t know how computers work. Patterns in computers only have meaning when they are caused by humans programming and using them. (Michael Egnor)