_{Natural and Artificial Intelligence News and Analysis}

^CategoryMachine Learning

Oh no!

^{Type
post

Author
News
Date
August 27, 2020

Categorized
Artificial Intelligence, Business and Finance, Creativity, Machine Learning

Tagged
___longform, Alan Turing, Algorithms, Chinese Room, Church–Turing Thesis, Creativity, Dweebs, Featured, George Gilder, Go, Jay Richards, Jeopardy, John Searle, Larry L. Linenschmidt, Lovelace test, Peter Thiel, qualia, Quantum Computing, Robert J. Marks, Satya Nadella, Surprise, Turing Test, Watson}

Six Limitations of Artificial Intelligence As We Know It

_{You’d better hope it doesn’t run your life, as Robert J. Marks explains to Larry Linenschmidt} _{News

August 27, 2020

18

Artificial Intelligence, Business and Finance, Creativity, Machine Learning}

The list is a selection from “Bingecast: Robert J. Marks on the Limitations of Artificial Intelligence,” a discussion between Larry L. Linenschmidt of the Hill Country Institute and Walter Bradley Center director Robert J. Marks. The focus on why we mistakenly attribute understanding and creativity to computers. The interview was originally published by the Hill Country Institute and is reproduced with thanks. https://episodes.castos.com/mindmatters/Mind-Matters-097-Robert-Marks.mp3 Here is a partial transcript, listing six limits of AI as we know it: (The Show Notes, Additional Resources, and a link to the full transcript are below.) 1. Computers can do a great deal but, by their nature, they are limited to algorithms. Larry L. Linenschmidt: When I read the term “classical computer,” how does a computer function? Let’s build on Read More ›

Real Php code developing screen. Programing workflow abstract algorithm concept. Lines of Php code visible under magnifying lens.

^{Type
post

Author
News
Date
May 8, 2020

Categorized
Artificial Intelligence, Machine Learning, Medicine and Health, Philosophy of Mind, Technocracy

Tagged
Algorithms, David C. Krakauer, InterPlanetary Project (SFI), Jorge Luis Borges (1899–1986), science}

Will Ideas or Algorithms Rule Science Tomorrow?

_{David Krakauer of the Santa Fe Institute offers an unsettling vision of future science as produced by machines that no one really understands} _{News

May 8, 2020

7

Artificial Intelligence, Machine Learning, Medicine and Health, Philosophy of Mind, Technocracy}

The basic problem is that accepting on faith what we can’t ever hope to understand is not a traditional stance of science. Thus it’s a good question whether science could survive such a transition and still be recognizable to scientists. But does turning things over to incomprehensible algorithms, as Krakauer proposes, really work anyway? Current results from a variety of areas give pause for thought.

Robot studies a coronavirus with magnifier,nano robot with bacterium,3d render.

^{Type
post

Author
News
Date
April 30, 2020

Categorized
Artificial Intelligence, Machine Learning, Medicine and Health

Tagged
Alex Engler, COVID-19, Matista Hollister, Robert J. Marks, Wim Naudé}

Can AI Save Us from COVID-19? An Expert Is Skeptical

_{To use AI more successfully next time, we need a clear understanding of its limitations as well as its capabilities} _{News

April 30, 2020

6

Artificial Intelligence, Machine Learning, Medicine and Health}

Experts list various problems, including the fact that AI is vulnerable to failure due to unforeseen problems, including problems with data (too sparse, too noisy, too many outliers, etc.). It also doesn’t learn as well from experience as humans do.

^{Type
post

Author
Denise Simon
Date
April 12, 2020

Categorized
Artificial Intelligence, Global Technology, Machine Learning, Medicine and Health

Tagged
Health Care, Institute for Health Metrics and Evaluation}

Why Depend on Only One Source for Modeling AI in Healthcare?

_{We may be missing many of the ways AI can help us} _{Denise Simon

April 12, 2020

5

Artificial Intelligence, Global Technology, Machine Learning, Medicine and Health}

As we struggle with the COVID-19 crisis, many are beginning to ask hard questions about how our system works, its strengths, weaknesses, and vulnerabilities. One vulnerability might be too heavy reliance on a single source for data modeling and predictions. Considering all the uses to which AI may be put in health care, getting our guidance exclusively from the Institute for Health and Metric Evaluation for modeling is reckless.

^{Type
post

Author
Brendan Dixon
Date
April 1, 2020

Categorized
Artificial Intelligence, Business and Finance, Machine Learning

Tagged
Automation, Coronavirus, COVID-19, Unemployment}

Will the COVID-19 Pandemic Promote Mass Automation?

_{Caution! Robots don’t file for benefits but that’s not all we need to know about them} _{Brendan Dixon

April 1, 2020

4

Artificial Intelligence, Business and Finance, Machine Learning}

I understand the panic many business leaders experience as they try to stay solvent while customers evaporate. Panic, however, is a poor teacher: AI-based automation will not only not solve all their problems, it may very well add to them. AI is not a magic box into which we can stuff them and make them disappear.

^{Type
post

Author
Brendan Dixon
Date
March 20, 2020

Categorized
Artificial Intelligence, Machine Learning, Medicine and Health, Social Media

Tagged
censorship, Content moderation, COVID-19, Featured}

AI Is Not Ready to Moderate Content!

_{In the face of COVID-19 quarantines for human moderators, some look to AI to keep the bad stuff off social media} _{Brendan Dixon

March 20, 2020

6

Artificial Intelligence, Machine Learning, Medicine and Health, Social Media}

Big social media companies have long wanted to replace human content moderators with AI. COVID-19 quarantines have only intensified that discussion. But AI is far, far from ready to successfully moderate content in an age of where virtual monopolies make single point failure a frequent risk.

^{Type
post

Author
Brendan Dixon
Date
March 16, 2020

Categorized
Artificial Intelligence, Ethics, Machine Learning

Tagged
Deep Learning, Moral decision-making}

All AI’s Are Psychopaths

_{We can use them but we can’t trust them with moral decisions. They don’t care why} _{Brendan Dixon

March 16, 2020

4

Artificial Intelligence, Ethics, Machine Learning}

Building an AI entails moving parts of our intelligence into a machine. We can do that with rules, (simplified) virtual worlds, statistical learning… We’ll likely create other means as well. But, as long as “no one is home”—that is, the machines lack minds—gaps will remain and those gaps, without human oversight, can put us at risk.

^{Type
post

Author
News
Date
February 6, 2020

Categorized
Artificial Intelligence, Arts & Culture, Machine Learning, Peer Review

Tagged
Jean-François Bonnefon, Plagiarism}

Anti-Plagiarism Software Goof: Paper Rejected for Repeat Citations

_{The scholar was obliged by discipline rules to cite the flagged information repetitively} _{News

February 6, 2020

3

Artificial Intelligence, Arts & Culture, Machine Learning, Peer Review}

Not only was Jean-François Bonnefon’s paper rejected by conventional anti-plagiarism software but the rejection didn’t make any sense. Bonnefon, research director at Toulouse School of Economics, was informed of “a high level of textual overlap with previous literature” (plagiarism) when he was citing scientists’ affiliations, standard descriptions, and papers cited by other—information he was obliged to cite accurately, according to a standard format. “It would have taken two [minutes] for a human to realise the bot was acting up,” he wrote on Twitter. “But there is obviously no human in the loop here. We’re letting bots make autonomous decisions to reject scientific papers.” Reaction to the post by Dr Bonnefon, who is currently a visiting scientist at the Massachusetts Institute Read More ›

^{Type
post

Author
Brendan Dixon
Date
January 28, 2020

Categorized
Artificial Intelligence, Machine Learning, Medicine and Health

Tagged
Data analysis, Eric Siegel, hype, media, Statistics}

Can The Machine TELL If You Are Psychotic or Gay?

_{No, and the hype around what machine learning can do is enough to make old-fashioned tabloids sound dull and respectable} _{Brendan Dixon

January 28, 2020

5

Artificial Intelligence, Machine Learning, Medicine and Health}

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.

^{Type
post

Author
Eric Holloway
Date
January 21, 2020

Categorized
Artificial Intelligence, Machine Learning, Philosophy of Mind, Programming

Tagged
Kernel, NP-Hard Problem, science, Support Vector Machines (SVMs), Vapnik–Chervonenkis (VC) dimension}

Will an AI Win a Nobel Prize for Science All by Itself One Day?

_{No, but Support Vector Machines (SVMs) can allow scientists to frame questions so that a comprehensible answer is more likely} _{Eric Holloway

January 21, 2020

6

Artificial Intelligence, Machine Learning, Philosophy of Mind, Programming}

AI can certainly help scientists. But to understand why AI can’t do science on its own, we should take a look at the NP-Hard Problem in computer science. The “Hard” is in the name of the problem for a reason…

^{Type
post

Author
Brendan Dixon
Date
December 23, 2019

Categorized
Education, Machine Learning

Tagged
Robert Wilson}

Machines Can’t Teach Us How To Learn

_{A recent study used computer simulations to test the “small mistakes” rule in human learning} _{Brendan Dixon

December 23, 2019

3

Education, Machine Learning}

Machine learning is not at all like human learning. For example, machine learning frequently requires millions of examples. Humans learn from a few examples.

^{Type
post

Author
News
Date
December 12, 2019

Categorized
Arts & Culture, Machine Learning, Work

Tagged
Archeology, Language, Mesopotamia, Minoan A, Minoan B, Sumerian, Ugaritic}

Can AI Help Us Decipher Lost Languages?

_{That depends mainly on the reasons we haven’t yet deciphered ancient texts} _{News

December 12, 2019

7

Arts & Culture, Machine Learning, Work}

AI can speed up translation of ancient documents where only a few scholars know the language. Whether it can help with mysterious unknown languages like Minoan A is another question.

^{Type
post

Author
Jay Richards
Date
December 6, 2019

Categorized
Ethics, Machine Learning

Tagged
John Waters, self-driving cars, Trolley problem}

Will Self-Driving Cars Change Moral Decision-Making?

_{It’s time to separate science fact from science fiction about self-driving cars} _{Jay Richards

December 6, 2019

6

Ethics, Machine Learning}

Irish playwright John Waters warns of a time when we might have to grant moral discretion to computer algorithms, just as Christians now grant to the all-knowing but often inscrutable decrees of God. Not likely.

^{Type
post

Author
Eric Holloway
Date
December 2, 2019

Categorized
Business and Finance, Machine Learning

Tagged
Empirical Generalized Information (EGI), Gini metric}

What Vehicle Would Bob Buy?

_{Both empirical generalized information (EGI) and the Gini metric can generate useful information} _{Eric Holloway

December 2, 2019

10

Business and Finance, Machine Learning}

Contrary to traditional Fisherian hypothesis testing, it is possible to create models after viewing the data and still quantify the generality of the model.

^{Type
post

Author
Eric Holloway
Date
November 25, 2019

Categorized
Machine Learning

Tagged
Empirical Generalized Information (EGI)}

Machine learning: Harnessing the Power of Empirical Generalized Information (EGI)

_{We can calculate a probability bound from entropy. Entropy also happens to be an upper bound on the binomial distribution} _{Eric Holloway

November 25, 2019

5

Machine Learning}

We want our calculation to demonstrate the notion that if we have high accuracy and a small model, then we have high confidence of generalizing. Intuitively, then, we add the model size to the accuracy and subtract this quantity from the entropy of having absolutely no information about the problem.

^{Type
post

Author
Eric Holloway
Date
November 20, 2019

Categorized
Machine Learning

Tagged
Clue (board game), decision tree, Entropy, Probability}

Machine Learning: Decision Trees Can Solve Murders

_{Decision trees increase our chance at a right answer. We can see how that works in a mystery board game like Clue} _{Eric Holloway

November 20, 2019

6

Machine Learning}

Entropy is a concept in information theory that characterizes the number of choices available when a probability distribution is involved. Understanding how it works helps us make better guesses.

^{Type
post

Author
Eric Holloway
Date
November 18, 2019

Categorized
Machine Learning

Tagged
Occam's razor, Probability}

Machine Learning: Using Occam’s Razor to Generalize

_{A simple thought experiment shows us how} _{Eric Holloway

November 18, 2019

4

Machine Learning}

This approach is contrary to Fisher's method where we formulate all theories before encountering the data. We came up with the model after we saw the cards we drew.

^{Type
post

Author
Brendan Dixon
Date
November 16, 2019

Categorized
Business and Finance, Machine Learning, Work

Tagged
Boeing, Elon Musk, robotics}

Boeing’s Sidelined Fuselage Robots: What Went Wrong?

_{It’s not what we learn, it’s what we forget} _{Brendan Dixon

November 16, 2019

4

Business and Finance, Machine Learning, Work}

By all means, let’s build machines that enhance our abilities. But let’s not forget that the really amazing thing is not the tool, but the tool builder.

^{Type
post

Author
News
Date
November 15, 2019

Categorized
Business and Finance, Machine Learning, Work

Tagged
Automation, Automation failure, robotics}

Boeing Workers, Please Don’t Kick the Robot on Its Way Out

_{The jetliner manufacturer’s decision to give the robots’ job back to machinists underlines the hard realities of automation. For example, it doesn’t always work} _{News

November 15, 2019

5

Business and Finance, Machine Learning, Work}

Robot error turned out to be a bigger problem than human error.