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CategoryMachine Learning

robots in a car plant

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

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.

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Woman in medical protective mask applying an antibacterial antiseptic gel for hands disinfection and health protection during during flu virus outbreak. Coronavirus quarantine and novel covid ncov

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

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.

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Businessman with psychopathic behaviors

All AI’s Are Psychopaths

We can use them but we can’t trust them with moral decisions. They don’t care why

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.

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Citation

Anti-Plagiarism Software Goof: Paper Rejected for Repeat Citations

The scholar was obliged by discipline rules to cite the flagged information repetitively

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 ›

Demographic Change

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

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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robot work on microscope

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

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… 

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Students studying in college library

Machines Can’t Teach Us How To Learn

A recent study used computer simulations to test the “small mistakes” rule in human 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.

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Archeological site of Phaistos in Crete

Can AI Help Us Decipher Lost Languages?

That depends mainly on the reasons we haven’t yet deciphered ancient texts

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.

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The difference between right and wrong

Will Self-Driving Cars Change Moral Decision-Making?

It’s time to separate science fact from science fiction about self-driving cars

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.

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Clouds Michael Weidner-h-rP5KSC2W0-unsplash

Improve Your Job Chances by Scaling the Cloud

WBC Fellow Releases introductory book on Building Scalable PHP web applications using the cloud

One new issue that the cloud creates is that programmers are more often required to be “full stack” developers,” Jonathan Bartlett explains. “Unfortunately, most programmers coming out of college have little to no system administration experience. That’s why this book is based on the ‘full stack’ concept, showing how system administration and programming relate to each other.”

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Red sports car Josh Rinard Unsplash

What Vehicle Would Bob Buy?

Both empirical generalized information (EGI) and the Gini metric can generate useful information

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

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Black balls white balls Adobe Stock

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

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.

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Missing piece

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

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.

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Playing cards for poker and gambling, isolated on white background with clipping path

Machine Learning: Using Occam’s Razor to Generalize

A simple thought experiment shows us how

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.

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Boeing 777

Boeing’s Sidelined Fuselage Robots: What Went Wrong?

It’s not what we learn, it’s what we forget

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.

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Burnout

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

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

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3D Rendering of abstract binary data in glowing blue and red color. For deep machine learning, crypto currency, hi tech product uses. Big data visualization, artificial intelligence. With copy space

The Greatest Threat We Face From AI—and What We Can Do

Here’s a list of things that have really happened with artificial intelligence (AI), in order of increasing severity.

When we get to the end of the list, we will see that it is like beads connected by a string—revealing the most dangerous threat.

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Beautiful Male Computer Engineer and Scientists Create Neural Network at His Workstation. Office is Full of Displays Showing 3D Representations of Neural Networks.

How Algorithms Can Seem Racist

Machines don’t think. They work with piles of “data” from many sources. What could go wrong? Good thing someone asked…

Some of the recent conflicts around algorithms and ethnicity are flubs that social media entrepreneurs will regret. Others may endanger life.

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Brush and razor for shaving beard. Concept background of hair salon men, barber shop

Occam’s Razor Can Shave Away Data Snooping

The greater an object's information content, the lower its probability.

One technique to avoid data snooping is based on the intersection of information theory and probability: An object’s probability is related to its information content. The greater an object’s information content, the lower its probability. We measure a model’s information content as the logarithmic difference between the probability that the data occurred by chance and the number of bits required to store the model. The negative exponential of the difference is the model’s probability of occurring by chance. If the data cannot be compressed, then these two values are equal. Then the model has zero information and we cannot know if the data was generated by chance or not. For a dataset that is incompressible and uninformative, swirl some tea Read More ›

AI face detection,Face Recognition Vendor

Big Tech Tries to Fight Racist and Sexist Data

The trouble is, no machine can be better than its underlying training data. That’s baked in

The problem with machine learning-based AI in police work is not so much its inherent bias (none of us is bias-free) but the delegation to a machine of what should be a human decision.

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