The Day Pain Died

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The date of the first operation under anesthetic, Oct. 16, 1846, ranks among the most iconic in the history of medicine.

Before 1846, the vast majority of religious and medical opinion held that pain was inseparable from sensation in general, and thus from life itself. Though the idea of pain as necessary may seem primitive and brutal to us today, it lingers in certain corners of healthcare, such as obstetrics and childbirth, where epidurals and caesarean sections still carry the taint of moral opprobrium. In the early 19th century, doctors interested in the pain-relieving properties of ether and nitrous oxide were characterized as cranks and profiteers. The case against them was not merely practical, but moral: They were seen as seeking to exploit their patients' base and cowardly instincts. Furthermore, by whipping up the fear of operations, they were frightening others away from surgery and damaging public health.

The "eureka moment" of anesthesia, like the seemingly sudden arrival of many new technologies, was not so much a moment of discovery as a moment of recognition: a tipping point when society decided that old attitudes needed to be overthrown. It was a social revolution as much as a medical one.

Mike Jay, The Atmosphere of Heaven

Leaders Make Wrong Assumptions about Toxic Work Culture

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In many organizations, bad news about toxic behaviors gets filtered out as it moves up the hierarchy. As a result, top leaders often think they’ve done a better job addressing toxic culture than they actually have. In a survey of 16,000 managers across nearly 500 companies, top executives were 24% more likely to say that they addressed unethical behavior quickly and consistently compared with how well middle managers thought the C-suite dealt with unethical actions. Top executives were 48% more likely to believe they dealt effectively with cutthroat managers. 

Donald Sull and Charles Sull writing for the MIT Sloan Management Review

8 iPhone Tricks Worth Knowing

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Observed Behavior is Changed Behavior

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When the lead singer at the concert asks you to scream as loud as you can, and then he asks again, going, “I can’t hear you! You can do better than that!” have you ever noticed that the second time is always louder?  Why wasn’t everyone yelling at the top of their lungs the first time?  Some really cool scientists actually tested this in 1979. (They) had people shout as loud as they could in a group and then alone, or vice-versa. Sure enough, the overall loudness of a small group of people was less than any one of them by themselves. You can even chart it on a graph. The more people you add, the less effort any one person does.

If you know you aren’t being judged as an individual, your instinct is to fade into the background. To prove this, psychologist Alan Ingram ruined tug-of-war forever. In 1974, he had people put on a blindfold and grab a rope. The rope was attached to a rather medieval-looking contraption that simulated the resistance of an opposing team. The subjects were told many other people were also holding the rope on their side, and he measured their efforts. Then, he told them they would be pulling alone, and again he measured. There were alone both times, but when they thought they were in a group, they pulled 18 percent less strenuously on average.

This behavior is more likely to show up when the task a hand is simple. With complex tasks, it is usually easy to tell who isn’t pulling their weight. Once you know your laziness can be seen, you try harder. You do this because of another behavior called evaluation apprehension, which is just a fancy way of saying you care more when you know you are being singled out. Your anxiety levels decrease when you know your effort will be pooled with others’. You relax. You coast. 

David McRaney, You are Not so Smart

Our Favorite Conclusions

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It would be unfair for teachers to give the students they like easier exams than those they dislike, for federal regulators to require that foreign products pass sticker safety tests than domestic products, or for judges to insist that the defense attorney make better arguments than the prosecutor.

And yet, this is just the sort of uneven treatment most of us give to facts that confirm and disconfirm our favored conclusions.

For example, volunteers in one study were told that they had performed very well or very poorly on a social-sensitivity test and were then asked to assess two scientific reports—one that suggested the test was valid and one that suggested it was not. Volunteers who had performed well on the test believed that the studies in the validating report used sounder scientific methods than did the studies in the invalidating report, but volunteers who performed poorly on the test believed precisely the opposite.

To ensure that our views are credible, our brain accepts what our eye sees. To ensure that our views are positive, our eye looks for what our brain wants.

Daniel Gilbert, Stumbling on Happiness

12 Recent Articles about AI Implications

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Study: The pandemic has aged the brains of teenagers

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The stress of living through the pandemic physically changed adolescents' brains and prematurely aged them by at least three or four years. That’s the finding of a new study out of Stanford University. If kids who experienced the pandemic show accelerated development in their brains, scientists say they will have to account for that abnormal rate of growth in any future research involving this generation. 

Study co-author Jonas Miller said, “Adolescence is already a period of rapid reorganization in the brain, and it’s already linked to increased rates of mental health problems, depression, and risk-taking behavior. Now you have this global event that’s happening, where everyone is experiencing some kind of adversity in the form of disruption to their daily routines – so it might be the case that the brains of kids who are 16 or 17 today are not comparable to those of their counterparts just a few years ago.”

Details are in the journal Biological Psychiatry: Global Open Science

The Smooth Handle

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One of (Thomas) Jefferson’s rules was this, and I think it is priceless, "Always take hold of things by the smooth handle." That is, go at a job or at your difficulty by the use of a method that will encounter the least resistance. Resistance causes friction in mechanics, therefore it is necessary in mechanics to overcome or reduce friction.

The negative attitude is a friction approach. That is why negativism develops such great resistance. The positive approach is the "smooth handle" technique. It is in harmony with the flow of the universe. It not only encounters less resistance, but actually stimulates assistance forces. It is remarkable how from early life until the end of your earthly existence the application of this philosophy will enable you to attain successful results in areas where otherwise you would be defeated.

Norman Vincent Peale, The Power of Positive Thinking

A basic explanation of the new AI bot called ChatGPT

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U.S.-based AI research company OpenAI, the San Francisco company behind the text-to-image creation tool named DALL-E, has created a chatbot that responds to user-submitted queries. The model was trained using reinforcement learning from human feedback. ChatGPT (GPT stands for “generative pre-trained transformer”) shows how far artificial intelligence—particularly AI text generators—has come. Because it remembers what you've written or said, the interaction has a dynamic conversational feel. That makes it different from other chatbots, which are static. It could be the basis for a medical chatbot to answer patient questions about very specific symptoms or serve as a personalized therapy bot.

Give the software a prompt — and it creates articles, even poetry. It writes code, too. And explains the code. Or makes correction to errors in code. GPT-3 came before it. Both are generative models. That means they are trained to predict the next word in a sentence. It’s like a topnotch autocompletion tool. What separates ChatGPT from GPT-3 is that ChatGPT goes beyond predicting the next word to also follow the users instructions. Training with examples of human conversations has made the experience with the bot more familiar to users.

ChatGPT is being used to rewrite literary classics, create a bible song about ducks, string cheese sonnet, explain scientific concepts, explain how to remove a peanut butter sandwich from a VCR in the style of the King James Bible, or write a story about a fictitious Ohio-Indiana war. The New York Times gushes, “ChatGPT is, quite simply, the best artificial intelligence chatbot ever released to the general public.” Some tech observers predict it could one day replace Google.

But the software has limitations: such as not having information about 2022 because it doesn’t “crawl” the web like Google in search of new information, it can spit out “plausible-sounding but incorrect answers,” and while it is designed to not provide inappropriate content as creators have taken steps to avoid racist, sexist and offensive outputs that have popped out of other chatbot, there is likely to be some hiccups in that process.

Some warn about its potential abuse—blurring the lines between original writing and plagiarism.

Mike Sharples, a U.K. professor, says such technology “could become a gift for student cheats, or a powerful teaching assistant, or a tool for creativity.” 

Ars Technica reporter Benj Edwards writes:

"[I]t’s possible that OpenAI invented history’s most convincing, knowledgeable and dangerous liar — a superhuman fiction machine that could be used to influence masses or alter history." 

Decide for yourself whether we’re on the cusp of new creativity or massive fraud. Create a free account using your email here. Or try the Twitter bot if you’d prefer not to sign up.

Articles about ChatGPT: 

New AI chatbot is scary good – Axios

OpenAI’s new chatbot ChatGPT could be a game-changer for businesses – Tech Monitor  

Google is done. Here’s why OpenAI’s ChatGPT Will Be a Game Changer – Luca Petriconi

The College Essay Is Dead – The Atlantic

The Brilliance and Weirdness of ChatGPT – New York Times

ChatGPT Is Dumber Than You Think - The Atlantic

The Lovelace Effect – AI generated texts should lead us to re-value creativity in academic writing - London School of Economics

Hugging Face GPT-2 Output Detector

AI is finally good at stuff, and that’s a problem - Vox

ChatGPT: How Does It Work Internally? - Toward AI

Your Creativity Won’t Save Your Job From AI - The Atlantic

Could your public photos be used in an AI deepfake? - Ars Technica

API access is expected early in 2023, so companies can create products based on the software. Later next year, rumors say OpenAI will introduce an even better AI model named GPT-4.

Brain damaged decision-making

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We humans make all the same mistakes, over and over again. It's how we are wired. To neurophysiologists, who research cognitive functions, the emotionally driven appear to suffer from cognitive deficits that mimic certain types of brain injuries. Not just partisan political junkies, but ardent sports fans, the devout, even hobbyists. Anyone with an intense emotional interest in a subject loses the ability to observe it objectively: You selectively perceive events. You ignore data and facts that disagree with your main philosophy. Even your memory works to fool you, as you selectively retain what you believe in, and subtly mask any memories that might conflict.

Barry Ritholtz writing in the Washington Post

Job Hopping

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In 2014, I reported on a new paper about young workers who regularly quit their jobs and ended up better for it. “People who switch jobs more frequently early in their careers tend to have higher wages and incomes in their prime-working years,” one of the co-authors, the economics professor Henry Siu, told me. “Job-hopping is actually correlated with higher incomes, because people have found better matches.”  

Last year, the benefits of role-switching crystallized when I read a paper by the Northwestern University economist Dashun Wang. In a deep analysis of the careers of scientists and artists, he found that their “hot streaks” tended to be periods of focused and narrow work following a spell of broader experimentation. This is sometimes called the “explore-exploit” sequence. The idea is that many successful people are like good oil scouts: They spend a lot of time searching for their space, and then they drill deep when they find the right niche.

Role-switching is important not because quitting is so wonderful, but rather because sampling from different skills and fields is helpful, provided that you’re prepared to pounce on an area that clicks for you.

Derek Thompson writing in The Atlantic

Resisting Simple Solutions

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People who have always operated without skin in the game (or without their skin in the right game) seek the complicated, centralized, and avoid the simple like the pest. Practitioners on the other hand have opposite instincts, looking for the simplest heuristics.

People who are bred, selected, and compensated to find complicated solutions do not have an incentive to implement simplified ones. 

Nassim Nicholas Taleb, Skin in the Game

20 Data Science Articles from Nov 2022

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3 approaches to track and reduce space debris

Big tech has a “blind spot about the severe limitations of large language models.” Meta’s Galactica is another example

A key advancement toward commercial quantum computing applications

Creating and deleting a SQL database on Azure Cloud

A dataset to train AI systems that can generate code

The NRO has released its formal request for proposals from commercial operators who can provide the spy satellite agency with hyperspectral imagery

Tracking the typical lifecycle of AI innovations in the aerospace and defense industry

Scientists call for better space weather alerts to prevent commercial space disasters

Data preparation is key to expanding military benefits of AI

The difficult search for dangerous space Junk that could potentially trigger devastating chain reactions 

The National Geospatial-Intelligence Agency plans to double spending on contracts to monitor global economic activity from space

“Our adversaries are coming after us in cyberspace” says a U.S. Space Force Col.

5 ways to use predictive insights to get the most from your data

Where is the satellite intelligence industry heading next?

15 of the little-known uses of artificial intelligence

Geopolitical threats in the space environment—debating a potential new cold war

AI creators have problems explaining how it works and determining why it has the outputs it has

Top C++ based data science and machine learning libraries

A moderately large atomic detonation could knock out satellites in low Earth orbit

7 Steps to Mastering Machine Learning with Python in 2022

Two major problems with IQ

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The first problem with IQ stems from those who misunderstand what it’s trying to measure. IQ measures your score on a test against the averages of everyone else taking that test. It tells you how good someone is at answering certain types of questions, as compared with others. Thus, it’s not about an absolute intelligence, but relative intelligence. The trouble occurs when people misunderstand this point. They assume IQ represents raw “brain power.” Worse, some people equate IQ with worth.    

In short, the data we have — the data some people use to pigeon-hole a person for life — is desperately weak and inconclusive.

The second problem is that IQ is far too narrow a metric to dominate so much of the psychometric landscape. IQ represents only one, or a few, kinds of intelligence. Psychologist Howard Gardener identifies eight different kinds of intelligence, and “IQ tests and other kinds of standardized tests valorize” only two of them.

Jonny Thomson writing in BigThink