There are many things to take from this story — about beginner’s mind, the diversity of human experience, and the interoperability of language. But what stood out to me most was two opposing lessons about shared protocols and modularity. Tomás’ experiment failed. It failed because each amateur cartographer injected their own methodology and process, resulting in incompatible maps. But in another sense, Tomás succeeded. Sure, maybe this collection of artifacts would be useless for military strategy or commerce, but on the other hand... LOOK AT THESE MAPS, THESE MAPS RULE.

source: HN

People who end up in the emergency room complaining of chest pains a few weeks before their 40th birthday are very similar to people who end up in the emergency room with chest pains a few weeks after their 40th birthday. But on a chart, the former are 39 years old and the latter are 40.

The point of these studies isn’t to titter or sigh at the peculiarities of human reasoning but to use these natural experiments to estimate the effect of medical procedures. If the only reason that near-18 and 18-year-olds are prescribed opioids differently is the semantics of “child” and “adult,” then we can use the discontinuity in prescriptions as a natural experiment—it’s as if prescribing around the age of 18 were randomly assigned. The authors find, for example, that compared to the just-under-18s, the just-over-18s were 12.6% more likely to later be diagnosed for an opioid-related adverse event such as an overdose. The greater rate of overdose is valuable information—but imagine the difficulty of trying to convince an Institutional Review Board that it would be ethical to randomly prescribe opioids to young people.

source: MR

Scientists are increasingly realizing that animals, like people, are individuals. They have distinct tendencies, habits and life experiences that may affect how they perform in an experiment. That means, some researchers argue, that much published research on animal behavior may be biased. Studies claiming to show something about a species as a whole—that green sea turtles migrate a certain distance, say, or how chaffinches respond to the song of a rival—may say more about individual animals that were captured or housed in a certain way, or that share certain genetic features. That’s a problem for researchers who seek to understand how animals sense their environments, gain new knowledge and live their lives.

source: ars

Picking colors is a common operation in many applications and over the years color pickers have become fairly standardized. Ubiquitous today are color pickers based on HSL and HSV. They are simple transformations of RGB values to alternative coordinates chosen to better correlate with perceptual qualities.

Is their dominance well deserved or would it be possible to create better alternatives? I at least think that this question deserves to be explored and that color picker design should be an active research topic. With this post I hope to contribute to the exploration of what a better color picker could and should be, and hopefully inspire others to do the same!

source: HN

I’m a capitalist. A friend of mine is a devoted Marxist. I think we mutually agree that, considering any particular employee, it is in that employee’s personal interest to stop selling hours of labor and start renting access to his accumulated capital as soon as humanly possible.

A lot of day jobs structurally inhibit capital formation. If I were a Marxist I’d say “And this is an intended consequence of Capital’s desire to keep Labor subservient to it”, but I honestly think it’s true even without anybody needing to twirl their mustache.

source: HN

We argue that the most important statistical ideas of the past half century are: counterfactual causal inference, bootstrapping and simulation-based inference, overparameterized models and regularization, multilevel models, generic computation algorithms, adaptive decision analysis, robust inference, and exploratory data analysis. We discuss common features of these ideas, how they relate to modern computing and big data, and how they might be developed and extended in future decades. The goal of this article is to provoke thought and discussion regarding the larger themes of research in statistics and data science.

source: danluu

Research unveiled on Thursday in Science finds that crows know what they know and can ponder the content of their own minds, a manifestation of higher intelligence and analytical thought long believed the sole province of humans and a few other higher mammals

https://science.sciencemag.org/content/369/6511/1626

source: K

The person who types “lol” is never actually laughing; the person who types I’M SCREAMING is silently dabbing at a screen. In the same way, the person who is perpetually shocked and outraged and brimming with righteous fury is almost always lying to themselves. They’re as affectless as the rest of us: play-acting, downloading synthetic emotions, and then passing them on.

source: jwz

I went through some of the examples of metaphors in Metaphors To Live By and grepped all the man pages on my computer for them.

Cognitive scientists have identified a number of common ways in which people avoid being gullible. But con artists are especially skillful at what social scientists call framing, telling stories in ways that appeal to the biases, beliefs and prominent desires of their targets. They use strategies that take advantage of human weaknesses.

Good collection of cons.

Cross post: https://theconversation.com/why-do-people-believe-con-artists-130361

Hindsight bias suggests that one day you’ll look back on all of this and... lie

In a classic experiment in 1972, researchers asked people to estimate the likelihood that various positive and negative outcomes might result from President Richard Nixon’s upcoming trips to China and Russia that year. We now call those visits “historic” because they thawed decades of hostility between the U.S. and the communist powers. In advance, no one knew whether the trips would accomplish anything. About two weeks after Nixon’s visits, 71% of people recalled putting better odds on his success than they had at the time. Four months on, 81% remembered being more sure Nixon would succeed than they had said beforehand.

In short, learning what did happen impedes you from retrieving what you thought would happen.

Quite a few studies in this area, all with the same result.

There is a widespread public misperception, particularly among the New Age sector, that the Chinese word for “crisis” is composed of elements that signify “danger” and “opportunity.” I first encountered this curious specimen of alleged oriental wisdom about ten years ago at an altitude of 35,000 feet sitting next to an American executive. He was intently studying a bound volume that had adopted this notorious formulation as the basic premise of its method for making increased profits even when the market is falling. At that moment, I didn’t have the heart to disappoint my gullible neighbor who was blissfully imbibing what he assumed were the gems of Far Eastern sagacity enshrined within the pages of his workbook. Now, however, the damage from this kind of pseudo-profundity has reached such gross proportions that I feel obliged, as a responsible Sinologist, to take counteraction.

10 short optical illusion videos.

source: HN

It pains me to admit it, but this one even confuses me.

You’re asking me if something I didn’t see looks like something you’ve never seen.

It’s a simple yes or no question.

Also: red light cameras.

Tests done since 1933 show that people who talk about their intentions are less likely to make them happen.

Announcing your plans to others satisfies your self-identity just enough that you’re less motivated to do the hard work needed.

More explanation: https://www.bassam.com/single-post/CSI-TED-Talks-What-Derek-Sivers-Was-Really-Saying

Follow up: https://sivers.org/zipit2

source: HN

Penn told this story and it provided a perfect opportunity to demonstrate the difference between recollection/a story VS the real event as there was video of the event.

I liked this a lot. It’s a pretty good story, first of all. Penn’s version is believable and essentially accurate, but suffers from a few discrepancies.

Rules have a time and place, and “doing things wrong” is just a matter of your opinion, man.

Information theory gives us precise language for describing a lot of things. How uncertain am I? How much does knowing the answer to question A tell me about the answer to question B? How similar is one set of beliefs to another? I’ve had informal versions of these ideas since I was a young child, but information theory crystallizes them into precise, powerful ideas. These ideas have an enormous variety of applications, from the compression of data, to quantum physics, to machine learning, and vast fields in between.

Unfortunately, information theory can seem kind of intimidating. I don’t think there’s any reason it should be. In fact, many core ideas can be explained completely visually!

source: E

Two papers. Man-Computer Symbiosis and The Computer as a Communication Device.

The first argues for interactive systems. The computer can’t be an extension of our mind if it’s not responsive.

The second is a vision for networked communications. It sounds a lot like today, but more optimistic. Where did we go wrong?