Two new color spaces for color picking
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!
Don't End The Week With Nothing
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.
What are the most important statistical ideas of the past 50 years?
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.
Brainiacs, not birdbrains: Crows possess higher intelligence long thought a primarily human attribute
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
The Art of the Bad Faith Argument
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.
Metaphors in man pages
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
The Panic of 2020? Oh, I Made a Ton of Money—and So Did You
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.
danger + opportunity ≠ crisis
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.
2019 Illusion of the Year Finalists
10 short optical illusion videos.
How to Explain What Words Mean
It pains me to admit it, but this one even confuses me.
How to Reassure Someone
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.
Announcing your plans makes you less motivated to accomplish them
Penn Jillette Talks About His 2nd Appearance On "Late Night w/ David Letterman" & The Actual Segment
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.
Doing Things The Wrong Way
Rules have a time and place, and “doing things wrong” is just a matter of your opinion, man.
Visual Information Theory
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!
In Memoriam: J. C. R. Licklider
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?
The Only Way to Win Is Not to Play the Game
When I became a math and science writer, I had no idea that one of the most common requests I would get would be to weigh in on order of operations problems that somehow go viral in some segment of the internet.
The real answer, the one I believe any mathematician, physicist, engineer, other number-cruncher would tell you is to make sure your expressions aren’t ambiguous.
Another take: https://danso.ca/blog/order-of-operations/
So one way of extending political time horizons and increasing is to age-weight votes. The idea is that younger people would get more heavily weighted votes than older people, very roughly in proportion with life expectancy.
I suspect this has very little chance of becoming reality.
The Resulting Fallacy Is Ruining Your Decisions
In it, Duke parlays her experience with cards into general lessons about decision making that are relevant for all of us. If a well-reasoned decision leads to a negative outcome, was it the wrong decision? How do we distinguish between luck and skill? And how do we move beyond our cognitive biases?