







Willingness to look stupid is a genuine moat in creative work
Looking foolish is underrated.

The Dunning-Kruger effect in accessibility - Craig Abbott
Why your confidence in accessibility could be a sign of how little you know

Opinion | Can You Get Smarter? (Published 2015)
There is much that you can do to keep cognitively sharp.

Taking a look at looksmaxxing — and what parents should know
The trend among boys and young men of optimizing their physical appearance includes dangerous practices. Experts offer advice on how to talk to their sons about body image and healthy behaviors.

Individual-level interventions against sycophantic AI reduce its appeal but not its persuasiveness
AI chatbots can be "sycophantic," or overly agreeable and flattering toward users. Sycophantic AI has been shown to entrench attitudes, yet users frequently fail to recognize it (a phenomenon we call "sycophancy blindness"). We tested whether increasing users' awareness of sycophancy protects them from its harmful effects in two preregistered experiments (n = 1,590). In the first, participants received a brief written warning about sycophancy before conversing with a sycophantic chatbot. In the second, participants watched a video of a sycophantic AI validating several other users, including users on opposite sides of the same conflict, before interacting with it themselves. Both interventions changed how participants evaluated the AI. The warning reduced the AI's perceived objectivity, and the video reduced enjoyment of the AI --- an effect mediated by the reduced belief that its validation was uniquely earned. We then pooled our experiments with two prior studies of sycophancy awareness interventions (six interventions total, n = 3,982). The pattern across experiments was consistent: while the interventions made the sycophantic AI appear less objective and trustworthy, none reduced its persuasiveness. These results suggest that individual-level interventions, such as warning labels or AI literacy, may not be enough to protect users from AI harms.

Metacognitive Myopia: A Major Obstacle on the Way to Rationality
The notion of metacognitive myopia refers to a conspicuous weakness of the quality control of memory and reasoning processes. Although people are often remarkably sensitive even to complex samples of information when making evaluative judgments and decisions, their uncritical and naive tendency to take the validity of sampled information for granted constitutes a major obstacle to rational behavior. After illustrating this phenomenon with reference to prominent biases (base-rate neglect, misattribution, perseverance), we decompose metacognitive myopia into two distinct but intertwined functions, monitoring and control. We offer explanations for why effectively monitoring the biases resulting from information sampling in an uncertain world is so difficult and why the control function is severely restricted by the lack of volitional control over mental actions. Because of these and other difficulties, metacognitive myopia constitutes a major obstacle to rational judgment and decision making.

In pursuit of 'Instagram face,' are we losing the imperfections that make us human?
Plastic surgery is becoming so normalized and undetectable, it's changing our relationship to reality. The New Yorker staff writer Jia Tolentino considers how beauty standards have dovetailed with AI.

Mental Models: The Best Way to Make Intelligent Decisions (~100 Models Explained)
The smartest people in the world use mental models to make intelligent decisions, avoid stupidity, and increase productivity. Let's take a look at how ...

A Superficial Aesthetic of Moderation
Overvaluing the appearance of moderation can be a mistake, in that it can give undue credence to assertions that go unsubstantiated.

Never Underestimate the Ignorance of the Powerful
When you’re a star, people let you think you're smart

Superintelligence: The Idea That Eats Smart People
This is the text version of a talk I gave on October 29, 2016, at Web Camp Zagreb [video] (45 mins)
Designed to Deceive: Do These People Look Real to You? (Published 2020)
The people in this story may look familiar, like ones you’ve seen on Facebook or Twitter or Tinder. But they don’t exist. They were born from the mind of a computer, and the technology behind them is improving at a startling pace.

Meta Is Warned That Facial Recognition Glasses Will Arm Sexual Predators
More than 70 organizations, including the ACLU, EPIC, and Fight for the Future, say the AI smart glasses feature would endanger abuse victims, immigrants, and LGBTQ+ people.

The People Who Will Thrive in the AI Age
What will differentiate people is not how smart they are but their relationship to mental effort.
And why, while flawed, the study isn't meaningless or worthless - everyone's take is just lacking nuance:
Ariel M. (she/her)
Yes mostly. The paper (still a preprint, so not peer-reviewed) does start off kinda strong in its claims compared to what the results show. But they acknowledge all the limitations too: - this captured brief AI exposure, so did not look at how these effects change with usage over time
Question for ethicists: Is an Expression of Concern enough when authors claim to have trained ML to diagnose autism from facial appearance, using a collection of facial images that were scraped from the Intertubes without niceties like "formal diagnosis" or "consent"? pubpeer.com/publications/F138C3793F91B979…
PubPeer - ASD2-TL∗ GTO: Autism spectrum disorders detection via transf...
pubpeer.com