That time I interviewed a fraud

Here’s a story about a job candidate I interviewed who seemed to be engaging in some sort of AI-assisted fraud.

Before the interview even occurred, there was already suspicion around the candidate. A couple other interviewers observed a lag between the voice and video, and they thought this might be a sign of an AI generated video. And the resume felt way too perfect, claiming extensive experience in basically everything that we do.

I don’t know about the video lag. To the extent there are AI tools out there, I don’t presume to know how exactly they work, nor do I presume that I am capable of distinguishing AI video from a bad internet latency. So I took an approach that was different from other interviewers: I looked at his LinkedIn page.

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Link Roundup: February 2026

This month, the ace journal club discussed an article about gender detachment.  And I wrote an article on the game design of my game.

Epstein Files Reveal How Pathetic Richard Dawkins & Other Men Are | Rebecca Watson (video + transcript, 27 min) – I get readers from outside FTB who have little background with the skeptical and atheist movements, and who don’t get what that means for us.  Here it is.  This is where we came from.  This is what we rejected.  These pathetic thought leaders who were enraged by a woman speaking, and turned around to seek bad advice from then-convicted pedophile Jeffrey Epstein.  First we wanted better, and then eventually we just wanted out.

The Fascists are Lying about ICE Murdering an Innocent Women | Rebecca Watson (video + transcript, 27 min) – Another cathartic video from Rebecca, also featuring a cameo from Michael Shermer.  Fun fact: Michael Shermer got me into the skeptical movement, and fun fact two: he’s a terrible person.

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What’s next in game dev?

So I’m finally done with my video game. What’s next? Should I make another?

I will definitely make a second game. One of my brothers has long been interested in making video games, but never found the motivation to start. So I offered to collaborate with him and show him how to use the game engine. Then I showed him my list of game ideas, and we’re making the very smallest idea on the list.

After that, who knows?
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Origami: Practical Bookmark

Practical Bookmark

Practical Bookmark, designed by me

Here’s a really old design of mine, back in 2013.  I wanted a simple origami bookmark–no frills, just mark my page please.  Some origami bookmarks stick out of the book, and that’s obviously not practical if I’m throwing the book in my bag or something.

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My game released

My game, Moon Garden Optimizer has finally released on Steam!

moon garden optimizer capsule

If you follow my blog, you may be aware that I have already made the game available for free on Itch, and as a Steam demo. The full version has a small price tag, but includes twice as many plants, and additional polish.

Moon Garden Optimizer is a strategy game where you manage a tiny garden to produce oxygen for moon habitats. It has no RNG and supports unlimited undo, much like a puzzle game. It’s mostly low pressure, but quite difficult to optimize. It doesn’t fit into any existing genre.

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My games of the year 2025

I play 50+ video games every year, so why not make a list of the best ones? People like listicles, right?

Personally, I don’t have much interest in Game-of-the-Years.  Usually, the games at the top of these lists are games I already heard about, because people had been talking about them!  So for my list, I’m doing things differently.

  • I’m only including games I played in 2025. That disqualifies Expedition 33, Silksong, and Hades 2! Older games are eligible if I happened to play them in 2025.
  • I am presenting the list in reverse order, with the top games first.  The top games are already widely recognized.  But a bit further down the list is where it gets more interesting, as I talk about obscure games that appealed to me personally.  I’d like to talk about these games without trying to claim that they’re actually the best games ever.

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Estimating true ratings

If you take a rating website, say IMDB, or Goodreads, and you sorted items purely by review scores, the stuff that would float to the top would be pretty obscure. That’s because the easiest way to maintain a perfect score is to have a very small sample size.

So, a math question: what is the statistically “correct” way to handle this?

In this analysis, I will assume there exists a “true” average review score, and we are trying to estimate it. The “true” average is the average that would be attained if there were a sufficiently large sample of reviewers. We’re not imagining that everyone in the world is reviewing the same book (for example, we don’t expect book reviews to reflect the opinions of people who don’t like reading books period). But we could imagine, what if there were a billion identical yet statistically independent Earths, and we averaged all their review scores.  Obviously it’s very hard to come across a billion identical yet statistically independent Earths, and that’s why we use math instead.

This premise may be fairly questioned. I once discussed the philosophical problems with review scores, including questioning the very idea of taking averages. But here, I’m just focusing on the math for math’s sake.  And, I really mean it, it’s hardcore math.  If you don’t want math, just skip to the last section I guess.

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