Electronic Shoe Explores Alleged Chess Misbehavior

A few months ago, a scandal erupted in the chess world which led to some pretty wild speculation around a specific chess player. We won’t go into any of the details except to say that there is virtually no physical evidence of any method this player allegedly used to cheat in a specific in-person chess match. But [Teddy Warner] and partner [Jack Hollingsworth] were interested in at least providing a proof-of-concept for how this cheating could have been done, though, and came up with this device which signals a chess player through a shoe.

The compact device is small enough to fit in the sole of one of the player’s shoes, and is powered by an ATtiny412 microcontroller paired with a HC-06 Bluetooth module. The electronics are fitted into a 3D printed case along with a small battery which can then be placed into the sole of a shoe, allowing the wearer to feel the vibrations from a small offset-weight motor. With a second person behind a laptop and armed with a chess engine, the opponent’s moves can be fed into the computer and the appropriate response telegraphed through the shoe to the player.

While [Teddy] and [Jack] considers the prototype a success in demonstrating the ease at which a device like this could be used, and have made everything related to this build open source, this iteration did have a number of issues including that the motor buzzing was noticeable during play, and that his chess engine made some bizarre choices in the end game. It also requires the complicity of a second person, which is something this other chess cheating machine does away with. They also note that it’s unlikely that any chess players at the highest levels use devices like these, and that other chess experts have found no evidence of any wrongdoing in this specific scandal.

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Hackaday Links: January 29, 2023

We’ve been told for ages that “the robots are coming for our jobs!” It’s true that we’ve seen robots capable of everything from burger flipping to bricklaying being demonstrated, and that’s certainly alarming for anyone employed in such trades. But now it looks like AI has set its sights set on the white-collar world, with the announcement that ChatGPT has managed a passing grade on a Wharton MBA exam.

For those not in the know, the University of Pennsylvania’s Wharton School of Business is in the major league of business schools; earning a Master’s in Business Administration from that august institution is no mean feat, and is likely to put the budding executive on a ballistic career trajectory. So the fact that ChatGPT could pass the exam is significant. But before you worry about a world in which our best and brightest business leaders are replaced with soulless automatons, relax. The exam presented to ChatGPT was just a final exam for one course, Operations Management, so it’s not like it aced everything an MBA is expected to know, and it took a lot of hints from a human helper to get it that far. It’s also reported that it made a lot of simple math mistakes, too, so maybe a Wharton MBA isn’t that much of a big deal after all.

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Seeing If Cheating At Chess The Hard Way Is Even Possible

With all the salacious stories about a cheating scandal rocking the world of championship-level chess, you’d think that we’d have delved into the story at least a bit here on Hackaday, especially given the story’s technical angle. But we haven’t, and it’s not because we’re squeamish about the details of the alleged cheat; rather, it’s because it’s just too easy to pun your way through a story like this. The lowest-hanging fruit isn’t always the sweetest.

But, we’ll give it a go, and play this one completely straight as we look at an experiment to determine if it’s even possible to cheat in the specific way that has been alleged. For the uninitiated, 19-year-old grandmaster [Hans Niemann] stands accused of cheating, possible through the use of a remote-controlled sex toy secreted in his rectum. The idea would be for an accomplice to use the toy, which contains a vibrating motor that’s controlled by an app either via Bluetooth or WiFi, to send suggested moves to [Niemann] based on a chess-playing AI’s analysis of the game.

Whether [Niemann] cheated or not is not the concern here, but rather [Captain Steel]’s experiment is just a first-pass look at whether it would be possible to cheat using the proposed technology — and most importantly, not get caught. He tried to replicate the scanning regime [Niemann] is now subject to at tournaments based on the allegations to see if a stand-in for the sex toy — a haptic motor attached to an ESP32 — would be detectable through various thicknesses of flesh. Rather than showing the same dedication to craft that [Niemann] is alleged to have shown, [Captain Steel] used slices of baloney as a stand-in for human flesh. He then tried scanning for RF emissions from the device through increasing layers of luncheon meat. We won’t spoil the results, other than to say that baloney turns out to actually be good for something.

We’ve covered another less-invasive method of cheating before, which given the results above is probably more likely to be discovered.

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21st Century Cheating: WiFi In A Calculator

Obviously, we would never endorse cheating on an exam, but sometimes a device is just too tempting to be left untouched. For [Neutrino], it was an old Casio calculator that happened to have a perfectly sized solar panel to fit a 128×32 OLED as replacement. But since the display won’t do much on its own, he decided to connect it to an ESP8266 and mount it all inside the calculator’s housing, turning it into a spy-worthy, internet-connected cheating device, including a stealthy user interface controlled by magnets instead of physical buttons. (Video, embedded below.)

Editor’s Update: Please read our follow-up coverage to the copyright claims made against this project. The video linked above and embedded below are unavailable due to these claims, despite widespread belief that this project does not violate copyright. For now, the original video is available via the Internet Archive.

To achieve the latter, [Neutrino] added two Hall effect sensors and a reed switch inside each end of the calculator. Placing a magnet — possibly hidden in a pen cap — near the reed switch will turn the display on, and placing another magnet near the Hall-effect sensors will navigate through the display’s interface, supporting two inputs with long, short, and multi-tap gestures each. To obtain information through WiFi, the ESP8266 connects to Firebase as backend, allowing to set up predefined content to fetch, as well as a possibility to communicate with your partner(s) in crime through a simple chat program.

As the main idea was to keep visible modifications to a minimum, one shortcoming is that charging the additional battery that powers the whole system would require an additional, external charging circuit. But [Neutrino] had a solution for that as well, and simply exposed two wires to the back, which could easily be mistaken for random solder splatters. And well, of course, requiring WiFi might also be tricky in some situations, so maybe you might want to consider a mobile network upgrade for yourself.

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Image from official site catan.com

How Provably Loaded Dice Lead To Unprovable Cheating

Here’s a really interesting writeup by [Mike] that has two parts. He shows that not only is it possible to load wooden dice by placing them in a dish of water, but that when using these dice to get an unfair advantage in Settlers of Catan, observation of dice rolls within the game is insufficient to prove that the cheating is taking place.

[Mike] first proves that his pair of loaded dice do indeed result in a higher chance of totals above seven being rolled. He then shows how this knowledge can be exploited by a Settlers of Catan player to gain an average 5-15 additional resource cards in a typical game by taking actions that target the skewed distribution of the loaded dice.

The second part highlights shortcomings and common misunderstandings in current statistical analysis. While it’s possible to prove that the loaded dice do have a skewed distribution by rolling them an arbitrary number of times, as [Mike] and his wife do, it is not possible to detect this cheating in a game. How’s that? There are simply not enough die rolls in a game of Settlers to provide enough significant data to prove that dice distribution is skewed.

Our staff of statistics Ph.D.s would claim that [Mike] overstates his claims about shorcomings in the classical hypothesis testing framework, but the point remains that it’s possible to pass through any given statistical testing process by making the effect just small enough. And we still think it’s neat that he can cheat at Settlers by soaking wooden dice in water overnight.

This isn’t the first time we’ve seen Settlers of Catan at the center of some creative work. There’s this deluxe, hand-crafted reboot, and don’t forget the electroshock-enabled version.

[via Reddit; images from official Catan site]

Fail Of The Week: Pinewood Derby Cheat Fails Two Ways

Would you use your tech prowess to cheat at the Pinewood Derby? When your kid brings home that minimalist kit and expects you to help engineer a car that can beat all the others in the gravity-powered race, the temptation is there. But luckily, there are some events that don’t include the kiddies and the need for parents to assume the proper moral posture. When the whole point of the Pinewood Derby is to cheat, then you pull out all the stops, and you might try building an electrodynamic suspension hoverboard car.

Fortunately for [ch00ftech], the team-building Derby sponsored by his employer is a little looser with the rules than the usual event. Loose enough perhaps to try a magnetically levitating car. The aluminum track provided a perfect surface to leverage Lenz’s Law. [ch00ftech] tried different arrangements of coils and drivers in an attempt to at least reduce the friction between car and track, if not outright levitate it. Sadly, time ran out and physics had others ideas, so [ch00ftech], intent on cheating by any means, tried spoofing the track timing system with a ridiculous front bumper of IR LEDs. But even that didn’t work in the end, and poor [ch00f]’s car wound up in sixth place.

So what could [ch00ftech] had done better? Was he on the right course with levitation? Or was spoofing the sensors likely to have worked with better optics? Or should he have resorted to jet propulsion or a propeller drive? How would you cheat at the Pinewood Derby?


2013-09-05-Hackaday-Fail-tips-tileFail of the Week is a Hackaday column which celebrates failure as a learning tool. Help keep the fun rolling by writing about your own failures and sending us a link to the story — or sending in links to fail write ups you find in your Internet travels.

Abusing A Cellphone Screen With Solenoids Posts High Score

This Raspberry Pi 2 with computer vision and two solenoid “fingers” was getting absurdly high scores on a mobile game as of late 2015, but only recently has [Kristian] finished fleshing the project out with detailed documentation.

Developed for a course in image analysis and computer vision, this project wasn’t really about cheating at a mobile game. It wasn’t even about a robotic interface to a smartphone screen; it was a platform for developing and demonstrating the image analysis theory he was learning, and the computer vision portion is no hack job. OpenCV was used as a foundation for accessing the camera, but none of the built-in filters are used. All of the image analysis is implemented from scratch.

The game is a simple. Humans and zombies move downward in two columns. Zombies (green) should get a screen tap but not humans. The Raspberry Pi camera takes pictures of the smartphone’s screen, to which a HSV filter is applied to filter out everything except green objects (zombies). That alone would be enough to get you some basic results, but not nearly good enough to be truly reliable and repeatable. Therefore, after picking out the green objects comes a whole chain of additional filtering. The details of that are covered on [Kristian]’s blog post, but the final report for the project (PDF) is where the real detail is.

If you’re interested mainly in seeing a machine pound out flawless victories, the video below shows everything running smoothly. The pounding sounds make it seem like the screen is taking a lot of abuse, but [Kristian] mentions that’s actually noise from the solenoids and not a product of them battling the touchscreen. This setup can be easily adapted to test out apps on different models of phones — something that has historically cost quite a bit of dough.

If you’re interested in the nitty-gritty details of the reasons and methods used for the computer vision portions, be sure to go through [Kristian]’s github repository where everything about the project lives (including the aforementioned final report.)

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