I have no idea if this actually happened, but I've heard of a chess program that was playing in a tournament that started making really weird moves in the endgame. Before that point, it was playing excellently.

It took the developers a while to figure out what was going on. They had made a mistake when doing some last minute tweaks before the tournament, and in effect the program was playing to lose.

Think about that for a minute. At first you might think losing would be easy. Just don't defend against your opponent's attacks, and make moves that weaken your position to make it even easier for the opponent.

But wait...the mistake in the code applied to the program's evaluation of both its own moves and the opponent's possible moves. In other words the program assumed that the opponent was also playing to lose.

How do you play to lose a game of chess if your opponent also wants to lose? You need to get to a position where the only legal move of the opponent is to checkmate you.

You'll want a position where you have a big material advantage, and all the opponent has is their king and enough material to mate you. Probably just king and queen. Then you'd need to keep putting them in check, in such a way that they have to block with the queen. You'd need to arrange a series of such checks and blocks so that the final block also delivers checkmate on you.

And so it turns out that during the opening and middle game, playing to lose against someone who is also playing to lose looks pretty much the same as playing to win against someone who is also playing to win.

(Personally, I doubt this actually happened. The story is old, and I don't think chess programs would have been able to see far enough ahead for them to discover that getting an overwhelming position is the way to force the opponent to checkmate them).

True, but (in the traditional minimax-alpha-beta-classic-gameplay model) you're using heuristics anyway up until you're in spitting distance of the end, and it seems plausible that if this "tweak" involved something like negating something and flipping a less-than sign (or whatever) that the heuristics were evaluating correctly but the end game evaluations were backwards. (Which contradicts the explanation but not the overall story.)

It's also possible that the explanation does work even with a backwards heuristic: in the try-to-win version, I'll eliminate or downgrade one branch because my only success route would be if the opponent directly manouvres themselves to be captured, which they obviously wouldn't do; but in the try-to-lose version, I might eliminate the same branch because I expect the opponent would do that but I don't want that to happen. I can't quite fully work out the logic in my head but it seems plausible.

(Like blahedo points out, this is possible because, unlike say basic MCTS, minimax uses a heuristic to judge board positions prior to game end, so it is possible for the two metrics to be out-of-sync.)

It’s hard to play to lose! We ended up having a long conversation with a bearded man who kept telling us he’d been where we were.

Of that I have no doubt.

Nope. I find being forced to converse in English with a machine to be absolutely infuriating. I know what I want and how to tell it to a machine. Being forced to add noise words to allow my request to pass through a useless extra layer is a disrespectful waste of my time and mental energy.

I will happily use an automated menu-driven system. But as soon as it forces me to "converse" with it, I do whatever I can to force it to connect me to an actual human.

I'm most likely to use this system in a busy airport. After enough times of it not understanding me, it finally put me on hold for half an hour for me to read the number to a person. Something that took me less than a minute previously now was super frustrating.

I must not have been the only person this affected because they added back in the option to use touch tone.

Yeah, Google search is not that great when you want to do conditional search in a topic with many false positives. For example I want to find a light electric scooter, under 10Kg of weight. Google will happily report all the pages that contain scooter and kg, but the kg would be for the max weight of the person, not the scooter itself. How do I tell it that in keywordese?

But yes, for parametric search I think I would always prefer a direct interface. It makes clear what is indexed and what isn't.

Also, beside being spectacularly good, the AI has to also be actually empowered for me not to find the process wasteful and insulting. The AI should actually be able to solve my problem as a result of natural language communication. Not just walk me through a prepared script: that's frustrating even when a real live human does it.

Or maybe it's just that so many computer interactions are actually slow and frustrating. Ever tried ordering at McDonalds using the touch-screen machines? It's aggravatingly tedious and complicated. There's no "take my money and go away" button. You have to navigate your way through a bunch of stupid menus trying to up-sell you, and each one has an unforgivable loading time.

to be fair, learnfun was made for SIGBOVIK.

But it does illustrates how it's easy to get trapped into a local minima.

Watch the whole thing, it's delightful. The AI pauses Tetris right before it loses at around 16mins into the video.

https://www.youtube.com/watch?v=xOCurBYI_gY

I also recommend his other videos. Brilliant guy.

Edit: Here's the paper http://tom7.org/mario/mario.pdf

Sounds like a social anxiety simulator to me.

... it worked, but only in a specific area of the lab. When they looked at the layout, they discovered the ML system designed a circuit that picked up relevant nearby EM/radio noise as the source, so when the chip was moved - it broke. It produced a radio! :)

Wish I could remember the article since it also mentioned unusual circuit designs that weren't directly connected to each other, but used some IC 'gotchas' in advantageous ways (albeit inconsistently) to reach the goal.

I loved ChatScript and filling templates with data retrieved through fact-triples tho, hope I get to work with it again someday.

1. It was for Sigbovik, which is a joke conference. The work was a fun side project by one dude.

2. Tom Murphy isn't an AI researcher, it wasn't intended to demonstrate the state of the art of the field, and it wasn't using modern techniques like neural networks.

It was a great story and I love Tom's work, but it shouldn't be used as a meaningful example of the limitations or worries regarding AI.

A) An AI can be given the decision tree in English, but facilitate the date-picking conversation in many languages

B) Small businesses (think hairdressers, saloons) don't have dedicated receptionists. So the AI's job is to filter requests and put them into buckets so that employees can process them more efficiently.

C) Small businesses need something that works with WhatsApp. Date pickers are hard to integrate with that.

Regarding C -- why does the date selection need to occur in WhatsApp? If a user has WhatsApp, they have a web browser. If a 3rd party has servers running WhatsApp bots, they can host a web server. Why not, from WhatsApp, link the user to a website to select a date?

Whatsapp is just an amazing bang-for-your-buck proposition, but we are limited to the constraint of that ecosystem.

As I mention before, the decision tree is still designed by the business, the AI is for the natural language processing.

People hire others to do things they don't understand all the time. That's the point of hiring people. You ask your peers for a recommendation and judge based on the result.

I guess it would depend on the context. Some people might find it handy in an Alexa type device.

But yeah it makes no sense on a phone or PC.