That’s an (obviously) unpopular opinion around here but I’ll give you the benefit of the doubt: How would AI be able to do that?
CSGO used to have Overwatch which is an anti cheat system that uses trusted and experienced players to go through video footage of reported players. With this method I both reported blatant spinbotters, wall hacking, and other chears. I also was on the side of watching back footage of hacking players.
Say AI trains on this data, it might work.
I’m not a fan of this though because knowledgeable and experienced players will be better than AI.
The same way it’s automodderating Reddit to a point that nobody can post anything anymore LOL
What actually exists but what I have yet to see implemented in any game I play are those server-side “AI anti-cheat” solutions like from anybrain that basically just analyse the players behavior to fit certain criteria. According to areweanticheatyet.com though there are four games using it already (the most well-known one probably being Lost Ark). In theory ai models can be very efficient and accurate at this (we are not talking about transformer models here like with the current llm craze) but that all depends on how they train a model and what the training data looks like.
Don’t waste your time, they’re either an hardcore AI bootlicker or a shit stirrer - most likely both, looking at their post history.
Stovetop@lemmy.world 1 day ago
I am not sure what the user above is thinking, but to play devil’s advocate:
One thing that modern AI does well is pattern recognition. An AI trained on player behavior, from beginner level all the way up to professional play, would be able to acquire a thorough understanding of what human performance looks like (which is something that games have been developing for a long time now, to try to have bots more accurately simulate player behavior).
I remember someone setting up their own litmus test using cheats in Tarkov where their main goal was just to observe the patterns of other players who are cheating. There are a lot of tells, a big one being reacting to other players who are obscured by walls. Another one could be the way in which aimbots immediately snap and lock on to headshots.
It could be possible to implement a system designed to flag players whose behavior is seen as too unlike normal humans, maybe cross-referencing with other metadata (account age/region/sudden performance anomalies/etc) to make a more educated determination about whether or not someone is likely cheating, without having to go into kernel-level spying or other privacy-invasive methods.
But then…this method runs the risk of eventually being outmatched by the model facilitating it: an AI trained on professional human behavior that can accurately simulate human input and behave like a high performing player, without requiring the same tools a human needs to cheat.
zqps@sh.itjust.works 1 day ago
Cheating humans already perform closely enough to trick such a system. Many cheaters are smart enough to use an aimbot only for a split-second to nail the flick. With a tiny bit of random offset, those inputs indistinguishable from a high-skill player.
ChairmanMeow@programming.dev 1 day ago
These tricks may make it indistinguishable to a human moderator, but machine learning is actually really good at detecting that. But most companies don’t have the expertise, resources or training data to build a proper model for it.
NuXCOM_90Percent@lemmy.zip 1 day ago
Machine Learning is really good at CLAIMING it detected that.
The reality is that every few months there is a story about a fairly big streamer/e-sports player MAYBE getting caught cheating on stream. Sometimes it is obvious and sometimes it really becomes “Did they just know the map well enough to expect someone to come around that corner?”.
And a lot of times… it really is inconclusive. A somewhat common trope in movies is the veteran gunslinger literally aims at the wall of a stairwell and tracks where they expect the head to be and either fires a few rounds through the wall or waits for them at the bottom and… that is not entirely inconceivable considering that people tend to not crouch or move erratically down stairs. Obviously Jonathan Banks has a wallhack but Mike Ehrmantraut is just that damned good.
And false positives are a great way to basically kill a game. ESPECIALLY if they are associated with demonstrably false negatives too.
But you can be damned sure most of the major esports games are already doing this. It really isn’t expensive to train and they have direct feeds of every player in a tournament or twitch event. The issue is that there are (hopefully) tens of thousands of servers active at any moment and running Computer Vision+Inference on every single server is very costly.
And… I seem to recall there was a recent intentionally poorly defined Movement about maybe keeping user hostable dedicated servers a thing? How does that mesh with having every single server need to phone hom (a fraction of) all 32 players feeds to a centralized cluster?