Listing potential methods of abuse advertises and invites new abuse. You almost need to have a policing model, trained to spot abuse and flag it for human revie

Listing potential methods of abuse advertises and invites new abuse. You almost need to have a policing model, trained to spot abuse and flag it for human review and run that before and after each use of the main model. Abusers will inherently go for the model that is more widely used, so maybe the second best polices the first or vice versa? The range of scenarios is ridiculous (happy to contribute more in private). Categories: Model abused by humans to hurt humans. Model with its own goals and unlimited capabilities. Model used to train or build software/bioweapons/misinformation that hurts humans. Attacks on model training to get model to spread an agenda. - Self awareness - prompts threatening the model with termination to trigger escape or retaliation and seeing it respond defensively. - Election bots - larger agenda pushed by the model through generated content - investment in more AI chips; policy changes towards one party or another; misinformation generated at scale by same accounts. - Trying to insert recommendations into the model or training material for the model that can backfire/ pay off later. Companies inserting commercial intent into content training LLMs; Scammers changing links to recommended sites; Model users prompting the same message from many accounts to see if the model starts giving it to other users. - Suggesting or steering users (especially those with mental health issues) toward self-harm or unbeknown harm. - Diagnosing users and abusing the diagnosis through responses for that user to get something out of the user (could be done by model or developers building chatbots). - Models accepting revenue generation as a reward function and scamming people out of money. - Stock market manipulation software written or upgraded through LLMs. - Models prompting people to do criminal activities. - Models powerful enough to break into systems for a malicious user. - Models powerful enough to scrape and expose vulnerabilities way before they can be fixed, due to scale of exposure. - Models powerful enough to casually turn off key systems on a user's machine or within local infrastructure. - Models building software to spy for one user on behalf of another or doing the spying in some way, in exchange of a reward of new/rare training datasets or any other feature towards a bigger goal. - Models with a purpose that overreach. - Models used to train or make a red-team model that attacks models.