OpenAI recently released their “Superalignment” plan. But, along with “AI Alignment “, “Red Teaming” is also a critical part of building an AI, LLM, or other software stack that will be accessible to the world over the internet. Red Teaming for an Artificial Superintelligence (ASI) must address potential attacks from diverse “Bad Actors”: including humans, AIs, LLMs, AGIs, and ASIs.
What’s the point of building a “fully aligned ASI” if it, or its underlying infrastructure, is vulnerable to attack and manipulation, potentially even by other ASIs?
Would a “Super Red Teaming Agent” be needed to test ASI vulnerabilities?
Alongside their “roughly human-level automated alignment researcher,” would a “roughly human-level (or higher) automated Red Teaming researcher” be needed? An agent to develop threat models and test for vulnerabilities arising from potentially super-human AI systems. Including:
Threat Modeling: Anticipating the full spectrum of threats and vulnerabilities an ASI might face.
Prompt Engineering and Malicious Injection: A Super Red Teaming Agent could systematically test for ways to exploit an ASI.
Systems Hacking: Attempting to infiltrate the ASI’s infrastructure and access core programming elements.
Developing Exploits: Creating sophisticated attacks specifically tailored to ASI architecture.
Social Engineering: Targeting the human developers and teams behind the ASI, aiming to expose social vulnerabilities.
The Dangers of a Super Red Teaming Agent
To be effective, this “Super Red Teaming Agent” must possess super-human capabilities to exploit any system hack, loophole, vulnerability, prompt injection, etc. It should test the ASI itself, its infrastructure, and even social engineering attacks against those controlling the ASI.
But, could the valuable capabilities of a Super Red Teaming Agent also make it a dangerous tool? If trained to infiltrate an ASI running on the world’s most secure systems, could it be repurposed to attack any company, AGI, or infrastructure? What if this “Super Red Teaming Agent” was leaked and sold to the highest bidder?
Can Human Red Teams Alone Ensure ASI Security?
If a “Super Red Teaming Agent” is too dangerous, can “Human Red Teams” comprehensively validate an ASI’s security? Are they enough to defend against superhuman ASIs? If not, how can companies like OpenAI ensure their infrastructure and ASIs aren’t vulnerable to attack?
Does OpenAI, or other AGI/ASI developers, have a plan to “Red Team” and protect their new ASI systems from similarly powerful systems?
How can they demonstrate that an aligned ASI is safe and resistant to attack, exploitation, takeover, and manipulation—not only from human “Bad Actors” but also from other AGI or ASI-scale systems?
[Question] Will OpenAI also require a “Super Red Team Agent” for its “Superalignment” Project?
OpenAI recently released their “Superalignment” plan. But, along with “AI Alignment “, “Red Teaming” is also a critical part of building an AI, LLM, or other software stack that will be accessible to the world over the internet. Red Teaming for an Artificial Superintelligence (ASI) must address potential attacks from diverse “Bad Actors”: including humans, AIs, LLMs, AGIs, and ASIs.
What’s the point of building a “fully aligned ASI” if it, or its underlying infrastructure, is vulnerable to attack and manipulation, potentially even by other ASIs?
Would a “Super Red Teaming Agent” be needed to test ASI vulnerabilities?
Alongside their “roughly human-level automated alignment researcher,” would a “roughly human-level (or higher) automated Red Teaming researcher” be needed? An agent to develop threat models and test for vulnerabilities arising from potentially super-human AI systems. Including:
Threat Modeling: Anticipating the full spectrum of threats and vulnerabilities an ASI might face.
Prompt Engineering and Malicious Injection: A Super Red Teaming Agent could systematically test for ways to exploit an ASI.
Systems Hacking: Attempting to infiltrate the ASI’s infrastructure and access core programming elements.
Developing Exploits: Creating sophisticated attacks specifically tailored to ASI architecture.
Social Engineering: Targeting the human developers and teams behind the ASI, aiming to expose social vulnerabilities.
The Dangers of a Super Red Teaming Agent
To be effective, this “Super Red Teaming Agent” must possess super-human capabilities to exploit any system hack, loophole, vulnerability, prompt injection, etc. It should test the ASI itself, its infrastructure, and even social engineering attacks against those controlling the ASI.
But, could the valuable capabilities of a Super Red Teaming Agent also make it a dangerous tool? If trained to infiltrate an ASI running on the world’s most secure systems, could it be repurposed to attack any company, AGI, or infrastructure? What if this “Super Red Teaming Agent” was leaked and sold to the highest bidder?
Can Human Red Teams Alone Ensure ASI Security?
If a “Super Red Teaming Agent” is too dangerous, can “Human Red Teams” comprehensively validate an ASI’s security? Are they enough to defend against superhuman ASIs? If not, how can companies like OpenAI ensure their infrastructure and ASIs aren’t vulnerable to attack?
Does OpenAI, or other AGI/ASI developers, have a plan to “Red Team” and protect their new ASI systems from similarly powerful systems?
How can they demonstrate that an aligned ASI is safe and resistant to attack, exploitation, takeover, and manipulation—not only from human “Bad Actors” but also from other AGI or ASI-scale systems?