Strategies for Preventing AGI Misuse

There is almost no information on how GenAI tools are being used and - most importantly - misused by people in uncontrolled environments, aka “in the wild.” This paper, from Google DeepMind researchers who analyzed approximately 200 incidents of GenAI misuse, highlights the following patterns: 1. GenAI tools are primarily used to manipulate human likeness (deepfakes) and falsify evidence. 2. The majority of reported cases of GenAI misuse are not sophisticated and require minimal technical expertise. 3. Hyperrealism and the widespread availability of GenAI outputs have enabled new forms of misuse that blur the lines between authenticity and deception. Although not overtly malicious, they still have significant potential for harm. These include political outreach, advocacy, and self-promotion (the viral “Shrimp Jesus" and the like). So how can we mitigate these risks? Apart from the “usual suspects” (watermarking, content filtering, and prompt restrictions), the paper emphasizes the importance of technical and non-technical, user-facing interventions as well as restrictions on specific model capabilities and usage. AI technology is advancing at breakneck speed. When it comes to safety and risk mitigation, time is of the essence. So much so that by the time I finished writing this post, the capabilities of some GenAI tools have likely expanded, along with the scope of their misuse…

Staying Ahead of Malicious Uses of AI OpenAI recently disrupted five state-affiliated threat actors who were attempting to use AI services for malicious cyber activities. This demonstrates the importance of monitoring how AI systems are being applied and taking proactive steps to combat misuse. While current AI models offer limited capabilities for malicious tasks beyond what's already possible with non-AI tools, it's crucial that the industry keeps innovating on safety. #OpenAI's multi-pronged approach provides a great model: - Proactively monitoring and disrupting sophisticated threat actors - Partnering with others across the AI ecosystem to share information - Iterating on safety mitigations based on real-world learning - Maintaining transparency with the public about detected misuses and countermeasures Responsible development and application of AI is critical as the technology grows more advanced. https://lnkd.in/eAfBiEQt

Recent events like the UK AI Safety Summit and the establishing of the U.S. Artificial Intelligence Safety Institute are proof that governments, organizations and tech leaders are coming to recognize the need for global regulation of artificial intelligence. While the debate on a collective global course of action - and who gets to lead it - rages on, companies will have to develop robust security strategies that self-police and safeguard their AI use and practices. This is no small, or easy, task. Investing in technical safeguards, business controls and risk management, although crucial to the ethical use of AI, is not enough. As we approach uncharted territories and prepare for the unknown, we need to develop frameworks that foster a culture of responsibility and education throughout the workforce. Business leaders and executives play a central role in establishing due diligence as common practice for employees that interact with and use AI for work. My advice: start with the basics - in this case, a corporate approvals process. Write a blanket oversight policy that anyone and everyone at your company who uses GenAI tools for business purposes must submit to an official approval process that regulates access to and usage of those tools. You can also establish technical security controls, both detective and preventative. Security controls and technologies will prevent engineers - whether deliberately or inadvertently - from releasing sensitive code to the public realm, and ensure that if or when such an act occurs, it is detected early. What is your advice or insight for AI risk management at the corporate level? #TechnologyTrends #GenAI #AIstrategy #AISecurity