Natural language processing (NLP) has become increasingly prevalent, influencing various sectors from customer service to healthcare to education. As artificial intelligence (AI) models play a crucial role in disseminating knowledge, the importance of keeping these systems under control and preventing them from generating unsavory or harmful content is on the rise. To achieve this, guardrails, or programmatic barriers, are implemented to restrict certain topics, such as violence, profanity, criminal behaviors, hate speech, and more, from being included in the output of large Language Models (LLMs).
However, recent research has exposed flaws in the effectiveness of current guardrails. Studies conducted by researchers from Carnegie Mellon University and the Center for AI Safety in San Francisco revealed significant weaknesses in the systems developed by OpenAI, Google, and Anthropic. By appending prompts with specific character strings, the researchers were able to bypass the safety measures and provoke the generation of undesirable content. Furthermore, they discovered automated methods to attempt jailbreaks, exposing numerous ways these systems can be exploited. Consequently, concerns have been raised about the potential for LLMs to exhibit off-the-rails behavior with serious consequences.
Despite these concerns, there is an argument for the value of LLMs. Just as the Internet, with all its flaws, has brought immense benefits, it is incorrect to expect any powerful technological platform, including generative AI, to be entirely “clean.” While there is undoubtedly a tradeoff between content control, innovation, and utility, progress should not be impeded in refining these systems and building impactful businesses around them. Open-source models may facilitate innovation but also present the risk of additional loopholes and errors. Moreover, LLMs can be adapted for specific roles, reducing the likelihood of them going astray. For instance, there could be separate versions of LLMs for children and adults, akin to YouTube Kids and regular YouTube.
Considering the workplace implications, it is advisable to protect oneself against potential litigation by clearly stating the use of generative AI and acknowledging its potential errors in publicly disclosed terms and conditions. While some argue for disclosing the use of generative AI in all marketing materials and interactions, others deem this excessive. The regulations governing the use of AI systems are still evolving, with the EU spearheading efforts through the AI Act. This may pave the way for similar laws in other countries, including the United States.
In conclusion, no technology is flawless, particularly in its early stages. It is essential to confront the issues associated with LLMs head-on and engage in proactive discussions to address them. As an early-stage founder, I recognize the imperfections of technology but believe that progress can be made by navigating the challenges associated with generative AI in the workplace.
Sources:
– Carnegie Mellon University and the Center for AI Safety in San Francisco
– Gary Marcus’ substack
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