MIT Research AI News & Updates
MIT Research Challenges Notion of AI Having Coherent Value Systems
MIT researchers have published a study contradicting previous claims that sophisticated AI systems develop coherent value systems or preferences. Their research found that current AI models, including those from Meta, Google, Mistral, OpenAI, and Anthropic, display highly inconsistent preferences that vary dramatically based on how prompts are framed, suggesting these systems are fundamentally imitators rather than entities with stable beliefs.
Skynet Chance (-0.3%): This research significantly reduces concerns about AI developing independent, potentially harmful values that could lead to unaligned behavior, as it demonstrates current AI systems lack coherent values altogether and are merely imitating rather than developing internal motivations.
Skynet Date (+4 days): The study reveals AI systems may be fundamentally inconsistent in their preferences, making alignment much more challenging than expected, which could significantly delay the development of safe, reliable systems that would be prerequisites for any advanced AGI scenario.
AGI Progress (-0.15%): The findings reveal that current AI systems, despite their sophistication, are fundamentally inconsistent imitators rather than coherent reasoning entities, highlighting a significant limitation in their cognitive architecture that must be overcome for true AGI progress.
AGI Date (+4 days): The revealed inconsistency in AI values and preferences suggests a fundamental limitation that must be addressed before achieving truly capable and aligned AGI, likely extending the timeline as researchers must develop new approaches to create more coherent systems.