According to @godofprompt, a recent analysis of 2,847 AI safety research papers shows that 94% focus on just six benchmarks, with 87% of studies exploiting existing metrics rather than exploring new safety methods (source: Twitter, Jan 14, 2026). Researchers are aware that these benchmarks are flawed, yet continue to optimize for them due to pressures related to publishing, funding, and career advancement. As a result, fundamental AI safety issues such as deception, misalignment, and specification gaming remain largely unresolved. This trend highlights a critical business and research opportunity for organizations focused on solving real-world AI safety challenges, signaling a need for innovative approaches and new evaluation standards within the AI industry.