OpenAI introduces LifeSciBench for life science research tasks

OpenAI has introduced LifeSciBench, a benchmark designed to test how well AI systems handle realistic life science research work. The benchmark focuses on tasks such as interpreting evidence, resolving conflicting results, designing experiments, and communicating scientific conclusions under uncertainty. The company says LifeSciBench includes 750 expertauthored tasks across seven workflows and seven biological domains. The tasks were created and reviewed by practicing life scientists with Ph.D.level training and industry experience in biotech and pharmaceuticals, with detailed rubrics used to grade scientific accuracy and usefulness. OpenAI says the benchmark is meant to measure more than fact recall or narrow prediction tasks. According to the report, models perform best on scientific communication and translation, but still struggle with artifactheavy analysis, exact outputs, and designoriented work. The company also notes that benchmark results should not be treated as proof of realworld research impact, and says future work should examine performance in live research settings.