Whether pairing people with AI helps or hurts is usually reported as a single average effect. Using a real-money prediction market (Polymarket) as an objective, externally resolved benchmark, this pilot shows that the value of human-AI collaboration depends on a specific, measurable form of human capital. Analyzed at the level of the individual forecaster, hybrid performance is trimodal: most people either deferred to the model (matching it) or used it to rubber-stamp a prior guess (performing worse than the model alone), while a minority engaged in genuine complementary reasoning and reached accuracy matching or even exceeding (i.e., lower error than) the market itself. Collaborative traits (perspective-taking, intellectual humility, and curiosity) rather than raw cognitive ability or model benchmarks, distinguished who reached that mode. The results are preliminary but statistically robust, and motivate a pre-registered replication now in preparation.
Benchmarking Artificial Intelligence Models for Daily Coastal Hypoxia Forecasting
Department of Environmental Sciences, Louisiana State University（环境科学系，路易斯安那州立大学）；Center for Computation and Technology, Louisiana State University（计算与技术中心，路易斯安那州立大学）；Department of Computer Science, Louisiana State University（计算机科学系，路易斯安那州立大学）；Department of Computer Science, Furman University（计算机科学系，富兰克林大学）；Department of Oceanography and Coastal Sciences, Louisiana State University（海洋学与沿海科学系，路易斯安那州立大学）
Talk, Walk, and Market Response: Multimodal Measurement of AI Washing and Its Capital Market Consequences in China
School of Economics and Trade, Guangdong University of Finance（广东金融学院经济贸易学院）；Department of Computer Science, Faculty of Science, Hong Kong Baptist University（香港 Baptist 大学科学学院计算机科学系）
Forecasting AI Progress: Evidence from a Survey of Machine Learning Researchers
人工智能（AI）的进步正在塑造现代生活，从交通，医疗保健，科学，金融到国防。对人工智能发展的预测可以帮助改善政策和决策。我们报告了对AI和机器学习（ML）研究人员进行的一项大型调查的结果，这些调查是关于他们对AI进展的看法。该调查于2019年底进行，对近期人工智能发展里程碑和高级或人类机器智能进行了预测，定义为机器能够完成人类目前能够完成的每一项或几乎每一项任务。作为这项研究的一部分，我们重新联系了Grace等人（2018）的一项被高度引用的研究的受访者，其中AI/ML研究人员对高级机器智能和AI发展的近期里程碑进行了预测。我们2019年的调查结果显示，总的来说，接受调查的AI/ML研究人员认为，到2060年实现人类水平的机器智能的可能性为50%。结果显示，2019年新联系的研究人员对先进人工智能的进展表达了与Grace et al.（2018）调查中的受访者相似的信念。对于Grace et al.（2018）研究中重新联系的参与者，对高水平机器智能50%可能性的总体预测从2062年转移到2076年，尽管这一变化在统计上并不显著，可能是由于我们的样本量较小。对人工智能近期几个里程碑的预测已经缩短，这表明人们对人工智能的进展更加乐观。最后，AI/ML研究人员还对人类水平的机器智能将如何影响社会表现出了极大的乐观。
Beyond headcount and human capital: The Effective Cognitive Population as a decomposable capacity unit for AI-era planning
Department of AI and Innovation Management, Hanil University and Presbyterian Theological Seminary（韩林大学与长老会神学院人工智能与创新管理系）；PolymathMinds Lab（博识 minds 实验室）
In the Shadow of Smith`s Invisible Hand: Risks to Economic Stability and Social Wellbeing in the Age of Intelligence
Brain and Mind Centre, University of Sydney, Camperdown, Australia（悉尼大学脑与心灵中心）；Mental Wealth Initiative, University of Sydney, Camperdown, Australia（悉尼大学心理财富倡议）；Computer Simulation & Advanced Research Technologies (CSART), Sydney, Australia（悉尼计算机模拟与先进研究技术）；Santa Fe Institute, Santa Fe, New Mexico, USA（圣菲研究所）；School of Computer, Data and Mathematical Sciences, Western Sydney University, Sydney, Australia（西澳大学计算机、数据与数学科学学院）；Baker Institute for Public Policy, Rice University, Houston, Texas, USA（赖斯大学贝克公共政策研究所）；Meadows Mental Health Policy Institute, Dallas, Texas, USA（达拉斯心理健康政策研究所）；University of Technology Sydney, Broadway, Sydney, Australia（悉尼技术大学）；Visiting Professor in Practice, London School of Economics Grantham Institute, London, UK（伦敦经济学院格兰塔姆研究所访问教授）；Swiss Tropical and Public Health Institute & University of Basel, Switzerland（瑞士热带与公共卫生研究所及巴塞尔大学）；Business School, University of Sydney, Sydney, Australia（悉尼大学商学院）
