The central question is not whether AI can imitate human conversation, but whether it can participate in the production of publishable scientific knowledge at a level comparable to a recognized human contributor.
大多数人认为AI科学贡献的衡量标准是其模仿人类对话的能力，而作者认为真正的标准应该是AI能否产生可发表的、相当于人类贡献者的科学知识。这一观点重新定义了AI科学成功的标准，挑战了当前AI评估的主流范式。
Daniël Lakens. (2020, October 28). This piece makes a great point about how we can try to make commentaries more useful for science—Turning them from ‘pointless quibbles’ into pieces where both parties actually commit to working out their disagreements. Https://t.co/fBKStzg7ib [Tweet]. @lakens. https://twitter.com/lakens/status/1321345954264633345
Heyman, T., Moors, P., & Rabagliati, H. (2020). The benefits of adversarial collaboration for commentaries. Nature Human Behaviour, 4(12), 1217–1217. https://doi.org/10.1038/s41562-020-00978-6
Anne Urai. (2020, November 15). All-inclusive authorship on large scientific papers can a be dangerous practice Alert: Potential unpopular opinion Thread 👇1/n [Tweet]. @AnneEUrai. https://twitter.com/AnneEUrai/status/1327934091929464832