Daily picks · 10月10日

提出可量化群际偏差的神经计算模型，推动从脑区定位到干预应用。

Zhang Hejing et al. from Beijing Normal University proposed the "intergroup reference point model" in Advances in Psychological Science, 2026, Vol. 34, No. 9, employing an angular parameter φ to quantify the ratio of subjective value weights between ingroups and outgroups, thereby achieving continuous and individualized characterization of intergroup bias. The article designed five progressive studies encompassing model validation, parameter construction, fMRI neural mechanisms, cooperation-conflict prediction, and oxytocin modulation, advancing intergroup bias research from brain region localization toward computational modeling and intervention applications.

Advances in Psychological Science ｜ 群体间偏见, 主观价值计算, 功能性磁共振成像（fMRI）, 催产素

探讨AI聊天机器人是否具备类似人类的符号推理能力。

When humans write sentences or solve math problems, they are thinking symbolically—each number, variable or word is expressed by a symbol. While AI chatbots do not "think" that way, if prompted, they can offer cogent advice about writing, math and many other topics as if a person were offering it.

Tech Xplore ｜ 聊天机器人, 思考, 神经网络

介绍EMR疗法帮助家庭暴力儿童从恐惧转向治愈的临床实践。

EMDRIA member M. Lupita Renteria discusses the impact of domestic violence on children, and how EMDR therapy can help young survivors move from fear and confusion toward healing and resilience.

EMDR International Association ｜ Eye Movement Desensitization & Reprocessing ｜ 家庭暴力, 儿童, EMDR, 打破循环, 治愈家庭

揭示AI招聘评估工具在效率背后可能存在的公正性隐忧。

Companies seeking to fill job openings are increasingly "drinking through a fire hose of applications," in the words of one hiring expert, with some popular postings receiving 1,000 applications in a single weekend. Amid this surge, some companies have begun using artificial intelligence tools, including large language models (LLMs), to help identify promising candidates. And it isn't just hiring: Under pressure to find needles in mounting haystacks, venture capital firms reviewing startup pitches and Hollywood studios assessing movie scripts have reported using AI tools as part of their decision-making processes. But can we trust LLMs to avoid racial and gender bias when wading through a sea of contenders? That's the question posed in a new paper by Tristan Botelho, an associate professor of organizational behavior at Yale SOM, and Yale SOM Ph.D. student Qingyang (Iris) Wang.

Tech Xplore ｜ 工作, 申请, 偏见, AI