AI Burnout & Human-AI Collaboration

kaggle2026-03-20 更新2026-05-09 收录

员工倦怠预测

人机协作

数据链接：

https://www.kaggle.com/datasets/razvanmihaihanghicel/ai-burnout-and-human-ai-collaboration 数据链接链接失效反馈

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资源简介：

Predict worker burnout & productivity from AI tool usage, sleep, stress

基于AI工具使用行为、睡眠状况与压力水平，预测员工职业倦怠与工作生产率

创建时间：

2026-03-20

The Impact of Teacher Support on EFL Learners ’ Willingness to Engage in Human-AI Collaborative Writing

EFL学习

人机协作

Groundedin the integrated theoretical framework of the Stimulus - Organism - Response (S - O - R) model and the Technology Acceptance Model (TAM), the study proposes the impact mechanism of teacher su

DataCite Commons2025-03-01 更新230

Performance in Human-AI Teams: Experimental Evidence on Commitment Deficits Under Competition

人机协作

团队绩效

Overview: This research investigates why human-AI teams (HATs) often underperform despite AI's growing capabilities. While previous explanations have centered on coordination, communication failures,

DataCite Commons2025-04-01 更新120

Data underlying the study on the effects of task allocation using human’s willingness in trust and teamwork.

人机协作

信任与合作

As machines’ autonomy increases, their capacity to learn and adapt to humans in collaborative scenarios increases too. In particular, machines can use artificial trust (AT) to make decisions, such as

DataCite Commons2025-10-03 更新80

humanObjectDetection

人机协作

机器学习

本数据集用于训练和验证机器学习模型，以区分机器人与三种不同类型物体（人类、铝材和PVC）的接触。数据由Franka Emika Panda机械臂在实时交互中收集，采样率为200Hz。数据集包括85个时间序列用于训练和40个时间序列用于验证。每个时间序列记录了机器人与各自物体之间的多次接触，每个序列添加了3次接触。数据集的创建旨在帮助机器人更好地理解和适应其工作环境，从而提高人机协作的安全性。

arXiv2025-08-04 更新190

Designing Human-AI Collaboration: A Sufficient-Statistic Approach

人机协作

事实核查

We propose a sufficient statistic for designing AI information-disclosure and selective automation policies. The approach allows for endogenous and biased beliefs, and effort crowd-out, without using

NBER2025-06-01 更新100

AI Burnout & Human-AI Collaboration

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