paper-with-me

Papers

Human-Centered AI for Data Science: A Systematic Approach

2021-10-03 · Dakuo Wang, Xiaojuan Ma, April Yi Wang

Human-Centered AI (HCAI) refers to the research effort that aims to design and implement AI techniques to support various human tasks, while taking human needs into consideration and preserving human control. In this short position paper, we illustrate how we approach HCAI using a series of research projects around Data Science (DS) works as a case study. The AI techniques built for supporting DS works are collectively referred to as AutoML systems, and their goals are to automate some parts of the DS workflow. We illustrate a three-step systematical research approach(i.e., explore, build, and integrate) and four practical ways of implementation for HCAI systems. We argue that our work is a cornerstone towards the ultimate future of Human-AI Collaboration for DS and beyond, where AI and humans can take complementary and indispensable roles to achieve a better outcome and experience.

📄 PDF Abstract BibTeX arXiv:2110.01108

Code (0)

등록된 구현이 없습니다.

Tasks

AutoML

Similar Papers 제목 키워드 기반

Towards Human-centered Explainable AI: A Survey of User Studies for Model Explanations

2022-10-20 · Yao Rong, Tobias Leemann, Thai-trang Nguyen, Lisa Fiedler 외

Explainable AI (XAI) is widely viewed as a sine qua non for ever-expanding AI research. A better understanding of the needs of XAI users, as well as human-centered evaluations of explainable models are both a necessity a…

Explainable Artificial Intelligence (XAI)Explainable ModelsFairnessRecommendation Systems+1

Large Language Model Psychometrics: A Systematic Review of Evaluation, Validation, and Enhancement

2025-05-13 · Haoran Ye, Jing Jin, Yuhang Xie, Xin Zhang 외

The rapid advancement of large language models (LLMs) has outpaced traditional evaluation methodologies. It presents novel challenges, such as measuring human-like psychological constructs, navigating beyond static and t…

BenchmarkingLanguage ModelingLanguage ModellingLarge Language Model

Evaluating Human-AI Safety: A Framework for Measuring Harmful Capability Uplift

2026-03-06 · Michelle Vaccaro, Jaeyoon Song, Abdullah Almaatouq, Michiel A. Bakker arxiv

Current frontier AI safety evaluations emphasize static benchmarks, third-party annotations, and red-teaming. In this position paper, we argue that AI safety research should focus on human-centered evaluations that measu…

Human-Centered Human-AI Interaction (HC-HAII): A Human-Centered AI Perspective

2025-08-05 · Wei Xu arxiv

This chapter systematically promotes an emerging interdisciplinary field of human-artificial intelligence interaction (human-AI interaction, HAII) from a human-centered AI (HCAI) perspective. It introduces a framework of…

Charting the Future of AI-supported Science Education: A Human-Centered Vision

2026-02-09 · Xiaoming Zhai, Kent Crippen arxiv

This concluding chapter explores how artificial intelligence (AI) is reshaping the purposes, practices, and outcomes of science education, and proposes a human-centered framework for its responsible integration. Drawing …