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arxiv 2110.01108 v1 pith:RNWCVOMH submitted 2021-10-03 cs.LG cs.AIcs.HC

Human-Centered AI for Data Science: A Systematic Approach

classification cs.LG cs.AIcs.HC
keywords approachhcaihumanresearchdatahuman-centeredillustratescience
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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