SPHERE: An Evaluation Card for Human-AI Systems

Dora Zhao; Qianou Ma; Xinran Zhao; Chenglei Si; Chenyang Yang; Ryan Louie; Ehud Reiter; Diyi Yang; Tongshuang Wu

doi:10.18653/v1/2025.findings-acl.70

SPHERE: An Evaluation Card for Human-AI Systems

Dora Zhao, Qianou Ma, Xinran Zhao, Chenglei Si, Chenyang Yang, Ryan Louie, Ehud Reiter, Diyi Yang, Tongshuang Wu

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Abstract

In the era of Large Language Models (LLMs), establishing effective evaluation methods and standards for diverse human-AI interaction systems is increasingly challenging. To encourage more transparent documentation and facilitate discussion on human-AI system evaluation design options, we present an evaluation card SPHERE, which encompasses five key dimensions: 1) What is being evaluated?; 2) How is the evaluation conducted?; 3) Who is participating in the evaluation?; 4) When is evaluation conducted?; 5) How is evaluation validated? We conduct a review of 39 human-AI systems using SPHERE, outlining current evaluation practices and areas for improvement. We provide three recommendations for improving the validity and rigor of evaluation practices.

Anthology ID:: 2025.findings-acl.70
Volume:: Findings of the Association for Computational Linguistics: ACL 2025
Month:: July
Year:: 2025
Address:: Vienna, Austria
Editors:: Wanxiang Che, Joyce Nabende, Ekaterina Shutova, Mohammad Taher Pilehvar
Venue:: Findings
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 1340–1365
Language:
URL:: https://aclanthology.org/2025.findings-acl.70/
DOI:: 10.18653/v1/2025.findings-acl.70
Bibkey:
Cite (ACL):: Dora Zhao, Qianou Ma, Xinran Zhao, Chenglei Si, Chenyang Yang, Ryan Louie, Ehud Reiter, Diyi Yang, and Tongshuang Wu. 2025. SPHERE: An Evaluation Card for Human-AI Systems. In Findings of the Association for Computational Linguistics: ACL 2025, pages 1340–1365, Vienna, Austria. Association for Computational Linguistics.
Cite (Informal):: SPHERE: An Evaluation Card for Human-AI Systems (Zhao et al., Findings 2025)
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PDF:: https://aclanthology.org/2025.findings-acl.70.pdf

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@inproceedings{zhao-etal-2025-sphere,
    title = "{SPHERE}: An Evaluation Card for Human-{AI} Systems",
    author = "Zhao, Dora  and
      Ma, Qianou  and
      Zhao, Xinran  and
      Si, Chenglei  and
      Yang, Chenyang  and
      Louie, Ryan  and
      Reiter, Ehud  and
      Yang, Diyi  and
      Wu, Tongshuang",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.findings-acl.70/",
    doi = "10.18653/v1/2025.findings-acl.70",
    pages = "1340--1365",
    ISBN = "979-8-89176-256-5",
    abstract = "In the era of Large Language Models (LLMs), establishing effective evaluation methods and standards for diverse human-AI interaction systems is increasingly challenging. To encourage more transparent documentation and facilitate discussion on human-AI system evaluation design options, we present an evaluation card SPHERE, which encompasses five key dimensions: 1) What is being evaluated?; 2) How is the evaluation conducted?; 3) Who is participating in the evaluation?; 4) When is evaluation conducted?; 5) How is evaluation validated? We conduct a review of 39 human-AI systems using SPHERE, outlining current evaluation practices and areas for improvement. We provide three recommendations for improving the validity and rigor of evaluation practices."
}

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%0 Conference Proceedings
%T SPHERE: An Evaluation Card for Human-AI Systems
%A Zhao, Dora
%A Ma, Qianou
%A Zhao, Xinran
%A Si, Chenglei
%A Yang, Chenyang
%A Louie, Ryan
%A Reiter, Ehud
%A Yang, Diyi
%A Wu, Tongshuang
%Y Che, Wanxiang
%Y Nabende, Joyce
%Y Shutova, Ekaterina
%Y Pilehvar, Mohammad Taher
%S Findings of the Association for Computational Linguistics: ACL 2025
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-256-5
%F zhao-etal-2025-sphere
%X In the era of Large Language Models (LLMs), establishing effective evaluation methods and standards for diverse human-AI interaction systems is increasingly challenging. To encourage more transparent documentation and facilitate discussion on human-AI system evaluation design options, we present an evaluation card SPHERE, which encompasses five key dimensions: 1) What is being evaluated?; 2) How is the evaluation conducted?; 3) Who is participating in the evaluation?; 4) When is evaluation conducted?; 5) How is evaluation validated? We conduct a review of 39 human-AI systems using SPHERE, outlining current evaluation practices and areas for improvement. We provide three recommendations for improving the validity and rigor of evaluation practices.
%R 10.18653/v1/2025.findings-acl.70
%U https://aclanthology.org/2025.findings-acl.70/
%U https://doi.org/10.18653/v1/2025.findings-acl.70
%P 1340-1365

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Markdown (Informal)

[SPHERE: An Evaluation Card for Human-AI Systems](https://aclanthology.org/2025.findings-acl.70/) (Zhao et al., Findings 2025)

SPHERE: An Evaluation Card for Human-AI Systems (Zhao et al., Findings 2025)

ACL

Dora Zhao, Qianou Ma, Xinran Zhao, Chenglei Si, Chenyang Yang, Ryan Louie, Ehud Reiter, Diyi Yang, and Tongshuang Wu. 2025. SPHERE: An Evaluation Card for Human-AI Systems. In Findings of the Association for Computational Linguistics: ACL 2025, pages 1340–1365, Vienna, Austria. Association for Computational Linguistics.