Four Years of FAccT: A Reflexive, Mixed-Methods Analysis of Research
Contributions, Shortcomings, and Future Prospects
- URL: http://arxiv.org/abs/2206.06738v1
- Date: Tue, 14 Jun 2022 10:38:05 GMT
- Title: Four Years of FAccT: A Reflexive, Mixed-Methods Analysis of Research
Contributions, Shortcomings, and Future Prospects
- Authors: Benjamin Laufer, Sameer Jain, A. Feder Cooper, Jon Kleinberg and Hoda
Heidari
- Abstract summary: Fairness, Accountability, and Transparency (FAccT) for socio-technical systems has been a thriving area of research in recent years.
This study aims to shed light on FAccT's activities to date and identify major gaps and opportunities for translating contributions into broader positive impact.
- Score: 7.002240694310424
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Fairness, Accountability, and Transparency (FAccT) for socio-technical
systems has been a thriving area of research in recent years. An ACM conference
bearing the same name has been the central venue for scholars in this area to
come together, provide peer feedback to one another, and publish their work.
This reflexive study aims to shed light on FAccT's activities to date and
identify major gaps and opportunities for translating contributions into
broader positive impact. To this end, we utilize a mixed-methods research
design. On the qualitative front, we develop a protocol for reviewing and
coding prior FAccT papers, tracing their distribution of topics, methods,
datasets, and disciplinary roots. We also design and administer a questionnaire
to reflect the voices of FAccT community members and affiliates on a wide range
of topics. On the quantitative front, we use the full text and citation network
associated with prior FAccT publications to provide further evidence about
topics and values represented in FAccT. We organize the findings from our
analysis into four main dimensions: the themes present in FAccT scholarship,
the values that underpin the work, the impact of the contributions both within
academic circles and beyond, and the practices and informal norms of the
community that has formed around FAccT. Finally, our work identifies several
suggestions on directions for change, as voiced by community members.
Related papers
- Peer Review as A Multi-Turn and Long-Context Dialogue with Role-Based Interactions [62.0123588983514]
Large Language Models (LLMs) have demonstrated wide-ranging applications across various fields.
We reformulate the peer-review process as a multi-turn, long-context dialogue, incorporating distinct roles for authors, reviewers, and decision makers.
We construct a comprehensive dataset containing over 26,841 papers with 92,017 reviews collected from multiple sources.
arXiv Detail & Related papers (2024-06-09T08:24:17Z) - Responsible developments and networking research: a reflection beyond a
paper ethical statement [0.0]
We focus on the specific case of networking research.
We reflect on the technical realization of the community and its incidence beyond techno-centric contributions.
In particular, we structure the discussion around two frameworks that were recently developed in different contexts to describe the sense of engagement and responsibilities to which the practitioner of a computing-related area may be confronted.
arXiv Detail & Related papers (2024-02-01T09:14:19Z) - Federated Learning for Generalization, Robustness, Fairness: A Survey
and Benchmark [55.898771405172155]
Federated learning has emerged as a promising paradigm for privacy-preserving collaboration among different parties.
We provide a systematic overview of the important and recent developments of research on federated learning.
arXiv Detail & Related papers (2023-11-12T06:32:30Z) - Chain-of-Factors Paper-Reviewer Matching [32.86512592730291]
We propose a unified model for paper-reviewer matching that jointly considers semantic, topic, and citation factors.
We demonstrate the effectiveness of our proposed Chain-of-Factors model in comparison with state-of-the-art paper-reviewer matching methods and scientific pre-trained language models.
arXiv Detail & Related papers (2023-10-23T01:29:18Z) - NLPeer: A Unified Resource for the Computational Study of Peer Review [58.71736531356398]
We introduce NLPeer -- the first ethically sourced multidomain corpus of more than 5k papers and 11k review reports from five different venues.
We augment previous peer review datasets to include parsed and structured paper representations, rich metadata and versioning information.
Our work paves the path towards systematic, multi-faceted, evidence-based study of peer review in NLP and beyond.
arXiv Detail & Related papers (2022-11-12T12:29:38Z) - Fairness in Recommender Systems: Research Landscape and Future
Directions [119.67643184567623]
We review the concepts and notions of fairness that were put forward in the area in the recent past.
We present an overview of how research in this field is currently operationalized.
Overall, our analysis of recent works points to certain research gaps.
arXiv Detail & Related papers (2022-05-23T08:34:25Z) - Revise and Resubmit: An Intertextual Model of Text-based Collaboration
in Peer Review [52.359007622096684]
Peer review is a key component of the publishing process in most fields of science.
Existing NLP studies focus on the analysis of individual texts.
editorial assistance often requires modeling interactions between pairs of texts.
arXiv Detail & Related papers (2022-04-22T16:39:38Z) - What's New? Summarizing Contributions in Scientific Literature [85.95906677964815]
We introduce a new task of disentangled paper summarization, which seeks to generate separate summaries for the paper contributions and the context of the work.
We extend the S2ORC corpus of academic articles by adding disentangled "contribution" and "context" reference labels.
We propose a comprehensive automatic evaluation protocol which reports the relevance, novelty, and disentanglement of generated outputs.
arXiv Detail & Related papers (2020-11-06T02:23:01Z) - A Correspondence Analysis Framework for Author-Conference
Recommendations [2.1055643409860743]
We use Correspondence Analysis (CA) to derive appropriate relationships between the entities in question, such as conferences and papers.
Our models show promising results when compared with existing methods such as content-based filtering, collaborative filtering and hybrid filtering.
arXiv Detail & Related papers (2020-01-08T18:52:39Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.