Crossing Margins: Intersectional Users' Ethical Concerns about Software

• URL: http://arxiv.org/abs/2410.08090v1
• Date: Thu, 10 Oct 2024 16:33:05 GMT
• Title: Crossing Margins: Intersectional Users' Ethical Concerns about Software
• Authors: Lauren Olson, Tom P. Humbert, Ricarda Anna-Lena Fischer, Bob Westerveld, Florian Kunneman, Emitzá Guzmán,
• Abstract summary: This work aims to fill the gap in research on intersectional users' software-related perspectives. We collected posts from over 700 intersectional subreddits discussing software applications. Our findings revealed that intersectional communities report textitcritical complaints related to cyberbullying, inappropriate content, and discrimination.
• Score: 3.0830895408549583
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Many modern software applications present numerous ethical concerns due to conflicts between users' values and companies' priorities. Intersectional communities, those with multiple marginalized identities, are disproportionately affected by these ethical issues, leading to legal, financial, and reputational issues for software companies, as well as real-world harm for intersectional users. Historically, the voices of intersectional communities have been systematically marginalized and excluded from contributing their unique perspectives to software design, perpetuating software-related ethical concerns. This work aims to fill the gap in research on intersectional users' software-related perspectives and provide software practitioners with a starting point to address their ethical concerns. We aggregated and analyzed the intersectional users' ethical concerns over time and developed a prioritization method to identify critical concerns. To achieve this, we collected posts from over 700 intersectional subreddits discussing software applications, utilized deep learning to identify ethical concerns in these posts, and employed state-of-the-art techniques to analyze their content in relation to time and priority. Our findings revealed that intersectional communities report \textit{critical} complaints related to cyberbullying, inappropriate content, and discrimination, highlighting significant flaws in modern software, particularly for intersectional users. Based on these findings, we discuss how to better address the ethical concerns of intersectional users in software development.

Related papers

• Ethics Whitepaper: Whitepaper on Ethical Research into Large Language Models [53.316174782223115]
  This whitepaper offers an overview of the ethical considerations surrounding research into or with large language models (LLMs) As LLMs become more integrated into widely used applications, their societal impact increases, bringing important ethical questions to the forefront.
  arXiv  Detail & Related papers  (2024-10-17T18:36:02Z)
• Ethical software requirements from user reviews: A systematic literature review [0.0]
  This SLR aims to identify and analyze existing ethical requirements identification and elicitation techniques. Ethical requirements gathering has recently driven drastic interest in the research community due to the rise of ML and AI-based approaches in decision-making within software applications.
  arXiv  Detail & Related papers  (2024-09-18T19:56:19Z)
• Towards Extracting Ethical Concerns-related Software Requirements from App Reviews [0.0]
  This study analyzes app reviews of the Uber mobile application (a popular taxi/ride app) We propose a novel approach that leverages a knowledge graph (KG) model to extract software requirements from app reviews. Our framework consists of three main components: developing an ontology with relevant entities and relations, extracting key entities from app reviews, and creating connections between them.
  arXiv  Detail & Related papers  (2024-07-19T04:50:32Z)
• Eagle: Ethical Dataset Given from Real Interactions [74.7319697510621]
  We create datasets extracted from real interactions between ChatGPT and users that exhibit social biases, toxicity, and immoral problems. Our experiments show that Eagle captures complementary aspects, not covered by existing datasets proposed for evaluation and mitigation of such ethical challenges.
  arXiv  Detail & Related papers  (2024-02-22T03:46:02Z)
• The Best Ends by the Best Means: Ethical Concerns in App Reviews [2.0625936401496237]
  App store reviews allow practitioners to collect users' perspectives, crucial for identifying software flaws. We collected five million user reviews, developed a set of ethical concerns representative of user preferences, and manually labeled a sample of these reviews. We found that users highly report ethical concerns about censorship, identity theft, and safety.
  arXiv  Detail & Related papers  (2024-01-19T23:53:26Z)
• Teaching Software Ethics to Future Software Engineers [6.384357773998868]
  The importance of teaching software ethics to software engineering (SE) students is more critical now than ever before. Traditional classroom methods, vignettes, role-play games, and quizzes have been employed over the years to teach SE students about software ethics. We developed an interactive, scenario-based Software Ethics Quiz.
  arXiv  Detail & Related papers  (2023-12-19T06:18:05Z)
• Unpacking the Ethical Value Alignment in Big Models [46.560886177083084]
  This paper provides an overview of the risks and challenges associated with big models, surveys existing AI ethics guidelines, and examines the ethical implications arising from the limitations of these models. We introduce a novel conceptual paradigm for aligning the ethical values of big models and discuss promising research directions for alignment criteria, evaluation, and method.
  arXiv  Detail & Related papers  (2023-10-26T16:45:40Z)
• Along the Margins: Marginalized Communities' Ethical Concerns about Social Platforms [3.357853336791203]
  We identified marginalized communities' ethical concerns about social platforms. Recent platform malfeasance indicates that software teams prioritize shareholder concerns over user concerns. We found that marginalized communities' ethical concerns predominantly revolve around discrimination and misrepresentation.
  arXiv  Detail & Related papers  (2023-04-18T10:15:16Z)
• Factoring the Matrix of Domination: A Critical Review and Reimagination of Intersectionality in AI Fairness [55.037030060643126]
  Intersectionality is a critical framework that allows us to examine how social inequalities persist. We argue that adopting intersectionality as an analytical framework is pivotal to effectively operationalizing fairness.
  arXiv  Detail & Related papers  (2023-03-16T21:02:09Z)
• An Ethical Highlighter for People-Centric Dataset Creation [62.886916477131486]
  We propose an analytical framework to guide ethical evaluation of existing datasets and to serve future dataset creators in avoiding missteps. Our work is informed by a review and analysis of prior works and highlights where such ethical challenges arise.
  arXiv  Detail & Related papers  (2020-11-27T07:18:44Z)
• Case Study: Deontological Ethics in NLP [119.53038547411062]
  We study one ethical theory, namely deontological ethics, from the perspective of NLP. In particular, we focus on the generalization principle and the respect for autonomy through informed consent. We provide four case studies to demonstrate how these principles can be used with NLP systems.
  arXiv  Detail & Related papers  (2020-10-09T16:04:51Z)

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.