Computer Science Communities: Who is Speaking, and Who is Listening to the Women? Using an Ethics of Care to Promote Diverse Voices

• URL: http://arxiv.org/abs/2101.07463v1
• Date: Tue, 19 Jan 2021 04:44:28 GMT
• Title: Computer Science Communities: Who is Speaking, and Who is Listening to the Women? Using an Ethics of Care to Promote Diverse Voices
• Authors: Marc Cheong and Kobi Leins and Simon Coghlan
• Abstract summary: This paper is a preliminary exploration of two hypotheses, namely 1) Each community has differing inclusion of minoritised groups (using women as our test case); and 2) Even where women exist in a community, they are not published representatively. We argue that ACM has an ethical duty of care to its community to increase these ratios, and to hold individual computing communities to account in order to do so, by providing incentives and a regular reporting system, in order to uphold its own Code.
• Score: 3.325932244741268
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Those working on policy, digital ethics and governance often refer to issues in `computer science', that includes, but is not limited to, common subfields of Artificial Intelligence (AI), Computer Science (CS) Computer Security (InfoSec), Computer Vision (CV), Human Computer Interaction (HCI), Information Systems, (IS), Machine Learning (ML), Natural Language Processing (NLP) and Systems Architecture. Within this framework, this paper is a preliminary exploration of two hypotheses, namely 1) Each community has differing inclusion of minoritised groups (using women as our test case); and 2) Even where women exist in a community, they are not published representatively. Using data from 20,000 research records, totalling 503,318 names, preliminary data supported our hypothesis. We argue that ACM has an ethical duty of care to its community to increase these ratios, and to hold individual computing communities to account in order to do so, by providing incentives and a regular reporting system, in order to uphold its own Code.

Related papers

• Assessing Computer Science Student Attitudes Towards AI Ethics and Policy [8.927858368749204]
  The attitudes and competencies with respect to AI ethics and policy among post-secondary students studying computer science (CS) are of particular interest. Despite computer scientists being at the forefront of learning about and using AI tools, their attitudes towards AI remain understudied.
  arXiv  Detail & Related papers  (2025-04-06T23:03:47Z)
• An investigation into the scientific landscape of the conversational and generative artificial intelligence, and human-chatbot interaction in education and research [0.0]
  This study investigates the scientific landscape of CGAI and human-chatbot interaction/collaboration. The prominent use cases of CGAI for teaching, learning, and research activities occurred in computer science, medical/healthcare, engineering, and business fields. Formulating strategies and policies to address potential CGAI challenges in teaching/learning and practice are priorities.
  arXiv  Detail & Related papers  (2024-06-15T12:37:29Z)
• Advancing Social Intelligence in AI Agents: Technical Challenges and Open Questions [67.60397632819202]
  Building socially-intelligent AI agents (Social-AI) is a multidisciplinary, multimodal research goal. We identify a set of underlying technical challenges and open questions for researchers across computing communities to advance Social-AI.
  arXiv  Detail & Related papers  (2024-04-17T02:57:42Z)
• Child Impact Statements: Interdisciplinary Collaboration in Political Science and Computer Science [0.0]
  This paper highlights an interdisciplinary collaboration between Social Science and Computer Science to create a Child Impact Statement tool in Shelby County, TN. Child Impact Statements (CISs) are instrumental in helping to foreground the concerns and needs of minor community members who are too young to vote and often unable to advocate for themselves politically.
  arXiv  Detail & Related papers  (2024-01-09T23:43:07Z)
• Report of the 1st Workshop on Generative AI and Law [78.62063815165968]
  This report presents the takeaways of the inaugural Workshop on Generative AI and Law (GenLaw) A cross-disciplinary group of practitioners and scholars from computer science and law convened to discuss the technical, doctrinal, and policy challenges presented by law for Generative AI.
  arXiv  Detail & Related papers  (2023-11-11T04:13:37Z)
• Voices of Her: Analyzing Gender Differences in the AI Publication World [26.702520904075044]
  We identify several gender differences using the AI Scholar dataset of 78K researchers in the field of AI. Female first-authored papers show distinct linguistic styles, such as longer text, more positive emotion words, and more catchy titles. Our analysis provides a window into the current demographic trends in our AI community, and encourages more gender equality and diversity in the future.
  arXiv  Detail & Related papers  (2023-05-24T00:40:49Z)
• AI Usage Cards: Responsibly Reporting AI-generated Content [25.848910414962337]
  Given AI systems like ChatGPT can generate content that is indistinguishable from human-made work, the responsible use of this technology is a growing concern. We propose a three-dimensional model consisting of transparency, integrity, and accountability to define the responsible use of AI. Second, we introduce AI Usage Cards'', a standardized way to report the use of AI in scientific research.
  arXiv  Detail & Related papers  (2023-02-16T08:41:31Z)
• Coordinated Science Laboratory 70th Anniversary Symposium: The Future of Computing [80.72844751804166]
  In 2021, the Coordinated Science Laboratory CSL hosted the Future of Computing Symposium to celebrate its 70th anniversary. We summarize the major technological points, insights, and directions that speakers brought forward during the symposium. Participants discussed topics related to new computing paradigms, technologies, algorithms, behaviors, and research challenges to be expected in the future.
  arXiv  Detail & Related papers  (2022-10-04T17:32:27Z)
• Neural Approaches to Conversational Information Retrieval [94.77863916314979]
  A conversational information retrieval (CIR) system is an information retrieval (IR) system with a conversational interface. Recent progress in deep learning has brought tremendous improvements in natural language processing (NLP) and conversational AI. This book surveys recent advances in CIR, focusing on neural approaches that have been developed in the last few years.
  arXiv  Detail & Related papers  (2022-01-13T19:04:59Z)
• Empowering Local Communities Using Artificial Intelligence [70.17085406202368]
  It has become an important topic to explore the impact of AI on society from a people-centered perspective. Previous works in citizen science have identified methods of using AI to engage the public in research. This article discusses the challenges of applying AI in Community Citizen Science.
  arXiv  Detail & Related papers  (2021-10-05T12:51:11Z)
• Gender Stereotype Reinforcement: Measuring the Gender Bias Conveyed by Ranking Algorithms [68.85295025020942]
  We propose the Gender Stereotype Reinforcement (GSR) measure, which quantifies the tendency of a Search Engines to support gender stereotypes. GSR is the first specifically tailored measure for Information Retrieval, capable of quantifying representational harms.
  arXiv  Detail & Related papers  (2020-09-02T20:45:04Z)
• Trustworthy AI in the Age of Pervasive Computing and Big Data [22.92621391190282]
  We formalise the requirements of trustworthy AI systems through an ethics perspective. After discussing the state of research and the remaining challenges, we show how a concrete use-case in smart cities can benefit from these methods.
  arXiv  Detail & Related papers  (2020-01-30T08:09:31Z)

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.