Participatory Design Landscape for the Human-Machine Collaboration, Interaction and Automation at the Frontiers of HCI (PDL 2021)

• URL: http://arxiv.org/abs/2207.03217v1
• Date: Thu, 7 Jul 2022 10:44:14 GMT
• Title: Participatory Design Landscape for the Human-Machine Collaboration, Interaction and Automation at the Frontiers of HCI (PDL 2021)
• Authors: Wies{\l}aw Kope\'c, Cezary Biele, Monika Kornacka, Grzegorz Pochwatko, Anna Jaskulska, Kinga Skorupska, Julia Paluch, Piotr Gago, Barbara Karpowicz, Marcin Niewi\'nski, Rafa{\l} Mas{\l}yk
• Abstract summary: This workshop will become a venue to share experiences and novel ideas in this area. We welcome a wide scope of contributions in HCI which explore sustainable opportunities for participatory design and development practices.
• Score: 7.305653067711372
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We propose a one-day transdisciplinary creative workshop in the broad area of HCI focused on multiple opportunities of incorporating participatory design into research and industry practice. This workshop will become a venue to share experiences and novel ideas in this area. At the same time, we will brainstorm and explore frontiers of HCI related to engaging end users in design and development practices of established and emerging ICT solutions often overlooked in terms of co-design. We welcome a wide scope of contributions in HCI which explore sustainable opportunities for participatory design and development practices in the context of interconnected business, social, economic and environmental issues. The contributions ought to explore challenges and opportunities related to co-design at the frontiers of HCI - participatory design of newest and complex technologies, not easily explainable or intuitive, novel collaborative (remote or distributed) approaches to empowering users to prepare them to contribute as well as to engaging them directly in co-design.

Related papers

• From Fake Perfects to Conversational Imperfects: Exploring Image-Generative AI as a Boundary Object for Participatory Design of Public Spaces [5.968063252533802]
  Image-generative artificial intelligence (IGAI) could support participatory design. We study how IGAI could facilitate participatory processes when designing public spaces. We conducted workshops and IGAI-mediated interviews in a real-world participatory process to upgrade a park in Los Angeles.
  arXiv  Detail & Related papers  (2024-11-01T18:02:46Z)
• Constraining Participation: Affordances of Feedback Features in Interfaces to Large Language Models [49.74265453289855]
  Large language models (LLMs) are now accessible to anyone with a computer, a web browser, and an internet connection via browser-based interfaces. This paper examines the affordances of interactive feedback features in ChatGPT's interface, analysing how they shape user input and participation in iteration.
  arXiv  Detail & Related papers  (2024-08-27T13:50:37Z)
• Exploring Links between Conversational Agent Design Challenges and Interdisciplinary Collaboration [0.0]
  The paper focuses on the socio-technical challenges of Conversational Agents (CA) creation. It proposes a taxonomy of CA design challenges using interdisciplinary collaboration (IDC) as a lens. The paper proposes practical strategies to overcome them which complement existing design principles.
  arXiv  Detail & Related papers  (2023-11-15T10:20:49Z)
• The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practice [64.29355073494125]
  This article aims to ground what we dub the "participatory turn" in AI design by synthesizing existing theoretical literature on participation. We articulate empirical findings concerning the current state of participatory practice in AI design based on an analysis of recently published research and semi-structured interviews with 12 AI researchers and practitioners.
  arXiv  Detail & Related papers  (2023-10-02T05:30:42Z)
• Investigating Practices and Opportunities for Cross-functional Collaboration around AI Fairness in Industry Practice [10.979734542685447]
  An emerging body of research indicates that ineffective cross-functional collaboration represents a major barrier to addressing issues of fairness in AI design and development. We conducted a series of interviews and design workshops with 23 industry practitioners spanning various roles from 17 companies. We found that practitioners engaged in bridging work to overcome frictions in understanding, contextualization, and evaluation around AI fairness across roles.
  arXiv  Detail & Related papers  (2023-06-10T23:42:26Z)
• An Uncommon Task: Participatory Design in Legal AI [64.54460979588075]
  We examine a notable yet understudied AI design process in the legal domain that took place over a decade ago. We show how an interactive simulation methodology allowed computer scientists and lawyers to become co-designers.
  arXiv  Detail & Related papers  (2022-03-08T15:46:52Z)
• Stakeholder Participation in AI: Beyond "Add Diverse Stakeholders and Stir" [76.44130385507894]
  This paper aims to ground what we dub a 'participatory turn' in AI design by synthesizing existing literature on participation and through empirical analysis of its current practices. Based on our literature synthesis and empirical research, this paper presents a conceptual framework for analyzing participatory approaches to AI design.
  arXiv  Detail & Related papers  (2021-11-01T17:57:04Z)
• Introducing "Neuromorphic Computing and Engineering" [2.8732531902793172]
  One of the strategies being proposed to address some of these problems is to develop novel brain-inspired processing methods. Neuromorphic Computing and Engineering has been launched to support this new community.
  arXiv  Detail & Related papers  (2021-05-30T20:12:27Z)
• Collaborative Intelligence: Challenges and Opportunities [80.22863657331622]
  The paper surveys the current state of the art in CI, with special emphasis on signal processing-related challenges in feature compression, error resilience, privacy, and system-level design.
  arXiv  Detail & Related papers  (2021-02-13T01:24:05Z)
• Artificial Intelligence for IT Operations (AIOPS) Workshop White Paper [50.25428141435537]
  Artificial Intelligence for IT Operations (AIOps) is an emerging interdisciplinary field arising in the intersection between machine learning, big data, streaming analytics, and the management of IT operations. Main aim of the AIOPS workshop is to bring together researchers from both academia and industry to present their experiences, results, and work in progress in this field.
  arXiv  Detail & Related papers  (2021-01-15T10:43:10Z)

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.