Publikationer från Malmö universitet
Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
From "Explainable AI" to "Graspable AI"
Malmö universitet, Fakulteten för kultur och samhälle (KS), Institutionen för konst, kultur och kommunikation (K3). Malmö universitet, Internet of Things and People (IOTAP).ORCID-id: 0000-0003-1852-3937
Pennsylvania State University.
Machine Learning Visualization Lab Decisive Analytics Corporation, United States.
Aarhus University, Denmark.
Vise andre og tillknytning
2021 (engelsk)Inngår i: Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction (TEI ’21), New York: Association for Computing Machinery (ACM), 2021, artikkel-id 69Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Since the advent of Artificial Intelligence (AI) and Machine Learning (ML), researchers have asked how intelligent computing systems could interact with and relate to their users and their surroundings, leading to debates around issues of biased AI systems, ML black-box, user trust, user’s perception of control over the system, and sys- tem’s transparency, to name a few. All of these issues are related to how humans interact with AI or ML systems, through an interface which uses different interaction modalities. Prior studies address these issues from a variety of perspectives, spanning from under- standing and framing the problems through ethics and Science and Technology Studies (STS) perspectives to finding effective technical solutions to the problems. But what is shared among almost all those efforts is an assumption that if systems can explain the how and why of their predictions, people will have a better perception of control and therefore will trust such systems more, and even can correct their shortcomings. This research field has been called Explainable AI (XAI). In this studio, we take stock on prior efforts in this area; however, we focus on using Tangible and Embodied Interaction (TEI) as an interaction modality for understanding ML. We note that the affordances of physical forms and their behaviors potentially can not only contribute to the explainability of ML sys- tems, but also can contribute to an open environment for criticism. This studio seeks to both critique explainable ML terminology and to map the opportunities that TEI can offer to the HCI for designing more sustainable, graspable and just intelligent systems.

sted, utgiver, år, opplag, sider
New York: Association for Computing Machinery (ACM), 2021. artikkel-id 69
Emneord [en]
Explainable AI, XAI, Machine Learning, Artificial Intelligence, Tan- gible Embodied Interaction, TEI, Interaction Design
HSV kategori
Forskningsprogram
Interaktionsdesign
Identifikatorer
URN: urn:nbn:se:mau:diva-38983DOI: 10.1145/3430524.3442704ISI: 001180182600069Scopus ID: 2-s2.0-85102059863ISBN: 978-1-4503-8213-7 (digital)OAI: oai:DiVA.org:mau-38983DiVA, id: diva2:1514500
Konferanse
ACM International Conference on Tangible, Embedded and Embodied Interaction (TEI'21)
Forskningsfinansiär
Knowledge FoundationTilgjengelig fra: 2021-01-05 Laget: 2021-01-05 Sist oppdatert: 2024-05-28bibliografisk kontrollert

Open Access i DiVA

Fulltekst mangler i DiVA

Andre lenker

Forlagets fulltekstScopus

Person

Ghajargar, MalihehCuartielles, David

Søk i DiVA

Av forfatter/redaktør
Ghajargar, MalihehCuartielles, David
Av organisasjonen

Søk utenfor DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric

doi
isbn
urn-nbn
Totalt: 706 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf