Malmö University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Tangible XAI
Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Culture and Society (KS), School of Arts and Communication (K3).ORCID iD: 0000-0003-1852-3937
Indiana University Bloomingtonm,USA.ORCID iD: 0000-0002-6864-6065
Dataminr, USA.
Royal Institute of Technology (KTH).
Show others and affiliations
2022 (English)Other (Other (popular science, discussion, etc.))
Abstract [en]

Computational systems are becoming increasingly smart and automated. Artificial intelligence (AI) systems perceive things in the world, produce content, make decisions for and about us, and serve as emotional companions. From music recommendations to higher-stakes scenarios such as policy decisions, drone-based warfare, and automated driving directions, automated systems affect us all.

But researchers and other experts are asking, How well do we understand this alien intelligence? If even AI developers don’t fully understand how their own neural networks make decisions, what chance does the public have to understand AI outcomes? For example, AI systems decide whether a person should get a loan; so what should—what can—that person understand about how the decision was made? And if we can’t understand it, how can any of us trust AI?

The emerging area of explainable AI (XAI) addresses these issues by helping to disclose how an AI system arrives at its outcomes. But the nature of the disclosure depends in part on the audience, or who needs to understand the AI. A car, for example, can send warnings to consumers (“Tire Pressure Low”) and also send highly technical diagnostic codes that only trained mechanics can understand. Explanation modality is also important to consider. Some people might prefer spoken explanations compared to visual ones. Physical forms afford natural interaction with some smart systems, like vehicles and vacuums, but whether tangible interaction can support AI explanation has not yet been explored.

In the summer of 2020, a group of multidisciplinary researchers collaborated on a studio proposal for the 2021 ACM Tangible Embodied and Embedded (TEI) conference. The basic idea was to link conversations about tangible and embodied interaction and product semantics to XAI. Here, we first describe the background and motivation for the workshop and then report on its outcomes and offer some discussion points.

Place, publisher, year, pages
New York, USA: Association for Computing Machinery (ACM), 2022.
Keywords [en]
Explainable AI, Tangible Embodied Interaction, Human-Centred AI
National Category
Design Human Aspects of ICT Human Computer Interaction
Research subject
Interaktionsdesign
Identifiers
URN: urn:nbn:se:mau:diva-50374OAI: oai:DiVA.org:mau-50374DiVA, id: diva2:1641101
Note

TANGIBLE XAI Blogs Posted: Tue, February 15, 2022 

Available from: 2022-02-28 Created: 2022-02-28 Last updated: 2022-12-13Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Fulltext

Authority records

Ghajargar, Maliheh

Search in DiVA

By author/editor
Ghajargar, MalihehBardzell, Jeffrey
By organisation
Internet of Things and People (IOTAP)School of Arts and Communication (K3)
DesignHuman Aspects of ICTHuman Computer Interaction

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 450 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf