Towards a heuristic model for experiential AI: analysing the Zizi Show in the new real

Drew  Hemment; Martin Zeilinger; Matjaz Vidmar; Jake Elwes; Holly Warner; David Sarmiento Pérez; Robin Hill

doi:10.21606/drs.2022.808

Towards a heuristic model for experiential AI: analysing the Zizi Show in the new real

Drew Hemment^*, Martin Zeilinger, Matjaz Vidmar, Jake Elwes, Holly Warner, David Sarmiento Pérez, Robin Hill

^*Corresponding author for this work

Department of Games and Arts

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

130 Downloads (Pure)

Abstract

Based on the rapid pace of evolving creative practice in AI arts, we identify and respond to an urgent need to develop frameworks for analysing the critical dimensions (including social/political) of this emerging field. This paper offers a comprehensive case study of The Zizi Show, by Jake Elwes, developed as part of The New Real and Experiential AI programme at the Edinburgh Futures Institute within the University of Edinburgh. Based on this case study analysis, we propose the structuring of distinct project characteristics into four categories (socio-cultural and institutional aspects; technology and media; experience and affect; and audience and impact) which form the basis for a heuristic model. The statements/descriptors collected in each category serve to capture creative and design strategies that can lead design processes from cultural and technological perspectives, enable projects’ cross-examination and evaluation and surface blindspots in the creative process.

Original language	English
Title of host publication	Proceedings of DRS2022 Bilbao
Subtitle of host publication	Design Research Society International Conference
Editors	Dan Lockton, Sara Lenzi, Paul Hekkert, Arlene Oak, Juan Sadaba, Peter Lloyd
Place of Publication	London
Publisher	Design Research Society
Number of pages	17
ISBN (Electronic)	9781912294572
DOIs	https://doi.org/10.21606/drs.2022.808
Publication status	Published - 25 Jun 2022
Event	DRS 2022 - Hybrid conference, Bilbao, Spain Duration: 25 Jun 2022 → 1 Jul 2022 https://www.drs2022.org/drs-2022/

Publication series

Name	DRS Biennial Conference Series
Publisher	Design Research Society
ISSN (Electronic)	2398-3132

Conference

Conference	DRS 2022
Country/Territory	Spain
City	Bilbao
Period	25/06/22 → 1/07/22
Other	Design Research Society International Conference
Internet address	https://www.drs2022.org/drs-2022/

Keywords

AI art
Artificial intelligence
Heuristics
Experiential AI

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.21606/drs.2022.808Licence: CC BY-NC

Zeilinger_TwardsAHeuristicModelForExperientialAI_Published_2022Final published version, 515 KBLicence: CC BY-NC

1 Article
1 Web publication/site

Responding to global challenges through data-driven art
Zeilinger, M., 27 Jun 2025, In: The New Real Magazine. 2, 1, p. 48-52 5 p.
Research output: Contribution to journal › Article › peer-review

Open Access
File
6 Downloads (Pure)
Responding to COVID-19 and the Climate Emergency through data-driven art
Zeilinger, M., 22 Mar 2022
Research output: Non-textual form › Web publication/site

Open Access

Cite this

Hemment, D., Zeilinger, M., Vidmar, M., Elwes, J., Warner, H., Pérez, D. S., & Hill, R. (2022). Towards a heuristic model for experiential AI: analysing the Zizi Show in the new real. In D. Lockton, S. Lenzi, P. Hekkert, A. Oak, J. Sadaba, & P. Lloyd (Eds.), Proceedings of DRS2022 Bilbao: Design Research Society International Conference (DRS Biennial Conference Series). Design Research Society. https://doi.org/10.21606/drs.2022.808

Hemment, Drew ; Zeilinger, Martin ; Vidmar, Matjaz et al. / Towards a heuristic model for experiential AI : analysing the Zizi Show in the new real. Proceedings of DRS2022 Bilbao: Design Research Society International Conference. editor / Dan Lockton ; Sara Lenzi ; Paul Hekkert ; Arlene Oak ; Juan Sadaba ; Peter Lloyd. London : Design Research Society, 2022. (DRS Biennial Conference Series).

@inproceedings{ca12749a88254a3fb1678059d01d00b8,

title = "Towards a heuristic model for experiential AI: analysing the Zizi Show in the new real",

abstract = "Based on the rapid pace of evolving creative practice in AI arts, we identify and respond to an urgent need to develop frameworks for analysing the critical dimensions (including social/political) of this emerging field. This paper offers a comprehensive case study of The Zizi Show, by Jake Elwes, developed as part of The New Real and Experiential AI programme at the Edinburgh Futures Institute within the University of Edinburgh. Based on this case study analysis, we propose the structuring of distinct project characteristics into four categories (socio-cultural and institutional aspects; technology and media; experience and affect; and audience and impact) which form the basis for a heuristic model. The statements/descriptors collected in each category serve to capture creative and design strategies that can lead design processes from cultural and technological perspectives, enable projects{\textquoteright} cross-examination and evaluation and surface blindspots in the creative process.",

author = "Drew Hemment and Martin Zeilinger and Matjaz Vidmar and Jake Elwes and Holly Warner and P{\'e}rez, \{David Sarmiento\} and Robin Hill",

note = "{\textcopyright} 2022 This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License Data availability statement: Not present.; DRS 2022 ; Conference date: 25-06-2022 Through 01-07-2022",

year = "2022",

month = jun,

day = "25",

doi = "10.21606/drs.2022.808",

language = "English",

series = "DRS Biennial Conference Series",

publisher = "Design Research Society",

editor = "Dan Lockton and Sara Lenzi and Paul Hekkert and Arlene Oak and Juan Sadaba and Peter Lloyd",

booktitle = "Proceedings of DRS2022 Bilbao",

url = "https://www.drs2022.org/drs-2022/",

}

Hemment, D, Zeilinger, M, Vidmar, M, Elwes, J, Warner, H, Pérez, DS & Hill, R 2022, Towards a heuristic model for experiential AI: analysing the Zizi Show in the new real. in D Lockton, S Lenzi, P Hekkert, A Oak, J Sadaba & P Lloyd (eds), Proceedings of DRS2022 Bilbao: Design Research Society International Conference. DRS Biennial Conference Series, Design Research Society, London, DRS 2022, Bilbao, Spain, 25/06/22. https://doi.org/10.21606/drs.2022.808

Towards a heuristic model for experiential AI: analysing the Zizi Show in the new real. / Hemment, Drew ; Zeilinger, Martin; Vidmar, Matjaz et al.
Proceedings of DRS2022 Bilbao: Design Research Society International Conference. ed. / Dan Lockton; Sara Lenzi; Paul Hekkert; Arlene Oak; Juan Sadaba; Peter Lloyd. London: Design Research Society, 2022. (DRS Biennial Conference Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Towards a heuristic model for experiential AI

T2 - DRS 2022

AU - Hemment, Drew

AU - Zeilinger, Martin

AU - Vidmar, Matjaz

AU - Elwes, Jake

AU - Warner, Holly

AU - Pérez, David Sarmiento

AU - Hill, Robin

PY - 2022/6/25

Y1 - 2022/6/25

N2 - Based on the rapid pace of evolving creative practice in AI arts, we identify and respond to an urgent need to develop frameworks for analysing the critical dimensions (including social/political) of this emerging field. This paper offers a comprehensive case study of The Zizi Show, by Jake Elwes, developed as part of The New Real and Experiential AI programme at the Edinburgh Futures Institute within the University of Edinburgh. Based on this case study analysis, we propose the structuring of distinct project characteristics into four categories (socio-cultural and institutional aspects; technology and media; experience and affect; and audience and impact) which form the basis for a heuristic model. The statements/descriptors collected in each category serve to capture creative and design strategies that can lead design processes from cultural and technological perspectives, enable projects’ cross-examination and evaluation and surface blindspots in the creative process.

AB - Based on the rapid pace of evolving creative practice in AI arts, we identify and respond to an urgent need to develop frameworks for analysing the critical dimensions (including social/political) of this emerging field. This paper offers a comprehensive case study of The Zizi Show, by Jake Elwes, developed as part of The New Real and Experiential AI programme at the Edinburgh Futures Institute within the University of Edinburgh. Based on this case study analysis, we propose the structuring of distinct project characteristics into four categories (socio-cultural and institutional aspects; technology and media; experience and affect; and audience and impact) which form the basis for a heuristic model. The statements/descriptors collected in each category serve to capture creative and design strategies that can lead design processes from cultural and technological perspectives, enable projects’ cross-examination and evaluation and surface blindspots in the creative process.

U2 - 10.21606/drs.2022.808

DO - 10.21606/drs.2022.808

M3 - Conference contribution

T3 - DRS Biennial Conference Series

BT - Proceedings of DRS2022 Bilbao

A2 - Lockton, Dan

A2 - Lenzi, Sara

A2 - Hekkert, Paul

A2 - Oak, Arlene

A2 - Sadaba, Juan

A2 - Lloyd, Peter

PB - Design Research Society

CY - London

Y2 - 25 June 2022 through 1 July 2022

ER -

Hemment D, Zeilinger M, Vidmar M, Elwes J, Warner H, Pérez DS et al. Towards a heuristic model for experiential AI: analysing the Zizi Show in the new real. In Lockton D, Lenzi S, Hekkert P, Oak A, Sadaba J, Lloyd P, editors, Proceedings of DRS2022 Bilbao: Design Research Society International Conference. London: Design Research Society. 2022. (DRS Biennial Conference Series). Epub 2022 Jun 16. doi: 10.21606/drs.2022.808

Towards a heuristic model for experiential AI: analysing the Zizi Show in the new real

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

Fingerprint

Research output

Responding to global challenges through data-driven art

Responding to COVID-19 and the Climate Emergency through data-driven art

Cite this