Creation, curation, and classification: Mario Klingemann and Emily L. Spratt in conversation

Spratt, Emily L.

doi:10.1145/3186677

Cited by 8 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The art exhibition setting also provided opportunities for curatorial interventions that contributed to shape receptions of the objects exhibited; interventions that both art and development communities recognize as imperative for positive AI-generated art reception (Spratt, 2018: 41). Gangadharbatla (2021) has experimentally shown that the information provided to viewers about AI-generated pictures impacts on their perception.…”

Section: Identifying the Lovelace Effect: The Case Of Aicanmentioning

confidence: 99%

The Lovelace effect: Perceptions of creativity in machines

Natale

Henrickson

2022

New Media & Society

View full text Add to dashboard Cite

This article proposes the notion of the ‘Lovelace Effect’ as an analytical tool to identify situations in which the behaviour of computing systems is perceived by users as original and creative. It contrasts the Lovelace Effect with the more commonly known ‘Lovelace objection’, which claims that computers cannot originate or create anything, but only do what their programmers instruct them to do. By analysing the case study of AICAN – an AI art-generating system – we argue for the need for approaches in computational creativity to shift focus from what computers are able to do in ontological terms to the perceptions of human users who enter into interactions with them. The case study illuminates how the Lovelace effect can be facilitated through technical but also through representational means, such as the situations and cultural contexts in which users are invited to interact with the AI.

show abstract

Section: Identifying the Lovelace Effect: The Case Of Aicanmentioning

confidence: 99%

The Lovelace effect: Perceptions of creativity in machines

Natale

Henrickson

2022

New Media & Society

View full text Add to dashboard Cite

show abstract

“…The term "engineer" is again borrowed from Lévi-Strauss and does not imply that these artists are trained as engineers or that engineering precedes artistic objectives. Mario Klingemann, for example, is an exemplar for the engineer in AI art, though he does not have a formal training in software engineering [23]. Despite this, Klingemann's work is technically as well as aesthetically masterful.…”

Section: <1> the Engineersmentioning

confidence: 99%

Who (or What) Is an AI Artist?

Browne

2022

Leonardo

View full text Add to dashboard Cite

The mainstream contemporary art world is suddenly showing interest in “AI art”. While this has enlivened the practice, there remains significant disagreement over who or what actually deserves to be called an “AI artist”. This article examines several claimants to the term and grounds these in art history and theory. It addresses the controversial elevation of some artists over others and accounts for these choices, arguing that the art market alienates AI artists from their work. Finally, it proposes that AI art's interactions with art institutions have not promoted new creative possibilities but have instead reinforced conservative forms and aesthetics.

show abstract