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Record W4393999588 · doi:10.1162/leon_r_02531

Boundary Images

2024· article· en· W4393999588 on OpenAlexaboutno aff
Jan Baetens

Bibliographic record

VenueLeonardo · 2024
Typearticle
Languageen
FieldNeuroscience
TopicAesthetic Perception and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsIconCitationTable of contentsDownloadSearch engine optimizationComputer scienceBoundary (topology)Information retrievalWorld Wide WebSearch engineMathematics

Abstract

fetched live from OpenAlex

For modern visual analysis, images are no longer pure images, they have become agents. Their actions and mechanisms no longer represent something, as traditionally studied in the field of semiotics, history, or art history, but actually do something: they produce various types of relationships and thus meanings in and outside the merely visual space. More concretely, they morph into “boundary images,” a concept that pays tribute to the work on WJT Mitchell and his interest in what pictures “want.” The boundary image can also refer to the broader definition of Susan Leigh Star and James R. Griesemer, for whom it is “an entity that links networks, elastic enough to be adapted to a new context and robust enough to keep its main characteristics” (p. 2). Boundary images are a subcategory of such boundary objects and are themselves capable of accepting new subcategories like “ontological boundary images,” which transgress the usual frontiers between the ontological domains of reality and fiction.As the four authors of this book state in their joint theoretical introduction and reflection on the meaning of “boundary,” such an object is “the exact opposite of ‘an end’ or marker of strict impermeability. Rather, a boundary object is a thing, entity, or any other type of object that can be shared or used differently by varying groups, with each holding its own interpretation, understanding or normative practices with that object” (p. 7). The concept of boundary is thus closer to the idea of contact than frontier, although the examples in this book will show that there are also strong limitations to this definition, at least in practice.Boundary images are a cutting-edge dimension of contemporary visual culture analysis. Not only do they help deconstruct conventional dichotomies (literal versus symbolic, rational versus affective, past versus future, single versus plural, subjective versus objective—the list is almost endless) but also foster a reading of images that tackles the dynamic and productive aspects of their social reading. In that sense, the analysis of boundary is political, or unavoidably becomes so. Boundary images aim to challenge the status quo while showing that their effect and impact are far from being as progressive and empowering as they may or should be.The three essays that follow, written by closely collaborating researchers with very different backgrounds (visual arts, curation, urban studies, anthropology) but a common interest in digital culture, live up to the high expectations raised by the general introduction of the book. They all do it convincingly while at the same time—perhaps unwillingly—highlighting a fundamental problem that I will return to in a concluding remark.The first essay by Winnie Soon and Magdalena Tyżlik-Carver is both a case study and a far-reaching exploration of how images are either made visible or withdrawn from the visible public domain (in this case, the internet). Taking as its starting point a cartographic metaphor (meaning that the image is not seen as the direct visual reproduction of a visual object but as the machine translation of a set of encoded data), the essay documents the ways in which an image of the “Lego Tank Man” (a Lego reconstruction of the famous solitary 1989 Tiananmen Square demonstrator, a world-famous icon of political resistance that remains heavily censored in China) appears on screen. For almost an entire year, artist Winnie Soon submitted the same Google search query every day, took a screenshot of the image’s presence on (or absence from) the display, and whitened out all other results of the query that appeared on the same screen. The shifting results of this operation show the underlying presence of mechanisms that disclose direct and indirect censorship. In the case of Chinese censorship, the mechanism is blatant (thanks to the Lego’s materiality, the image could nonetheless penetrate the digital sphere in China for a couple of hours before being blocked). In the case of the logarithms outside China that influence and determine how encoded data are translated into images on a screen, the mechanism is less visible but no less effective.Thus, the essay draws attention to the manifold biases and manipulations that intervene in the visibility of images at the level of data encoding. The key problem is the fact that all the verbal and visual criteria used to describe the images before they become visible on screen involve a kind of statistical average that is far from being a natural given, although the AI mechanisms and procedures in this domain are among the best kept secrets of the industry (the notion of “face recognition” for instance is based on models that rely on Western ideas of “normal” faces). The curation of “Lego Tank Man” expands on this message, emphasizing the role of machine and technology interfaces in the process of making something visible or invisible. Both the artwork and its curated version are very efficient in showing the concrete results of these mechanisms. They destroy the illusion that what we see, even if it is what we get, is not what there is to be seen in the real world.The second and third essays equally expand on the basic insights of the joint introductory essay with its strong focus on ideology critique of technology, but they move from the artistic environment to direct the discussion towards political analysis and action. Melody Devries offers an anthropological study on the use of ontological boundary images in U.S. and Canadian far-right propaganda, often giving them a strong evangelical twist, and its attempt to produce belief in nonrational ideas and behaviors. The essay also makes more general claims on belief systems, which are not defined as one-time decisions to accept this or that set of values but as the result of a repeated—if not permanent—exposure to certain objects, images, messages, and behaviors (in this sense, screen addiction is directly shown as leading to kinds of conspiracy theories, apocalyptic thinking, and more generally “crazy” belief systems). The power of this exposure is taken very seriously by the researcher, who observes and acknowledges the limits of her own rational thinking in certain circumstances. The final essay by Giselle Beiguelman, artist and professor of architecture, urbanism, and design in São Paolo, establishes a thought-provoking analysis of the standardizing aspects of AI and related technologies, which are all reframed in light of the history of eugenics. Very briefly and schematically, the end of the essay also makes room for non-Western approaches to visual analysis, image collection, and image presentation and use.This last point hints at the major question that this book does not address. On the one hand, boundary image theory and analysis are introduced in the opening essay as a world of new opportunities (agency, empowerment, political action, inclusion, democracy, etc.). However, this stimulating horizon is systematically contradicted by each of the three case studies, which all heavily insist on the dangers and evils of technology and AI (the notion of boundary thus moves back from contact to frontier). Granted, art and critical theory are shown here to possess some degree of counterhegemonic power, but this power seems fragile—and perhaps even somewhat elitist—in comparison with the bulldozer effects of modern technological mainstream culture, both Western and non-Western (China, Russia, Iran, and the like know perfectly well how to use AI for their own needs). At the end of this exciting publication, the gap between the optimism of the introduction and the pessimism of the case studies leaves a strange taste in the mind.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.951
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.294
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
Admission routes1
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