Bibliographic record
Abstract
CYBERFEMINISM AND ARTIFICIAL LIFE Sarah Kember London and New York: Routledge, 2003; 257pp. In order to appreciate Sarah Kember's approach to identity and information and communication technologies or global information network, you need to appreciate concepts such as materialization within technoscience, technological discursivity, and posthumanism. This means that having read Karen Barad, Donna Haraway and Katherine Hayles respectively, you would be better able to appreciate what Kember attempts to do in advancing bioethics of posthumanism in context of artificial life or alife, not to be confused with artificial intelligence that Kember maps out for us as Alife's post Cold War precedent. To simplify, and perhaps oversimplify, Alife is to AI what postmodernism is to modernism. To develop her theoretical position, which is that of democrat in age of globalization, postmodern and somewhat reluctant cyberfeminist, and an ethically aware student of technoscience, Kember first engages with key principles from identity politics, including autonomy and artificiality, within discursive analysis of AI and Alife. Technoscience here refers to Haraway-like play between technology or artificiality and biology or what is traditionally structured as life. In particular, Kember examines cognitive psychology, biological meaning of life, and its increased alignment with communication and information technologies: the new biology. And finally, Kember engages with development of Alife, and computational modeling of living systems, in terms of autonomy, agency and vitalism. She grounds and further engages with all of these principles in case study based on in-depth interviews with Alife computer game designer, Steve Grand. Her conclusion, she says, synthesizes and explicates critical positions outlined in earlier chapters and [is] manifested, I hope, in degree of patience and at least willingness to risk deferring until sense of of field [has] been presented (pp. ix-x). The terms judgement and complexity are important. They refer to struggle both in feminist criticism and in so-called science wars over constitution and significance of materiality (particularity corporality for feminists) and way of truth (especially for traditional scientists). Kember engages with material, particularly alife (intentional lower case to distinguish her approach from formal one), hopefully and through dialogue, rather than, as she quotes from Haraway, in a kind of hands-on-your-hips negative critique (p. 52). In her earlier discursive critics of Alife and its various contexts, Kember claims that concept of technological autonomy is anthropomorphized and maintains too discreet distance from social, political and psychological. It is Kember's position that feminism can contaminate this position and thus realize potential for non-dualistic, non-anthropomorphic and non-social Darwinist alife that she unearths in Alife. She challenges feminists to veer away from simple counter positions to claims of artificial and autonomous intelligence in information technology and to risk entering dynamic dialogic relationship which. …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".