Book Review | The Smart Wife: Why Siri, Alexa, and Other Smart Home Devices Need a Feminist Reboot, by Yolande Strengers and Jenny Kennedy (MIT Press, 2020)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Consumer AI is hella sexist-it's about time someone called it out.That's what Yolande Strengers and Jenny Kennedy's book The Smart Wife does, from Alexa being modeled on the 1950s housewife to sex robots designed to frame sex in unconsensual ways.The argument builds around the titular theory of the "smart wife."These devices, according to the authors, are actually designed to act as surrogate wives and to take on the domestic labor traditionally coded as wife work.With this design comes all the sexism embedded in the role of wife-asdomestic-servant, thereby remediating 1950s sexism for the digital age.Building on similar critiques such as Safiya Noble's Algorithms of Oppression (2018) and Jennifer Rhee's The Robotic Imaginary (2018), the authors' aim is "to develop smart wives that promote gender equity and diversity" (209).This feminist reading is an important step in the analysis of consumer AI, and the examples are insightful, thoroughly researched, and related with hilarious irony.Following the first introductory chapter, the next four chapters each take on a specific digital assistant as a case study to analyze domestic labor, robot gender, resource extraction, and sex, respectively.Chapter six turns towards humans to examine sexist behavior directed at feminized AI; while chapter seven continues this human focus to examine men and technology, particularly in terms of domestic abuse and surveillance.All these chapters are filled with a wealth of surprising examples, delivered in a humorous and compelling style.This impressive research makes the book worth reading, for anyone interested in critical analysis of AI.
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.
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 | 0.003 | 0.000 |
| 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 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it