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Record W4399164302 · doi:10.1353/hpu.2024.a928623

The Initial Stage of the Artificial Intelligence Revolution: Access to Basic Income is a Human Rights Issue

2024· article· en· W4399164302 on OpenAlex
Ehsan Jozaghi

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Health Care for the Poor and Underserved · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsnot available
Fundersnot available
KeywordsDignityBasic incomePovertyEconomic growthPolitical scienceDevelopment economicsEconomicsLaw

Abstract

fetched live from OpenAlex

The Initial Stage of the Artificial Intelligence Revolution:Access to Basic Income is a Human Rights Issue Ehsan Jozaghi To the Editor, Background In addition to Ontario and Manitoba, universal basic income pilot programs have been run in Africa, Asia, Europe, and South America.1 The programs have been a resounding success, giving participants dignity and improving their health.2 For example, there has been a decreased use of alcohol and tobacco and improved sleep and mental health among recipients.1 At the same time, family members reported improvements in their children's school performance, health, nutrition, stability, and social networks.1,3 Unfortunately, despite such successes, the pilot programs have not materialized into permanent national initiatives.4 This is particularly important in the era where many nations face a growing housing shortage, poverty, and inequality. In addition to the increasing inequality of income and housing shortage, there has also been a shift from traditional economic approaches to increasingly knowledge-based economies in which access to affordable post-secondary education, vocations/trades, life-long learning, and online modes of learning play a crucial factor in securing higher wages.5 Artificial intelligence revolution The shift to a knowledge-based economy has been linked to the initial stage of the artificial intelligence revolution, which is changing society, economy, culture, science, and medicine much more quickly than the first or second industrial revolutions.6 While previous work has attributed the rapid nature of change during industrial revolutions to many positive developments (e.g., new medicine and scientific discoveries), there have also been some inadvertently adverse effects.6 Similarly, the initial stage of the AI revolution has helped in numerous positive ways, such as developing new innovative methods to quickly develop a vaccine during the Covid-19 pandemic, which saved millions of lives and contributed trillions of dollars to the global economy by enabling faster economic recovery.7 Lamentably, the growing AI advancement and technologies have begun an irreversible reality that AI will replace countless human tasks/jobs.6 Therefore, it is expected that without universal basic income support, millions of people will become homeless and suffer severe health outcomes due to AI's advancements. Conclusion As AI's evolutionary process enters its early stage, rapid change is expected to shock the economy, society, health, and social safety net without appropriate [End Page xv] government interventions.6 Universal basic income support is an innovative solution to tackle this inevitable reality while allowing citizens to upgrade their educational qualifications via government subsidies and social programs. Therefore, universal basic income will become a human rights issue in the AI era when AI takes over many tasks that were previously performed by millions of citizens. Governmental economic policies and inaction will continue to affect the social determinants of health directly. How governments decide to implement basic income support can influence health and stability across the country for future generations. Please address all correspondence to: Ehsan Jozaghi, Faculty of Dentistry, University of British Columbia, 2206 East Mall, Vancouver, BC Canada V6T 1Z3. Reference 1. Basic Income Earth Network. Countries that have tried universal basic income. Toronto, ON: Basic Income Earth Network, 2024. Available at https://basicincomecanada.org/countries-that-have-tried-universal-basic-income/. Google Scholar 2. McDowell T, Ferdosi M. The experiences of social assistance recipients on the Ontario basic income pilot. Can Rev Sociol. 2020 Nov;57(4):681–707. Epub 2020 Nov 5. https://doi.org/10.1111/cars.12306 PMid:33151642 Google Scholar 3. Hamilton L, Mulvale JP. "Human again": The (unrealized) promise of basic income in Ontario. J Poverty. 2019;23(7):576–99. https://doi.org/10.1080/10875549.2019.1616242 Google Scholar 4. Law S. As Ontario faces a certified class action, former recipients of basic income pilot share their struggles. Toronto, ON: CBC News, 2024. Available at https://www.cbc.ca/news/canada/thunder-bay/ontario-basic-income-pilot-class-action-1.7149814. 5. Jozaghi E. A new innovative method to measure the demographic representation of scientists via Google Scholar. Method Innov. 2019 Sept-Dec;12(3):2059799119884273. https://doi.org/10.1177/2059799119884273 Google Scholar 6. Jozaghi E, Jozaghi P. A new innovative method for evaluating monarchies (crowns): A...

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.765
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.076
GPT teacher head0.379
Teacher spread0.303 · 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