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Enregistrement 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 sur OpenAlexaboutno aff
Ehsan Jozaghi

Notice bibliographique

RevueJournal of Health Care for the Poor and Underserved · 2024
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueHealth, Environment, Cognitive Aging
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDignityBasic incomePovertyEconomic growthPolitical scienceDevelopment economicsEconomicsLaw

Résumé

récupéré en direct d'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...

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,765
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,076
Tête enseignante GPT0,379
Écart entre enseignants0,303 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeAutre devis
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations6
Publié2024
Routes d'admission1
Résumé présentoui

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