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Enregistrement W4379743538 · doi:10.1353/iur.2018.a838290

The Future of Work is Ours

2018· article· en· W4379743538 sur OpenAlexaboutno aff
Marc Hollin

Notice bibliographique

RevueInternational Union Rights · 2018
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueDigital Economy and Work Transformation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWork (physics)Technological changeConversationFutures contractPosition (finance)Public relationsNothingFeelingPower (physics)Private sectorPolitical scienceBusinessSociologyEngineeringEconomicsLawPsychologySocial psychology

Résumé

récupéré en direct d'OpenAlex

Unifor recently held a one-day conference on Automation, New Technology and the Future of Work. As part of this event, the union released a discussion paper called The Future of Work is Ours: Confronting risks and seizing opportunities of technological change. With 315,000 members across the country in almost every sector of the economy, Unifor is Canada’s largest private-sector union. The union’s response to technological change is very much a work in progress, and the conference and discussion paper serve as a starting point in this process. The fundamental question at hand: how do we develop a worker-led program allowing us to get the best of technological change while avoiding the worst? We know that working people in Canada and around the world have been experiencing the negative impacts of technological change, and are feeling threatened and afraid for their own futures. At the same time, we have seen incredible opportunities for new and better jobs, union growth, and advancements in workplace health and safety due to technological change. Our responsibility as workers and as a union is to take control of this conversation and move from a position of fear and defence to a position of power and action. Making the transition means first understanding the problem, and a portion of our discussion paper and day-long conference focused on deepening our understanding of exactly what we’re talking about when we discuss technological change at work. Of course, our members know that technological change is nothing new. We have always experienced the effects of technological change, from the invention of the printing press, to the Industrial Revolution, to the invention of the modern computer. But what is new is the speed of that change. In just a generation, we’ve seen the invention of the internet and artificial intelligence, so-called ‘big data’ and the advent of mass surveillance, and the widespread use of advanced robotics and other automation. A flurry of negative headlines have made wild claims about the coming ‘robot apocalypse’, where millions of jobs would be replaced by automation. However, more recently we have seen a more nuanced analysis emerge. This revised analysis focuses on the difference between a task and a job. A task is a discrete segment of work done as part of a worker’s duties of employment, while a job is a bundle of tasks assigned to a worker who performs those tasks and exchanges their labour for pay. A recent report from McKinsey Global Institute estimates that fewer than 5 percent of existing occupations are candidates for full automation. Frequently, rather than completely eliminating jobs, automation and artificial intelligence will replace some tasks, requiring workers to adjust their level of skills and knowledge used in the workplace. In terms of the Canadian context, four separate think tanks estimated the share of tasks susceptible to automation in Canada as ranging between 35 percent and 47 percent. This is across all sectors of our economy. Understanding the Impacts Part of the challenge we identified was how to create an analysis that allows our members to engage in a meaningful way. We created a framework that identifies six general areas of impact – both positive and negative – to make this issue more digestible. The first, and probably most obvious, impact is job loss or displacement, and job estrangement. Job loss or displacement is what most of us think of when we consider tech change at work – ‘I was fired from work and replaced by a robot’. But as we’ve seen, the situation is more complex, and often less dire, than that. Less obvious is what we’ve called job estrangement, where a worker’s role in her workplace changes due to technological change, leaving her feeling alienated from her work, where her skill and knowledge are no longer valued. The second major category of impact is changes in work organisation and required skills. These are impacts that many of us have experienced already. We’ve probably all heard about, and perhaps even participated in ‘up-skilling’, when workers displaced by technological change upgrade their skills to fill new roles that complement and support new technologies. But the...

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,019
score de la tête « metaresearch » (Gemma)0,031
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,062
Score d'incertitude au seuil0,207

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0190,031
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,002
Études des sciences et des technologies0,0250,027
Communication savante0,0420,034
Science ouverte0,0030,020
Intégrité de la recherche0,0100,013
Charge utile insuffisante (le modèle a refusé de juger)0,0620,027

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 Opus0,008
Tête enseignante GPT0,265
Écart entre enseignants0,257 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

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

En bref

Citations1
Publié2018
Routes d'admission1
Résumé présentoui

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