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GCRI · الذكاء الاصطناعي والنظم المستقلة

الآثار العمالية والاجتماعية

AI changes which tasks people do, how work is organised, which skills are valued and how information spreads. Effects differ by occupation, country, gender and age, and depend on how firms and governments choose to deploy it. This page sets out how AI affects work and society, how exposure and impacts are measured, and what evidence serves the labour ministries, employers, unions and educators involved.

01سجّل

Labour and social effects on the record.

02السؤال

Labour and social effects: how the risk develops.

Work, education, public trust and inclusion. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.

الآلية

Tasks change before jobs do

AI automates or assists specific tasks within occupations. Jobs are reorganised around remaining tasks before they disappear or new ones form.

الآلية

Exposure is uneven

Clerical and some professional tasks are highly exposed to generative AI, while manual and interpersonal work is less exposed. Women are over-represented in some highly exposed clerical jobs.

الآلية

Skills and training lag

Workers need new skills to use AI well, and those displaced need retraining. Training النظم often respond more slowly than technology adoption.

الآلية

Information ecosystems shift

Generated content, recommendation systems and synthetic media change how people find and judge information, with effects on trust and public debate.

03الأساليب والأدلة

How labour and social effects is modelled, measured and tested.

النموذج وافتراضاته وبياناته وعدم اليقين فيه، بالصورة التي يفحصها بها عالم أو مهندس. وتتبع البنى أساليب منشورة. والقيم المرسومة توضيحية، وليست نتائج.

نموذج النظام

The couplings between the systems in labour and social effects: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.

++−+الذكاء الاصطناعيالبياناتالمجتمعاتالاقتصاد⁨R⁩ معزِّزة⁨B⁩ موازِنة
Causal loop diagram from the page’s systems; signs show the direction of influence. Illustrative structure for a system dynamics or network model, not estimated couplings.
مبادئ FAIR التوجيهية · GO FAIR وFORCE11⁨W3C PROV⁩ · اتحاد الشبكة العالميةإرشادات بشأن المعالجة المتسقة لأوجه عدم اليقين · الهيئة الحكومية الدولية المعنية بتغير المناخبيانات CEOS الجاهزة للتحليل · لجنة سواتل رصد الأرض
04عبر المجالات

AI’s effects on work vary across domains.

05المؤشرات الفرعية

ما الذي يُقاس، ومدى جودة قياسه.

يحمل كل مؤشر وحدته ووتيرته ونوع المصدر الذي يستند إليه ووسم الأدلة الذي ستحمله القيمة. ولا تُعرض أي قيم: فالبرنامج يقدّمها بموجب سلطته الخاصة.

المؤشرالوحدةوتيرة الإصدارنوع المصدرالوسم
Employment in occupations highly exposed to AIpercent of employmentلكل تقييمExposure studies using occupational dataمُقدَّر
Firms using AIpercent of firmsسنويBusiness surveysمُبلَّغ عنه
Workers using AI tools at workpercent of workersper surveyLabour force and worker surveysمُبلَّغ عنه
AI-related job postingsshare of postingsشهريOnline job posting dataمرصود
Participation in AI skills trainingpercent of workforceسنويTraining surveysمُبلَّغ عنه
Wage changes in exposed occupationspercent changeسنويWage statisticsالإحصاءات المنشورة
06المصادر

من أين تأتي الأدلة.

مجموعات بيانات عامة مسمّاة وسجلات مؤسسية، لكلٍّ منها فئة ترخيصها. ولا تُستخدم المصادر المتاحة بموجب اتفاق إلا وفق شروطها، ولا يُعاد نشرها أبدًا.

المصدرما يقدّمهفئة الترخيص
ILO studies on generative AI exposure of occupationsOccupational exposure estimates by country and genderPublic, ILO terms
OECD Employment Outlook and AI in work studiesEvidence on AI adoption and labour effectsPublic, OECD terms
Eurostat ICT usage in enterprises surveyShare of enterprises using AIOpen, Eurostat reuse policy
Online job posting data such as Lightcast summariesDemand for AI skillsCommercial; public summaries (to check)
Stanford AI IndexCompiled indicators on AI adoption, investment and labourPublic, licence to check
07القرارات

من يقرر، وما الذي تخدمه الأدلة.

استوديو الذكاء الاصطناعي و النظم prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

من يقررالسؤالالأدلة التي تخدمها هذه الصفحة
Labour ministriesWhich workers and sectors need transition supportExposure analyses; adoption tracking
Employers and unionsHow to introduce AI at work and share its gainsAdoption and wage evidence
التعليم and training bodiesWhich skills to teach and to whomSkills demand evidence

المخرجات التي يُنتجها هذا الموضوع

  • Occupational exposure analyses by sector, gender and region
  • Adoption tracking from business and worker surveys
  • Evaluation designs for AI training programmes
  • Evidence notes for social dialogue on AI at work
08الأسئلة الجوهرية

What researchers ask about social effects.

  • Which tasks can current AI perform well, and how does that map onto occupations?
  • Does AI substitute for workers, complement them or change what their jobs consist of?
  • How does AI change learning and assessment in education?
  • How do errors, opacity and misuse affect trust, and who is excluded?
09الآليات

Tasks, not jobs.

Jobs are bundles of tasks. AI tends to automate or assist specific tasks, such as drafting, summarising, coding or classifying images, which changes the content of jobs rather than simply removing them. Whether that raises productivity and wages or displaces workers depends on how organisations redesign work and how gains are shared.

In education, AI can personalise support but also undermine assessment and the learning that comes from effort. Trust depends on experience: visible errors, unexplained decisions and synthetic content erode it, while accountable use can build it. People with limited digital access, skills or language support risk exclusion.

10المناهج والبيانات

Evidence on social effects.

  1. 01

    Task exposure analysis

    Mapping AI capabilities onto occupational task data. Exposure is not the same as displacement.

  2. 02

    Field and natural experiments

    Studying workplaces and classrooms that adopt AI, using العلوم الاجتماعية والسلوكية. Early studies may not generalise.

  3. 03

    Surveys of trust and use

    Measuring how people use and perceive AI. Attitudes change quickly and vary by context.

  4. 04

    تقييم القدرات

    Linking what النظم can actually do, from هندسة تقييم الذكاء الاصطناعي وضمانه, to claims about social effects.

12Where this page’s references

Where this page’s references lead.

الهيئات والوثائق التي تُقرأ هذه الصفحة في ضوئها. وتتغير الحالات والإصدارات؛ ويقود كل رابط إلى الهيئة المُصدِرة.

13أسئلة

أسئلة وأجوبة.

Will AI take jobs?
Evidence so far suggests AI changes tasks within jobs more often than it eliminates whole jobs, but effects differ by occupation and depend on how it is deployed. Long-term effects are uncertain.
What is occupational exposure to AI?
A measure of how many of an occupation’s tasks AI could perform or assist, based on task descriptions, which indicates potential, not realised, change.
Who is most exposed to generative AI?
Studies by the ILO and others find clerical and some professional occupations most exposed, with women over-represented in highly exposed clerical work.
Will AI cause mass unemployment?
The evidence does not support confident predictions either way. Effects depend on adoption, work redesign, policy and how gains are shared, and they differ by occupation and place.
Which workers are most exposed?
Exposure analyses suggest many office and knowledge tasks are exposed to current AI, unlike earlier automation that mainly affected routine manual work. Exposure does not mean those jobs disappear.
How does this topic relate to Future of Work and Skills?
This topic connects AI capabilities to social effects; Future of Work and Skills studies labour markets, skills and institutions in depth. The two share evidence.
Does the platform advise employers?
No. It publishes research that employers, unions and public bodies can use.
التقاريرساهم

ساهم بأدلة من هذه الصفحة.

التقارير is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

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