OECD Employment Outlook 2023 Artificial Intelligence and the Labour Market
The 2023 edition of the OECD Employment Outlook examines the latest labour market developments in OECD countries. It focuses, in particular, on the evolution of labour demand and widespread shortages, as well as on wage developments in times of high inflation and related policies. It also takes stoc...
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
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Paris :
OECD Publishing
2023.
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| Edición: | 1st ed |
| Colección: | OECD Employment Outlook Series
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| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009759332306719 |
Tabla de Contenidos:
- Intro
- Foreword
- Editorial: Beyond the hype on AI - early signs of divides in the labour market
- Employees say AI can improve work, but fear it will threaten jobs and wages
- An urgent need to act
- Executive summary
- Labour markets remain tight despite some signs of easing
- Real wages are falling in almost all OECD countries amid a cost of living crisis
- With little sign of a price-wage spiral, minimum wages and collective bargaining can help cushion losses in purchasing power
- AI is likely to have a significant impact on the labour market
- So far, job quality has been impacted more than job quantity
- Policies and social dialogue will play a key role
- Key facts and figures (infographic)
- 1 Under pressure: Labour market and wage developments in OECD countries
- Introduction
- 1.1. As economic growth lost momentum in 2022, labour market indicators across the OECD stabilised
- 1.1.1. Inactivity rates have generally declined but average hours worked are slightly below pre-crisis levels in several countries
- 1.1.2. Labour markets remain tight even as there are signs that pressure is easing
- In some countries, quits increased as workers reaped the benefits of tight labour markets
- Amid tight labour markets, online job postings have offered benefits more frequently while temporary contracts and involuntary part-time have decreased among new hires
- 1.1.3. Economic growth in the OECD is expected to remain subdued in 2023 and 2024, with moderate employment growth and a small increase in unemployment
- 1.2. Inflation reached levels not seen in decades, causing real wages to fall across the OECD
- 1.2.1. Low-income households often face higher effective inflation rates and have less leeway to absorb increases in the cost of living.
- 1.2.2. Despite a pickup in nominal wage growth, real wages are falling in all OECD countries
- Real wages are falling across industries, but they are faring relatively better in low-pay industries in many countries
- Tight labour markets have contributed to stronger nominal wage growth
- The developments of wages by industry suggest a compression of wages across pay levels, but more granular data are needed to assess the impact of the real wage crisis on inequality
- 1.2.3. In many OECD countries, profits have grown faster than wages, making an unusually large contribution to price pressures and reducing the labour share
- Data from Europe and Australia show that in the last year unit profits increased more than unit labour costs in several sectors beyond the energy one
- With no indication of a price-wage spiral in recent data, there is room to adjust wages at least for the most vulnerable
- 1.3. Wage setting in a high inflation environment
- 1.3.1. Minimum wages have kept pace with inflation
- 1.3.2. Negotiated wages: falling in real terms even in countries with high collective bargaining coverage
- Collective bargaining: A tool to ensure fair and tailored responses to inflation cost
- Negotiated wages are reacting with longer delay
- Recent bargaining rounds suggests that, after a catch-up phase, negotiated wage growth should go back to previous trends
- 1.4. Concluding remarks
- References
- Annex 1.A. Additional results
- Annex 1.B. Identifying employee benefits in online job postings
- Annex 1.C. Latest developments on minimum wages and negotiated wages
- Notes
- 2 Artificial intelligence and the labour market: Introduction
- We need to talk about the future of work (again…)
- For better or for worse, AI is already making its way into the workplace
- The time to act is now
- References
- Notes.
- 3 Artificial intelligence and jobs: No signs of slowing labour demand (yet)
- Introduction
- 3.1. Artificial intelligence expands the set of jobs at risk of automation
- 3.1.1. Artificial intelligence will automate certain tasks, but the net impact on employment is ambiguous
- 3.1.2. AI has made the most progress performing non-routine, cognitive tasks
- 3.1.3. High-skilled, white-collar occupations have been most exposed to recent progress in AI
- 3.2. It is too early to detect meaningful employment changes due to artificial intelligence
- 3.2.1. In the aggregate, negative employment effects due to artificial intelligence are (so far) hard to find
- 3.2.2. High-skilled workers have seen employment gains
- 3.2.3. Why is the employment effect of AI small (so far…)?
- Currently, AI adoption is low and the cost savings to firms are modest
- Firms rely on worker attrition rather than layoffs to adjust labour demand
- AI may be leading to greater efficiencies in labour market matching
- Advances in artificial intelligence only account for a small part of automation
- The creation of new tasks and jobs is not well captured by studies focusing only on exposure
- 3.3. Policy can promote AI use that complements human labour and broadly shared productivity gains
- References
- Notes
- 4 Artificial intelligence, job quality and inclusiveness
- Introduction
- 4.1. Workers with AI skills earn significant wage premiums, but it is too soon to see AI's effects on labour productivity
- 4.1.1. Some workers with the right skills have seen wage gains after AI adoption
- Workers with AI skills earn significant wage premiums
- Workers exposed to AI have seen stable or increasing wages, but more research is needed
- 4.1.2. Larger, more productive firms tend to adopt AI, but its effects on labour productivity are so far inconclusive.
- Larger, more productive firms are more likely to adopt AI
- AI appears to be producing modest productivity increases, but the evidence is far from conclusive
- 4.2. Using AI is associated with higher job satisfaction and occupational safety, but there are some risks
- 4.2.1. So far, AI use appears to be associated with greater job satisfaction
- AI is more likely to automate tedious, repetitive tasks
- AI broadens and deepens the task content of jobs and gives workers greater autonomy in their work
- AI can change the social environment of the workplace
- 4.2.2. AI is associated with improved mental health and physical safety but also greater work intensity
- AI generally leads to improved mental health and physical safety
- AI may also lead to a higher pace and intensity of work
- 4.3. AI-led reorganisation or automation of managers' tasks has downstream effects on their subordinates
- 4.3.1. Algorithmic management raises risks for increased work intensity
- 4.3.2. Algorithmic management affects subordinates' space for autonomy
- 4.3.3. Algorithmic management raises risks for workers' privacy
- 4.4. The impact of AI on inclusiveness and bias in the labour market
- 4.4.1. AI can improve inclusiveness for some disadvantaged groups but not for others
- 4.4.2. If not designed and implemented well, AI may systematise existing human biases
- 4.5. Concluding remarks
- References
- Notes
- 5 Skill needs and policies in the age of artificial intelligence
- Introduction
- 5.1. The development and adoption of AI will have an impact on skill needs
- 5.1.1. AI has made important progress replicating cognitive and manual skills
- 5.1.2. AI increases the demand for both skills required to develop AI systems and skills to use AI applications
- Skills to develop and maintain AI systems
- Skills to use and interact with AI applications.
- 5.2. Changes in skill needs call for new training opportunities
- 5.2.1. AI development and adoption call for specialised education pathways as well as specific AI literacy courses
- Training to develop and maintain AI systems
- Training to use and interact with AI applications
- 5.2.2. Specific groups of workers deserve special attention
- 5.3. Firms implementing AI say they provide training to their employees, but more training may be necessary
- 5.3.1. Firms provide training following AI adoption
- 5.3.2. Yet, more training would help address existing barriers to AI adoption
- A lack of skills is a major barrier to AI adoption
- Data and cultural acceptance constitute other important adoption barriers that can be addressed through training
- 5.4. Existing public policies supporting training for AI are not sufficient
- 5.4.1. Public policies could encourage the provision of more training for AI
- 5.4.2. Few policies propose sufficient actions to develop skills for AI
- 5.5. AI has the potential to improve adult learning systems but risks exist
- 5.5.1. AI could be used to help plan training
- 5.5.2. AI could be used to deliver and personalise training
- 5.5.3. AI may impact training participation and inclusiveness
- 5.6. Despite a growing body of research on AI and its impact on skills and learning systems, important knowledge gaps persist
- References
- Notes
- 6 Ensuring trustworthy artificial intelligence in the workplace: Countries' policy action
- Introduction
- 6.1. Soft law for trustworthy AI in the workplace
- 6.2. Legislation for trustworthy AI in the workplace
- 6.2.1. Legislation to protect workers' fundamental rights
- Capacity for human determination and human interaction
- Breaches of privacy
- Bias and discrimination
- Freedom of association and the right to collective bargaining.
- Occupational safety and health.
