A potential boost from AI in ageing societies : early insights

(고령화 사회에서 AI가 가져올 잠재적 활력 : 초기 통찰)

목차

Title page 1

Contents 5

Abstract/Résumé 4

1. Introduction 7

2. How may AI affect different age groups? 12

2.1. Measuring exposure to AI 12

2.2. AI exposure by age groups and countries 18

3. AI may require ample labour reallocation, which ageing makes more difficult 23

3.1. AI is likely to increase needs for reskilling and upskilling 27

3.2. Age-related discrimination remains widespread 32

3.3. Entry-level jobs and the intergenerational transmission of knowledge 33

4. Business dynamism may be weaker in older societies 35

5. Concluding remarks and future work 36

References 38

Annex A. Additional figures and tables 44

Table 1. AI labour market impact, and opportunities and challenges for ageing societies 10

Table 2. A classification of AI exposure 15

Figure 1. The impact of ageing and AI potential vary widely across countries 9

Figure 2. AI can alleviate labour and skill shortages 11

Figure 3. PIAAC-based AI exposure correlates strongly with existing measures of AI exposure in the literature 16

Figure 4. AI exposure exhibits strong age profiles in the PIAAC data 20

Figure 5. The share of workers classified as exposed to AI differs across countries 21

Figure 6. Age and occupational composition only partly explain country-level differences in AI exposure 22

Figure 7. Labour mobility falls steeply with age 25

Figure 8. Older workers face high barriers to job mobility 26

Figure 9. Participation in training varies widely across countries and age groups 28

Figure 10. Older workers are less likely to use advanced ICT tools 29

Figure 11. Nearly half of trainings cover how to use digital equipment and knowledge at work 30

Figure 12. Participation in training is more prevalent in more strongly AI-exposed sectors 30

Figure 13. The productivity implications of workforce ageing differ across sectors and can depend on skill requirements 32

Figure 14. Perceived age-related discrimination varies widely across countries 33

Figure 15. The share of STEM graduates varies widely across countries 35

Boxes 6

Box 1. Construction of AI exposure index 15

Box 2. Automation versus augmentation: possible labour market Implications 17

Box 3. The productivity implications of workforce ageing differ across sectors and can depend on skill requirements 31

Box 4. Does AI adoption impact entry-level jobs? 34

Table A.1. Occupational classification of AI exposure 44

Table A.2. Exposure to AI is strongly associated with participation in training at the individual level 45

Figure A.1. The projected gains from AI and losses from population of ageing over the next decade vary widely across countries 46

Figure A.2. Conditional age profiles of AI exposure are more pronounced when accounting for differences across age groups in only... 47

Figure A.3. Age profiles of AI exposure differ by education but have similar shape 48

Figure A.4. Female workers are more exposed to AI than male workers 49

Figure A.5. Participation in training is only weakly associated with relative automation exposure at the sectoral level 50

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A potential boost from AI in ageing societies : early insights

(고령화 사회에서 AI가 가져올 잠재적 활력 : 초기 통찰)

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