## A PLACE FOR HUMAN TALENT IN THE AI AGE

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### Overview
- Artificial intelligence (AI) can both expand and shrink opportunities for human talent depending on availability and ethical, fair use.
- Policymakers must create conditions to allow AI to enhance human potential.

### Effects on labor markets and talent
- AI increasingly handles complex tasks, risking a shrinking role for human labor and reducing the relevance of previously prized talents (memorization, multilingualism, pattern recognition).
- AI can free people from routine duties and allow focus on more complex tasks, individualized education, and faster scientific discovery.

### Key statistics and empirical findings
- About 40 percent of global employment, across a wide range of occupations, could be affected by AI. (Estimate based on share of tasks AI can already perform, including translation, summarizing information, and coding.)
- Following the release of AlphaFold2, the number of predicted protein structures available to scientists surged from 200,000 to 200 million within months.
- A study in new materials found AI discovery tools boosted research output by 44 percent; but 82 percent of scientists in the same study reported less job satisfaction because of diminished creativity and neglect of their skills.
- Examples of AI impacts on occupations:
  - AI assists lawyers with legal research, textual analysis, and drafting documents, reducing reliance on paralegals.
  - AI-driven translation software has decreased demand for human translators in business.
  - AI systems in health care outperform humans at early cancer detection through image analysis and blood screening.

### Distributional effects and risks
- AI tools tend to improve output of less experienced and lower-performing workers, narrowing the performance gap with top-tier talent (Brynjolfsson, Li, and Raymond 2023).
- Levelling effects could devalue human talent as distinctions between exceptional and average performance recede.
- Overreliance on AI risks:
  - Reduced human creativity and originality (Dell’Acqua et al. 2023 found consultants using AI produced less original work—higher quality but greater sameness).
  - Appropriation of human-generated material without compensation, prompting lawsuits by content creators (examples cited: New York Times vs. OpenAI; Universal Music Group, Warner Music Group, Sony Music Entertainment vs. Suno and Udio).
  - Ethical and legal questions about training data use and “fair use” claims.

### Opportunities enabled by AI
- Education:
  - AI-powered platforms enable customized education, breaking geographic, resource, and systemic constraints.
  - AI-driven reading and math coaches help identify learning gaps and tailor instruction.
  - AI can address teacher shortages in developing economies and increase access to individualized learning.
- Workplace:
  - AI can handle repetitive tasks and administrative duties, allowing workers to focus on complex, creative, and human-centric responsibilities (e.g., more time for patient care in health care settings).
- Scientific discovery:
  - AI has accelerated breakthroughs (example: protein structure prediction recognized by the 2024 Nobel Prize in Chemistry).
- Talent identification:
  - AI helps scouts identify sports talent through data analysis, potentially reducing bias and expanding inclusion.
  - Creative tools (DALL-E, AIVA, Amper Music) democratize arts education and experimentation.

### Trade-offs and managerial considerations
- AI-driven productivity gains can concentrate among top researchers who use AI to automate idea generation and then evaluate AI suggestions.
- Many scientists report lower job satisfaction due to diminished creativity and underutilized skills.
- Ensuring ethical, fair, and compensatory uses of creator-generated data is necessary to avoid devaluing original work and stifling creativity.

### Policy implications and priorities
- Promote wide and fair access to AI tools to maximize benefits across populations.
- Establish legal and regulatory frameworks to address:
  - Copyright, ownership, and compensation for content creators whose work trains AI systems.
  - Definitions and limits of “fair use” for large-scale AI training.
- Support educational policies that integrate AI as a complement to human learning, particularly in developing economies with teacher shortages.
- Encourage responsible use of AI in workplaces to preserve human creativity and job satisfaction while boosting productivity.
- Use AI to identify and reduce biases in talent discovery and expand opportunities for underrepresented groups.

*Marina M. Tavares is a senior economist in the IMF’s Research Department.*

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_Source: https://www.imf.org/-/media/files/publications/fandd/article/2025/03/tavares.pdf_