Recent advances in artificial intelligence (AI) have renewed interest from policy makers and the public about the implications of AI for jobs and workers.
AI technology is at an inflection point: a surge of technological progress has driven the rapid development and adoption of generative AI systems, such as ChatGPT, which are capable of generating text, images, or other content based on user requests.
This technical progress is likely to continue in coming years, with the potential to complement or replace human labor in certain tasks and reshape job markets. However, it is difficult to predict exactly which new AI capabilities might emerge, and when these advances might occur.
This National Academies’ report evaluates recent advances in AI technology and their implications for economic productivity, job stability, and income inequality, identifying research opportunities and data needs to equip workers and policymakers to flexibly respond to AI developments.
KEY TAKEAWAYS
It is impossible to predict exactly the nature of the coming changes in AI and all their effects on the economy and society.
Collecting and disseminating information on AI technology and its adoption, demand for expertise, and impacts on the workforce can help to empower workers and decision makers. This could be achieved by building capabilities for:
- Rapid data gathering and analysis to track these changes
- A flexible approach for reacting to the changes observed
Most relevant for workers is how AI will reshape the demand for expertise, and in that way change the nature of various jobs. It is difficult to anticipate what types of expertise will be augmented by AI, and what new forms of expertise will be demanded.
Access to continuing education will be key to enabling the workforce to adapt. AI may play a role in providing new online learning environments.
Responding to Advances in AI
AI is a tool with the potential to enhance human labor, complement human expertise, and create new forms of valuable work—but this is not an inevitable outcome. Policy makers, business leaders, AI researchers, employers, and workers all have an opportunity to intentionally design AI systems in accordance with society’s shared values and goals. This beneficial deployment of AI would augment collective capabilities, enhance human well-being, and support a workforce that is equipped to meet future challenges.
To reach this goal, it is imperative to improve near real-time observation and tracking of progress in AI and its impacts on the workforce, and to widely share this information to better inform and equip workers and policymakers to flexibly respond to AI developments. This will mean collecting and transparently disseminating information on changes in AI, its adoption, and demand for different types of expertise.
AI and the Labor Market
Substantial and ongoing improvements in AI’s capabilities, along with its broad applicability to a large fraction of the cognitive tasks in the economy and its ability to spur complementary innovations, offer the promise of significant improvements to productivity and implications for workforce dynamics.
Advances in AI Technology
Innovations in neural networks and a shift to larger, unannotated data sets have driven a surge of technical progress in AI, in particular the emergence of generative AI with the ability to hold meaningful conversations in dozens of languages, summarize key points in large text documents, and write computer programs.
At the same time, steady progress has continued in other subareas of AI such as robotics, with self-driving cars now being tested in many US cities, and the application of machine learning to large data sets. Despite these advances, there is a great deal of uncertainty about the future course of AI. Further, AI systems today remain imperfect in multiple ways. For example, large language models (LLMs) can “hallucinate” incorrect answers to questions, exhibit biased behavior, and fail to reason correctly.
AI and Productivity
Generative AI has already been found to increase productivity in specific applications including contact centers, software development, and writing, and its potential to accelerate scientific discovery innovation could further compound productivity gains.
However, there is no guarantee that these benefits will be distributed equitably. Without institutional and policy changes, this could lead to job losses and wage disparities, increased inequality, and adverse effects on job quality and worker satisfaction.
It is important to also consider the societal risks associated with AI, including threats to privacy, the potential for discrimination and bias, risks to democracy and political stability, and national security concerns.
It will take deep technical knowledge and may require new institutional forms for governments to stay abreast of and address these issues, given the rapidly changing technology.
Workforce Implications
The most relevant concern for workers is not whether AI will eliminate jobs in net, but rather how it will impact the labor market by shifting demands for certain types of expertise. AI could both erode the value of existing types of expertise and create opportunities for jobs that require new kinds of expertise. There is substantial uncertainty about how these forces will balance over time.
Some insight comes from looking back at previous technological transitions, where important categories of previously valuable human expertise, for example artisanal skills or routine clerical tasks, were stranded by new machines and novel forms of work organization. Recent research estimates that more than 60 percent of current employment is in occupational specialties that didn't exist in 1940.
AI is likely to speed the rate of automation of “mass expertise” tasks such as taking retail inventory at stores and stocking warehouses. It is also likely to enable the partial automation of tasks requiring “elite expertise” such as summarizing lengthy documents or managing complex systems. However, it appears likely AI could also complement workers by providing relevant information, guidance, and potentially digital guardrails, thereby enabling workers who possess expert judgment to perform a broader variety of tasks. For example, AI could augment the role of healthcare workers by providing quick access to relevant, specific information about conditions or treatments from medical journals and databases, or instructions and guidance to quickly master new equipment.
Effects on Education and Training
AI has the potential to transform the education system and improve learning outcomes by making education more personalized, engaging, and cost effective.
Public and private investments likely will be needed to increase access to online learning opportunities, to incorporate safeguards into AI-enhanced education, to test the effectiveness of AI in education, and to train teachers to make use of AI tools.
As AI shifts skill demands for workers, access to continuing education and retraining programs will be key to enabling the workforce to adapt to the changing jobs environment.
Key Opportunities
The impact of AI on the workforce will be influenced by what different institutions throughout society—including businesses, nonprofit institutions, worker organizations, colleges and universities, and government—choose to do to guide its development and use.
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Measure the Workforce Impacts of AI
Government leaders and others can expand data collection efforts, including high-frequency, real-time tracking of the use of AI by businesses and workers, through opportunities such as:
- Creating new public-private data partnerships to widely share data on skills supply and demand, wages, and continuing education opportunities.
- Measuring impacts of new technologies on marginalized groups and communities, and on AI adoption across and within economic sectors and geographic regions.
- Exploring the development of an independent, not-for-profit, government-chartered entity to create the infrastructure, protocols, and expertise needed to support public-private data sharing and integrated analysis.
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Support the Technological Development of AI
As AI technology advances and is broadly adopted, there are numerous opportunities to influence the direction, robustness, and speed of AI development, including:
- Basic research in AI and research into standards and guardrails.
- Incentives, standards, and regulations to encourage sharing and transparency regarding the data used to train advanced AI models.
- Research into high-priority AI applications such as education and training, health care, climate change, and national security.
- Initiatives such as the National AI Research Resource and the Microelectronics Commons to provide hubs for computational resources and foster the talent needed to keep U.S. universities at the forefront of AI development.
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Share the Productivity Benefits of AI
The potential productivity gains from AI are large, but those benefits will not be distributed equitably without institutional and policy changes in areas including:
- Assessing the effectiveness of policies that could enable labor mobility among occupations, firms, and geographical locations and help workers take better advantage of new job opportunities.
- Investigating factors that contribute to regulatory uncertainty such as product liability, copyright, privacy, and bias—and that complicate efforts of decision-makers to assess benefits and risks, speed adoption and implementation, and drive productivity gains.
- Identifying and assessing the potential for AI technologies to create new harms, either inadvertently or through abuse, and help policymakers work with the private sector to develop sensible guardrails.
- Research on the implications for market concentration in AI, such as winner-take-most dynamics, and options for maintaining a competitive marketplace while still enabling the benefits of scale and scope.
- Supporting AI research that speeds scientific discovery, which is a key contributor to productivity growth.
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Balance Workforce Impacts
Achieving the beneficial deployment of AI will require intentional design that seeks to complement and expand the applicability of human expertise, rather than displacing it. Policies to further these objectives include:
- Research on AI systems that augment, rather than replace, human workers, resulting in human-AI teams that produce higher quality outputs than either could alone.
- Exploring best practices for fostering inclusive AI adoption within firms and organizations and other ways to strengthen worker voice in business decisions.
- Research ways for individuals to control and be compensated for the use of their likenesses, their other personal attributes, and their creative works.
- Building AI expertise within the federal government to support effective investment, oversight, and regulation across all mission areas, including transportation, labor, health care, education, environmental protection, public safety, and national security.
- Evaluating and certifying the quality of purported human-complementary technology before adopting it for publicly funded programs in such areas as education and health care.
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Understand the Implications of AI for Continuing Education
AI is likely to change the nature of many jobs, boosting the need for continuing education programs to help workers adapt to the changing jobs landscape. Opportunities to assist workers with retraining include:
- Research on effective continuing education approaches to teach specific skills in high and growing demand and foster workforce flexibility.
- Exploring how AI, augmented reality, and other technologies can be used to improve education, particularly continuing education and retraining programs.
- Research into standards and certification for training programs to help community colleges and other educational institutions improve the match of new graduates to in-demand job opportunities.
- Developing, maintaining, and disseminating a “career roadmap” to enable workers to navigate shifting demand for different types of skills and continuing education opportunities to acquire high-demand skills.
- Establishing new education objectives for all levels of education to provide the knowledge and skills needed to take full advantage of future AI capabilities.