The United States must adopt a comprehensive approach to prepare the workforce for the transition to an AI-driven economy. The impacts of AI on the workforce are unpredictable. Many are concerned about significant workplace disruption and displacement. In the face of rapid change and uncertainty, it’s crucial to build workforce resilience and adaptability. Success can lead to a more productive and innovative workforce, but failure poses risks to American competitiveness and workers.
The New AI Landscape
AI technology is transforming many sectors of the economy. One survey found that organizations adopting AI more than doubled between 2017 and 2022. The same survey also showed that an organization’s number of AI capabilities, such as robotics, natural language processing, or recommendation systems, has doubled over the same period.
Businesses recognize the value of AI in their operations, but impacts differ across industries due to the distinct utilization of various AI capabilities and applications. For instance, the retail sector uses chatbots to improve customer experiences and satisfaction. At the same time, the health care industry has made significant use of computer vision and biometric-related AI tools to analyze data for more effective treatments. The diverse applications of AI imply that each industry will experience unique effects.
Today, we’re witnessing the emergence of novel developments and increased access to generative AI models that learn from vast amounts of data to create content that can seem indistinguishable from human output. Writing tools such as ChatGPT and Bard and image generators such as Stable Diffusion and Dall-E were introduced to the public in just the last year. We have only begun to scratch the surface of the impact these technologies will have on society.
Impact of AI Technology on the Workforce
The introduction of new AI technology raises important questions about their impacts on the workforce and job disruption. Despite the complexity and unpredictability of AI’s impact on jobs, some studies have still tried to quantify these effects. For instance, one research paper projects that “roughly two-thirds of current jobs are exposed to some degree of AI automation, and that generative AI could substitute up to one-fourth of current work,” but notes “worker displacement from automation has historically been offset by creation of new jobs.” Another research paper on AI language modeling capability finds that the “top occupations exposed to language modeling include telemarketers and a variety of post-secondary teachers” and that the “top industries exposed to advances in language modeling are legal services and securities, commodities, and investments.” Given the high uncertainty around these issues, these papers are highly speculative.
If history is a guide, often it is individual tasks within jobs that are most susceptible to being automated. The difference between jobs and tasks is an important distinction when looking at how emerging technologies will affect the workforce. AI is often more effective at automating individual actions or steps within a job rather than automating the job entirely. AI is often also effective in complementing other parts of a job. For instance, an AI system may replace the time doctors spend analyzing medical images but aid doctors’ ability to explore new treatments. Given how AI can automate certain tasks and augment others, governments and businesses should focus on cultivating workforce resilience and adaptability to empower workers to develop skills for tasks that are complemented by AI as part of a lifelong learning process.
The impacts of AI technology on the workforce will not just be on the number and types of jobs. Other challenges include how AI impacts privacy, bias, equity, and innovation in the workplace. For instance, how will employees use AI to monitor workers, and what privacy protections should workers have? AI governance will be key to managing and addressing many of these issues.
The workforce of the AI economy should greatly benefit from thoughtful policies that help them seize opportunities and address challenges. As a result, below are three broad recommendations for policymakers.
- Promote lifelong learning: Workers need to be ready and empowered to adapt quickly to a constantly changing work environment. Promoting lifelong learning will help workers regularly update their skills as the workplace, and the tasks that make up the jobs of the future evolve in unpredictable ways. Policymakers should emphasize promoting lifelong learning policies in an inclusive manner.
- Empower workers to develop skills that leverage and complement AI: While AI technology will automate certain tasks, it will also complement others and create opportunities for workers to develop new skills. Predicting these skills is difficult, which is why adaptability and lifelong learning are so important, but businesses and government should empower workers to develop skills that leverage and complement AI technology.
- Strengthen AI governance: The workforce is affected by many of the broader AI governance and ethical challenges, such as protecting privacy and addressing bias, that AI raises. Strengthening AI governance can help organizations implement best practices when applying AI tools in the workplace. The National Institute of Standards and Technology put together an AI Risk Management Framework and a Trustworthy and Responsible AI Resource Center that can serve as a guide. Congress and various agencies are also considering different legislative, regulatory, and soft law tools for addressing workforce challenges. When addressing AI governance issues, policymakers should focus on building from existing laws when appropriate, tailoring regulation around use cases based on the risks and rewards they can produce, and passing federal privacy legislation.
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