While Holzer recognizes the current preference of the US tax code for mobility, he also highlights the lack of support for significant automation or artificial intelligence (A.I.) duties, as imposing such taxes could hinder output growth.
Instead, he proposes a form of mobility income where companies are obligated to pay taxes each time they dismiss an employee due to A.I. advancements. Holzer suggests using these taxes to discourage unnecessary mobility while utilizing the payment system to finance retraining programs. This approach aims to create suitable opportunities for the current workforce.
Holzer emphasizes the importance of aligning the motivations of businesses developing A.I. and those implementing it towards a more human-centric approach rather than a purely automated one.
To achieve this, companies are encouraged to invest in A.I. technologies that complement rather than entirely replace the unique skills that human employees bring to the table. Research by Autor, Chin, Salomons, and Seegmiller indicates that when technology complements workers instead of displacing them, it leads to the creation of more meaningful jobs, increased labor demand, and higher wages.
In areas where A.I. introduces novel tasks that enhance individual performance and innovative products and algorithms, governments, as per Acemoglu’s research, can take the lead in supporting A.I. development.
The Biden administration has already initiated various measures to promote responsible A.I. advancement, including earmarking $140 million for research and development in 2023 and issuing a comprehensive executive order addressing concerns related to health, ethics, and potential job displacement. The European Parliament has also approved a review of A.I., potentially paving the way for one of the initial comprehensive regulations governing these systems. This legislation focuses on ensuring the security of workers who interact with company A.I. platforms, emphasizing privacy protection and workplace safety.
Companies integrating A.I.-enabled technologies are advised to conduct thorough assessments to ensure that these systems meet the needs of their workforce, as outlined in the Partnership on AI’s guidelines for shared prosperity. Recommendations include establishing teams to oversee system usage, maintaining transparency regarding employee data collection and utilization, and offering employees the choice to opt out of certain data practices. The guidelines also advocate for secure systems that enhance job quality, recognize additional work facilitated by A.I., and ensure proper acknowledgment and compensation for such contributions.
The Partnership on AI is actively collaborating with unions, businesses, and policymakers to enhance, test, and promote the implementation of their shared prosperity guidelines.
Creating Opportunities for Upskilling
The concept of implementing universal basic income programs to support workers displaced by automation and A.I. has gained traction in recent years, with advocates like Andrew Yang promoting the idea. However, some economists, including Humlum, prefer prioritizing upskilling over income replacement, emphasizing the value of investing in people rather than simply providing financial assistance.
Diane Coyle from the University of Cambridge dismisses UBI as a concept advocated by Silicon Valley individualists who evade social responsibility for the consequences of their innovations. Coyle suggests that adult earnings could be better utilized for investments in infrastructure, transportation systems, or public education.
Studies suggest that reskilling programs can significantly benefit individuals with outdated skill sets, helping them progress in their careers. The White House has emphasized the importance of investing in training and job transition services to facilitate the successful integration of employees disrupted by A.I. into new roles that leverage their skills and experience effectively.
Holzer highlights the success of sector-based training programs in the US, preparing individuals for lucrative careers in high-demand industries even without college degrees. These programs typically involve collaboration between training providers, such as community or technical colleges, employers, and industry associations, to support underserved individuals.
Research by Lawrence F. Katz, Jonathan Roth, Richard Hendra, and Kelsey Schaberg demonstrates that sector-based programs focusing on industries like healthcare, transportation, IT, and manufacturing have led to significant earnings growth ranging from 14% to 38% in the year following program completion. These programs, such as WorkAdvance and Year Up, have shown sustained income gains over several years, indicating their long-term impact.
While these programs have predominantly benefited disadvantaged workers rather than those displaced by automation, Holzer suggests that the model could also be applicable to individuals affected by A.I.-related job losses. By facilitating quick retraining, particularly at the community-college level, workers can adapt to evolving job markets more efficiently.
Research conducted by Booth’s Humlum, in collaboration with Pernille Plato Jrgensen and Jakob R. Munch from the University of Copenhagen, evaluated the outcomes of a reskilling initiative in Denmark for workers injured on the job. While the focus was on injury-related displacement, the program’s success could potentially extend to workers displaced by automation. Participants who engaged in formal training programs or on-site education rather than opting for disability benefits experienced significant career transitions, leading to increased earnings and job stability.
Similarly, initiatives like the UK’s National Retraining Scheme and programs like Amazon’s Upskilling 2025 in the US aim to equip workers, especially those affected by automation and A.I., with the necessary skills for higher-level positions.
As technology advances rapidly and the workforce undergoes transformations, investing in retraining and upskilling initiatives becomes increasingly crucial. By prioritizing education and skill development, countries can better prepare their workforce for the evolving job landscape, ensuring long-term economic resilience and individual prosperity.
