Industrialization historically disrupted artisans and craftspeople, much like information technology and automation have altered job roles, making certain skills obsolete. With the rapid advancement of artificial intelligence (AI) and related technologies, questions arise regarding their impact on workers, potential displacements, and the collaborative skills that AI might promote. To address these concerns, the Northwestern University Center for Human-Computer Interaction + Design (HCI+D) organized a virtual panel featuring David Autor from MIT and Eric Horvitz from Microsoft. Both are contributors to the National Academies of Sciences’ report, "Artificial Intelligence and the Future of Work, " which assesses AI’s economic and workforce implications. Event moderator Liz Gerber pointed out that while AI encourages significant experimentation, the future is not set in stone. Decisions made today will shape new forms of valuable work. The report classifies AI as a general-purpose technology, crucial for long-term economic growth and capable of transforming cognitive tasks across various industries. Despite uncertainties surrounding AI’s economic effects, Autor and Horvitz agree it will unevenly reshape the labor market.

While some jobs may become automated, AI can create new roles and enhance human skills, particularly in decision-making and complex problem-solving. Autor emphasized AI’s ability to support human judgment in critical situations, comparing its guidance to navigational tools. Horvitz recognized the vast, untapped potential for human-AI collaboration, urging a focus on promoting human agency through AI technologies. AI could also democratize access to traditionally specialized fields, potentially requiring less formal training. Autor and Horvitz warned against underestimating the power of technology to enable new capabilities, using the Apollo Guidance Computer as an example of groundbreaking technological impact. They discussed AI's transformative potential in sectors such as education, healthcare, and science, especially in drug discovery and health diagnostics, where AI can improve discovery rates and address significant global challenges. Looking forward, the panelists cautioned against a passive approach to AI, advocating for proactive policies, governance, and training to effectively shape AI's role in the labor market. They emphasized society's responsibility to design a future where shared prosperity can be achieved rather than worsening economic inequalities. As Autor noted, the future should be viewed not only as a prediction but as a collaborative design exercise, with collective decision-making influencing outcomes.