Scenario Planning for an A(G)I Future in the World of AI

Exploring the Implications of Artificial Intelligence Growth on Future Economies and Workforce

Bullet Points:

Artificial intelligence (AI) has been rapidly evolving, with recent advancements hinting at a future where AI may surpass human intelligence. The development of ChatGPT, which can generate human-like text, code, and creative content, signifies the significant progress made in the AI landscape. The computational resources used to train cutting-edge AI systems have doubled every six months over the past decade, leading to AI models that can now provide substantial productivity gains across various industries.

In the realm of AI, there are different perspectives on the trajectory of AI development. Some experts suggest that AI, particularly Artificial General Intelligence (AGI), could reach human-level intelligence within the next few years, potentially transforming how tasks are performed and impacting the workforce significantly. However, there are also skeptics who believe that the pace of AI progress may not be as rapid as projected.

The uncertainty surrounding AI's future development poses essential questions about the nature of intelligence and the capabilities of the human brain. Some believe that the human brain has no bounds in solving complex tasks, while others argue that there is an upper limit to the brain's computational abilities. This discrepancy in perspectives influences how we foresee the automation of tasks in the future as AI systems become more sophisticated.

Given this uncertainty, economists advocate for scenario planning as a strategy to navigate the potential outcomes of AI growth. Economic policymakers need to consider various scenarios, from traditional business advancements to the aggressive adoption of AGI in a short time frame, to ensure they are prepared for a range of future possibilities.

Analyses of these scenarios reveal significant economic implications, including impacts on growth, wages, capital returns, inequality, and political stability. Policy frameworks must be adaptable to respond effectively to the diverse trajectories that AI development could take, ensuring that institutions remain resilient in the face of AI-driven changes.

The rapid evolution of AI also underscores the importance of monitoring key indicators to gauge the pace and implications of AI progress. These indicators include technological benchmarks, investment levels in AI, adoption rates across sectors, and macroeconomic trends influenced by AI technologies.

As policymakers navigate the complexities of AI advancement, embracing adaptive, scenario-based approaches can help maximize the benefits of AI while mitigating potential risks to the economy and the workforce. By staying informed and proactive, stakeholders can navigate the changing landscape of AI with greater agility and foresight.

Author: ANTON KORINEK, Professor of Economics and AI Lead at the University of Virginia