The Economic Impact of AI: Navigating News Shocks and Future Predictions
Since the launch of ChatGPT in December 2023, artificial intelligence (AI) has captured public and policymaker attention, raising questions about its potential promises and threats to the economy. AI tools like Microsoft’s Copilot in Word and customer service chatbots are revolutionizing business processes.
This evokes a crucial question: What is the economic impact of AI? Will the influence of AI match that of the steam engine during the Industrial Revolution, or resemble the computer age, where economist Robert Solow noted, ‘You can see the computer age everywhere but in the productivity statistics’?
Economists are examining various aspects of AI’s integration into the economy, especially its implications for GDP, employment, and inequality. Notably, a recent analysis explores how news regarding AI’s arrival has already influenced economic outcomes even before its full deployment.
Understanding News Shocks
The emergence of AI creates ‘news shocks,’ a concept introduced in macroeconomic literature by economists Paul Beaudry and Franck Portier. These shocks denote unexpected information that affects economic fluctuations.
Essentially, news shocks are closely tied to total factor productivity (TFP), which gauges the productivity of an economy by accounting for various inputs. A TFP news shock implies receiving information indicating future TFP improvements. The prospect of higher future productivity can spur current economic activity as households anticipate increased wealth, bolstering consumption.
AI as a TFP News Shock
The launch of AI represents a significant news shock, as technologies like ChatGPT have become transformative forces in economic processes. Although the underpinnings of AI were accessible, it was the simplicity and utility of ChatGPT that propelled its recognition as a potential game-changer in various sectors. Observations suggest that ChatGPT is increasingly integrated throughout the economy.
Economists assess news shocks based on how innovations diffuse through an economy. Historically, it’s taken time for new technologies to transition from mere ideas to consumer-ready products. This slow diffusion can delay the realization of economic impacts, yet anticipatory behavior often results in immediate responses from economic agents.
Measuring News Shocks
Researchers employ various methodologies to identify and quantify news shocks. One effective method involves analyzing the macroeconomic data patterns that slow news diffusion generates. The max-share identification technique helps economists isolate these shocks from broader economic variables, like GDP and consumption.
Economic Implications of AI News Shocks
Research indicates substantial effects of AI on major economic aggregates quality. Anticipation of AI-led productivity increases sees immediate rises in GDP, consumption, and investment, driven by two main mechanisms: a wealth effect and an expected higher marginal return on capital.
Conclusion
This analysis indicates that AI’s progression through the economy could significantly enhance TFP and related economic measures, although future predictions remain uncertain. If initial expectations of AI’s effects do not materialize, the outcomes may reflect negatively, representing a setback in economic expansion.
