The Hidden Threat of AI: A Potential Catalyst for Economic Crisis

In a recent speech at an AI summit in Switzerland on May 30, IMF First Deputy Managing Director Gita Gopinath raised a crucial yet underexplored concern: the true disruptive effects of artificial intelligence (AI) on the economy and financial markets may not become apparent until there’s a downturn. According to Gopinath, this could spiral into a full-blown crisis unless the risks of AI are addressed promptly.

AI’s Potential to Amplify Economic Downturns

Gopinath emphasized that while discussions about AI’s risks have largely focused on privacy, security, and misinformation, there is far less discourse on how AI could exacerbate the next recession. In a world of widespread AI adoption, the technology could convert an otherwise ordinary downturn into a much deeper economic crisis by disrupting labour markets, financial markets, and supply chains.

AI Risks in Labour Markets

Historically, during economic booms, companies invest in automation while still retaining their workforce due to strong profits. However, during downturns, companies often cut costs, leading to layoffs and increased reliance on automation. Gopinath highlighted IMF research indicating that 30% of jobs in advanced economies are at high risk of AI substitution, compared to 20% in emerging markets and 18% in low-income countries. This widespread potential for job loss poses significant risks of long-term unemployment, which could have severe economic consequences.

AI Risks in Financial Markets

The financial sector has long embraced automation and earlier forms of AI, such as algorithmic trading, and is rapidly adopting newer AI technologies. Gopinath noted that some AI trading is evolving into more complex, self-learning models, with forecasts suggesting that robo-advisors will control over $2 trillion in assets by 2028, up from less than $1.5 trillion in 2023. While AI can enhance market efficiency and inclusion, its risks become more pronounced in downturns. New AI models might perform poorly in unprecedented events, potentially leading to a rapid shift to safe assets and a sharp decline in risk asset prices.

AI Risks in Supply Chains

As businesses increasingly rely on AI for inventory and production decisions, the potential for efficiency gains is significant. However, Gopinath warned that AI models trained on outdated data could make critical errors, resulting in supply-chain breakdowns. In normal times, these errors might be manageable, but during a downturn, they could cascade into severe disruptions.

Mitigating AI’s Risks

Despite these grim scenarios, Gopinath offered recommendations to mitigate AI’s risks without stifling its positive impacts.

1. Enhanced Regulation and Oversight: Regulatory frameworks need to evolve to keep pace with AI advancements, ensuring that AI systems are robust and transparent.
2. Investment in Human Capital: Governments and companies should invest in upskilling and reskilling workers to prepare them for an AI-driven economy, reducing the risk of mass unemployment.
3. AI Model Robustness: Developing AI models that can handle novel scenarios and ensuring they are trained on diverse and up-to-date data sets can mitigate risks in financial markets and supply chains.
4. Collaborative International Efforts: International cooperation is crucial for setting global standards and sharing best practices in AI governance.

Gopinath’s insights serve as a crucial reminder that while AI holds enormous potential for boosting productivity and economic growth, it also presents significant risks that must be carefully managed. As AI continues to permeate various sectors, proactive measures are essential to safeguard against its potential to deepen economic crises.