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The inexorable growth of technology has been a constant for many decades, and now, the rise of Artificial Intelligence (AI) is gaining widespread popularity across various fields of study. Countries and institutes are actively exploring the applications of AI in areas such as defense, banking, and the economy. A crucial aspect of economic theories and policymaking involves mitigating the uncertainties associated with policy decisions.

This article delves into the definitions of AI and economics, exploring the intersection of the two and examining findings from various studies on AI and its impact on economic dynamics.

Definition of Artificial Intelligence (AI)

AI is lucidly defined as machines capable of human-like thinking, performing tasks that demand human intelligence. Processing large volumes of data and conducting analyses based on specific requirements, AI mimics human capabilities such as speech recognition, decision-making, judgment, and pattern recognition. The diverse approaches employed by AI are causing a paradigm shift across all sectors of the technology industry. Economics and Artificial Intelligence (AI)

AI and the Labour Market

The International Monetary Fund, in its report titled “Gen-AI: Artificial Intelligence and the Future of Work,” assesses the global impact of AI on the future of work, both at the country and state levels. The report underscores that AI has the potential to reshape the global economy, particularly the labor market. Nearly 40 percent of global employment is exposed to AI, with advanced economies facing both higher risks and greater opportunities compared to emerging market and developing economies. The prevalence of cognitive-task-oriented jobs in advanced economies puts around 60 percent of their jobs at risk.

The report also predicts that AI will influence income and wealth inequality. The adoption of AI is anticipated to increase total income, with stronger productivity gains leading to higher growth and incomes.

AI and Economic Predictions

While economists traditionally struggle with accurate economic predictions, AI systems, with their intelligent behavior encompassing learning, reasoning, and problem-solving, offer a promising solution. An IMF paper by Prakash Loungani acknowledges the historical failure of economists to predict recessions but suggests that AI can significantly enhance prediction accuracy. AI predictive analysis has the potential to overcome challenges in current economic forecasting, enabling economists to provide more precise estimates and assess the impact on the economy.

AI in the Financial Sector

In the realm of trading and investing, concepts like algorithmic trading, black-box trading, and automated trading have become familiar. These methods leverage AI to study market movements and investment strategies. AI’s role in the financial market extends to making decisions based on market dynamics, central bank interest rate policies, and predicting systematic risks, thereby helping to avert crises like subprime and financial meltdowns.

AI to Prevent Loan Default

AI proves instrumental in identifying potential loan defaults by analyzing extensive data on defaulters across banks. Its application in the financial sector enhances crisis prevention and risk management.

AI for Economic Research

Economic research involves theorizing economic behavior and analyzing data on economic activities. AI’s role in this domain is transformative, allowing researchers to process voluminous data swiftly and provide precise predictions and policy recommendations efficiently.

AI in General Equilibrium

General Equilibrium, a crucial concept in economics, significantly influences policy-making. AI expedites the delivery of General Equilibrium by processing and analyzing data across sectors faster and more accurately than traditional methods.

AI and Socio-Economical Issues

AI’s ability to analyze big data enables more accurate predictions of developmental and socio-economic issues. It can forecast inflation, unemployment rates, the influx of migrant labor forces, interest losses from loan defaulters, income losses for farmers, and identify beneficiaries of government schemes, among other applications.

Conclusion

While AI offers tremendous potential, it is not without its biases, mirroring the biases present in human minds. AI biases stem from the information, data, and methodologies used for processing and analysis. Despite the management of biases being possible, complete eradication remains challenging.

The utilization of AI spans multiple fields, and ongoing research on its applications in economics is still in its nascent stages. The societal impact of AI should ideally be more beneficial than detrimental. Aligning research priorities with effective policymaking can foster inclusive and sustained economic growth.