Macroeconomics impacts of artificial intelligence on global economy

As the technology continues to improve, it may have a substantial impact on the economy with respect to productivity, growth, inequality, market power, innovation, and employment Agrawal

FOREIGN TRADE UNIVERSITY Department of International Economics

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MACROECONOMICS

IMPACTS OF ARTIFICIAL INTELLIGENCE

ON GLOBAL ECONOMY

Group: 1

Members: Đỗ Quang Anh - 2313550003

Nguyễ n Qu nh Anh - 2312550012 ỳ Nguyễn Ngọc Trâm Anh - 2313550008 Nguyễn Mai Liên - 2312550035 Phạm Tuấn Minh - 2312550048 Nguyễn Mai Nhung - 2312550056 Nguyễn Yến Nhi - 2314550706 Trần Hoàng Phương Thả - 2312550065 o Nguyễn Văn Sơn - 2312550060 Nguyễn Minh Yến - 2313550073

Class: K62- KTEE203(2324-2)1.14

Instructor: Assoc Prof., Dr Hoang Xuan Binh

Hanoi, March 18 , 2024 th

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TABLE OF CONTENTS

I Introduction 3

II Notable study cases of AI applications to different sectors of the economy 5 III Scope of AI’s impacts on Macroeconomic variables 6

1 On global GDP 6

2 On inflation 7

3 On unemployment & labor resources 8

IV Forecast possible advantages and disadvantages 9

1 Advantages 9

2 Disadvantages 10

3 How to leverage the benefits and mitigate the drawbacks? 11

V Findings-based policies for Vietnam 12

VI Conclusion 12

CITATION AND REFERENCES 14

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IMPACTS OF ARTIFICIAL INTELLIGENCE (AI)

ON GLOBAL ECONOMY

I Introduction

1 Overview

Artificial intelligence (AI) technologies have advanced rapidly over the last several years As the technology continues to improve, it may have a substantial impact on the economy with respect

to productivity, growth, inequality, market power, innovation, and employment (Agrawal, Gans and Goldfarb, 2019b) The rapid development of artificial intelligence has made great shocks to the modern macro-economy According to The “Artificial Intelligence, Automation, and the Economy” report from the White House discusses the impact of AI-driven automation on the economy and suggests strategies to increase the benefits of AI and mitigate its costs

2 Rationale

The rationale for this presentation on the impact of AI on the global economy is rooted in the transformative potential of AI technologies AI is not in its infancy, but most of its economic impact

is yet to come (Bughin, 2018) The McKinsey Global Institute suggests that AI could add 16% or about $13 trillion to the global economy by 2030 (globalization partners, 2020) PwC’s study also suggests that AI could contribute up to $15.7 trillion to the global economy in 2030 (Bughin, 2018)

AI technologies, such as computer vision, natural language, virtual assistants, robotic process automation, and advanced machine learning, are expected to be adopted by companies to varyin degrees However, the adoption and absorption of AI could widen gaps among countries, companies and workers (Bughin, 2018) Therefore, it is crucial to understand the economic implications of AI

on a global scale

Moreover, the advent of generative AI (GAI) systems, which can understand human language and produce human-like dialogue and content, is creating an “iPhone moment” for AI This technological leap is democratizing data by making it available to billions of people through a growing array of commercial uses (Bank of America, no date)

However, the transition to AI is likely to cause disruptions that countries, companies, and workers will need to navigate These potential challenges and costs need to be factored into any estimate of AI’s economic impact (Bughin, 2018)

3 Aims of the study

A presentation on the impact of artificial intelligence (AI) on the global economy serves multiple aims, each contributing to a nuanced understanding of this complex phenomenon Firstly, it seeks to inform and educate the audience by providing a comprehensive overview of how AI is shaping the global economy, elucidating its diverse applications, implications, and potential future trends Concurrently, the presentation aims to highlight both the opportunities and challenges inherent in AI's integration into economic systems This entails discussing the potential for economic growth, innovation, and efficiency improvements alongside the attendant challenges such as job displacement, ethical considerations, and the risk of exacerbating inequalities Moreover, the presentation endeavors to explore the policy implications stemming from AI's influence on economic governance, regulation, and international cooperation, with a specific focus on equipping policymakers in Vietnam with insights for informed decision-making Lastly, it aims to raise awareness among the general public regarding the pervasive impact of AI on various facets of the

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global economy, fostering a more informed and engaged citizenry capable of navigating the evolving landscape of AI-driven economic transformations

4 Objectives of the study

The objectives of this presentation for university students are multifaceted, aiming to cultivate both interest and understanding in the realm of artificial intelligence (AI) and its impact on the global economy Firstly, the presentation endeavors to spark students' interest by delivering pertinent and engaging content that explores the implications of AI Additionally, it seeks to educate students on the diverse applications of AI across various sectors of the economy, including finance, healthcare, manufacturing, and entertainment Moreover, the presentation aims to provide insights into the array

of career opportunities available in the AI field, ranging from data science to machine learning, robotics, and AI ethics Furthermore, it aspires to inspire students to delve into research opportunities related to AI and its economic implications, fostering curiosity and innovation in their academic pursuits Lastly, the presentation underscores the real-world relevance of AI concepts by linking them to current events, industry trends, and practical applications in the global economy, thereby enriching students' understanding and appreciation of the subject matter

5 Methodology

The methodological approach employed in this study comprises qualitative research, specifically document analysis This involves a comprehensive examination of existing research papers, reports from reputable organizations such as PWC and the European Parliament, as well a scholarly articles and news reports that center on the influence of artificial intelligence (AI) on the global economy The overview of the essay delineates its focus on exploring the impact of AI on the global economy, encompassing both its advantageous and adverse effects, while also providing insights relevant to Vietnam's developmental trajectory

6 Background information and context

The history of AI dates back to the 1950s and 1960s when researchers began developing algorithms and programs that imitates human thinking In 1943, Alan Turing introduced the groundbreaking concept of the Turing Test, setting the standard for intelligent machines by aiming

to create a computer capable of deceiving a human into believing they were conversing with another person Isaac Asimov's publication of "Robot" in 1950 introduced the notion of machines with narrative capabilities The term "artificial intelligence" was coined by John McCarthy in 1956, marking a pivotal moment in the field's development During this era, a top-down approach dominated, focusing on pre-programming computers with the rules governing human behavior Since then, remarkable progress has been made, enabling machines to undertake complex tasks such speech recognition, computer vision, and machine learning Among the notable advancements is the creation of the GG app in 2009, representing a significant milestone towards the development of modern virtual assistants like Apple's Siri, Google Assistant, Amazon Alexa, and Microsoft Cortana

AI can be divided into strong AI - a system with generalized human cognitive abilities and weak AI

- a system that is designed and trained for a particular task (Lanna Deamer, 2019)

The evolution of artificial intelligence has fundamentally reshaped both our interactions with technology and the landscape of professional activities AI's capacity to undertake intricate cognitive tasks, automate repetitive functions, and make data-driven decisions has become increasingly evident This automation, driven by AI, is significantly impacting the job market, with countries like China, the US, Japan, the UK, and Germany leading in AI development In the realm of business, AI's influence is profound, particularly in the automation of repetitive tasks that traditionally

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demanded human intervention However, as algorithms continue to advance, AI is transcending its role in merely enhancing productivity to becoming a vital tool for customer engagement, service excellence, and innovation Various industrial sectors illustrate this transformation In contact centers, for instance, technological advancements like Chatbots and Talkbots ensure 24/7 availability and immediate responses, enhancing service capabilities and mitigating service failures often attributed to underperforming agents or emotional labor E-commerce giants leverage AI to understand customers better, offering personalized services such as intelligent product recommendations based on past purchases and browsing habits In logistics and supply chain management, AI's utilization of big data automates inventory management workflows, streamlining processes and reducing errors Additionally, AI algorithms forecast market demand, optimize shipping routes, and even predict and manage traffic flow, further enhancing efficiency across operations (Wallace de Oliveira, 2023)

II Notable study cases of AI applications to different sectors of the economy

Retail: Walmart uses AI to optimize inventory management, reducing waste and increasing profitability The AI-powered system is called Eden Its function is to manage Walmart’s inventory across the stores Eden uses machine learning algorithms to predict demand, optimize inventory levels, and reduce waste As a result, Walmart has been able to reduce out- -stock incidents by 30%of while also reducing overstocking and waste (Nicoleta, 2023) Moreover, Amazon uses AI to personalize the shopping experience for customers, increasing customer satisfaction and loyalty Central to this is a deep learning-based algorithm to help each customer find their best-fitting size in any style According to Amazon, this algorithm considers the sizing relationships between brands and their size systems, a product’s reviews and other details, and a customer’s own fit preferences to recommend the best-fitting size for a customer (Marcus Law., 2024)

Transportation: Uber uses AI to predict rider demand and optimize driver routes, increasing efficiency and reducing wait times The company uses its deep learning algorithm, DeepETA, to enhance forecasts of rider demand and predict pick-up and drop-off times based on map data an traffic measurements It also uses a machine-learning-powered algorithm to calculate the variation

of fares and facilitate its surge pricing The ride-hailing company also improved its conversational platform to make communication with customers more accessible This enhancement benefits drivers, who can better focus on driving thanks to hands-free pick-up and one-click chat features Healthcare: Aetna uses AI to analyze medical records and identify high-risk patients, improving patient outcomes The health insurer developed an artificial intelligence application to resolve claims, freeing up staff to focus on higher-level tasks Aetna has created artificial intelligence (AI) software to settle claims, a solution that could provide a blueprint for broader automation of complex processes at the health insurance giant The software rapidly parses complex healthcar provider contracts, whose blend of information about medical conditions and financial data often tax the patience of the trained humans who process them Aetna’s solution also highlights efforts companies are taking to reduce manual grunt-work performed by humans Insurers, in particular, have emerged as leaders in adopting ML, AI and robotic process automation (RPA) to optimize business processes and improve employee productivity The companies believe that improving these areas will in turn create a better experience for customers (Boulton C 2019)

Trading and Finance: Bank of America uses AI to detect fraud and money laundering, making financial transactions more secure If a customer reports a fraudulent charge, an advanced

AI system could one day analyze large datasets and provide an employee with a specific judgment

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about whether the charge was indeed fraudulent, based on the customer’s past purchase behaviors and other data (Sara Castellanos, 2019) Another notable application belongs to PayPal, an online payment platform utilizes AI algorithms for fraud detection These algorithms analyze transaction data, user behavior patterns, and other factors to identify and prevent fraud, ensuring financial transaction security

Business Analysis: The genAI technology is short for “general artificial intelligence.” GenAI excels in tasks such as editing copies, refining text, including spell-checking, suggesting headlines, and even creating text specifically tailored for social media advertising GenAI tools, like ChatGPT’s Advanced Data Analysis, are highly useful for economic research: technical tasks such

as coding, providing mathematical evidence, setting up economic models, deducing equations, and explaining them GenAI is excellent at inflation forecasting—surpassing even today’s economists Specifically, inflation predictions from Google’s PaLM, a large language model chatbot similar to ChatGPT, had fewer errors than the macroeconomic prediction sources, the Survey of Professiona Forecasters (SPF) SPF’s aggregated predictions made by highly qualified experts in economics, finance, and related fields (CNN Business, 2023)

III Scope of AI’s impacts on Macroeconomic variables

1 On global GDP

The majority of studies emphasize that AI will have a significant economic impact Research launched by consulting company Accenture covering 12 developed economies, which together generate more than 0.5 % of the world's economic output, forecasts that by 2035, AI could double annual global economic growth rates AI will drive this growth in three important ways.(European Parliament, 2019)

It will lead to a strong increase in labor productivity (by up to 40 %) due to innovative technologies enabling more efficient workforce-related time management Second, AI will create a virtual workforce of intelligent machines that can solve problems and learn on their own Third, AI will spread innovation across different industries, opening up new ways to make money.(European Parliament, 2019)

A study by PricewaterhouseCoopers (PwC) estimates that global GDP may increase by up to

14 % (the equivalent of US $15.7 trillion) by 2030 as a result of the accelerating development and take-up of AI It will boost standardization and consequently automation, as well as enhance the personalisation of products and services PwC sees two main channels through which AI will impact the global economy: the production-side and consumption-side effects of AI (European Parliament, 2019)

The first involves AI leading to productivity gains in the near term, based on automation of routine tasks, which is likely to affect capital-intensive sectors such as manufacturing and transport This will include extended use of technologies such as robots and autonomous vehicles Productivity will also improve due to businesses complementing and assisting their existing workforce with AI technologies This will make them better and faster at their jobs, freeing them up for more interesting and valuable work Overall, automation might mean needing fewer workers, but it will also mean a big boost in productivity The second channel the availability of personalized and higher-quality – AI-enhanced products and services will become even more important, as this availability is likely –

to boost consumer demand that would, in turn, generate more data Or, as PwC puts it: 'in turn, increased consumption creates a virtuous cycle of more data touchpoints and hence more data, bett insights, better products and hence more consumption' (PwC, 2018)

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The McKinsey Global Institute expects that around 70 % of companies would adopt at least one type of AI technology by 2030, while less than half of large companies would deploy the full range McKinsey estimates that AI may deliver an additional economic output of around US$13 trillion by 2030, increasing global GDP by about 1.2 % annually This will mainly come from the substitution of labor by automation and increased innovation in products and services (European Parliament, 2019)

According to several findings and research, AI has a positive impact on global GDP, especially in North America and China which are likely the first to adopt these powerful technologies Looking at the output approach, robots and other advanced equipment boost productivity which reduces the value of intermediate consumption and increases the number of final goods then leads to a rise in GDP Productivity and innovation will also increase profits and new revenue streams which raise GDP according to the Income method In the last approach, calculated

by expenditure, consumers not only have a new market for personalized products but also have a wider range of choices for products and services encouraging them to spend more AI has the potential to be a sustainable factor in increasing GDP in both the short and long run

2 On inflation

Inflation is a measure of the rate of rising prices of goods and services in an economy Put simply, it reflects a decrease in the purchasing power of money, meaning that the same amount of currency buys fewer goods and services than it did previously Therefore, it can have a negative impact on the overall economy

There are 2 common causes of inflation The first is Demand-pull Inflation: A surge in demand for products and services can cause inflation as consumers are willing to pay more for the product The second one is Cost-Push Inflation: Inflation can occur when prices rise due to increases

in production costs, such as raw materials and wages

Technology can have both inflationary and deflationary effects There are 2 ways technology can contribute to inflation The first one is the cost of technology implementation Investment and ongoing costs associated with adopting new technologies can be passed on to consumers at highe prices The second one is increased demand: Technological advancements create new products an services, potentially driving up consumer demand

By contrast, there are 3 ways technology can result in deflation The first and most convincing one is increased productivity Technological innovations often improve efficiency and productivity

in various sectors This can lead to cost savings for businesses, reducing their production costs which

in turn reduces the prices consumers pay The second way in which technology can contribute to deflationary effect is that technology can lower entry barriers and foster increased competition in markets This competition can lead to greater price transparency and pressure businesses to offe better products at lower prices The third deflationary effect of AI technology is automation and labor market effects: Technology makes processes more cost-efficient and less labor intense Supply and demand dynamics drive labor market costs down As a result, businesses pass lower expense

on to consumers

Although AI in principle can contribute to inflation and deflation, it has a trend towards deflation

Regarding inflationary mechanisms, the costs of implementing AI are primarily borne by providers such as OpenAI, Microsoft, Alphabet, or Meta It remains to be seen whether AI will create new products and thus create new needs, or merely improve existing products without boosting consumer spending

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On the other hand, AI has clear deflationary potential Firstly, it can significantly increase productivity Secondly, the abundance of new downstream applications suggests that AI will lower barriers to entry, as exemplified by large language models Lastly, the prospect of making human labor more scalable will impact labor markets The combination of these factors creates a powerful mix with a potential deflationary effect

3 On unemployment & labor resources

In the most recent few years, the literature on the topic of the effect of AI on unemployment has notably expanded (Ernst et al., 2019, Martens and Tolan, 2018), while various contributions consider AI as a component of a more complicated automation procedure (Wang & Siau, 2019) Generally, two-fold approaches can be discovered

The first part of the literature validates the ‘‘replacement effect’’, which consists of various aspects In this part, the application of artificial intelligence negatively impacts the labor market, causing unemployment because of being without a job as an outcome of replacement Some of the first academic studies about the negative impact of AI on employment belong to Leontief (1983) He highlights that nearly the entire workforce would be replaced by AI in future decades, expanding unemployment as an outcome Ngo et al (2014) discovered that 48% of specialists in the technology field believe robots may possibly perform the most standardized and automated labor Consequently

in the age of AI, except for a few highly skilled employees in related industries, traditional jobs will

be at risk of unemployment Susskind and Susskind (2016) consider that in the age of artificial intelligence, high-tech unemployment will be additionally increased, and the work in traditional industries will be processed into routine labor, which technologies will replace Frey and Osborne (2017) constructed a model, and the study found that 47% of 700 occupations are at risk of being replaced in the next two decades

The second part of the literature proposes the ‘‘displacement effect’’ In this respect, AI positively impacts the labor market, decreasing the unemployment level because of its job-creating effect Scholars believe that although artificial intelligence will have an impact on the job market in the short term, due to the substantial increase in production efficiency, the expansion of production will create more jobs and employment opportunities in the long term According to the McKinsey Global Institute Research (2016) study group, which strengthens this theory, there will be a demand for 250,000 data scientists by 2024 Koch et al (2021) analyzed a panel of Spanish manufacturing firms They pointed out that robot adoption led to a net increase in jobs of 10%, while firms that did not invest in robots suffered job losses over the period

In relation to the labor force, except for a few high-skill jobs, AI will substitute most traditional and routine jobs Routine tasks are characteristic of many middle-skilled cognitive and manual activities: for example, the mathematical calculations involved in simple bookkeeping; the retrieving, sorting, and storing of structured information typical of clerical work; and the precise executing of a repetitive physical operation in an unchanging environment as in repetitive production tasks Computers cannot substitute nonroutine tasks, including abstract tasks (which require problem-solving skills, intuition, creativity and persuasion) and manual tasks (which require situational adaptability, visual and language recognition and in-person interactions) (David H Autor, 2015)

Because jobs that are intensive in either abstract or manual tasks are generally found at opposite ends of the occupational skill spectrum - in professional, managerial, and technical occupations on the one hand, and in service and laborer occupations on the other - this reasonin implies that computerization of “routine” job tasks may lead to the simultaneous growth of high-education, high-wage jobs at one end and low-high-education, low-wage jobs at the other end, both at the

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expense of middle-wage, middle education jobs - a phenomenon that Goos and Manning (2003) called “job polarization”

According to Rakesh Kochhar’s report, workers with more education, women, Asian and White and workers with higher wages are the groups of workers that have higher levels of exposure

to AI In particular:

Workers with a bachelor’s degree or more (27%) are more than twice as likely as those with

a high school diploma only (12%) to see the most exposure

A greater share of women (21%) than men (17%) are likely to see the most exposure to AI Asian (24%) and White (20%) workers are more exposed than Black (15%) and Hispanic (13%) workers

In 2022, workers in the most exposed jobs earned $33 per hour, on average, compared with

$20 in jobs with the least amount of exposure

These bases show an ambiguous future of the status of unemployment under the influence of

AI Whether AI adoption leads to the increase or fall in unemployment rate is rather equivocal However, most economists believe that it will bring about the decrease in unemployment in the future It means that AI may take away but also create jobs According to the World Economic Forum, by 2025, AI would possibly take away 85 million jobs, but also generate 97 million jobs in related fields (big data, digital marketing, etc.) Labor force may experience a similar ambiguous trend, since AI could either replace or complement workers’ tasks However, experts believe that AI will rather reshape the workforce, not completely replace the workforce An example of how AI can reshape the workforce is when data analysts may spend less time on data collection, and more o interpreting the AI-generated data and insights AI adoption also leads to the emerging requirements for new skills, including technical skills that enable workers to perform tasks with AI and other technological advances and help them to strive in the technological era

IV Forecast possible advantages and disadvantages

1 Advantages

The initial advantage of applying AI technology resides in its profound impact on productivity Through AI-enhanced automation, processes are streamlined, inefficiencies are minimized, and overall productivity is significantly enhanced By delegating routine tasks to AI systems, human workers are liberated to concentrate on more creative and strategic dimensions o their roles This not only accelerates workflow but also fosters a more dynamic and innovative work environment With AI seamlessly handling repetitive tasks, employees can redirect their efforts towards high-value initiatives, problem-solving, and innovation, thereby maximizing their potential contribution to organizational goals Ultimately, the integration of AI-driven automation empowers businesses to operate more efficiently, adaptively, and competitively in a rapidly evolving landscape Besides, the transformative power of AI within the labor market is worth mentioning, heralding a paradigm shift in employment dynamics One notable advantage lies in the emergence

of novel roles tailored to harnessing the potential of artificial intelligence Emerging areas are AI and machine learning specialists, projected to experience a remarkable 40% surge in demand by 2027 showcasing the growing reliance on advanced computational algorithms (weforum) Additionally, the indispensability of data analysts and scientists becomes increasingly apparent in the age of data driven decision-making, highlighting the need for skilled professionals adept at deriving meaningful insights from vast datasets Furthermore, digital transformation specialists are poised to play a pivotal

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role in navigating the complex landscape of technological evolution, facilitating seamless integration and adaptation to emerging innovations According to the World Economic Forum, while forecasts predict the displacement of around 85 million jobs by machines by 2025, there's a simultaneous creation of approximately 97 million new roles, reflecting a dynamic reconfiguration of the division

of labor between humans, machines, and algorithms This evolution not only underscores the adaptability of the workforce but also presents opportunities for individuals to thrive in a digitally driven era

Another significant advantage of AI lies in its capacity to revolutionize economic prediction Through sophisticated machine learning algorithms, vast datasets can be meticulously analyzed to discern intricate patterns, enabling more precise forecasts and informed decision-making processes This capability translates to heightened efficiency in resource allocation and strategic planning, as businesses and policymakers can leverage predictive insights to anticipate market trends, mitigate risks, and capitalize on emerging opportunities By harnessing the power of AI-driven economic prediction, organizations can optimize their operations, enhance productivity, and foster sustainable growth in an increasingly dynamic and competitive global landscape

2 Disadvantages

Job Replacement:

AI was responsible for 3,900 jobs cuts in the US in May 2023, roughly 5% of all jobs lost, making it the seventh-highest contributor to employment losses in May cited (According to data from Challenger, Gray & Christmas)

AI will replace repetitive tasks and manual work such as data collection, routine tasks, and administrative work Sectors like office support, customer service, and food service may experience significant impact from AI transformation (According to research of McKinsey Global Institute) It also leads to a requirement for a highly skilled labor force

If the number of job creation is not higher than that of job losses, the unemployment will increase, which leads to decreased domestic consumption

Economic inequality:

Income: Blue-collar workers are more likely to be replaced by AI because of the lack of technological knowledge, which leads to an increase in income disparity (Kharate's research) Industries: A 2018 survey by the Boston Consulting Group points to the transport, logistics, automotive and technology sectors as already being at the forefront of AI adoption, and process industries (such as chemicals) are lagging behind

Countries: AI adoption levels across the world vary AI front-runners, located mostly in developed countries, are likely to increase their lead over their counterparts in developing countries This potential effect is likely to be explained by the fact that high wages in developed economies create a stronger incentive to substitute labor with AI than in lower-wage economies (Szczepański 2019)

Cybercrime and security concerns:

By possessing large data sets, hackers can take advantage of AI to steal users’ information

and make spoofing attacks

Microsoft and OpenAI reported that Russian military-linked Fancy Bear uses LLMs to research various satellite and radar technologies that could be related to military operations in Ukraine Two China-linked groups Charcoal Typhoon and Salmon Typhoon have used — —