Introduction of the Speaker, Professor Hal Varian:
Professor Richard Blundell from the UCL Department of Economics introduces Professor Hal Varian, the guest speaker for the UCL student-organized economics conference. Blundell highlights Varian’s renowned reputation as an accomplished economist.

Varian’s Impressive Contributions to Economics:
Varian’s scientific articles have earned him numerous awards and accolades. His groundbreaking research spans various fields, including price discrimination, public goods, revealed preference, informational economics, and more. Varian’s book, “Information Rules,” is recognized as one of the most insightful books on strategy by Fortune magazine. He served as the founding Dean of the School of Information at Berkeley. Since 2003, Varian has played a pivotal role at Google, bringing economic insights to the digital business landscape.

Welcome and Introduction of the Lecture Topic:
Blundell expresses excitement for Varian’s lecture, particularly focusing on the topic of technology, the changing world of work, and the intriguing title, “Automation versus Procreation.” Blundell hands over the stage to Professor Hal Varian for his presentation. Varian expresses his gratitude to the organizers and acknowledges the convenience of the 10 AM lecture time.

The Transformation of Labor:
The interaction between artificial intelligence, robotics, and labor-saving devices affects the demand for human labor. Demographic factors also influence the supply of labor.

Demographic Shifts:
The baby boom and the baby bust shaped labor force dynamics in the 20th century. Post-World War II, women entered the labor force in significant numbers, transforming employment patterns.

Automating Tasks, Not Jobs:
Automation primarily eliminates dull, tedious, and repetitive tasks from jobs. Cognitive tasks, such as making change and memorizing maps, have also been automated.

Eliminating vs. Changing Jobs:
The impact of automation on jobs is nuanced, rarely eliminating entire occupations. Jim Besson observed that only one detailed occupation listed in the 1950 census had been eliminated due to automation: elevator operators.

Changing Tasks within Jobs:
Elevator operators still exist but have different tasks, including safety monitoring and customer service. Complex jobs involve diverse tasks that are challenging to automate entirely.

Automating Tasks:
Automating tasks is feasible but can be expensive and time-consuming. Tasks like trimming flowers and shoveling snow can be automated, but it requires significant resources and technological development.

Robotics and Standardization:
Robots are most efficient in standardized environments with repetitive tasks, such as assembly lines. Optimizing workflows and standardizing tasks increase productivity in assembly lines.

Technology Advancements:
Industrial robots are widely used in auto plants and consumer electronics, where they perform repetitive assembly tasks due to their suitability for standardized environments.

Challenges in Heterogeneous Environments:
Automating tasks in more complex environments, such as gardens and hotel rooms, is challenging due to the need for specialized equipment for each task.

Modern Apple Orchards:
Modern apple orchards have been standardized to make them more suitable for automation, with short trees and apples growing on one side. This simplifies tasks like pruning and picking.

Automation of Fruit Harvesting:
Automating the harvesting of delicate fruits like apples, peaches, and strawberries remains challenging due to their susceptibility to damage. However, progress is being made in this area.

The First Invasion of Machines:
The first wave of automation in the 1880s focused on domestic labor, replacing manual tasks with devices like washing machines and vacuum cleaners.

Key to Eliminating Routine Labor:
Standardizing the environment and simplifying tasks make them more suitable for automation, similar to assembly line production.

Imitating Nature:
Attempts to imitate nature in technology have not been entirely successful, as seen in the failure of early aviation efforts that tried to mimic bird flight.

Routine vs. Non-Routine Work:
Employment in non-routine cognitive and manual jobs is increasing, while routine cognitive and manual jobs are stagnating due to automation.

Henry Ford on Mass Production:
In 1929, Henry Ford emphasized the elimination of fitters in mass production, referring to workers who adjusted parts due to imperfect manufacturing.

Elon Musk’s Perspective:
In 2018, Elon Musk acknowledged that excessive automation at Tesla was a mistake, recognizing the importance of human workers in dealing with anomalies in manufacturing.

Changing Nature of Jobs with Automation:
Automation is transforming various tasks and jobs, leading to questions about what tasks can be automated, how job-related activities will change, and which jobs cannot be easily automated.

Estimates of Job Loss Due to Automation:
Numerous studies, such as those by Oxford Price Waterhouse Coopers, OECD, and ITIF, have attempted to estimate the percentage of the workforce at risk of job loss due to automation. However, these estimates vary significantly due to the complexity of the issue.

Examples of Automation Impact on Specific Occupations:
Retail salespeople, cashiers, and fast food workers have already been impacted by automation, such as self-ordering kiosks in restaurants.

Automation in Food Preparation:
Automation is increasingly used in food preparation, with timers for tasks like frying French fries, leaving humans to handle exceptions.

Top 10 Largest Occupations in the US:
The 10 largest occupations in the US are mostly service jobs, with a combined employment share of 21% and an average income of $48,000.

Implications for Work Structure:
Automation and increased productivity could lead to reduced workweeks, more flexible working arrangements, or increased consumption.

Historical Perspective on Work Hours:
Historically, people worked long hours, with an average of 66 hours per week in 1850 due to agricultural needs. Over time, work hours have decreased, with 62 hours in 1870 and 60 hours in 1890.

Work Hours:
There has been a consistent decline in average work hours in the US since the 1950s, from 38.5 hours to current levels. Significant differences in work hours exist across countries, with Mexico having a 45-hour workweek and the Netherlands having a 29-hour workweek. The Netherlands’ shorter workweek is due to the prevalence of part-time jobs and the sharing of childcare responsibilities between parents.

Potential for a Shorter Workweek:
It is possible to have a 29-hour workweek in countries like the US and the UK by implementing effective coordination and leveraging technology. The COVID-19 pandemic may accelerate the adoption of flexible work arrangements and contribute to a shorter workweek.

People’s Desires:
People generally desire more jobs and less work. Universal basic income is a controversial concept, but most people appreciate having three-day weekends. Many countries offer long weekends during festive occasions, demonstrating the feasibility and popularity of shorter workweeks.

Education and Unemployment:
Higher educational attainment generally leads to lower unemployment rates. However, there is a fallacy of composition: if everyone becomes more educated, who will fill the jobs that don’t require higher education?

Technology-Enabled On-the-Job Training:
Online resources like YouTube provide a vast amount of instructional material, making it easier for individuals to acquire new skills. YouTube has over 1 billion daily views of how-to videos covering various topics, from cognitive skills like mathematics and computer science to manual skills like plumbing and welding. This democratizes access to educational content and makes YouTube an integral part of modern education.

Cognitive and Manual Skills:
Technology enables the delivery of both cognitive and manual skills through online platforms. Cognitive skills, such as mathematics and computer science, are well-represented in online courses. Manual skills, such as plumbing and welding, are more effectively taught through videos.

Technology Reducing Barriers to Entry:
Advances in technology have eliminated the need for certain skills in various occupations, reducing barriers to entry. Examples include cashiers no longer needing to know how to make change, writers no longer needing to be expert spellers, taxi drivers no longer needing to memorize city streets, and hospitality workers no longer needing to know multiple foreign languages. Technology now provides assistance for tasks like plant recognition and dog breed recognition, which were previously required knowledge for gardeners and veterinarians.

Upskilling vs. Downskilling:
When there is a skills gap, technology can either help workers acquire new skills to meet job requirements (“upskilling”) or reduce the skill requirements to match workers’ competencies (“downskilling”).

Technology as a Catalyst for Change:
The impact of technology on cognitive labor is comparable to the impact of gasoline engines and tractors on manual labor in the 1800s, making labor more efficient and accessible.

Labor Force Growth:
Labor force growth in the US from 2020 to 2040 is projected to be the lowest ever, with a slight uptick in the 2030s and 2040s. Population growth is outpacing labor force growth, with the labor force growing at only half the rate. Without immigration, the working-age population in the US would decrease by 2035.

Baby Boomers and Labor Shortages:
Baby boomer retirements are expected to continue, leading to labor shortages. Northern US states face labor shortages and may not benefit from younger populations migrating from the south. Developed countries worldwide are experiencing labor shortages, with Japan, Spain, Korea, Italy, Germany, and France facing significant challenges.

Birth Rates and Economic Factors:
Birth rates have declined during recent recessions, including the Great Recession and COVID-19 pandemic, impacting the future labor force. Low birth rates are primarily driven by economic factors.

Countries with Aging Populations:
Countries with aging populations, such as Korea, Japan, Germany, and Italy, are investing in robots to address labor shortages.

Impact of Automation and Demographics on Labor Markets:
Automation reduces labor demand and shifts labor supply, leading to an overall decline in employment population ratio. Boston Consulting Group estimates a 1.76% decline due to automation and 2.7% decline due to demographics.

Aging Workforce and Healthcare Costs:
As retirees age, they often become more costly due to increased healthcare expenses, exacerbating the labor market effects.

Economic Benefits of Automation:
Cost savings from automation are likely to be passed on to investors and consumers, leading to increased spending and job creation. High-income individuals have accumulated savings during COVID due to reduced spending opportunities, which may lead to increased consumption post-pandemic, further boosting the economy.

Economic Thought and Modeling in the Age of Big Data:
Machine learning and big data provide novel indicators of economic activity, such as Google’s mobility index and consumer intent through Google Trends. Utilizing this new data can lead to more accurate predictions and insights into economic variables.

Impact of Automation on Labor Specialization:
While automation promotes specialized tasks, advancements in technology also lead to a demand for a diverse set of skills, as seen in the rise of do-it-yourself videos on YouTube. This DIY trend is driven by a scarcity of skilled workers willing to work for low wages.

Automation, Inequality, and Immigration:
Automation may contribute to income inequality, as low-skilled workers might lack access to necessary training. However, remote learning and online resources offer opportunities for individuals to acquire new skills. The impact on inequality over time will depend on the balance between automation and demographic trends, with the next 30 years likely to see a reduction in inequality. Immigration is a critical factor in addressing labor supply shortages in developed countries, as they face declining workforces while developing countries experience population growth.