Tuesday, October 8, 2024

AI Will Eliminate Whole Industries, Not Just Some Jobs

Virtually all observers believe artificial intelligence is going to eliminate some jobs, in line with the ability AI might have to automate key job functions. The attrition could come because higher output can be achieved using fewer people, perhaps more so than because AI completely eliminates a particular job role. 


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But that is not even the most important "threat." Whole industries can disappear when a general-purpose technology appears, and AI is likely to be a GPT.


Industry

Disrupted by

New Industries/Roles

Horse-drawn carriage manufacturing

Internal combustion engine

Automobile manufacturing, transportation services

Typewriter manufacturing

Personal computer

Computer hardware and software manufacturing, word processing services

Film photography

Digital photography

Digital camera manufacturing, digital imaging services

Record stores

Digital music distribution (MP3, streaming)

Music streaming services, digital music production

Travel agents

Online travel booking websites

Travel technology companies, online travel booking services

Traditional retail

E-commerce

Online retail, logistics and delivery services


If AI does prove to be a general-purpose technology on the pattern of agriculture, steam power, the internal combustion engine, computing or electricity, that is inevitable. A look at the impact of various computing technologies, from personal computers to AI, illustrate the point, but huge changes in labor forces have always accompanied the emergence of a new GPT. 


Agriculture allowed humans to settle, rather than living as hunters and gatherers, creating the underpinnings for economic surplus that in turn enabled population growth, job specialization and settlements that enabled  the development of art, writing, legal systems, mathematics, new tools,  medicine and more-complex social structures. 


Study Title

Date

Publisher

Key Findings

The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies

2014

W. W. Norton & Company

Discusses how technologies like AI, robotics, and personal computers have automated routine jobs in clerical, manufacturing, and administrative sectors, while creating new roles in software development, IT management, and creative industries.

The Race between Education and Technology

2014

National Bureau of Economic Research (NBER)

Shows how general-purpose technologies, particularly computers, have reduced demand for middle-skill jobs (clerks, machine operators) and increased demand for high-skill (software engineers, data analysts) and low-skill jobs (service workers).

Technological Change and the Labor Market: A Survey

2017

Journal of Economic Surveys

Examines how the introduction of GPTs (such as AI, automation, and IT) has led to job polarization, with job losses in low-to-middle skill categories and gains in high-skill, technology-oriented positions, such as data scientists, AI researchers, and cybersecurity experts.

Automation, Jobs, and the Future of Work

2019

International Monetary Fund (IMF)

Reviews global trends in automation and AI, showing how GPTs have reduced the need for routine manual and cognitive jobs (e.g., typists, cashiers, machine operators), while increasing demand for jobs in tech, management, and highly skilled service sectors.

AI, Robotics, and the Future of Work

2018

Brookings Institution

Analyzes how AI and robotics, as general-purpose technologies, have transformed sectors like manufacturing, retail, and logistics by displacing low-skill jobs, but creating high-skill roles in programming, system analysis, and tech support.

Digital Transformation and the Future of Jobs

2020

World Economic Forum

Finds that GPTs like AI, blockchain, and the Internet of Things (IoT) have contributed to job displacement in traditional sectors like agriculture and manufacturing, while creating job opportunities in digital and tech sectors, such as cloud computing and cybersecurity.

The Impact of Information Technology on Labor Demand

2019

Journal of Economic Surveys

Examines the role of IT and general-purpose technologies in reshaping labor demand. It finds that routine jobs in finance, clerical work, and manual labor have declined, while demand for IT professionals, software developers, and project managers has risen.

How AI and Robotics are Transforming Labor Markets

2020

European Central Bank (ECB)

Demonstrates that AI and robotics have led to the disappearance of low-wage, routine manual jobs, and the growth of tech jobs in AI systems, machine learning, data processing, and AI ethics. Also highlights growing demand for high-skilled healthcare roles enabled by AI.

The Effects of Automation on Jobs and Wages: A Global Perspective

2023

OECD

Highlights that GPTs like AI and robotics have not only automated routine jobs in manufacturing and services but also created new job categories in software development, healthcare technology, and digital infrastructure management.

Automation and the Shift in Labor Markets: Evidence from AI and Robotics

2021

Review of Economics and Statistics

Provides evidence that AI and robotics have led to the shrinking of low-skilled jobs (e.g., assembly line workers) while new opportunities have emerged in tech-heavy fields like AI programming, cybersecurity, and data analysis, where skill requirements are much higher.

Technology, Jobs, and Inequality: A Survey of the Evidence

2018

Economic Policy Institute

Analyzes how the adoption of GPTs, including AI and automation, leads to job polarization, creating a split between low-wage, low-skill jobs in the service sector and high-wage, high-skill jobs in tech fields like cloud computing, data science, and AI.

Work in the Age of AI: The Impact of Automation and AI on Job Categories

2022

MIT Technology Review

Examines the effects of AI-driven GPTs on job categories, showing a decline in traditional roles such as truck drivers and retail workers, while new categories like AI ethics officers, machine learning trainers, and drone operators emerge.

The Future of Jobs in the Age of Automation

2017

McKinsey Global Institute

Explores how general-purpose technologies like automation and AI displace routine work (e.g., cashiers, clerks), but open up new career categories, particularly in fields such as AI system design, data analytics, and machine maintenance.

The Economic Impact of Automation and AI

2021

Stanford Center for Digital Economic Studies

Shows that GPT adoption has led to a shift in employment patterns: many low-skill roles have been automated (e.g., assembly line workers, clerks), while there is an increased demand for data scientists, digital marketers, and machine learning engineers.


So concerns about changes in job composition of the labor force are realistic, if quite possibly inevitable. U.S. dockworkers recently conducted a strike among which key demands included a complete ban on automation of dock work. Discussions about that portion of new contracts remain active, but the larger point is that demands by workers to ban the use of machinery of all types has arguably slowed, but never stopped, the deployment of new technology based on a GPT that automated formerly-human labor. 


Personal computers, for example, did not so much eliminate whole jobs as make possible the ability of each worker to produce some output that formerly might have been created by others (people write their own emails and documents, where in the past stenographers would have done so. 


PCs democratized access to tools that allowed workers at all levels to produce output that once would have been handled by others, such as document production, data entry, analysis, and design.


Before PCs became widespread, tasks like document production, data processing, and basic design were often handled by specialized staff such as secretaries, typists, clerks, and graphic designers. “Desktop publishing,” for example, was an early use case for Apple computers. 


As always, new jobs arose, as well. 


Sector/Occupation

Job Function Pre-PC

Job Function Post-PC

Change in Demand

Clerical/Administrative

Typist, Data Entry Clerk, Secretary

Office Manager, Executive Assistant, Office Coordinator

Decreased

Accounting/Finance

Bookkeeper, Ledger Clerk, Accounts Clerk

Financial Analyst, Accounting Software Specialist

Decreased

Manufacturing

Manual Laborer, Assembly Line Worker, Machine Operator

CNC Operator, Maintenance Technician, Robotics Specialist

Decreased

Retail

Inventory Clerk, Cashier, Stock Clerk

E-commerce Manager, Inventory System Analyst

Decreased

IT and Technology

None

Software Developer, Systems Administrator, IT Support

Increased

Customer Service

Telephone Operator, Customer Service Representative

Help Desk Technician, Customer Support via Online Platforms

Increased

Marketing and Sales

Sales Clerk, Telemarketer, Market Research Assistant

Digital Marketing Specialist, Social Media Manager

Increased

Education

School Secretary, Paper-Based Research Assistant

EdTech Specialist, E-learning Coordinator, Curriculum Developer

Increased

Health Services

Medical Records Clerk, Billing and Coding Clerk

Medical Data Analyst, Health IT Specialist, Telemedicine Support

Increased

Logistics/Transportation

Shipping Clerk, Inventory Handler, Dispatcher

Supply Chain Analyst, Logistics Software Manager

Increased


At a high level, most observers might agree that AI poses similar sorts of upside and downside, from the standpoint of jobholders. New jobs are going to be created, but some existing jobs will likely decrease in number. In that sense, we can expect continued opposition to the use of AI in many industries, though such opposition will fail, over time, as obvious productivity gains often compel all contestants in a market to adopt the new technologies. 


Study Title

Date

Publisher

Key Findings

The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies

2014

W. W. Norton & Company

The adoption of digital technologies leads to a polarization of the job market, creating high-skill, high-pay jobs while diminishing middle-skill jobs.

The Impact of Digital Technologies on Employment

2016

International Labour Organization (ILO)

Found that automation through digital technologies has the potential to displace a significant number of jobs, especially in manufacturing, but also create new job categories in tech and service sectors.

Automation, Skills, and the Future of Work

2019

McKinsey Global Institute

Predicts that up to 375 million workers may need to switch occupational categories due to the adoption of automation and AI, necessitating retraining and new skill development.

The Future of Jobs Report 2020

2020

World Economic Forum

Identified the net job creation potential from GPTs, predicting that 85 million jobs may be displaced while 97 million new roles could emerge, emphasizing the need for upskilling.

Artificial Intelligence and the Future of Work

2021

Brookings Institution

Discusses how AI adoption can create job growth in sectors requiring complex human interactions and creativity, but also warns of significant job displacement in routine tasks.

The Economic Impact of Artificial Intelligence on Work

2022

MIT Technology Review

Highlights that GPTs like AI can lead to job transformation rather than outright replacement, with new roles in data management, AI oversight, and ethics emerging as key areas of growth.

Industry 4.0 and Its Impact on the Labor Market

2023

Journal of Business Research

Analyzes the impact of Industry 4.0 technologies on job dynamics, indicating a shift towards more specialized roles and increased demand for technical and soft skills.

The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies

2014

W. W. Norton & Company

Examines how advances in automation and artificial intelligence (AI), including GPTs, lead to job displacement in routine tasks, but also creates opportunities for higher-skill jobs in sectors like healthcare and education.

The Impact of Information Technology on Labor Demand: A Review of the Literature

2019

Journal of Economic Surveys

Analyzes the role of IT and GPT adoption in reshaping labor demand across industries, revealing a shift toward higher-level cognitive tasks, while routine manual and clerical jobs decline.

Artificial Intelligence and the Economy

2020

Federal Reserve Bank of Dallas

Highlights that AI and GPTs automate a wide range of tasks, particularly in manufacturing and services, leading to job displacement but also the creation of new roles in data analysis, AI training, and tech support.

Technology, Jobs, and Inequality: A Survey of the Evidence

2018

Economic Policy Institute

Reviews evidence that while GPTs like AI and robotics reduce demand for low-skill jobs, they lead to greater inequality, with job growth concentrated in high-skill and managerial sectors.

Labor Market Polarization and Technological Change: A Historical Perspective

2016

National Bureau of Economic Research (NBER)

Finds that technological advancements, including GPTs, result in labor market polarization: growth in high-skill jobs and decline in middle-skill jobs, with a hollowing out of mid-level occupations.

Automation, Skills, and the Future of Work

2021

Brookings Institution

Concludes that GPT adoption accelerates demand for highly skilled labor (in areas like data science, programming), while jobs in routine sectors such as manufacturing and transportation face displacement.

The Effects of AI and Automation on Jobs and Wages: A Global Perspective

2023

OECD

Examines global trends in AI and automation adoption, indicating that the adoption of GPTs displaces low-wage jobs but creates more skilled positions in technology management, software development, and AI maintenance.

How Automation Affects Occupations: Assessing the Task Content of Occupations

2019

Quarterly Journal of Economics

Analyzes how automation via GPTs impacts occupations by reducing routine, repetitive tasks, but increasing demand for creative, problem-solving, and technical roles.

Digital Transformation and the Future of Jobs

2020

World Economic Forum

Provides evidence that GPTs spur job growth in technology-driven sectors (e.g., software development, cybersecurity) but reduce demand for jobs in routine, manual, and clerical functions.

Technological Change and the Labor Market

2017

Journal of Labor Economics

Identifies that technological progress, including GPTs, leads to increased job turnover and retraining requirements, with displaced workers often finding new roles in technology and service sectors.

Technological Shocks and Labor Markets: Evidence from GPTs and AI

2022

Review of Economics and Statistics

Examines the effect of GPTs on labor markets and finds a clear correlation between GPT adoption and shifts in employment toward knowledge-based industries, with a decline in jobs that involve manual labor.

The Impact of AI and Robotics on Labor Markets: A Review of Empirical Evidence

2018

International Journal of Robotics Research

Reviews empirical evidence on the impacts of AI and robotics (a form of GPTs) on job displacement in manufacturing and logistics, while showing job growth in healthcare, software, and robotics management.


Monday, October 7, 2024

Even Before AI, Data Center "Net Zero" Was an Impossible Goal, for Most

It is in some ways refreshing when realistic assessments are made about potential progress towards climate goals, as we are unlikely to meet the current goals in any case, as Eric Schmidt, former Google CEO, notes. “We're not going to hit the climate goals anyway,” he bluntly said. 


We might as well be realistic about how much can be done, in terms of carbon and other emissions. Nearly every stated goal we see is unlikely to be met. We might not prefer that outcome, but that seems to be the reality, so we might as well work on what can be accomplished, rather than pursuing unworkable plans that already are destined to fail.


And that applies to data center sustainability as to all other sustainability goals. In other words, present net zero goals, to say nothing of negative emissions profiles, are impossible in the artificial intelligence era. 


Of course, any person, company or nation can choose not to use AI, but that will not prevent climate goal failure. That would happen even in the absence of any additional AI processing activities.  


Climate Target

Organization/Agreement

Target Deadline

Goal

Current Progress and Likelihood of Success

Net-Zero Global Carbon Emissions

Paris Agreement (2015)

2050

Limit global warming to below 2°C, preferably 1.5°C above pre-industrial levels

Unlikely under current policies. Global emissions are still rising, and only a few countries have detailed roadmaps to achieve net-zero by 2050. A massive scale-up in renewable energy, electrification, and industrial reform is required.

Reduce Emissions by 45% from 2010 levels

Paris Agreement (IPCC SR15)

2030

Achieve 1.5°C temperature increase limit

Unlikely. While some regions (EU) have committed to reductions, global emissions need to fall by 7.6% annually to meet this target, but they are still rising.

Phase out coal power plants

Various pledges, COP26

2030s (developed); 2040s (developing)

End reliance on coal as a primary energy source

Mixed. Coal usage has been reduced in the EU and US, but major emitters like China and India continue to expand coal power. Global coal phase-out is slow.

Methane emissions reduction by 30% from 2020 levels

Global Methane Pledge (COP26)

2030

Reduce methane emissions to limit short-term warming

Uncertain. Methane emissions from agriculture and oil/gas remain high, but new policies to detect and reduce leaks in energy and industry are promising.

100% sales of zero-emission vehicles (ZEVs)

COP26 ZEV Declaration

2040 globally; 2035 for major markets

End sales of internal combustion vehicles

Possible in some regions. Several countries (UK, EU) have set ambitious bans on fossil-fuel vehicles, but progress in developing markets is slower.

Halting deforestation and land degradation

Glasgow Leaders’ Declaration (COP26)

2030

Stop deforestation to protect carbon sinks

Unlikely. Deforestation continues in regions like the Amazon and Congo. Efforts to reduce illegal logging are hindered by political and economic factors.

Finance for climate mitigation and adaptation

Paris Agreement and UNFCCC

$100 billion per year by 2020, extended through 2025

Provide climate financing for developing countries

Behind schedule. Developed nations have not fully met this target. The annual climate finance commitment remains short of the promised $100 billion.

Energy from renewable sources at 60-80%

Various (IEA, IPCC reports)

2050

Global energy generation from renewables

Possible but challenging. The renewable energy capacity is growing rapidly (solar, wind), but fossil fuels still dominate energy consumption globally.

Achieving Circular Economy principles

EU Circular Economy Action Plan, UN SDGs

2030

Reduce waste, increase recycling and efficiency

Possible in some regions. The EU leads in circular economy initiatives, but widespread adoption globally is still limited by lack of infrastructure and policy.

Ocean Protection: 30x30 Initiative

High Ambition Coalition (Biodiversity)

2030

Protect 30% of the world's oceans

Uncertain. Ocean protection commitments are increasing, but enforcement of protected areas and addressing overfishing remain major challenges.

Climate Resilient Infrastructure

Paris Agreement, IPCC

Ongoing

Build resilient infrastructure to withstand climate impacts

Lagging. Many countries lack adequate infrastructure planning for climate resilience. Investments in adaptation are growing but still insufficient.

Sunday, October 6, 2024

Yes, Virginia, You Can Yell "Fire" in a Crowded Theater

As it turns out, one actually can lawfully “yell ‘fire’ in a crowded theater,” the traditional example of a limitation of free speech protections under the First Amendment to the U.S. Constitution.


When U.S. politicians support arguments for greater censorship, they often argue that such First Amendment rights are restricted. The common refrain is that one cannot “yell ‘fire’ in a crowded theater” or that “misinformation” or “hate speech” are similarly not protected.


But many would argue such interpretations are indeed calls for restrictions (violations) of the First Amendment to the U.S. Constitution. Since the time of the Supreme Court’s Schenck v. U.S. decision, where the phrase “shouting ‘fire’ in a crowded theater first emerged, courts have ruled that incendiary, distasteful, rude speech actually is protected.


Perhaps the clearest clarification of Schenck is Brandenburg. Unless immediate illegal action is intended and likely, even “yelling ‘fire’ in a crowded theater” is protected speech. 


The other obvious problem is that “misinformation” or “hate speech,” even if odious, inflammatory or believed to be false, still is protected speech. Ideas “one hates” remain the test of free speech protections. 


Case

Year

Ruling Summary

Relation to 'Yelling Fire' Metaphor

Schenck v. United States

1919

Upheld conviction for distributing anti-draft pamphlets during WWI. Established that speech presenting a "clear and present danger" could be restricted.

Justice Holmes introduced the famous metaphor of falsely shouting "fire" in a crowded theater.

Abrams v. United States

1919

Upheld convictions under the Espionage Act for distributing anti-war leaflets.

Built upon the "clear and present danger" standard, but Holmes dissented, moving towards more speech protection.

Gitlow v. New York

1925

Upheld conviction of a socialist for advocating the violent overthrow of the government.

Suggested that even speech not directly causing harm could be limited if it had the potential to incite violence.

Dennis v. United States

1951

Upheld convictions of communist leaders advocating for the violent overthrow of the U.S. government.

Argued that advocating dangerous ideas, even without immediate action, could be restricted.

Yates v. United States

1957

Ruled that advocating abstract doctrine (such as communism) is protected speech, unless it incites illegal action.

Limited previous rulings, clarifying that abstract ideas are protected unless linked to action.

Brandenburg v. Ohio

1969

Overturned conviction of a KKK leader for inflammatory speech. Held that speech is protected unless it incites imminent lawless action.

Effectively replaced the "fire in a crowded theater" metaphor. Protected even dangerous speech unless immediate illegal action is intended and likely.

Texas v. Johnson

1989

Ruled that flag burning constitutes protected free speech under the First Amendment.

Protected highly offensive speech, further distancing from "fire in a theater" metaphor.

Snyder v. Phelps

2011

Protected Westboro Baptist Church's right to protest at military funerals, ruling that offensive speech on public issues is protected.

Even offensive and distressing speech was deemed protected. Shows broad protection for public speech.


The phrase "freedom for the idea one hates" is closely associated with Justice Oliver Wendell Holmes and Justice Louis Brandeis, two influential figures in the development of free speech jurisprudence in the early 20th century. 


In his famous dissent in United States v. Schwimmer (1929), Holmes said "If there is any principle of the Constitution that more imperatively calls for attachment than any other, it is the principle of free thought—not free thought for those who agree with us but freedom for the thought that we hate."


The point is that free speech requires freedom for “highly offensive” or “controversial” speech. Without tolerance for such speech, the government could censor any speech that threatens its interests.


The phrase "Yes, Virginia" The phrase "Yes, Virginia" comes from a famous editorial published in The New York Sun on September 21, 1897, in response to a letter from an 8-year-old girl named Virginia O'Hanlon. Virginia had written to the newspaper asking whether Santa Claus really existed, because some of her friends had told her he did not.

Her letter read:

"Dear Editor: I am 8 years old.
Some of my little friends say there is no Santa Claus.
Papa says, 'If you see it in The Sun, it’s so.'
Please tell me the truth, is there a Santa Claus?"

The editorial was written by Francis Pharcellus Church, a veteran journalist. His response, titled "Yes, Virginia, there is a Santa Claus," became one of the most famous newspaper editorials in American history.

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