Showing posts sorted by date for query remote work. Sort by relevance Show all posts
Showing posts sorted by date for query remote work. Sort by relevance Show all posts

Tuesday, October 13, 2026

Technology Does Not Eliminate Human Choice

Technological determinism is a recurrent idea, suggesting that technology is a primary force shaping society. The notion is that once a technology appears, its capabilities and economic logic tend to push society toward particular outcomes. But a survey of Goldman Sachs interns suggests the limits of such thinking. 


About 60 percent of respondents prefer no AI involvement in creative work such as art, music, and books. They are comfortable with some AI assistance for content curation, healthcare, shopping, customer service or personal finance, so long as there is human validation. 


source: Goldman Sachs 


In other words, the survey suggests a human response to AI that is not a simple or passive role, despite much “doomerism” about it. 


To be sure, technology creates possibilities. But that does not necessarily mean it is imperative. The telephone could have eliminated face-to-face meetings, but it didn't. Television could have eliminated newspapers, but it didn't. ATMs could have eliminated bank tellers. The automobile made commuting possible but did not make commuting inevitable.


Calculators changed which mathematical skills were economically valuable, but not lower-order operations. When computation became cheap, computation itself became less economically scarce. The value shifted toward applications, data, organizational knowledge and decisions.


The point is that predictions about deterministic technological outcomes have often been wrong. 



Technology

Deterministic prediction

What actually happened

What it illustrates

Telegraph

Near-instant communication would effectively eliminate the importance of distance and perhaps produce a unified world

Distance became less important for information, but geography, politics, culture and institutions remained extremely important

Technology can reduce one constraint without eliminating others

Telephone

Telephones would largely replace face-to-face interaction

Telephone communication became complementary to physical interaction

People value how interaction occurs, not merely information transfer

Radio

Mass broadcasting would create a common national culture and potentially make older media obsolete

Radio became one medium among many; audiences fragmented and new media emerged

New media usually complement as well as substitute

Television

Television would replace newspapers, radio, books and perhaps traditional education

All survived, although their roles changed substantially

Technologies rarely eliminate an entire human activity simply because they can perform part of it

Automobile

Cheap personal transportation would make cities and mass transit obsolete

Cars produced suburbs and highways, but dense cities, rail and walking remained valuable

Technology interacts with urban design, policy and preferences

Air conditioning

Climate would cease to constrain where people live and work

It transformed settlement patterns, but water, energy, geography, culture and economics continued to matter

Removing one constraint doesn't remove the system of constraints

Nuclear power

Extremely cheap electricity would make energy essentially unlimited and transform society

Nuclear power became important but expensive, politically contested and institutionally constrained

Technical potential ≠ economically or politically realized potential

Computers

Automation would eliminate large portions of clerical and administrative employment

Computers eliminated many tasks but also created enormous new categories of work and increased demand for information-intensive occupations

Productivity and employment aren't mechanically inversely related

ATMs

Banks would need dramatically fewer employees because machines could replace tellers

ATM deployment coincided with changes in branch economics, but banks retained many tellers and expanded some branch networks

Lower cost per transaction can increase total demand

The Internet

Physical retail, newspapers, television and other intermediaries would disappear

They were disrupted, but many adapted; new intermediaries emerged

Disintermediation often produces reintermediation

E-books

Paper books would rapidly disappear

E-books became substantial but physical books remained remarkably persistent

Consumers don't optimize solely for technical efficiency

MP3/digital music

Recorded music would become essentially free and traditional music companies would disappear

Streaming created new subscription and platform models; recorded music remained a major business

New technology changes the business model rather than necessarily destroying the activity

Social media

Universal connectivity would produce greater understanding and democratic consensus

It also produced polarization, fragmentation, communities and entirely new forms of political communication

Technology amplifies social forces rather than determining their direction

Online education

Internet video would make physical universities largely unnecessary

Online education grew enormously, but residential universities remained important for social, credentialing and institutional reasons

Education is an institution, not merely information delivery

Remote work

Once high-quality videoconferencing existed, offices would largely become unnecessary

Remote/hybrid work expanded substantially, but many organizations retained physical workplaces

Work has coordination, social and cultural dimensions

3D printing

Manufacturing would move from centralized factories to individuals producing objects at home

3D printing found important niches, but mass manufacturing remained highly centralized

Unit economics and supply chains matter alongside technical capability


Technology does constrain the choice set, though. Once something becomes dramatically cheaper, faster or more capable, people change their behavior. 


Social media reshapes content production, consumption and value. Automobiles changed the geography of cities.


Artificial intelligence can automate many routine operations. But efficiency is not the only key value for humans. People don't optimize every aspect of life for minimum cost, greatest efficiency or least time. 


Often, value is generated by activity itself. Live music, handmade objects, sports, religious services, face-to-face education, crafts, gardening, cooking and all manner of “live” experiences have intrinsic value, so we keep doing those things. 


So the issue is more “what do you do with more free time?” 


AI might allow us to focus more on purpose, meaning, responsibility, relationships and judgment as the need to spend so much time on instrumental activities decreases. As unfashionable as “religion” might be in some quarters, it is possible its value could become more important. 


Humans make choices, even when technology creates possibilities or conditions. We don't always choose efficiency over other values.


Thursday, September 3, 2026

Study Says AI Reshaping Labor Markets

A new Dallas Federal Reserve study suggests generative artificial intelligence adoption is reshaping the Texas labor market, primarily by reducing demand for some types of work, not so much by eliminating existing positions but by reducing demand for recent college graduates. 


“The most exposed occupations are generally in software development, web design and other computer-heavy occupations,” the report says. “Managers, clerical workers, editors and other white-collar occupations are also subject to some of the highest levels of AI task exposure.”


source: Dallas Federal Reserve


“There is strong evidence that GenAI has decreased labor demand for occupations consisting of tasks that can be performed by these new tools,” the researchers say. Still, “the overall effect on aggregate online job posting behavior thus far has been modest.”


“Recent college graduates, whose unemployment rate rose to unusually high levels during this period of rapid GenAI adoption, are where effects of GenAI on employment and earnings are likely to first appear,” the study suggests. 


So far, AI's labor-market effect is that “fewer people get hired into certain jobs,” rather than “large numbers of existing workers fired from those jobs.” 



Study

Data / period

Main finding

Job impact

Brynjolfsson, Chandar & Chen — “Canaries in the Coal Mine” (Stanford, revised 2026)

ADP payroll data, millions of workers, through June 2026

No widespread economy-wide displacement, but employment of 22–25-year-olds in highly AI-exposed occupations is 19% below the counterfactual. Experienced workers show no comparable gap.

Strong evidence for the hiring channel. The authors say the adjustment occurs primarily through reduced hiring of young workers rather than increased separations. (Stanford Digital Economy Lab)

Hosseini Maasoum & Lichtinger — “Generative AI as Seniority-Biased Technological Change” (Harvard, 2026 revision)

65 million résumés, 280,000+ firms

Junior employment falls following GenAI adoption, particularly in highly exposed occupations; senior employment is largely unchanged.

Decline is driven primarily by slower hiring rather than increased separations. (SSRN)

Tucker — “You're (not) Hired” (U.S. Census, 2026)

Matched employer-employee administrative data

Early-career employment in the most AI-exposed industry/state cells fell 12% over 10 quarters after ChatGPT.

The paper finds the decline in employment was primarily caused by a large decrease in hiring. This is perhaps the clearest administrative-data evidence of the mechanism. (Census.gov)

Liu, Wang & Yu — “Labor Demand in the Shadow of Generative AI” (World Bank, 2026 revision)

285 million U.S. online job postings, 2018–2025

Postings for occupations highly vulnerable to AI substitution fell 9% relative to less-vulnerable occupations, with the differential reaching 15% by the third year.

Direct evidence of reduced labor demand, rather than layoffs. Particularly important because it examines vacancies at enormous scale. (SSRN)

Audoly, Guerin & Topa — New York Fed, “Do Job Postings Show Early Labor-Market Effects of AI?” (2026)

U.S. Lightcast postings

Overall hiring has slowed, but they find little evidence of a distinct AI-driven decline in postings for AI-exposed occupations.

Important counterweight: the aggregate slowdown in postings cannot confidently be attributed to AI. (Liberty Street Economics)

Federal Reserve Board — “AI Adoption and Firms' Job-Posting Behavior” (2026)

Firm/industry AI adoption + job postings

No evidence that firms or industries with greater AI adoption have reduced total job postings.

Suggests that if AI is eliminating some positions, firms may be switching hiring toward other jobs, rather than simply reducing total hiring. (Federal Reserve)

Gimbel, Kendall & Nunn — Yale Budget Lab (2026)

Monthly CPS employment/wage data

After controlling for differences between exposed and unexposed occupations, they find no statistically or economically significant aggregate employment or wage effect.

Again, little evidence of broad existing-job destruction. The effects may be concentrated in particular populations. (The Budget Lab)

Humlum & Vestergaard — “Still Waters, Rapid Currents” (NBER, 2025/26)

Danish administrative records + AI adoption surveys

No detectable effect on earnings or hours, even among early adopters and highly exposed workers. But substantial task restructuring and occupational switching occurred.

Little evidence of job elimination so far. Firms appear initially to be reorganizing work rather than cutting employment. (National Bureau of Economic Research)

Chandar — “Tracking Employment Changes in AI-Exposed Jobs” (2025)

U.S. CPS, Q4 2022–Q1 2025

No substantial aggregate employment/earnings difference in highly exposed occupations, although software and customer-service occupations diverge.

Overall employment effects small; evidence of localized employment declines, not economy-wide displacement. (SSRN)

Frank et al. / related job-posting research summarized by Stanford

U.S. job postings

Several studies find greater declines in postings in AI-exposed occupations. But some declines began before ChatGPT and correlate with interest rates/remote work.

Supports reduced postings, but attribution to GenAI is contested. (Brookings)

“Winners and losers of generative AI” (JEBO, 2025)

Online freelance marketplace

About 10% of postings were judged substitutable by GenAI; demand for those skill clusters fell as much as 50% in short-term roles.

Strong evidence of demand substitution in particular tasks, although aggregate freelance demand did not fall. (ScienceDirect)

PwC 2025 AI Jobs Barometer

Lightcast job postings, 2019–2024

U.S. occupations with greater GenAI exposure experienced substantially slower job-posting growth: roughly 2% vs. 20% for less-exposed occupations.

Strong descriptive evidence of slower demand growth, though not necessarily causal evidence of AI. (PwC)


But trends could, or maybe, should, change over time, as actual job displacement or elimination, plus creation of new jobs, happens. 


Effect

Evidence so far

Mass layoffs caused by GenAI

🔴 Little evidence

Economy-wide employment decline

🔴 Little/no evidence

Reduced total hiring because of AI

🟡 Weak/mixed

Reduced hiring in particular AI-exposed occupations

🟢 Increasing evidence

Reduced entry-level hiring

🟢 Significant evidence, but causality disputed

Reduced job postings in AI-substitutable occupations

🟢 Fairly strong evidence

Task substitution/reorganization

🟢 Strong evidence

Productivity increases without employment reductions

🟢 Strong evidence

Wage effects

🟡 Generally small so far

Long-term displacement

❓ Still largely unknown


On balance, it is possible net job creation could happen, as AI creates new jobs and roles, despite AI-induced reductions. 


Study

Period / data

Main finding

Implication

Autor, Chin, Salomons & Seegmiller, “New Frontiers: The Origins and Content of New Work” (QJE, 2024)

U.S., 1940–2018; ~35,000 Census occupations

About 60% of employment in 2018 was in occupations that did not exist in 1940. New work emerged alongside technological change, particularly in professional and service occupations after 1980. (National Bureau of Economic Research)

Perhaps the strongest evidence that technology doesn't simply redistribute a fixed number of jobs. It creates new categories of work.

Autor, “Why Are There Still So Many Jobs?” (JEP, 2015)

Historical review

Automation substitutes for labor in particular tasks but also complements workers, raises productivity and output, and increases demand for labor elsewhere. (TopCat)

Explains why technological progress can eliminate particular jobs without eliminating work generally.

Acemoglu & Restrepo, “Automation and New Tasks” (JEP, 2019)

U.S. historical/employment evidence

Automation creates a displacement effect, but creation of new tasks produces a reinstatement effect that raises labor demand. (AEA Publications)

Provides a theoretical framework for understanding why job creation can offset automation.

Acemoglu & Restrepo, “The Race Between Man and Machine” (AER, 2018)

Long-run economic model

Technology that automates existing tasks reduces labor demand, while creation of new tasks has the opposite effect. (American Economic Association)

Net employment depends on the balance between automation and new-task creation.

Bessen, “Automation and Jobs: When Technology Boosts Employment” (2017)

Historical industries, including textiles, steel and automobiles

Industries experiencing rapid productivity growth sometimes experienced employment growth, because lower costs stimulated demand sufficiently to offset labor-saving technology. The OECD reviews this evidence. (OECD)

Lower prices can create enough additional demand to more than compensate for labor-saving technology.

Mann & Puttmann, “Benign Effects of Automation” (2018)

U.S. counties/industries, patent data

Automation innovations were associated with declining manufacturing employment but increasing employment in services. (OECD)

Job destruction and creation can occur in completely different industries and locations.

Autor & Salomons, “Is Automation Labor-Displacing? Productivity Growth, Employment, and the Labor Share” (2018)

28 industries, 19 advanced economies, 1970–2015

Productivity improvements can reduce employment within an industry, but positive spillovers to other industries more than offset those losses. The OECD summarizes the evidence. (OECD)

This is especially important: you shouldn't look only at the industry where automation occurs.

OECD, Employment Outlook 2019

OECD countries, long historical perspective

Despite substantial technological displacement, overall employment has generally grown. The OECD concludes that historically the net effects of major technological revolutions on employment have been positive. (OECD)

Broad institutional review supporting the historical pattern.

OECD, Technology, Productivity and Job Creation (1998)

OECD historical evidence

Technological change destroys jobs in some industries while creating jobs in others; historically the process produced net job creation as new industries replaced old ones and demand expanded. (OECD)

An earlier, broad cross-country examination reaching the same conclusion.

The Dalai Lama is Right