Sunday, July 6, 2025

Computing Always Has Caused Job Losses: Why Would AI be Different?

Since all prior instances of computing applied to work have eliminated some number of jobs, it only makes sense to predict that artificial intelligence also will do so. But among the questions is the issue of incidence: where the job losses will occur.


Historically, the introduction of computers and automation led to the reduction or elimination of many routine, repetitive, or data-driven job functions. And though we might be tempted to think the jobs were “blue collar,” most of the losses affected “white collar” workers in offices. 


AI seems destined to become a substitute for a wider range of “routine tasks” but also is ;going to affect more complex cognitive work as well. 


Job Title/Function

Cognitive Tasks

Risk from AI

AI Substitution

Data Analyst/Market Researcher

Data analysis, report generation, forecasting

AI excels at pattern recognition, data processing, and generating insights from large datasets

Automated data analytics, predictive modeling 1,2,3

Paralegal/Legal Assistant

Document review, legal research, drafting

AI can rapidly review documents, extract information, and draft legal texts

AI-powered document review, legal research bots 1,2,3

Content Writer/Copywriter

Article writing, editing, content creation

Generative AI can produce high-quality written content at scale

Automated content generation, editing tools 1,2,4

Entry-Level Accountant/Financial Analyst

Bookkeeping, financial reporting, auditing

AI automates repetitive calculations, reconciliations, and report generation

Automated bookkeeping, financial analysis 1,4,2

Customer Service Representative

Responding to inquiries, troubleshooting

AI chatbots and virtual assistants handle routine queries and support tasks

AI chatbots, automated helpdesks 2,4,3

Junior Software Developer

Writing/debugging code, code review

AI can generate, test, and debug code with increasing accuracy

AI code generation, bug detection 2,3

HR/Administrative Assistant

Scheduling, resume screening, workflow management

AI automates scheduling, candidate screening, and routine admin tasks

Automated scheduling, resume parsing 2,4

Middle Manager (Routine Tasks)

Report consolidation, performance tracking

AI can aggregate data, generate reports, and monitor KPIs

Automated  reporting, dashboarding 5,4

Translator

Language translation, localization

AI models can translate text and speech across languages with high accuracy

Machine translation, localization tools 6,7

Insurance Underwriter

Risk assessment, policy review

AI can analyze risk factors and automate policy decisions

Automated risk analysis, policy generation 4


Routine, structured cognitive tasks are most vulnerable, especially those involving data processing, document review, and standardized content creation. We might already guess that entry-level and support roles in law, finance, marketing, and administration face the highest risk.

Jobs requiring human judgment,  creativity or complex interpersonal skills are less exposed, but even these may see significant transformation as AI tools become more sophisticated.

The history of applied computerization also set that pattern.


Job Function

Technology

Impact/Change

Era

Source(s)

Typis, /Secretary

Word Processing, PCs

Drastic reduction; executives self-type documents

1980s–1990s

1,3

Data Entry Clerk

Databases, Automation

Largely automated; fewer manual data entry roles

1980s–2000s

2,6

Bookkeeper, Payroll Clerk

Accounting Software

Routine tasks automated; fewer clerical jobs

1980s–2000s

4,5,1,3

Switchboard Operator

Digital Telephony

Obsolete; replaced by automated systems

1970s–1980s

2,3

Travel Agent

Online Booking Platforms

Reduced demand; self-service travel arrangements

1990s–2000s

4,6

Paralega, /Legal Assistant

AI Document Review

AI handles research, document review

2020s–

6,10

Financial Analyst, Trader

AI, Algorithmic Trading

Automated analysis and trading

2010s–

7,8,6

Customer Service Rep

Chatbots, AI Assistants

AI handles routine inquiries

2010s–

1,11,2

Content Writer, Editor

Generative AI

AI drafts articles, reduces junior writing roles

2020s–

7,6,10

Junior Software Developer

AI Code Generation

AI writes/debugs code, reducing entry-level roles

2020s–

9,10


Saturday, July 5, 2025

How Long Before Consumers Rebel Against Higher Electricity Rates Driven by Data Center Consumption?

It has been a couple of decades since the “rate base” was a key driver of revenues for U.S. telcos, in large part because the services affected by the rate base have declined so much (voice services). 


But the rate base is going to continue to affect consumer electricity prices for the foreseeable future, as additional power generation and transmission capacity is built to support higher demand for power to support data centers and artificial intelligence operations. 


In some states, such as Virginia, it is possible that rates could rise substantially, as much as 70 percent from current levels. California and Texas are additional states where price hikes could be higher.  


But those sorts of shocks are virtually certain to raise calls for reform of the rate base rules, as it is going to be said, with good reason, that consumers are subsidizing the operations of data center owners and operators. 


But that has been a rare approach. Past rate base reforms have rarely directly targeted large customer-driven infrastructure costs when allocating costs among customer classes. 


Traditionally, the costs of new infrastructure investments (generation, transmission, or distribution) have been spread across all ratepayers through general rates, regardless of which customer category caused the need for the investment.


Many observers and electricity customers will not be aware of such precedents, and are certain to be shocked by the growing cost of electricity. 


The rate base is the total value of a utility’s assets (power plants, transmission lines, and distribution infrastructure) used to provide service to customers, and forms the basis for setting the rates that utilities can charge their customers.


So the basic formula for setting consumer prices is the rate base times the allowed rate of return) plus operating expenses, with a return for investors as well, as a practical matter. 


Data centers matter because the common costs of new generation capacity and transmission can be charged, and will be charged, to all customers. 


If data centers currently account for four percent to five percent  of U.S. electricity consumption, but grow to 12 percent  by 2028, and current rate base rules do not change, that cost will be borne by all ratepayers.


Computing Always Has Caused Job Losses: Why Would AI be Different?

Since all prior instances of computing applied to work have eliminated some number of jobs, it only makes sense to predict that artificial i...