52 Weeks of Cloud

No Dummy, AI Isn't Replacing Developer Jobs

Episode Summary

Critical examination of false claims about AI replacing software developers. Six key factors explain job losses: non-productive employees, low-skilled developers, basic automation, outsourcing, routine corporate layoffs, and deceptive marketing.

Episode Notes

Extensive Notes: "No Dummy: AI Will Not Replace Coders"

Introduction: The Critical Thinking Problem

• America faces a critical thinking deficit, especially evident in narratives about AI automating developers' jobs
• Speaker advocates for examining the narrative with core critical thinking skills
• Suggests substituting the dominant narrative with alternative explanations

Alternative Explanation 1: Non-Productive Employees

• Organizations contain people who do "absolutely nothing"
• If you fire a person who does no work, there will be no impact
• These non-productive roles exist in academics, management, and technical industries
• Reference to David Graeber's book "Bullshit Jobs" which categorizes meaningless jobs:
  • Task masters
  • Box tickers
  • Goons
• When these jobs are eliminated, AI didn't replace them because "the job didn't need to exist"

Alternative Explanation 2: Low-Skilled Developers

• Some developers have "very low or no skills, even negative skills"
• Firing someone who writes "buggy code" and replacing them with a more productive developer (even one using auto-completion tools) isn't AI replacing a job
• These developers have "negative value to an organization"
• Removing such developers would improve the company regardless of automation
• Using better tools, CI/CD, or software engineering best practices to compensate for their removal isn't AI replacement

Alternative Explanation 3: Basic Automation with Traditional Tools

• Software engineers have been automating tasks for decades without AI
• Speaker's example: At Disney Future Animation (2003), replaced manual weekend maintenance with bash scripts
• "A bash script is not AI. It has no form of intelligence. It's a for loop with some conditions in it."
• Many companies have poor processes that can be easily automated with basic scripts
• This automation has "absolutely nothing to do with AI" and has "been happening for the history of software engineering"

Alternative Explanation 4: Narrow vs. General Intelligence

• Useful applications of machine learning exist:
  • Linear regression
  • K-means clustering
  • Autocompletion
  • Transcription
• These are "narrow components" with "zero intelligence"
• Each component does a specific task, not general intelligence
• "When someone says you automated a job with a large language model, what are you talking about? It doesn't make sense."
• LLMs are not intelligent; they're task-based systems

Alternative Explanation 5: Outsourcing

• Companies commonly outsource jobs to lower-cost regions
• Jobs claimed to be "taken by AI" may have been outsourced to India, Mexico, or China
• This practice is common in America despite questionable ethics
• Organizations may falsely claim AI automation when they've simply outsourced work

Alternative Explanation 6: Routine Corporate Layoffs

• Large companies routinely fire ~3% of their workforce (Apple, Amazon mentioned)
• Fear is used as a motivational tool in "toxic American corporations"
• The "AI is coming for your job" narrative creates fear and motivation
• More likely explanations: non-productive employees, low-skilled workers, simple automation, etc.

The Marketing and Sales Deception

• CEOs (specifically mentions Anthropic and OpenAI) make false claims about agent capabilities
• "The CEO of a company like Anthropic... is a liar who said that software engineering jobs will be automated with agents"
• Speaker claims to have used these tools and found "they have no concept of intelligence"
• Sam Altman (OpenAI) characterized as "a known liar" who "exaggerates about everything"
• Marketing people with no software engineering background make claims about coding automation
• Companies like NVIDIA promote AI hype to sell GPUs

Conclusion: The Real Problem

• "AI" is a misnomer for large language models
• These are "narrow intelligence" or "narrow machine learning" systems
• They "do one task like autocomplete" and chain these tasks together
• There is "no concept of intelligence embedded inside"
• The speaker sees a bigger issue: lack of critical thinking in America
• Warns that LLMs are "dumb as a bag of rocks" but powerful tools
• Left in inexperienced hands, these tools could create "catastrophic software"
• Rejects the narrative that "AI will replace software engineers" as having "absolutely zero evidence"

Key Quotes

"We have a real problem with critical thinking in America. And one of the places that is very evident is this false narrative that's been spread about AI automating developers jobs."

"If you fire a person that does no work, there will be no impact."

"I have been automating people's jobs my entire life... That's what I've been doing with basic scripts. A bash script is not AI."

"Large language models are not intelligent. How could they possibly be this mystical thing that's automating things?"

"By saying that AI is going to come for your job soon, it's a great false narrative to spread fear where people worry about all the AI is coming."

"Much more likely the story of AI is that it is a very powerful tool that is dumb as a bag of rocks and left into the hands of the inexperienced and the naive and the fools could create catastrophic software that we don't yet know how bad the effects will be."