With the release of the AI 2027 report, the rhetoric or storytelling is amping up:

The AIs of 2024 could follow specific instructions: they could turn bullet points into emails, and simple requests into working code. In 2025, AIs function more like employees…

[by 2026], AI has started to take jobs, but has also created new ones. The stock market has gone up 30% in 2026, led by OpenBrain, Nvidia, and whichever companies have most successfully integrated AI assistants.

The job market for junior software engineers is in turmoil: the AIs can do everything taught by a CS degree, but people who know how to manage and quality-control teams of AIs are making a killing. Business gurus tell job seekers that familiarity with AI is the most important skill to put on a resume. Many people fear that the next wave of AIs will come for their jobs; there is a 10,000 person anti-AI protest in DC. (source: AI 2027)

Is It All Fake?

While that may be fiction, while prepping for a workshop session, I spotted this graph by Ethan Mollick:

I have to pair it with these two takes from Lester Mapp and Paul Roetzer. Paul has asserted (stridently, passionately) that as costs for AI drop, there has to be an impact on jobs, especially those being done by average workers.

 ZDnet’s Lester Mapp is making:

The days of being average and just getting by are officially over. 😖

Once upon a time, a team was structured like this:

• 1x senior level
• 4x mid level
• 8x junior level

But that’s rapidly shifting to something more like this:

• 1x senior level
• 4x mid level
• AI agents

AI hasn’t taken the junior-level jobs directly. Instead, what’s really happening is that mid-level employees have become dramatically more productive by eliminating mundane, repetitive, or tedious tasks. Thanks to AI, mid-level workers get 13 hours of productivity out of a standard 8-hour day. 

Is it the death of the average worker?

The Average Worker Faces A Coming Sunset

As Paul Roetzer points out in this podcast, Episode 141: The AI Timeline is Accelerating, the workplace is made up of a lot of average workers. Businesses and teams (with A, B, C players) need to ask, “Are AI models at the B-player, or average human level?” Roetzer makes the point like Lester above does that people doing “simply” average work can be replaced by Competent AI…we don’t need to get to the “expert” or “Ph.D” level AI.

He drops some quotes from Demis Hassabis (prob this one with Hannah Fry interviewing Demis about AGI) then cites the levels of AGI:

• Level 0: No AI
  • Narrow Non-AI: Calculator software; compiler
  • General Non-AI: Human in the loop computing, e.g. Amazon Mechanical Turk
• Level 1: Emerging – equal or somewhat better than an unskilled human
  • Emerging Narrow AI: Simple rule-based systems
  • Emerging AGI: ChatGPT, Llama, Gemini
• Level 2: Competent – at least 50th percentile of skilled adults
  • Competent Narrow AI: Toxicity Detectors, Smart Speakers like Siri, Alexa, Google Assistant, Watson, short essay writing, simple coding
  • Competent: Not yet achieved
• Level 3: Expert – at least 90th percentile of skilled adults.
  • Expert Narrow AI: spelling and grammar checkers such as Grammarly; Imagen
  • Expert AGI: not yet achieved
• Level 4: Virtuoso – at least 99th percentile of skilled adults
  • Virtuoso Narrow AI: Deep Blue, AlphaGO
  • Virtuoso AGI: not yet achieved
• Level 5: Superhuman – outperforms 100% of humans
  • Superhuman Narrow AI: AlphaFold, AlphaZero, StockFish
  • Artificial Superintelligence (ASI): not yet achieved

Moving at the speed of Competence may be the same as mediocrity these days. When average workers can be replaced by AI, should they be?