ASIA
21 August 2026
The AI Con
Demystifying AI
Artificial Intelligence (AI) is a marketing term which refers to a group of unrelated technologies, according to Alex Hanna and Emily M. Bender in their book The AI Con: How to Fight Big Tech’s Hype and Create the Future We Want
Stop calling it “AI” and start calling it what it is – automation – once exhorted Emily M. Bender. Reframing AI as automation rather than a kind of intelligence strips away the mystique and returns us to the real questions. Many “large language models” (LLMs) promise intelligence but deliver automation in disguise. They do not possess minds or real understanding, but function instead as automated pattern-matching tools.
The AI label creates a false sense of an inevitable godlike entity. When you lump together things like – chat GPT, image production machines like Dolly and Midjourney, self-driving cars, automated decision systems, spell check and the systems that play Go and chess – and say all of that is one thing, AI, then you are more likely to believe that it can probably do anything.
What Silicon Valley frames as a revolution in thinking, Bender and Hanna reframe as more of the same – an intensification of automated systems. Automated decision-making systems have been in place for decades now. What is new on the block are LLMs which started in 2018.
The most common LLMs – Gemini, Chad GPT, Claude – are built on absolutely enormous, poorly curated and undisclosed training sets. We don't really know what's in there. We don't have the ability to understand the kinds of biases that these LLMs embody.
If AI’s importance is overhyped, why do so many believe it? After all, political leaders are all in, believing everything Silicon Valley says, and offering government support. It is perhaps not surprising that people clutch at something that could solve all of the crises that we're facing right now. And of course there is lots of money to be made for “AI boosters”. Major technology companies use exaggerated AI claims to justify mass data scraping and surveillance, and firing workers.
Stop calling it “AI” and start calling it what it is – automation – once exhorted Emily M. Bender. Reframing AI as automation rather than a kind of intelligence strips away the mystique and returns us to the real questions. Many “large language models” (LLMs) promise intelligence but deliver automation in disguise. They do not possess minds or real understanding, but function instead as automated pattern-matching tools.
The AI label creates a false sense of an inevitable godlike entity. When you lump together things like – chat GPT, image production machines like Dolly and Midjourney, self-driving cars, automated decision systems, spell check and the systems that play Go and chess – and say all of that is one thing, AI, then you are more likely to believe that it can probably do anything.
What Silicon Valley frames as a revolution in thinking, Bender and Hanna reframe as more of the same – an intensification of automated systems. Automated decision-making systems have been in place for decades now. What is new on the block are LLMs which started in 2018.
The most common LLMs – Gemini, Chad GPT, Claude – are built on absolutely enormous, poorly curated and undisclosed training sets. We don't really know what's in there. We don't have the ability to understand the kinds of biases that these LLMs embody.
If AI’s importance is overhyped, why do so many believe it? After all, political leaders are all in, believing everything Silicon Valley says, and offering government support. It is perhaps not surprising that people clutch at something that could solve all of the crises that we're facing right now. And of course there is lots of money to be made for “AI boosters”. Major technology companies use exaggerated AI claims to justify mass data scraping and surveillance, and firing workers.