A Few Unpopular Opinions about AI

When to tell the machine to STFU

In a conversation with Jason Howell for his upcoming AI podcast on the TWiT network, I came to wonder whether ChatGPT and large language models might give all of artificial intelligence cultural cooties, for the technology is being misused by companies and miscast by media such that the public may come to wonder whether they can ever trust the output of a machine. That is the disaster scenario the AI boys do not account for.

While AI’s boys are busy thumping their chests about their power to annihilate humanity, if they are not careful — and they are not — generative AI could come to be distrusted for misleading users (the companies’ fault more than the machine’s); filling our already messy information ecosystem with the data equivalent of Styrofoam peanuts and junk mail; making news worse; making customer service even worse; making education worse; threatening jobs; and hurting the environment. What’s not to dislike?

Below I will share my likely unpopular opinions about large language models — how they should not be used in search or news, how building effective guardrails is improbable, how we already have enough fucking content in the world. But first, a few caveats:

I do see limited potential uses for synthetic text and generative AI. Watch this excellent talk by Dr. Emily M. Bender, one of the authors of the seminal Stochastic Parrots paper and a leading critic of AI hype, suggesting criteria for acceptable applications: cases where language form and fluency matter but facts do not (e.g., foreign language instruction), where bias can be filtered, and where originality is not required.

Here I explored the idea that large language models could help extend literacy for those who are intimidated by writing and thus excluded from discourse. I am impressed with Google’s NotebookLM (which I’ve seen thanks to Steven Johnson, its editorial director), as an augmentative tool designed not to create content but to help writers organize research and enter into dialog with text (a possible new model for interaction with news, by the way). Gutenberg can be blamed for giving birth to the drudgery of bureaucracy and perhaps LLMs can save us some of the grind of responding to it.