Here is an exchange with ChatGPT, published prematurely it seems, that demonstrates how the LLM seems to have adopted a profile of my interests from uploaded files and previous threads. Referring to my book “AI and Language in the Urban Context,” I asked: “In the book I make reference to ‘revelation.’ It’s from concepts by Heidegger…More
Category Archives: Artificial Intelligence
Beyond urban metrics
In AI and Language in the Urban Context, I make the case that cities are substantially linguistic entities, their social, cultural, and material dimensions shaped and sustained through conversations. As large language models (LLMs) exert increasing influence within public life, they not only automate services but contribute to these urban conversations. The AI Index Report 2025 that…More
Urban AI
“Everybody’s talking about AI!” This week’s joke is that the US Education Secretary spoke enthusiastically about the introduction of A1 into early schooling. A1 is a brown sauce, similar to HP sauce in the UK. Contrarily, the Stanford AI Index 2025 Annual Report shows that people are now more aware of AI, particularly large language…More
Mobile AI does fieldwork
My book came out this week: AI and Language in the Urban Context published open access (i.e. free to download) by Routledge. In that book I advance the case that places and spaces are enjoyed, appreciated, resisted, interpreted and even created through language — including conversations. LLM applications are evolving constantly. It’s feasible to think…More
The future of writing
A well-read academic colleague of mine once remarked that books that become important in the intellectual sphere are generally “well written.” That observation could apply to novels, fiction, non-fiction, popular science, academic books or any other genre. The judgement about what makes writing “good” presumably includes the quality of its arguments, messages, narrative content, but…More
Evidence and absurdity
In the previous posts I recalled five categories of design explanation. I used the innocuous example of deciding to insert a large window into a living room. I explored how a client/reader might regard various explanations as either sensible or absurd. I wanted to avoid the language of truth and falsity, arguing that decisions and…More
Absurdum explicandum
Following my previous past on different modes of explanation, I was interested in how an audience would decide that an explanation was inadequate, did not make sense or was full of errors. Avoiding the language of truth and falsity, I asked NotebookLM: “Please mirror these five categories of explanation with examples of explanations that most…More
Explain this …
In my previous post I explored how LLMs provide explanations of the “reasoning” by which they produce their outcomes (i.e. responses, answers, decisions). At least in their current iteration, platforms such as ChatGPT are tuned to generate an explanation independently of the process by which they came up with their response in the first place.…More
The meta-reasoning illusion
The ability of an LLM to provide an account of the processes by which it came up with its results, as in the inventory table I showed in the last posting, is indeed convincing. But apparently it is an “illusion.” I can’t yet find an article on the subject, so I have come to rely…More
AI explains itself (again)
I’m just back from a holiday in Malta. Two AI events entered my awareness. The first was meeting an American language teacher who said she had used AI to find her a “charming B&B” just outside Valletta. The second event was news that Elon Musk had sent an email to all US Federal employees to…More