This is my AI statement (as of October 2026), as posted on this site:
Where do I not use AI? I wrote the words you’re reading on this site (aside from possible spelling and grammar checks), but I’ve been using Obsidian, BBEdit, and the WordPress editor, which are all pretty basic from this perspective. Try to find an AI that would generate that awkward sentence. 😜
Where do I use AI? I use Claude to aid in searches, planning, research, and analysis. I also use Claude Code for some aspects of this WordPress theme, extensively in the WordPress plugins I’ve been developing, and for some of the other data visualisations you see here. Any changes will be posted here.
My statement represents what I do and do not do, and I think it speaks pretty clearly for itself. However, I’d like to talk more about the “why” behind my statement and give a little more insight into my thinking and give a few related resources I’ve found useful.
What is my philosophy of AI use?
There are many concise and pithy quotes around that convey a wide spectrum of positions on Generative AI out there, and mine isn’t going to be one of them. My thoughts on “ethical use” below are going to focus on the demand side of the issue. But, I will briefly say that on the supply side I believe that sensible and evidence-based regulation is a prerequisite, and these supply-side issues are distinct from and likely quite a bit more consequential than my “ethical use” perspective below.
Back to the demand side. I believe Generative AI, including chatbots (e.g. NotebookLM/Gemini Notebook) and agents (e.g. Claude Code) can be used ethically, but one must do so mindfully and with the discipline to use these tools to enable and extend one’s own thought, and not as a replacement of the process.
What does this mean in practice?
Write your own words, think critically, and use AI tools to improve, extend, and expedite your processes: use these tools to do more, not think less.
(That’s my attempt at pithy and concise, and it contains a colon and is followed by an explanatory parenthesis.)
An example of AI use to enable and extend rather than replace?
Google’s NotebookLM/Gemini Notebook can be used to house collections of documents that can then be analysed and investigated using plain-language queries. This allows faster, broader search, analysis, and organisation of large libraries of documents. In practice, this could be as simple as asking questions of a library of product manuals and documentation (e.g. What methods are available to change the charging schedule and behaviour of my battery via the solar inverter interface?) to investigating common themes across disparate fields of research and/or sources (e.g. Provide a list of instances of the discussion of, references to, or examples of time of use (ToU) energy pricing in these academic publications, white papers, policy statements, and news items; provide citations.). Tip: read those citations and verify any claims.
I believe these examples enable working with large amounts of data (i.e. scale) with relatively low barriers to entry/learning curve (e.g. plain language queries) that can extend one’s ability to analyse these data and move more quickly (i.e. expedite) to interpretation, understanding and perhaps even action. That’s doing more, not thinking less.
Where do I find challenges and contradictions in my own philosophy and use?
Claude Code and agentic (or the more judgemental vibe) coding. Is using an AI agent to develop a WordPress plugin ethical (when viewed from my premise of extend and enable rather than replace)? This is a tough one, and I think it depends on your perspective on software development. In the beginning there was machine code (at least for my purposes) where we can write instructions (almost) directly to the machine. We can take a step and use a semantically awkward language (e.g. C); it’s easier to write and understand, but we still need a pretty deep understanding of what our code is doing (remember: 1. free(), and 2. your arrays start at 0, not 1 (yes, I checked with Claude to confirm/correct my recollection of memory management in C)). There are more steps along this path from machine code to more and more understandable statements (e.g. the garbage-collecting Java).
What’s at the end of this path? I don’t think it’s necessarily unreasonable to say it’s plain readable (but still precise and structured) language, and from that perspective Claude Code is one hell of a compiler (only if you don’t mind that your compiler is probabilistic rather than deterministic (another double-nested parentheses: Isn’t that called a software developer?)).
If agentic coding is a step down this path, maybe we’re at a point where “software development” and the corresponding “software developer” are no longer accurate (or at least precise) and we need to reframe what we’re actually doing here. Perhaps we need to move down the path alongside our coding agents and along to the vaunted middle management or director roles? If we do all this, maybe we’ve worked out our ethical agita (no, I didn’t use an AI to come up with this word, I took it from Kai Ryssdal) via semantics? 🤔
All that said, I’m not completely convinced here, and I think this is one of the absolutely important and deeply interesting aspects of AI use that we should all engage with and think critically about (and maybe use it to restructure our sentences so they don’t end in prepositions).
References and resources
Below are a few related resources and podcasts I’ve found beneficial for continually thinking through my position and actively deciding how I intend to use these tools now and in the future.
- Center for Humane Technology, Your Undivided Attention (humanetech.com) provides thoughtful and constructive perspectives on technology (including AI) and society.
- Mystery AI Hype Theater 3000 (dair-institute.org) is an overly cynical and often sarcastic critique of AI that is insightful, valuable, and identifies some of the major issues AI presents.
- Intelligent Machines, formerly This Week in Google (twit.tv) gives current AI news and often (and likely unintentionally) cautionary tales of what might happen if you go too far.
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