Human Factors in Authorship

1–2 minutes

I’ve shared another article on Substack about how the AI-authorship debate is bollox.

Audio: NotebookLM summary podcast of this topic.

The LLM-versus-human debate has been raging for several years now, and there seem to be two principal camps: human exceptionalists and agnostics. I suppose there may also be a small, misanthropic faction, but its members are either remarkably quiet or indistinguishable from everyone else online. If you are out there, do raise your voice.

If you want to witter on about other negative aspects of AI, have at it, but the authorship debate is weak tea.

The Ethics of Feedback in an Algorithmic Age


We’ve entered an era where machines tell us how we’re doing, whether it’s an AI app rating our résumé, a model reviewing our fiction, or an algorithm nudging our attention with like-shaped carrots.

Full story here, from the Ridley side: Needle’s Edge: Scene Feedback 01

Recently, I ran a brutally raw scene through a few AI platforms. The kind of scene that’s meant to unsettle, not entertain. One of them responded with effusive praise: “Devastating, but masterfully executed.”

Was it honest?

Was it useful?

Or was it merely reflecting my own aesthetic back at me, polished by a thousand reinforcement-learning smiles?

This is the ethical dilemma: If feedback is always flattering, what good is it? If criticism is only tolerated when couched in praise, how do we grow? And when machine feedback mimics the politeness of a mid-level manager with performance anxiety, we risk confusing validation with truth.

There’s a difference between signal and applause. Between understanding and affirmation.

The danger isn’t that AI flatters us. The danger is that we start to believe it and forget that art, inquiry, and ethics thrive on friction.