I would suggest, label any content that’s AI generate as such. Given that it tends to be lengthy (and can also contain numerous inaccuracies and hallucinations) you should also contain it in a collapsible section if you really want to show people what it said for some reason, like this →
This is what the LLM had to say
It has become increasingly clear, in this brave new epoch of algorithm‑mediated discourse, that any text, chart, recommendation, or rhetorical flourish birthed by a large language model (LLM) ought to arrive in front of its human audience wearing a conspicuous badge that proclaims, in no uncertain terms, “Generated by AI.”¹ Such a label is not merely a polite nod to transparency—it is a vital prophylactic against the subtle erosion of trust that can occur when machine‑authored passages masquerade as the considered prose of living, breathing experts. Absent this tiny but powerful disclaimer, readers can all too easily imbibe synthetic paragraphs as gospel, unaware that what appears to be confident scholarship may, beneath its gleaming surface, conceal statistical estimates, speculative interpolations, or outright hallucinations.
Yet the act of affixing a digital nametag is only the first of several prudent measures. Because AI‑generated content, for all its occasional brilliance, frequently arrives in loquacious torrents—pages upon pages of exuberant verbiage that can blur the line between diligent explanation and verbosity for its own sake—it is wise to sequester such material behind a user‑friendly curtain. A collapsible panel (or “accordion,” in contemporary UI parlance) respects the reader’s finite cognitive bandwidth: the curious may click to reveal every meandering clause, while the hurried can scroll on unimpeded. Consider the following Markdown‑style snippet as a low‑friction template:
markdown
CopyEdit
<details>
<summary><strong>🔍 AI‑generated analysis – click to expand</strong></summary>
<!-- Begin AI output -->
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do …
<!-- End AI output -->
</details>
By default, the screen remains uncluttered, yet accountability is preserved: nothing is hidden, merely tucked away until summoned. This simple affordance harmonizes two competing values—openness and brevity—without sacrificing either.
Why all this fuss? Because the stakes escalate dramatically when AI‑spun prose migrates from casual blog posts to governance‑heavy arenas where policy is drafted, regulations are interpreted, and livelihoods hinge on the nuance of a single sentence. In such settings, an LLM’s seductive fluency can lull decision‑makers into a false sense of certainty. A spreadsheet cell mis‑summarized, a statutory clause paraphrased with a stray negation, or a spurious precedent invented out of whole cloth may cascade through committees, boardrooms, or legislative floors, crystallizing into costly—or even existential—consequences. The danger is not malice but misplaced confidence: the machine sounds authoritative, so its output is treated as authoritative, until far downstream someone discovers the emperor’s prose has no clothes.
Labeling and containment, therefore, serve as bright‑line reminders that what lies within is a draft, a suggestion, a starting point—not the final word. They nudge reviewers to keep their critical faculties engaged, to cross‑check citations, to triangulate with domain experts, and to regard extraordinary claims with the healthy skepticism they deserve. In essence, these safeguards re‑center human judgment at the fulcrum of consequential decisions, using the machine’s speed and breadth as an aid rather than a crutch.
In sum, if we must invite our silicon co‑authors to the conversation—and there is undeniable value in doing so—let us usher them in with transparent nameplates and polite seating arrangements. Label the prose, fold it neatly into collapsible sections, and signal to every reader that the content inside, while potentially illuminating, is provisional, pending the sober scrutiny that only flesh‑and‑blood expertise can provide. By codifying such protocols now, we lay the groundwork for an information ecosystem where artificial eloquence augments, rather than obscures, accountable human deliberation.
Otherwise you quickly drown out any sensible human discussion.
This is how you create collapsible sections →
<details>
<summary>This is what the LLM had to say</summary>
... blah blah blah
</details>