The use of artificial intelligence to produce internet content raises questions about authorship, originality, and moral responsibility. AI does not act independently. Its outputs reflect the instructions and intentions embedded in the user’s prompt i.e., if garbage in, then garbage out. This establishes a clear dependency where the system is shaped by the human who operates it.

When a human supplies a prompt based on their own reasoning or imagination and uses AI to refine, edit, or structure that material, the process remains rooted in the user’s authorship. In such cases, AI functions as a tool. It plays a supporting role similar to spelling correction or layout formatting. The core idea remains human, and the final product reflects an extension of the author’s thinking.

Fat causes heart disease. This nutritional certainty dominated health advice for decades until emerging evidence suggested sugar is the real culprit. It’s incredulous that experts in the field provided incorrect guidance for so long.

In the 1950s, two scientists proposed competing theories. Ancel Keys claimed saturated fat causes heart disease. John Yudkin argued sugar poses the real threat. Keys happened to hold positions on influential health boards and directed research funds toward supporters. When Yudkin published evidence against sugar, Keys called it “a mountain of nonsense.” Siding with the loudest voice, the nutrition establishment marginalized Yudkin and his research.

I recently came across some examples of homonyms and oddities of English language that caught my attention while editing work memos. Nothing revolutionary here, just a few curiosities I enjoyed stumbling across, but still worth a quick mention since they don’t seem to appear outside a few niche forum discussions.

Gleam vs. Glean: At first glance, “gleam” and “glean” look like they should be related. “Gleam” refers to something shiny or bright e.g., sunlight “gleams” off a lake. “Glean”, on the other hand, is about slowly gathering or extracting information e.g., to “glean” insights from data.