Dan Nguyen, a journalist and programmer, writes about data journalism, coding, spreadsheets, and web design, plus some photography.
HN commenters cite his post on the plural of anecdote being data, and his pieces on Etsy's infinite scroll and price anchoring.
You shouldn't blindly perform standard statistical analysis on such data with the usual techniques. But to declare it statistical garbage is simply going too far.
In fact, anecdotes are the way in which we are able to make sense of the world at all. We do not as individuals do most of our learning via explicit statistical analysis.
Your essential point, however, stands in the sense that one should certainly not act as if anecdotes are statistically unbiased. And your average person is terrible at proper statistical reasoning. People tend to over-emphasize their own experience. (Though this is evolutionarily and historically useful - a feature, not a bug). So, yes, someone presenting their own anecdote or set of anecdotes as data is often misguided.
But there are, in fact, many studies (academic or industrial), that, are, in fact, just that! Collections of anecdotes. Self-reported experiences via surveys, error reports, reviews, and the like, which can be mined for data or looked at to see if there are any patterns.
There are issues such as "WEIRD" (Western, Educated, Industrialized, Rich, and Democratic) samples.
https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/article/weirdest-people-in-the-world/BF84F7517D56AFF7B7EB58411A554C17
There are three basic approaches: Ignore the problem and use the results as-is. Declare the sample hopelessly biased and throw it out altogether until you can find a more representative sample. Or acknowledge the bias in…
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In no particular order. From: https://jessimekirk.com/blog/hn_users_links/. I went through about half of the list looking for personal websites to use as inspiration for my own.
The way I view copyright law (IANAL), this is the correct approach. Each upload of an item to Megaupload is an independent assertion by the uploader that they have a license to put the work in question on the site. _Content_ itself is not prima facie infringing; instead, it is the unlicensed _use_ of the content that is infringement. This was essentially Youtube's argument when Viacom uploaded "roughed up" content to their site [1]. In that case, the roughed up copy as originally uploaded would be a licensed copy, but any copies that other users uploaded, even with the same MD5 hash, would be unlicensed.
On the other hand, child pornography can never be "non-infringing." It is always illegal to knowingly store obscene content, regardless of who stores it. Thus, one link to a child-pornographic file is as culpable as the next, justifying mass removal. This is essentially the argument made by Katherine Oyama of Google at one of the SOPA hearings [2].
[1] http://news.bbc.co.uk/2/hi/8575666.stm
[2] http://danwin.com/2012/01/the-sopa-debate-and-how-its-affected-by-congresss-understanding-of-child-porn/ (Ctrl-f "REP. MARINO")
> But no one really show how they're actually solving problems with LLMs and how the alternatives were worse for them. It's all claims that it's great with no further elaboration on the workflows.
To give an example, one person (a researcher at DeepMind) recently wrote about specific instances of his uses of LLMs, with anecdotes about alternatives to each example. [1] People on HN had different responses with similar claims with elaborations on how it has changed some of their workflows. [2]
While it would be interesting to see randomized controlled trials on LLM usage, hearing people's anecdotes brings to mind the (often misquoted) phrase: "The plural of anecdote is data". [3] [4]
[1] https://nicholas.carlini.com/writing/2024/how-i-use-ai.html
[2] https://news.ycombinator.com/item?id=41150317
[3] http://blog.danwin.com/don-t-forget-the-plural-of-anecdote-is-data/
[4] originally misquoted as "Anecdote is the plural of data."
I can't speak to the name (or even existence) of any fallacy that this describes, but pricing strategy you mentioned is known as price anchoring, where a higher number anchors the value against which the lower number is compared. Sometimes it's an explicit comparison of price, for or example where a higher price is offered, then "discounted" to a still high, but percieved bargain price; or a comparison of price to value (eg. ROI); or to an unrelated value that sets a subconscious numeric anchor for the price that follows.
This is relevant: http://danwin.com/2011/12/the-irrationality-of-price-anchoring/
Could have used etsy's help back in 2013:
“Seeing more items faster is presumed to be a better experience”, McKinley said. But the A/B tests showed various negative effects of the feature, including fewer clicks on the results and fewer items “favorited” from the infinite results page. And curiously, while users didn’t buy fewer items overall, “they just stopped using search to find these items.”
http://danwin.com/2013/01/infinite-scroll-fail-etsy/