The Most Human Human

What Hacker News says

1. postexitusJan 2026
   Tangentially related, but I enjoyed reading "The Most Human Human" by Brian Christian - granted it's written in a pre-LLM world, it's still very much relevant.

   The book is following the annual Turing Test competition, in which, humans are chatting with AIs or real humans without knowing which is which and give them a score out of 10 for being most human and the AI that is "the most human" wins the competition. The twist is, not all humans get 10/10 for being human either - so the human that's the most human also wins a prize.

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2. topaz0Apr 2015
   "The Moon is Down" by John Steinbeck, and "A Discipline of Programming" by Edsger Dijkstra. Before that, "The Most Human Human", by Brian Christian. "The Most Human Human" was particularly interesting, about what we can learn about being human by looking at machines.
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3. benjaminashleyJun 2012
   I really enjoyed The Most Human Human by Brian Christian. It's about Turing tests and The Loebner Prize.
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4. jazzdevJan 2012
   I got "The Most Human Human: What Talking with Computers Teaches Us About What It Means to Be Alive" for Christmas and it's just fascinating. Interesting history on the Turing test and AI and philosophy and very well written. I highly recommend it.
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5. elil17May 2020
   I can't believe how bad I am with this! It reminds me of the book "The Most Human Human." Every year, at the competition for the Loebner Prize (a five minute chatbot Turing test), an award is given not only to the AI which convinces the most humans that it is a human (The Most Human Machine), but also to the human who convinces the most humans that they are a human (The Most Human Human). The author of the book tried to set the record for being the highest scoring human in the test. His book dives into just how smart, curious, and empathetic you have to be to show your human-ness. The Goop authors, it seems, are not going to be in the running for "Most Human Humans" any time soon.
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6. cdbattagsJan 2019
   I know this might be fuel to the fire on here, but I think Tanushree's work at Georgia Tech in her paper "A Parsimonious Language Model of Social Media Credibility Across Disparate Events" [1] is a good stab at the "fake news" problem with a lens of "credibility".

   As a disclaimer, we tried to get this model off the ground in YC summer 2017 batch but were rejected after the phone interview. I did not assist in the research; only an effort to publicize.

   I whole-heartedly believe this is our best bet at combatting "fake news" online for the moment. Taking the lessons of "The Most Human Human: What Artificial Intelligence Teaches Us About Being Alive" [2], we might tease out credibility instead of fact or fiction to help guide our biased/opinionated labels.

   From the abstract:

   "In other words, the language used by millions of people on Twitter has considerable information about an event’s credibility. For example, hedge words and positive emotion words are associated with lower credibility"

   [1]: https://credcount.com/whitepaper.pdf

   [2]: https://www.amazon.com/Most-Human-Artificial-Intelligence-Te...

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