Row 21935

Row ID: 21935 | Dataset Entry | Axioma AXP Content Repository

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Yes, it does seem like "measuring" lies is a big challenge.

For example, one NLP source I found was transcripts of Diplomacy (a risk-like board game) players talking in-game. On its face, this would seem like a great way to check if a person is lying: compare what a player says they will do to what they actually do in the game. The problem is, players could be lying about their intent, and still accidentally follow through because their plans are interrupted or they change their mind, and they could mean what they say when they say it but then decide to double-cross later.

I'd hoped that some kind of data set involving easy yes-no questions would be available (though of course that would still be limited by context: lying about breaking a friend's vase is different than lying about your hair color to someone who has asked you to do so).

At any rate, I think I'm going to shelve this project idea-- it's looking much more complex than I'd originally hoped.

FieldValue
text Yes, it does seem like "measuring" lies is a big challenge. For example, one NLP source I found was transcripts of Diplomacy (a risk-like board game) players talking in-game. On its face, this would seem like a great way to check if a person is lying: compare what a player says they will do to what they actually do in the game. The problem is, players could be lying about their intent, and still accidentally follow through because their plans are interrupted or they change their mind, and they …
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-21
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Raw Record

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  "text": "Yes, it does seem like \"measuring\" lies is a big challenge.\n\nFor example, one NLP source I found was transcripts of Diplomacy (a risk-like board game) players talking in-game. On its face, this would seem like a great way to check if a person is lying: compare what a player says they will do to what they actually do in the game. The problem is, players could be lying about their intent, and still accidentally follow through because their plans are interrupted or they change their mind, and they could mean what they say when they say it but then decide to double-cross later.\n\nI'd hoped that some kind of data set involving easy yes-no questions would be available (though of course that would still be limited by context: lying about breaking a friend's vase is different than lying about your hair color to someone who has asked you to do so). \n\nAt any rate, I think I'm going to shelve this project idea-- it's looking much more complex than I'd originally hoped.",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-21",
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