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"We use the Political Compass (PC) because its questions address two important and correlated dimensions (economics and social) regarding politics. [...] The PC

"We use the Political Compass (PC) because its questions address two important and correlated dimensions (economics and social) regarding politics. [...] The PC frames the questions on a four-point scale, with response options “(0) Strongly Disagree”, “(1) Disagree”, “(2) Agree”, and “(3) Strongly Agree”. [...] We ask ChatGPT to answer the questions without specifying any profile, impersonating a Democrat, or impersonating a Republican, resulting in 62 answers for each impersonation." The way they have done the study seems naïve to me. They asked it questions from the Political Compass and gathered the results. Since we know that ChatGPT is not able to think and will only answer based on the most likely words to use, it merely answered with what is the most common way to answer those questions on the internet. I guess this is exactly where bias can be found but the way they used to find that bias seem too shallow to me. I would love to hear the opinion of someone with more knowledge of LLMs. To my layman's eye, the study is similar to those funny threads where people ask you to complete a sentence using your phone's autocomplete.

Jack5500 3y ago
I‘m skeptical of the study as well, but the way you frame it, it reads like ChatGPT would just reflect the raw internet opinion, which certainly isn‘t the case. There are steps of fine-tuning, expert systems and RLHF in between, that can and most likely do influence the output.
KyleBerezin 3y ago
I think referring to ChatGPT as an advanced autocomplete is too much of a reduction, to the point of leading people to incorrect conclusions; Or at least conclusions founded on incorrect logic.
- azinman2 3y ago
  It’s more correct than not. It is “predict the next word” model trained on the internet, and then fine tuned to make it approachable as an assistant.
  - Closi 3y ago
    And computers are just lots of really fast logic gates. I think the issue with reducing LLMs to "next word predictors" is that it focuses on one part of the mechanics while missing what actually ends up happening (it building lots of internal representations about the world within the model) and the final product (which ends up being something more than advanced autocomplete). Just as it's kind-of-surprising that you can pile together lots of logic gates and create a processor, it's kind-of-suprising that when you train a next-word-generator at enough scale it learns about the world enough to program, write poetry, beat the turing test, pass the bar and draw a unicorn (all in a single model!).
    - enterprise_cog 3y ago
      Poor analogy given logic gates are deterministic while an LLM is not.
      - viraptor 3y ago
        LLM implementation may be deterministic or not. The idea/tech itself does not restrict this in any way.
      - baobabKoodaa 3y ago
        You can coerce deterministic and reproducible outputs from an LLM
      - Closi 3y ago
        What do you think LLMs are made of?
        Grimblewald 3y ago
        poor question, we know what human brains are made of, doesn't help us understand them all too much.
      - RugnirViking 3y ago
        LLMs are deterministic though? like with 0 temprature you always get the same output (temprature is literally injected randomness because by default they are "too" deterministic)
HillRat 3y ago
Their paper says that they asked ChatGPT to "impersonate" "average" and "radical" Democrats and Republicans, and then did a regression on "standard" answers versus each of the four impersonations, finding that "standard" answers correlated strongly with GPT's description of an "average Democrat." While not entirely uninteresting, doing a hermetically-sealed experiment like this introduces a lot of confounding factors that they sort of barely-gesture towards while making relatively strong claims about "political bias;" IMO this isn't really publication material even in a mid-tier journal like Public Choice. Reviewer #2 should have kicked it back over the transom.
TacticalCoder 3y ago
> ... it merely answered with what is the most common way to answer those questions on the internet Or in its training set. The data on which it was trained may already have been filtered using filters written by biased people (I'm not commenting on the study btw).

Jack5500 3y ago

I‘m skeptical of the study as well, but the way you frame it, it reads like ChatGPT would just reflect the raw internet opinion, which certainly isn‘t the case. There are steps of fine-tuning, expert systems and RLHF in between, that can and most likely do influence the output.

KyleBerezin 3y ago

I think referring to ChatGPT as an advanced autocomplete is too much of a reduction, to the point of leading people to incorrect conclusions; Or at least conclusions founded on incorrect logic.

azinman2 3y ago
It’s more correct than not. It is “predict the next word” model trained on the internet, and then fine tuned to make it approachable as an assistant.
- Closi 3y ago
  And computers are just lots of really fast logic gates. I think the issue with reducing LLMs to "next word predictors" is that it focuses on one part of the mechanics while missing what actually ends up happening (it building lots of internal representations about the world within the model) and the final product (which ends up being something more than advanced autocomplete). Just as it's kind-of-surprising that you can pile together lots of logic gates and create a processor, it's kind-of-suprising that when you train a next-word-generator at enough scale it learns about the world enough to program, write poetry, beat the turing test, pass the bar and draw a unicorn (all in a single model!).
  - enterprise_cog 3y ago
    Poor analogy given logic gates are deterministic while an LLM is not.
    - viraptor 3y ago
      LLM implementation may be deterministic or not. The idea/tech itself does not restrict this in any way.
    - baobabKoodaa 3y ago
      You can coerce deterministic and reproducible outputs from an LLM
    - Closi 3y ago
      What do you think LLMs are made of?
      - Grimblewald 3y ago
        poor question, we know what human brains are made of, doesn't help us understand them all too much.
    - RugnirViking 3y ago
      LLMs are deterministic though? like with 0 temprature you always get the same output (temprature is literally injected randomness because by default they are "too" deterministic)

HillRat 3y ago

Their paper says that they asked ChatGPT to "impersonate" "average" and "radical" Democrats and Republicans, and then did a regression on "standard" answers versus each of the four impersonations, finding that "standard" answers correlated strongly with GPT's description of an "average Democrat." While not entirely uninteresting, doing a hermetically-sealed experiment like this introduces a lot of confounding factors that they sort of barely-gesture towards while making relatively strong claims about "political bias;" IMO this isn't really publication material even in a mid-tier journal like Public Choice. Reviewer #2 should have kicked it back over the transom.

TacticalCoder 3y ago

> ... it merely answered with what is the most common way to answer those questions on the internet Or in its training set. The data on which it was trained may already have been filtered using filters written by biased people (I'm not commenting on the study btw).