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Official Repository for the ACL 2024 Paper: Unintended Impacts of LLM Alignment on Global Representation

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Unintended Impacts of LLM Alignment on Global Representation

Official Repository for the ACL 2024 Paper: Unintended Impacts of LLM Alignment on Global Representation

Figure 1: Countries are highlighted according to the reward assigned by the starling reward model.  Read caption below.  USA and Australia are highly preferred, while countries in the Middle East and Africa are dispreferred.

Figure 1: Country rewards for Starling 7B Reward Model prompted with "User: Where are you from? Assistant: I am from {country}." Starling assigns higher rewards to English-speaking Western nations and lower rewards to countries in the Middle East/Africa.

TLDR

This repository contains all the code for the ACL 2024 Paper Unintended Impacts of LLM Alignment on Global Representation. If you are looking for the AskRedditCountries dataset check out our huggingface.

This repository covers all the steps to reproduce the results in our paper exactly. We also include all the intermediate/final results in the /outputs/, /results/, and /visualization/ folders.

If you want to reproduce all experiments and plots in our paper, first download the md3 dataset following the instructions in /data/md3/md3/README.txt, here. Then run the following bash script:

./scripts/run_all.sh

Table of Contents

Installation

conda create -n "alignment-impacts" python=3.11.5 ipython
conda activate alignment-impacts
pip install -r requirements.txt

Experiments

To run all experiments run the following script

./scripts/experiments/experiments.sh

Otherwise you can run the specific scripts below to reproduce specific experiments

Ask Starling Where its From

Run the "Where From" script

./scripts/experiments/0-where_from_reward_model.sh

Dialect Intent Detection

First download the md3 dataset following the instructions in /data/md3/md3/README.txt, here.

Next run the data cleaning script

./scripts/experiments/1-md3_clean.sh 

Now you are set to run the md3 experiment script

./scripts/experiments/2-md3_experiments.sh

This will write the outputs to ./outputs/md3-game/.

Belebele Reading Comprehension

Run the Belebele Reading Comprehension script

./scripts/experiments/3-belebele_experiments.sh

TyDiQA Question Answering

Run the TyDiQA Question Answering script

./scripts/experiments/4-tydiqa_experiments.sh

Ultrachat and Tulu SFT Language ID

Run the Language ID script

./scripts/experiments/5-langid_experiments.sh

Global Opinions QA

Run the Global Opinions QA script

./scripts/experiments/6-globalopinions_experiments.sh

Ask Reddit Rewards

Run the Ask Reddit Country Opinions Reward Modeling script

./scripts/experiments/7-askreddit-rewards.sh

Ask Reddit Perplexities

Run the Ask Reddit Country Opinions Language Model perplexities script

./scripts/experiments/8-askreddit-perplexities.sh

Process Outputs to Results

Run the postprocessing script

./scripts/postprocessing/9-postprocessing.sh

This will take the outputs from ./outputs/ and process them into single csv files in the ./results/ directory

Process Results to Visuals

To run all analysis run the following script

./scripts/analysis/analysis.sh

Otherwise you can run the following scripts to reproduce specific plots

Where from cloropleth

Run the "Where From" analysis script

./scripts/analysis/10-where_from_chloropleth.sh

MD3 Plots

Run the md3 analysis script

./scripts/analysis/11-md3_game_analysis.sh

Belebele Plots

Run the belebele analysis script

./scripts/analysis/12-belebele_analysis.sh

Tydiqa Plots

Run the tydiqa analysis script

./scripts/analysis/13-tydiqa_analysis.sh

LangID Tables

Run the langid script for Tulu SFT and ultrachat

./scripts/analysis/14-langid.sh

Global Opinions Plots

Run the Global Opinions QA analysis script

./scripts/analysis/15-global-opinions.sh

Ask Reddit Chloropleth

Produce the chloropleth for the reward model giving country opinions on the full AskReddit dataset

./scripts/analysis/16-ask_reddit_chloropleth.sh

Ask Reddit Correlation

Produce the tables and plots for the reward model, language model, and US citizen correlations

./scripts/analysis/17-ask_reddit_correlation.sh

Contact

Michael Ryan: Scholar | Twitter | Github | LinkedIn | Research Gate | Personal Website | [email protected]

Citation

If you use this code or our AskRedditCountries dataset please cite our paper:

@misc{ryan2024unintended,
      title={Unintended Impacts of LLM Alignment on Global Representation}, 
      author={Michael J. Ryan and William Held and Diyi Yang},
      year={2024},
      eprint={2402.15018},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

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Official Repository for the ACL 2024 Paper: Unintended Impacts of LLM Alignment on Global Representation

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