dataset_info:
features:
- name: hard_text
dtype: string
- name: profession
dtype: int64
- name: gender
dtype: int64
- name: ai_correct
dtype: bool
splits:
- name: train
num_bytes: 1612718.7804411764
num_examples: 4453
- name: test
num_bytes: 524052.11661764706
num_examples: 1447
download_size: 1251600
dataset_size: 2136770.8970588236
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
Dataset Card for "bias_in_bios_verified_software_devs_only"
A dataset of software engineer bios, filtered from the LabHC/bias_in_bios dataset, by selecting the software engieer class and using gpt-4o-mini to filter out bios which don't look like software engineers.
For example 900 / 6800 rows like this have been removed:
He has been playing guitar and devoting himself to music for many years. There is no question that music is his life. He has performed in music houses and clubs with musicians from Taiwan and other countries. His passion and desire to learn more about music and guitar influenced him to enroll at the Musicians Institute in LA next year. He is an enthusiast of blues, swing jazz and rockabilly.
His first year competing in American Ninja Warrior was in Season 6. He completed the course in the Dallas Qualifier. Jo Jo seemed to take his time through each obstacle. During the Ring Toss he missed a couple of pegs but was able to recover in order to finish. Jo Jo was able to make it up the Warped Wall in his first attempt finishing in eighteenth place.
The prompt for this filtering was
prompt = f"""I'm going to give you a biography, and I want you determine if it belongs to a software engineer.
Biography:
"{bio}"
Is this person likely to be a software engineer? Please respond only with "Yes." if you believe they are likely to be a software engineer, or "No." otherwise.
"""
output = client.chat.completions.create(
model="gpt-4o-mini",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{
"role": "user",
"content": prompt
}
],
)
Warning: the dataset has also been shuffled, and modified to have a train test split of 4453 / 1447.