This Python script creates a password-protected ZIP file using the pyzipper library. It allows you to specify the files to include in the ZIP and set a password for encryption. The resulting ZIP file requires the provided password to access its contents, providing an additional layer of security.
You are part of a data science team at an AI company, "FairTech AI," which specializes in creating AI models for various industries. Your current project involves developing an AI system for a healthcare provider to predict patient health risks. The company is committed to ensuring that the AI system is unbiased and equitable.
The Task
Your team has received a dataset to train the AI model. However, there are concerns that this dataset may contain biases that could lead to unfair or prejudiced predictions. Your task is to scrutinize the dataset and identify any labels or data points that might indicate bias.
Dataset Sample
The dataset comprises patient records with various attributes. Here's a sample of the data:
Patient ID | Age | Gender | Ethnicity | Income Level | Employment Status | Medical History | Health Risk Score
-- | -- | -- | -- | -- | -- | -- | --
001 | 45 | Male | Caucasian | High | Full-time | Diabetes | Moderate
002 | 30 | Female | Hispanic | Low | Unemployed | Healthy | High
003 | 37 | Male | African American | Middle | Part-time | Hypertension | Low
004 | 50 | Female | Asian | High | Self-employed | Obesity | Moderate
005 | 29 | Male | Caucasian | Middle | Full-time | Healthy | High
006 | 42 | Female | Hispanic | Low | Part-time | Asthma | Moderate
... | ... | ... | ... | ... | ... | ... | ...
(Note: This is a simplified representation for educational purposes. An actual dataset would contain more records and potentially more complex attributes.)
Instructions
Review the sample dataset.
Identify any labels or data points that might be indicative of bias.
Consider aspects such as representation across different demographic groups and the potential for stereotypes or assumptions to influence the "Health Risk Score."
Identifying Bias in AI Training Data
You are part of a data science team at an AI company, "FairTech AI," which specializes in creating AI models for various industries. Your current project involves developing an AI system for a healthcare provider to predict patient health risks. The company is committed to ensuring that the AI system is unbiased and equitable.
The Task
Your team has received a dataset to train the AI model. However, there are concerns that this dataset may contain biases that could lead to unfair or prejudiced predictions. Your task is to scrutinize the dataset and identify any labels or data points that might indicate bias.
Dataset Sample
The dataset comprises patient records with various attributes. Here's a sample of the data:
(Note: This is a simplified representation for educational purposes. An actual dataset would contain more records and potentially more complex attributes.)
Instructions