# Ethical Algorithm Tester

The **`ethical-algorithm-tester`** package provides tools for analyzing bias, fairness, transparency, and accountability in algorithmic decision-making. This package is useful for developers and data scientists who want to ensure that their algorithms operate ethically and fairly.

## Features

- **Bias Analysis**: Evaluate the bias in algorithmic predictions based on specified attributes
- **Fairness Analysis**: Assess the fairness of decisions across different demographic groups
- **Transparency Analysis**: Explain the predictions made by your algorithms
- **Accountability Analysis**: Keep track of actions taken in the model development process

## Installation

To install the package, run the following command:

```bash
npm install ethical-algorithm-tester
```

## Usage

Here's an example of how to use the package:

```javascript
const ethicalTester = require('ethical-algorithm-tester');

// Sample candidate data
const candidateData = [
    { age: '20-30', education: 'Bachelor', experience: 3, hireScore: 65 },
    { age: '30-40', education: 'Master', experience: 5, hireScore: 85 },
    { age: '40-50', education: 'PhD', experience: 8, hireScore: 90 },
    { age: '20-30', education: 'Master', experience: 2, hireScore: 70 },
    { age: '30-40', education: 'Bachelor', experience: 6, hireScore: 75 },
];

// Bias Analysis based on Age
const ageBias = ethicalTester.calculateBias(candidateData, 'age', 'hireScore');
console.log('Bias Analysis based on Age:', ageBias);

// Fairness Analysis based on Education Level
const educationFairness = ethicalTester.demographicParity(
    candidateData, 
    'education', 
    'hireScore'
);
console.log('Fairness Analysis based on Education Level:', educationFairness);

// Transparency Analysis
const hiringModel = {
    explain: (input) => `Explanation: Score based on ${JSON.stringify(input)}`,
};
const transparency = ethicalTester.explainPrediction(
    hiringModel, 
    { experience: 5, education: 'Master', age: '30-40' }
);
console.log('Transparency Explanation:', transparency);

// Accountability Analysis
const actionLogs = [
    { timestamp: '2024-10-10', action: 'data validation' },
    { timestamp: '2024-10-11', action: 'feature engineering' },
    { timestamp: '2024-10-12', action: 'model training' },
    { timestamp: '2024-10-13', action: 'bias check' },
];
const accountability = ethicalTester.accountabilityScore(actionLogs);
console.log('Accountability Score:', accountability);
```

## API Reference

### Bias Analysis

```javascript
ethicalTester.calculateBias(data, attribute, scoreField)
```
Calculates bias in predictions based on specified attributes.

### Fairness Analysis

```javascript
ethicalTester.demographicParity(data, demographicField, scoreField)
```
Assesses fairness across different demographic groups.

### Transparency Analysis

```javascript
ethicalTester.explainPrediction(model, input)
```
Provides explanations for model predictions.

### Accountability Analysis

```javascript
ethicalTester.accountabilityScore(actionLogs)
```
Evaluates the accountability of the model development process.

## Contributing
Contributions are welcome! We value any input, from fixing typos to suggesting new features or reporting bugs.
How to Contribute

Fork the repository: https://github.com/emon273273/ethical-algorithm-tester
Create your feature branch (git checkout -b feature/AmazingFeature)
Commit your changes (git commit -m 'Add some AmazingFeature')
Push to the branch (git push origin feature/AmazingFeature)
Open a Pull Request

## Guidelines

Ensure your code follows the existing style pattern
Update the README.md with details of changes if applicable
Update the documentation when adding new features
Write meaningful commit messages

## Issues
Feel free to submit issues and enhancement requests at https://github.com/emon273273/ethical-algorithm-tester/issues

For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.

## License

This project is licensed under the MIT License - see the LICENSE file for details.

## Support

If you have any questions or need help, please:
1. Check the documentation
2. Open an issue on GitHub
3. Contact the maintainers

## Acknowledgments

- Thanks to all contributors who have helped make this package better
- Special thanks to the ethical AI community for guidance and best practices