Ethics Framework

A JavaScript framework for ethical decision-making using supervised and unsupervised machine learning models.

Features

- Ethical decision-making model
- Bias detection and mitigation
- Compliance monitoring
- Anomaly detection
- Pattern recognition
- Feature extraction

Installation

To install the package, use npm:

``bash
npm install ethics-framework
`

Usage

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First, import the EthicsFramework class:

`javascript
import EthicsFramework from 'ethics-framework';
`

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Here’s an example demonstrating how to use the framework:

`javascript
import EthicsFramework from 'ethics-framework';

const framework = new EthicsFramework();

const trainingData = [
[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0],
[1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1]
];
const trainingLabels = [[1], [0]];

(async () => {
// Train the ethical decision model
await framework.trainEthicalDecisionModel(trainingData, trainingLabels);

const testData = [
[0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 0.1],
[0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 1.0]
];

// Predict with the ethical decision model
const predictions = framework.predictWithEthicalModel(testData);
console.log("Predictions:", predictions);

// Detect bias in data
const biases = framework.checkForBias(testData);
console.log("Biases detected:", biases);

// Mitigate detected bias
const mitigatedData = framework.mitigateDetectedBias(testData);
console.log("Mitigated Data:", mitigatedData);

// Ensure compliance
const compliance = framework.ensureCompliance(testData);
console.log("Compliance:", compliance);

// Detect anomalies in data
const anomalies = await framework.detectEthicalAnomalies(testData);
console.log("Anomalies:", anomalies);

// Recognize patterns in data
const patterns = await framework.recognizeEthicalPatterns(testData);
console.log("Patterns:", patterns);

// Extract features from data
const features = await framework.extractEthicalFeatures(testData);
console.log("Features:", features);
})();
``

API

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#### Methods

- trainEthicalDecisionModel(data, labels): Trains the ethical decision model with provided data and labels.
- predictWithEthicalModel(data): Predicts outcomes using the ethical decision model.
- checkForBias(data): Detects bias in the provided data.
- mitigateDetectedBias(data): Mitigates detected bias in the provided data.
- ensureCompliance(data): Ensures the provided data complies with predefined rules.
- detectEthicalAnomalies(data): Detects anomalies in the provided data.
- recognizeEthicalPatterns(data): Recognizes patterns in the provided data.
- extractEthicalFeatures(data): Extracts features from the provided data.

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#### EthicalDecisionModel

A machine learning model for ethical decision-making.

- train(data, labels): Trains the model.
- predict(data): Predicts outcomes.

#### BiasDetection

Detects and mitigates bias in data.

- detectBias(data): Detects bias in the provided data.
- mitigateBias(data): Mitigates detected bias in the provided data.

#### ComplianceMonitor

Ensures data complies with predefined rules.

- checkCompliance(data): Checks compliance of the provided data.

#### AnomalyDetector

Detects anomalies in data.

- detect(data): Detects anomalies in the provided data.

#### PatternRecognizer

Recognizes patterns in data.

- recognizePatterns(data): Recognizes patterns in the provided data.

#### FeatureExtractor

Extracts features from data.

- extractFeatures(data): Extracts features from the provided data.

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

License

This project is licensed under the MIT License.

Bugs and Issues

Please report any bugs or issues on the GitHub issues page.

Author

Beta Priyoko - Email