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Faraday

Discover responsible AI with features like bias detection, explainability and robust data with Faraday.

AI Assistant Updated 1 day ago
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Faraday

Faraday's Top Features

Algorithmic Bias Detection
Bias Management
AI Explainability
Built-in Consumer Data
Automated Feature Engineering
Fair and Transparent AI
Comprehensive Data Insights
1,500+ Consumer Attributes
Cold-start Problem Mitigation
Multiple Bias Mitigation Options

Frequently asked questions about Faraday

Faraday focuses on creating a predictive future that benefits society by using AI responsibly, including features like algorithmic bias detection and bias management.

Faraday automatically identifies biases in your data and predictions, providing insights into how these biases operate.

Yes, with Faraday, you have the choice to correct biases when necessary through its bias management features.

AI explainability involves algorithms that justify their predictions, ensuring transparency and trust in AI decisions.

Yes, Faraday includes over 1,500 consumer attributes on nearly 240 million adults, which helps in improving prediction accuracy and solving the cold-start problem.

Faraday's automated feature engineering can analyze any first-party data to find patterns, enhancing prediction accuracy further.

Faraday’s database includes a wide array of attributes such as age, social media activity, number of online/offline purchases, home equity, and more.

Explainability builds trust in AI predictions by revealing why a specific decision or prediction was made, thus supporting transparency.

Using built-in data allows for more accurate predictions and mitigates issues like the cold-start problem, providing a robust predictive tool.

Yes, users can choose whether to intervene and correct biases based on their specific needs and context.

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