What is Faraday's approach to AI safety?

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

How does Faraday detect algorithmic bias?

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

Can I manage detected biases in Faraday?

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

What is AI explainability, according to Faraday?

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

Does Faraday include pre-existing consumer data?

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.

How does Faraday handle first-party data?

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

What kind of consumer attributes are included in Faraday's database?

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

Why is AI explainability important in Faraday's system?

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

How does Faraday's use of built-in consumer data benefit users?

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

Is the bias management feature optional in Faraday?

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

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Faraday

Name: Faraday
Brand: Faraday
Rating: 1 (1 reviews)
Author: Faraday

Last updated: August 8, 2024

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Faraday's AI Safety and Responsible AI page emphasizes a commitment to building a predictive future that benefits society by using AI responsibly. It highlights features like algorithmic bias detection, bias management, AI explainability, and the use of built-in consumer data to ensure fairness and accuracy in predictions. Additionally, Faraday provides automated feature engineering to enhance prediction accuracy using both built-in and first-party data.

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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's pricing

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