FairLens: Fostering Responsible AI through Unbiased Data

In the race for innovation, efficiency and enhanced customer experience, organisations are increasingly turning to AI and automation. With such a rapidly growing technology, sometimes commercial, operational and reputational risks can arise when AI models rely on limited, poor-quality or skewed data. That's when applications often fail to do the job for which they were created, and negatively impact under-represented groups.
FairLens is the world's first data-centric software for discovering hidden biases and ensuring data transparency and fairness.
FairLens Unveiled

Fairness and Data Transparency at the Core of Your AI Practices

The Challenge
Limitations in the availability of representative and high-quality data can often unintentionally perpetuate bias in AI algorithms. Lack of representation of non-traditional customer groups in the data may lead to skewed models with real implications on the customer experience or in the worst case scenario discriminating against customer groups.
Algorithmic bias often results in compliance failures and has negative reputational consequences.
The Solution

With FairLens you can:

Gain visibility and insights into the biases found in data
Improve model performance by making use of hiqh-quality representative data products
Mitigate compliance and legal risks to avoid reputational and financial damages
Seize new business opportunities
Calling out the data science community!

Contribute to FairLens Open Source Project

Fairlens is a developer toolkit for automatically discovering and measuring various types of bias, identify sensitive attributes, visualising bias and scoring fairness.Contribute to the development and growth of FairLens to drive fair and ethical use of data in analysis and data science.
Contribute to FairLens

Learn More about AI and Data Bias

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