New software from Synthesized enables global businesses to instantly visualise and measure data inequality
Synthesized, the leading all-in-one DataOps platform, has offered businesses across the globe a simple way to discover bias within their data which, if mitigated, could ensure fairer treatment for customers and help protect brand reputation.
The innovative AI-based UK startup has this week unveiled FairLens, the world’s first data-centric open-source software for identifying and measuring data bias.
Award-winning Synthesized is keen to encourage companies and sectors around the globe to make use of FairLens as part of their in-house technology stack to discover if their data contains bias, so that the effects can be mitigated to benefit customers. Developers are also being urged to contribute to the development of new capabilities of Fairlens as part of an open source initiative on the developer’s site, GitHub.
Nicolai Baldin, co-founder and chief executive of Synthesized added “While data bias is still a taboo subject for many companies and industries, what FairLens enables is a behind-the-scenes discovery of data bias, which can then be mitigated. FairLens could instantly help the insurance, health and public sectors find unfair data bias which could be discriminating against their customers. I would urge every organisation to take a look at their data through FairLens and decide whether they are treating customers fairly.”
Many insurance apps, for instance for automobile, health or life insurance make a decision without human involvement, based on a company’s data. With limited, poor-quality or skewed datasets, data-driven applications often fail to achieve their intended purpose, as they are inherently biased.
Customers of insurance companies could benefit immediately if businesses could test their data in their own safe environment through FairLens which will be able to reveal, in seconds, any undiscovered biases in the data. Understanding the hidden biases in data will help calibrate their data science models to ensure fairer outcomes for wider population, more inclusive offerings and access to previously underserved and under-represented customers. It would potentially dramatically reduce the risk of non-compliance with regulations and help protect brand reputation.
FairLens allows data scientists to automatically discover and visualise hidden biases and measure fairness in data.
Denis Borovikov, co-founder and chief technology officer at Synthesized, said: “Many Artificial Intelligence models unfortunately rely on biased and skewed datasets. What we have created, with FairLens, is a mathematical framework to discover and visualize data bias. We hope FairLens will enable data practitioners to gain a deeper understanding of their data, and to help ensure fair and ethical use of data in analysis and data science tasks.”
FairLens decreases the time it takes data scientists to find bias in their models, which can often take months. FairLens takes a different approach and can calculate bias contained in hundreds of thousands of columns of data, in seconds. With FairLens, data scientists can:
Measure bias
Identify sensitive attributes
Visualise bias
Score fairness