Surveys have been used since time immemorial to obtain information about populations, products and public opinion. And while methodologies have changed over the millennia, one thing has remained constant: the need for people, many people.
But what happens if you can’t find enough people to make a large enough sample to generate meaningful results? Or what if you could potentially find enough people, but budget constraints limit the number of people you can recruit and interview?
It’s here that Fairgen wants to help. The Israeli startup is today launching a platform that uses “statistical AI” to generate synthetic data that it claims is as good as the real thing. The company also announces a new funding round of $5.5 million from Maverick Ventures Israel, The Creator Fund, Tal Ventures, Ignia and a handful of angel investors, bringing the total cash raised since its inception to 8 million dollars.
“False data”
The data could be lifeblood of AI, but it has also always been the cornerstone of market research. So when the two worlds collide, as they do in Fairgen’s world, the need for quality data becomes a little more pronounced.
Founded in Tel Aviv, Israel in 2021, Fairgen previously focused on tackling bias in AI. But at the end of 2022, the company turned to a new product, Fairboostwhich it is now launching in beta.
Fairboost promises to “boost” a smaller dataset by up to three times, enabling more granular insights into niches that might otherwise be too difficult or expensive to reach. With this, businesses can train a deep machine learning model for each dataset they upload to the Fairgen platform, with AI statistical learning models across different segments of the survey.
The concept of “synthetic data” – data created artificially rather than from real-world events – is not new. Its roots go back to the early days of computing, when it was used to test software and algorithms and simulate processes. But synthetic data, as we understand it today, has taken on a life of its own, especially with the advent of machine learning, where it is increasingly used to train models. We can solve both data scarcity problems and data privacy problems by using artificially generated data that does not contain any sensitive information.
Fairgen is the latest startup to test synthetic data and has market research as its main focus. It’s worth noting that Fairgen doesn’t produce data from scratch, nor throw millions of historical surveys into an AI-powered melting pot: market researchers should conduct a survey for a small sample of their target market , and from there, Fairgen builds models to expand the sample. The company claims that it can guarantee at least a two-fold increase compared to the original sample, but on average it can achieve a three-fold increase.
In this way, Fairgen might be able to establish that someone in a particular age range and/or income level is more likely to answer a question in a certain way. Or,…
