Can Synthetic Data Save AI From Bias and Model Drift? Expert Analysis

Businesses and organizations around the world are rapidly settling into the harsh reality of safely deploying artificial intelligence. After barging into the global scene fueling the biggest hype in tech in the past decade, AI presented itself as a magical black box that could do almost anything — although black box comes with some negative connotations, including not knowing what is going on inside. Still, progress marches forward, and the revolution to integrate AI into operations everywhere is irresistible. But companies are learning, often the hard way, that AI risks are abundant, and — when mismanaged — the risks far outweigh the benefits. The biggest problems with AI? Compliance, data consent, copyright issues, training data, and bias. Synthetic data — created artificially — can mimic real-world data and could be the key to unlocking AI’s full potential. But can it save AI?

Ilia Badeev, Head of Data Science, Trevolution Group, innovating the travel industry with new technologies, spoke to Techopedia about how they use synthetic data. “We use AI to generate synthetic training data that resembles real data without involving our clients’ information,” Badeev said. “This allows us to train AI models effectively without even the slightest risk of compromising our user privacy. “Synthetic data can, however, still inherit or even amplify biases if the generation algorithms themselves are biased.”

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