Generative AI (GenAI) is making waves in all sorts of industries, from content creation to software development. But one area where it could really shake things up is in revealing dark data. For those not familiar, dark data is all the information an organization collects, processes and stores but doesn’t actually use. It’s kind of like an iceberg — the majority of it is hidden beneath the surface, untapped and often ignored. While it might seem harmless, there’s potential gold (and a few landmines) in that dark data, and GenAI could be the key to exposing it. This interesting news came to us from Fierce Network in their article, “GenAI could illuminate decades worth of dark data.”

Dark data can come from all sorts of places: emails, customer service logs, old reports, social media interactions, sensor data and much more. It’s often left untouched because it’s unstructured or too messy to analyze without significant effort. This is where GenAI shines. With its ability to process and understand massive amounts of data, GenAI can quickly identify patterns, trends and insights hidden in this unstructured mess.

While the potential value of dark data is exciting, uncovering it isn’t without risks. One of the biggest issues is privacy. A lot of dark data contains sensitive information, especially in fields like healthcare or finance. GenAI could unintentionally dig up personal details that are better left buried, or worse, expose them to misuse or data breaches. Companies will need to take extra care to ensure that sensitive data is handled responsibly when using AI to explore these hidden stores of information.

There’s also the issue of data quality. Dark data is often incomplete, outdated, or inaccurate, and feeding that kind of data into AI systems could lead to faulty insights. Garbage in, garbage out, as they say. Organizations will need to invest in cleaning and validating this data before they can trust the insights that GenAI generates.

In the end, GenAI’s ability to expose dark data could be a game-changer, but it’s a double-edged sword. Handle it with care, and the rewards could be significant. Mishandle it, and the consequences could be just as profound.

Everyone is looking at AI. Everyone is getting mixed results. The main issue is that data science has not changed, and scientific content is very complex and needs more attention to get the most out of the new AI engines. This is not new for Access Innovations.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, uniquely positioned to help you in your AI journey.