The speed at which technology is growing is 2x every 18 months when computing is measured. Over 89% of big data has been produced within the last 2 years. Let that sink in. This interesting topic came to us from datanami in their article, “What’s Holding Up Progress in Machine Learning and AI? It’s the Data, Stupid.”

Is the lack of a solid data foundation and solid data workflows preventing companies from making more progress with machine learning and artificial intelligence (AI)?

Some think that while companies are having some success in putting machine learning and AI into production, they would be further along if data management issues weren’t getting in the way.

While the sophistication of available machine learning and AI technologies is growing quickly, companies are finding they haven’t done some of the core data management work that’s needed to put them in a position to take advantage of that progress.

I think we also have to acknowledge the elephant in the room. Most organizations have little knowledge of how AI systems make the decisions they do, or how the results are applied in various fields. “Explainable AI” is used to describe an AI model, its expected impact and potential biases.

Melody K. Smith

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

Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.