Federal Tech Podcast: for innovators, entrepreneurs, and CEOs who want to increase reach and improve brand awareness Ep. 131 Exploring and Understanding Data
A recent study by Deloitte indicates that 67% of executives struggle with data analytics. The knight in shining armor that offers a rescue is artificial intelligence.
Today’s interview pours the promise of artificial intelligence into both ends of the spectrum: qualifying data sets that are being used and, subsequently, producing explainable results.
The headline overview of artificial intelligence involves writing a report by ChatGPT. Although that may be true, the article will be derivative and will not move the ball intellectually.
You will hear Kyle Rice discuss how Virtualitics can use artificial intelligence methods to look at data sets that are being investigated. Once those libraries are produced, then they can take artificial intelligence to look at making conclusions.
When analysis is approached from that point, you eliminate the guess-and-test method. That is to say, there is a good chance that the hypotheses that are created by humans. In other words, you will not spend precious time trying to answer the wrong questions.
Virtualitics poses that a rational way to generate data sets can give users the ability to form elusive data-derived decisions.
During the interview, Kyle describes the approach as “intelligent data exploration.” The added value of this approach is defensibility. For example, if a data scientist produces a conclusion, their sources can be questioned. Instead of pointing to a black box in the corner, a team can produce explainable artificial intelligence.
Interested in reading more from Virtualitics? Why AI’s Success Depends on Making it More Explainable and Conversational
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