Artificial intelligence (AI) analytics refers to a subset of business intelligence (BI) in which software exhibits behaviors typically attributed to humans, such as learning and reasoning, in the process of data analysis. This interesting information came to us from inside BIG DATA in their article, “How AI-Unified Data Analytics Is Good for Your Business.”
AI and big data are changing the world of technology. Countless think pieces have talked about their potential, leading many businesses to invest in them, but many AI and data projects fall short of expectations. This is where AI-unified data analytics is different. It provides a solution to this hurdle.
AI automates the steps that humans would take to complete analysis in an exhaustive fashion. AI can test every possible data combination to determine hierarchies of relationships between different data points— and it can do so much faster than a person could.
The biggest challenge is that most organizations have little knowledge on how AI systems make their decisions, and as a result, they know little regarding how the results could be applied by those AI and machine learning systems. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. Explainable AI is used to describe an AI model, its expected impact, and its potential biases.
Melody K. Smith
| Data Harmony is an award-winning semantic suite that leverages explainable AI. |
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Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.
