Business is more digital than ever, and small- and medium-sized businesses are finding new ways to optimize their operations with artificial intelligence (AI) tools. Businesses can manage and improve products, automate services, and be proactive with customer data using AI. This interesting topic came to us from Inc. in their article, “What Do Small Business Owners Need to Know About Data and A.I.?“
While software cannot actually think, it can be programmed to solve problems in ways that emulate perception, reasoning, and learning. AI is not an exact replica of a human’s capabilities, but it can be used to interpret language, perform tasks, and make predictions. AI is an algorithm, which at its most basic level is a process that takes in one thing and outputs another. Machine learning algorithms need large volumes of data to do work.
As more organizations, regardless of size, implement AI, it has never been more important for them to understand how AI systems make decisions. 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. Why is this important? Because explainability becomes critical when the results can have an impact on data security or safety.
Melody K. Smith
| Data Harmony is an award-winning semantic suite that leverages explainable AI. |
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