An algorithm is a procedure used for solving a problem or performing a computation. Algorithms act as an exact list of instructions that conduct specified actions step by step in either hardware- or software-based routines. This interesting topic came to us from eWeek in their article, “AI vs. Algorithms.”

Even the smallest of artificial intelligence (AI) designs need basic instructions in order to function. And that’s where algorithms come into the overall process. Algorithms are widely used throughout all areas of IT. In mathematics and computer science, an algorithm usually refers to a small procedure that solves a recurrent problem. Algorithms are also used as specifications for performing data processing and play a major role in automated systems.

There is no doubt; algorithms are a huge part of today’s world. By giving our daily tech tools the descriptive instructions they need to carry out specific tasks, we’re able to automate many of the processes human beings had to do by hand for thousands of years. Algorithms help form the intense calculation that has led to some of the greatest discoveries in medicine, science, engineering, and other areas. 

It can be challenging when the understanding of how AI systems work is limited. Most organizations fall short in this area. 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 potential biases. Why is this important? Because 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.

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