A Quick Guide to AI Terms You Need to Know

With the increasing use of AI being implemented to run everything from IT Ops to service desk processes, it is increasingly incumbent upon business leaders to understand and to be able to communicate effectively regarding Machine Learning and its employment throughout organizations.

Here is a quick guide to the key terms, an Artificial Intelligence Glossary, if you will, in which we try to showcase some of the most essential terms and provide a bit of information about their application and usefulness.

Adversarial Machine Learning

A key technique used by developers to train AI by giving it intentionally deceptive data to generate incorrect choices or conclusions. This data can then be used to further advance the usefulness of the AI. Unfortunately, adversarial machine learning can also be used by bad actors to cripple AI.

Algorithmic Auditing

A tool used to test for bias in machine learning application algorithms by examining the decision-making process and conclusions drawn by AI for patterns of error and other issues.

Chatbots

Chatbots are software programs utilized to help enhance the user’s experience of IT and other processes and environments. They are increasingly being developed with somewhat individual personality and backstory to enhance the user’s perception of their engagement.

Conversational UI or Voice AI

Conversational UI, which also goes by the name of voice AI, is the software-based processing of natural human language, giving chatbots and other AI the ability to recognize, interpret, and interact with humans through speech and text.

Re‑skilling

The development and employment of machine learning and Artificial Intelligence across organizations brings with it the opportunity for workers, including IT ops professionals, to spend less of their workday engaged with the actual running of processes that can instead be automated. Re-skilling pertains to the retraining or re-education of workers to help them manage AI, and to perform the high level tasks that by necessity require human skills.

Robotic Process Automation (RPA)

Simply put, RPA is the management of processes by AI managed by other AI – applications instructing other applications to automate a wide variety of potential work that at one time required human labor.

Unstructured Data

Data that requires human interpretation, because it cannot be readily understood by artificial intelligence due to its complexity or lack of specific organization. Examples can include some nuanced text, video, and still images. However, unstructured data can be converted into data organized around a framework by some advance AI.

Jargon by Any Other Name – An Artificial Intelligence Glossary

This artificial intelligence glossary is by no means meant to represent a comprehensive look at all of the terms involved in the burgeoning field of the application of machine learning through AIOps. It does, however, include most of the absolute key terms that business leaders need to have in their vocabulary in the immediate future.

Learn more about Artificial Intelligence and how it can help the IT service desk.