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{"id":3416,"date":"2020-09-21T18:20:59","date_gmt":"2020-09-21T18:20:59","guid":{"rendered":"https:\/\/proactivetraining.com.au\/news\/2020\/09\/21\/how-good-is-ai-at-improving-training\/"},"modified":"2020-09-21T21:35:20","modified_gmt":"2020-09-21T21:35:20","slug":"how-good-is-ai-at-improving-training","status":"publish","type":"post","link":"https:\/\/proactivetraining.com.au\/news\/2020\/09\/21\/how-good-is-ai-at-improving-training\/","title":{"rendered":"How Good Is AI at Improving Training?"},"content":{"rendered":"
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Understanding how artificial intelligence works is the first step in figuring out how we can apply it to training.<\/div>\n<\/div>\n<\/div>\n
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Article Author: <\/div>\n
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Roy Saunderson, MA, CRP, Chief Learning Officer, Rideau Recognition Solutions<\/div>\n<\/div>\n<\/div>\n
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When I think of artificial intelligence (AI), I can’t help but jump back to my first exposure to the concept with the film, 2001: A Space Odyssey.<\/em> Called HAL 9000, the computer in the movie runs by artificial intelligence and is the main antagonist in Arthur C. Clarke’s “Space Odyssey” book series.<\/p>\n

HAL initially is portrayed as a dependable member of the crew, maintaining ship functions and engaging genially with its human crewmates on an equal footing. Then malfunctions occur in the system and the astronauts try to shut it down. However, HAL takes over the spaceship’s system in order to fulfill its programmed directives and ends up killing one of the astronauts.<\/p>\n

Thank goodness, this is just science fiction—it’s not exactly what you want happening with today’s workplace training.<\/p>\n

But we are more used to machine learning than we realize. Take, for example, the Internet searches we conduct, working with virtual assistants, or even shopping online and checking out recommended purchases.<\/p>\n

Interestingly, in a recent survey of HR professionals by the Engage2Excel Group, when asked which technology trends HR professionals were most interested in learning about, 81 percent chose AI.<\/p>\n

QUICK SNAPSHOT OF MACHINE LEARNING<\/strong><\/p>\n

Let’s dive into the beginning steps toward AI. Rule-based machine learning (RBML) is a term computer science uses to include any machine learning method that identifies, learns, or evolves “rules” to then store, manipulate, or apply those rules.<\/p>\n

Data fed into a computer can handle multidimensional and multi-varied inputs. No human intervention is required, and computer analysis can easily identify various trends and patterns. This has wide applications, including training, and allows organizations to use data synthesis and analysis for ongoing continuous improvement.<\/p>\n

The disadvantages of machine learning include acquiring the right kind of data, which consumes a fair amount of time and people to access. This human element of data selection can generate a susceptibility to higher error levels, as well as questionable interpretation of data.<\/p>\n

SAS, a leader in business analytics software and services, states that machine learning tackles tasks in four primary ways through:<\/p>\n