Machine learning and Artificial Intelligence (AI) are all around us, and we are more used to it than we realize. For example, the internet searches we conduct, working with virtual assistants, or even shopping online and checking out recommended purchases.
Interestingly, in a recent survey to HR professionals by Engage2Excel Group, when asked which technology trends HR professionals most were interested in learning about, 81 percent responded with Artificial Intelligence (AI).
Quick Snapshot of Machine Learning
Rule-based machine learning (RBML) is a term computer science uses to include any machine learning method that identifies, learns, or evolves 'rules' to store, manipulate or apply those rules.
Data is fed into a computer and analyzed quickly to identify various trends and patterns. No human intervention is required. RBML has a wide variety of applications, like training, and allows organizations to use data synthesis and analysis for ongoing continuous improvement.
The disadvantages of machine learning are 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 susceptibility to higher error levels as well as questionable interpretation of data.
SAS, a leader in business analytics software and services, states that machine learning tackles tasks in four primary ways:
- Machines need to be taught by example before they can apply the resulting insight to similar tasks.
- Machines can extrapolate from a general pattern and apply it to other data.
- Machines can, unsupervised, study data to find patterns, getting better with experience (though never autonomous).
- Machines can work with and exploit a given set of rules to move towards a desired outcome.
Applying AI to Learning
When AI is applied to various learning tools and programs available to us today, Learning and Development professionals can fully utilize these solutions to deliver learning that is:
- Automated in its delivery
- Personalized to the individual learner
- Intuitive in its application
- Data-driven across the organization
- Fostering continuous learning throughout the organization
The data gained from employee usage of AI driven learning programs will give L&D professionals a better understanding of the insights of learners’ behavior. This helps improve the overall learning experience by developing intuitive learning pathways. AI provides a predictive analytics component that examines data, or content, to answer the question, “What is going to happen?”, or more precisely, “What is likely to happen?”
Learning content becomes much smarter in its application because it is more intuitive and responsive to learners’ needs. Learning content can be delivered through various mediums, like chatbots, and help with retaining the knowledge learned. This can be through continuous delivery of courses in progress or with Just-In-Time learning of new material the AI system recommends for the learner.
How AI Helps Training
Using AI in training will become an essential tool for improving learning and retaining new knowledge and skills. Employees will receive learning content prescribed from knowledge and skill-based assessment tools. Also, they will receive personalized course recommendations.
AI helps in making all types of learning content accessible to individuals with most forms of disabilities. Consider Microsoft’s Seeing AI app that narrates to a low vision individual the world going on around them. Imagine the learning possibilities.
Besides innovative possibilities such as digital AI tutors, the biggest asset of AI and training still comes back to data. Analyzing all the training data through AI will help to provide the best kind of training for the future, delivered the preferred way, at the difficulty level best suited to each employee.
Authors note: This article originally appeared on TrainingMag.com. Click here to read it in its entirety.