AI And Automation: Finding Smarter Ways To Learn

AI and automation technologies deliver effective remote interactive training for workers

Ask most technical training instructors whether in-person sessions are preferable to remote classes and they will likely say that they are. In large part, this is because they give trainees the benefit of hands-on learning.

Having in-person sessions has been a challenge over the past year, as many training programs have had to shift to an online format due to the Covid-19 pandemic. However, that does not mean the training has been less effective. In fact, new interactive learning programs supported by emerging artificial intelligence (AI) and, more specifically, natural language processing (NLP) tools, are changing the way enterprises approach training.
 

For example, learning companies can leverage advanced NLP engines to deliver fast, contextually relevant answers to the challenging technical questions a user has while taking a course or training session. Additionally, it can also help organizations understand which skills employees are looking to refine, arming them with helpful business insights about the tools and knowledge their team needs to succeed. 

While traditional search engines might do a good job surfacing content by topics, titles, or authors, those same search engines fall short when users have very specific questions in mind. In this case, searching by metadata and keywords might not be sufficient to find answers quickly. As a result, workers can spend hours on end looking for pieces of information needed to complete a project or to solve a problem, resulting in a significant drain on employee productivity.

A search experience powered by NLP enables users to ask questions and then gain immediate access to the most relevant excerpts of content that can answer the question at hand. This eliminates the need for users to drill down into volumes of text and scan through dense chapters and paragraphs to find exactly what they are looking for.

NLP-powered solutions are designed to accept questions from users in the same conversational, natural language people use every day when speaking with one another, and retrieve relevant answers from a vast online library of textual content, whether it be eBooks, video transcriptions, event excerpts, and or any other type of text-based training material. 

This type of human-to-computer interaction is so impactful because it flips the current paradigm, enabling computers to adapt to our speech patterns, rather than the other way around. For instance, when using a search interface such as Google, people tend to use keywords or phrases instead of complete sentences. They tend to assume that computers will not be able to grasp the nuance and context that comes with speaking in complete sentences. NLP is changing that. 

Over the coming months and years, as machine learning models become smarter, the methods of communication will become far more humanized. If trained on enough data, a system can parse intention and context from just a single sentence and respond accordingly.

To accomplish these advances in NLP, machine learning platforms have started employing a methodology called “transfer learning,” which takes language constructs they understand in one setting and apply them to a new situation, much like the human brain would do. And the emerging NLP tools go well beyond keyword-based search. They possess the ability to analyze questions and display answers buried deep within any given content, create more realistic chatbots, and power virtual assistants, to name just a few applications of the technology.

Looking ahead, we will no doubt see an uptick in the use of AI applications and automation to support and augment the responsibilities of the workforce with both technologies playing a critical role in employee training and education programs. To keep pace with technology and business, smart organizations are investing more in training and continuous learning, and these new features better enable workers to take advantage of these tools, while staying motivated and productive in their day-to-day workflow. 

Driving this trend is the proliferation of cloud-based AI platforms, which provide companies of all sizes with access to useful AI tools. This shift further democratizes AI capabilities, enabling any type of organization to leverage the technology as part of its training strategy and beyond. 

As a result of this democratization, AI capabilities are becoming increasingly important in assisting learners in fast information retrieval with minimal disruption to their regular responsibilities. Learning in the flow of work should be a pillar of forward-thinking companies, and those that keep this in mind will see better outputs of productivity and employee retention. 

All things considered, it’s safe to predict that the use of AI will continue to evolve as a way to assist corporate training, and will vastly reshape how people learn. It will be exciting to see how far technologies like NLP can launch skills-building initiatives over the next several years, and the business results. 

Adam Witwer is VP of Product Management at O’Reilly. Adam has a background in technical publishing and switched his career focus to product management. After launching several successful products in the digital learning space, Adam went on to build the product team at O'Reilly. His focus today is on creating experiences for technical professionals who always want to keep learning. Visit www.oreilly.com Connect Adam Witwer