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Artificial intelligence still needs human intelligence

Everyone seems to be talking about artificial intelligence. While AI first emerged in the 1950s, AI has made advances as technology has improved.

Just about every industry uses some form of artificial intelligence. But how will it affect learning and development for nonprofits and associations?

First, as it stands now, professionals shouldn’t worry AI will take away their jobs, says Docebo in a new whitepaper. AI is nothing without people. When it comes to e-learning, humans direct AI to make logic-based “decisions.”

And that’s why metadata and properly tagging content is so critical, the report says. Both allow AI to learn what content is relevant.

However, since AI is simply an algorithm, content needs to be valuable. 

“It is also interesting to note that AI in L&D is becoming increasingly important because it can use proper metadata and xAPI-driven intelligence to determine which users ought to take a certain course based on behaviors and situations,” Docebo says. “It can, in the best examples, tell a learner a certain course is useful given certain parameters and apply rules accordingly. This is the infancy of AI learning to understand the learner, and the potential of this is vast.”

So what about learners?

Learners play a key role in shaping AI. The more a learner uses a system, the better AI will be able to understand a user’s needs. When AI can predict what learners want to know, it can make recommendations. Allowing AI to perform that work allows time for instructional designers to improve content – which ultimately benefits learners.

“That’s why improving user experience through more enriching content is critical and – here’s where AI won’t own L&D anytime soon – you need humans to create and enhance great learning content on an ongoing basis. As they say, Content is King.”

And more good news for learning and development staff.

Docebo says AI will be able to suggest or assign learning assets based on a set of criteria:

  • Learning objectives: Identifying the most relevant learning objectives and topics for the role and the task at hand
  • Skills data: Suggesting what has worked in the past to increase specific skills in similar roles
  • Performance data: Suggesting what has worked in the past to increase specific KPIs (i.e. reach 80 percent of sales quota in six months)
  • Learning style: Suggesting preferred format based on learning style: i.e. a full course or a
  • collection of small content bytes
  • Preferred channel: Suggesting the use of mobile for people that are constantly on the go or full desktop for highly technical and detailed instructions
  • Personal interests: Taking into account user preferences
  • Organizational behavior: Taking into account the traits of the organization to which learners belong
  • Learning interventions: Triggered based on a change in regulations, compliance or in company policy

“The impact of AI in elearning may be nebulous at this point, but there’s no doubt that AI has arrived and, in the coming years, will affect the sphere in a big way,” Docebo contends. “It will contribute to how we learn and how we teach and, increasingly, it will affect how we delegate learning to automation and, eventually, artificial intelligence. Although AI in elearning is already here in many ways, it is important to consider how it will manifest itself in the near future, and to understand that the associated implications will come very soon.”

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