SMEs in the AI ​​era: when the expertise is the most important

Is the involvement of SMEs essential when using AI?

Experts in the matter have in -depth expertise in the area acquired through observation and practical experience. Their ideas are essential to design relevant and personalized learning solutions that really meet the needs of learners. You will find below five key directives to help you determine when the participation of SMEs is essential and when to combine the content generated by AI with SME information for the best results.

AI VS. PME: Five key directives

1. Shhh, it is the owner

Ai PME

(Public data) (owner)

Each organization has tools, technology and best practices that succeed. Can you find this secret sauce through AI? The answer is “unlikely” because organizations must keep this information closely for competitive purposes.

For example, you create integrated content to show how an organization uses owner technology to meet the different customer needs. Thanks to AI research, you find articles on technology, including case studies, published in commercial magazines. That's good, but these articles do not deal with what new hires should learn.

You can only draw these nuances from experts in the matter, who generally have a multitude of knowledge on technology and the ability to apply this complex knowledge to various situations.

2. Human expertise is important when the issues are high

Ai PME

(Low issues) (high issues)

A recent article by Los Angeles Times highlighted the controversy around the replacement of SMEs by AI. THE California's status bar has admitted He used AI to develop exam questions, triggering a new fury. Mary Basick, assistant dean of academic skills at UC Irvine School of Law, told Times that “I am almost speechless. Having the questions written by non-avocates using artificial intelligence is simply incredible”.

This case study raises several problems which have an impact on the use of AI in the future.

• Transparency
  The use of AI to generate exams of examination without informing candidates compromises equity, especially when the result considerably affects their career.
• Ethics
  The use of AI is not ethical when it misleads others on how the questions have been generated.
• Academic integrity
  The use of the AI ​​to create exam questions undermines the credibility of the examination, the examiners and its director.
• Precision
  The content generated by AI is not always correct. We know the trend of AI to hallucinate with its answers. In high issues scenarios – such as examination of the bar – correct questions are not negotiable.

Obviously, AI is not the solution when the issues are high (for example, certification) and academic integrity is essential. There are also problems of contamination by the answers by answers which can be “sycophan” (AI agrees with you) or “sandbags” (AI provides answers according to the indices of your question).

3. Knowledge type: General vs. Personalized

Ai PME

(General) (personalized)

Learning professionals already use AI to discover new subjects and create content. The AI ​​gives access to several sources of general knowledge, including the practices of the real world industry, case studies, trends, leadership behavior and industry best practices to help novices reach a basic level of competence in a subject. Collaborating with an SME is essential for developing learning content adapted to an organization, a process or a specific tool.

Let's look at an example. You have been responsible for improving collaboration between two commercial functions at the key points of interaction. Employee surveys have shown a lack of understanding between roles and dissatisfaction with the current quality of interactions.

You use AI to generate best practices and case studies on an effective collaboration of industry leaders. However, this knowledge is too large to ensure exploitable and authentic learning for your audience. You must now explore to find out how you can customize this general knowledge of specific roles or areas.

You work in close collaboration with the SMEs of the two functions to cause real scenarios that include interfunctional pain points. You design a workshop for delivery in person or virtual. While working on these scenarios and choosing the best answers, learners reflect on errors to avoid and best practices.

4. The learner's results: Understand vs. Apply

Ai PME

(Understand) (Apply)

The example of collaboration above illustrates how you can personalize knowledge for a specific field. This example also shows the differences between understanding a subject and applying it to new situations.

Considering Bloom lenses taxonomyThe AI ​​is the most suitable for content collection to “remember” and “understand”. SMEs are better suited when you need to get content to “apply” knowledge with real scenarios, advice on gray areas and best practices.

Here is an example of how they can work together. A company adopts a new quality management method, total quality management. To search for new solutions, you take advantage of AI to find easily digestible information on executives, define the terminology used in the documentation provided by the commercial unit and research examples on how the frame was applied in different industries.

You also explore the advantages of frames and trends that surround them. These, as well as key concepts, will be presented in the “why” and “What It for me” (WIIFM) sections of a brief Elearning Introduction.

The gaps remain because the true complexity of this subject lies in its current application, and the collection of content of SMEs is essential to remedy it. With real examples, non-examples, stories, case studies and scenarios, SMEs can help:

• Provide the context necessary to apply executives.
• Contact gray areas around the application of “basic rules” at work.
• Guide novices through complex situations.
• Highlight the mistakes to avoid.
• Make the abstract concepts real.
• Provide advice to combat new situations.

Once you have collected this information, you can integrate it into workshops based on applications adapted to various roles through the organization. Another advantage: experts in the field are available to answer questions and support the change process.

5. Let humans do what they do best

Ai PME

(Machine) (Human)

According to the World Economic Forum: Future Report of Jobs 2025The following elements are among the ten skills most requested for the coming years:

• Analytical thinking and problem solving.
• Creativity and innovation.
• Emotional intelligence and empathy.
• Resilience, flexibility and agility.
• Leadership and social influence.

What is all these skills in common? These are only human forces! AI can simulate thought, but it cannot feel – the human touch remains out of its reach. AI has no subjective experiences or does not understand the context. He also needs a clear structure to produce solid outings and cannot respond significantly when meeting situations outside of his training.

This is why, with regard to general skills, you will always need an SME to create significant learning. Imagine if the AI ​​existed before 2020 and the start of the COVVI-19 pandemic. Do you think this would have provided the solutions necessary to provide answers to the unexpected and tragic impacts of the pandemic? In a situation where there was a high degree of uncertainty, nuance and empathy necessary, human expertise was and is always necessary.

Summary

While AI continues to move forward, the question of when relying on AI and SMEs will become more and more important. Currently, the most effective approach to achieving the learner's results is to combine the efficiency of the AI ​​(for general knowledge and data -oriented to remember and understand) with the tacit knowledge of SMEs for proprietary, personalized, complex and applied content.