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Humans at the Front, AI at the Back
So, a couple of months into the year, what trends can we see across the Learning and Development landscape for 2024?
Well, some of the key trends are ‘carry overs’ from previous years such as hybrid workplace management, virtual onboarding, and upskilling. However, it’s hard to get away from the one big topic of the moment: Generative AI.
A recent article in the Harvard Business Review examined how Generative AI could accelerate employee learning and development[1]. Although at a nascent stage, the influence of Generative AI might quickly become significant due to the convergence of rapid technological advancements and entrepreneurial innovation.
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The article highlights some of the ways it sees this happening:
- Personalised Learning Pathways: data can be collected from learners that Generative AI can then use to dynamically customise learning content.
- Continuous Content Evolution: Generative AI can be used to keep content permanently up-to-date (apparently, Salesforce’s Einstein already does this).
- Immersive Simulation Scenarios: Generative AI can create highly realistic, varied training simulations that respond dynamically to learners’ interactions.
- Addressing the Skill Gaps: Generative AI can be used to analyse data and target specific gaps in employee competencies.
- Mentorship and Feedback: Generative AI can be used to simulate mentoring interactions and provide real-time feedback.
One of the leading figures in the world of corporate learning and hr, Josh Bersin, has gone even further stating that “thanks to Generative AI, we’re about to see the biggest revolution in corporate learning since the invention of the internet”[2].
Bersin believes the driver of this revolution will be content generated by AI “on the fly” and he sees this happening in four principal ways:
Firstly, new content can be dynamically incorporated into a Large Language Model to create a digital ‘subject matter expert’ that never becomes out of date (ref Salesforce’s Einstein above).
Secondly, Generative AI can dynamically create entire courses containing text, video, audio, quizzes, and simulations.
Thirdly, Generative AI can provide personalised tuition and coaching to employees and learners.
Fourthly, in addition to creating the learning content, Generative AI can then personalise it for each learner.
Bersin believes the emergence of a range of specialist Generative AI-powered learning content authoring tools will lead to a “democratising” of the field of instructional design and see it opened up to “non-designers”.
However, it will be essential to critically evaluate exactly how Generative AI can perform as a tool for instructional design. The role of the instructional designer involves far more that simply producing polished, professional-looking content. Among other things, an instructional designer needs to clearly understand the requirements of both the organisation and the learner; be able to choice an appropriate design model (such as Gagné, Kemp,etc.); select the most effective instructional media, and also develop performance measurement instruments aligned with the learning.
Therefore, any Generative AI tool used to create learning materials should be judged not just on the quality of the content produced but also whether it adheres to the principles of good instructional design. The kind of questions that need to be asked are: Does the learning content generated hold up to pedagogic scrutiny? Are the media used to deliver the learning appropriate to both the content and the target audience? Does Generative AI produce assessments that truly and accurately measure the learning?
Looking at the formal education sector, Generative AI is beginning to have a major impact with a Forbes article claiming its effect will be transformational on a scale not seen since the industrial revolution[3].
Generative AI is accelerating the emergence of new technologies, intelligent agents, digital tutors, and adaptive learning that can provide engaging learning experiences to every age, ability, experience, and background.
Generative AI is also obliging educators to re-think what, when, and how they assess student learning, and it offers the possibility of not just assessing what students are learning but how they are learning – what is referred to as metacognition.
Looking further ahead, it will be interesting to see if Generative AI can be leveraged to assist in the creation of AR/VR learning content. Currently, the creation of learning content for AR/VR environments is both time-consuming and expensive with some of the skills required in short supply[4].
Given the impact Generative AI is already having on the wider field of digital content authoring, it seems reasonable to expect it to start having an impact in the area of AR/VR in the very near future.
Finally, there are some significant things happening regarding the regulation of AI that anyone planning to use it for Learning and Development will have to keep a close eye on.
The European Union plans to provide oversight and regulation of Generative AI through the recently published AI Act[5].
The purpose of the act is to achieve the following aims:
- address risks specifically created by AI applications.
- propose a list of high-risk applications.
- set clear requirements for AI systems for high-risk applications.
- define specific obligations for AI users and providers of high-risk applications.
- propose a conformity assessment before the AI system is put into service or placed on the market.
- propose enforcement after such an AI system is placed in the market.
- propose a governance structure at European and national level.
The new EU AI Act and accompanying regulations make adherence to ethical standards when using AI a legal requirement for all organisations across the member states. The Act is expected to be voted into law in April 2024 at which point the lead-times for compliance will be set out.
At the same time, the government in the UK are taking a significantly more ‘hands off’ approach and recently made clear they have no immediate plans to enact new legislation in response to the rapid developments in the world of AI[6].
The UK government intends to rely on the existing range of legislation that applies to AI – such as data protection, equality law or medical device regulation – while at the same time monitoring and assessing any emerging risks. Where it believes a significant new threat with has emerged as a result of the use of AI, the UK government will then decide on the appropriate measures.
[1] https://hbr.org/2023/12/how-genai-could-accelerate-employee-learning-and-development
[3] https://www.forbes.com/sites/vickiphillips/2024/01/03/in-2024-5-big-issues-will-shape-education/
[4] https://www.learningguild.com/articles/near-term-vr-ar-and-ai-inroads-in-skills-based-learning-/
[5] https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai
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