In recent years, higher education institutions and various online platforms have been quick to provide microcredentials, these conveniently digestible and stackable nuggets of knowledge that sharpen specific skills.
The appeal has been obvious: microcredentials offer a flexible, cost-efficient way for the modern workforce to swiftly acquire competencies in areas of high demand. Simultaneously, they enable institutions to generate revenue in challenging times with limited funding. It is a win-win.
Or at least it was before November 2022.
The Rise of AI
I believe the narrative of microcredentials, as the future of education, is beginning to fray at the edges. As AI becomes increasingly capable, it is poised to automate many tasks that microcredentials currently equip people to perform. Foundational skills and learning will be as important as ever, but unless it’s your profession, why spend time learning financial analysis if an AI algorithm can sift through data more efficiently and accurately? Or why train specialised medical professionals in areas like radiology or pathology to enhance their diagnostic abilities when AI-powered diagnostic tools are becoming increasingly proficient in analyzing medical images and identifying patterns associated with various diseases? There are noticeable exceptions, of course, but the general idea stands.
While the trajectory of AI is still unpredictable, it is already abundantly clear that future developments in AI will lead to machines supplementing humans in areas like bookkeeping, data analysis, languages, media, logistics, and more. This doesn’t signal the disappearance of human jobs altogether, but it will lead to a substantial modification of them. Naturally, this modification implies a fundamental change in the function of shorter skills-based modules of learning like microcredentials as well.
In our new reality, what becomes paramount are not so much specific skill sets as more abstract and uniquely human qualities like forming hypotheses, using one’s imagination, and developing critical thinking abilities, amongst other things. I’ve written fairly extensively about this in the posts On AI and the Problem with Instant Answers and The Problem with AI Chatbots in Literature.
AI Renders Microcredentials Irrelevant
In a future world of education dominated by AI, microcredentials, with an emphasis on transmitting particular skills and knowledge, will gradually lose their relevance. They will need to become something else to survive.
For example, a microcredential in statistics furnishes you with the skills to conduct statistical analyses. But understanding when, why, and how to apply these skills requires discernment and insight that can't easily be packaged into a microcredential. Similarly, simple tutorials in basic office software might equip learners with surface-level skills, but navigating an ever-changing workplace necessitates traits like imagination, ethics, and teamwork.
The argument for radical change and adaptability in higher education isn't new, but AI brings a fresh urgency to this old debate. Instead of collecting a string of microcredentials as we know them today, learners would be better served by pursuing a more AI-integrated style of learning. Let me illustrate how this might work.
A New Approach to Microlearning and Credentials
When a user engages with a chatbot that may have been trained on university proprietary data and begins to ask multiple questions on a given topic, the chatbot could ask if the learner wants to get serious about studying the topic, possibly for an exam. The chatbot would be able to discern and adapt to the appropriate level, depending on the learning objectives and any similar documentation the learner may provide.
AI technologies like GPT-4 are capable of conducting sophisticated conversations and presenting information in a structured and comprehensible way. If a learner wished to delve deeper into a subject, the AI could adapt the difficulty level and complexity of the information provided.
In terms of studying for exams or pursuing a microcredential, AI could assist in providing study materials, practice questions, and even mock exams. It could also track a user's progress over time, identifying areas of weakness and tailoring multimodal content to help improve those areas.
Perhaps an AI-generated summary of the chat, automatically formatted to the school’s standards and forwarded for human consideration, would even be adequate to grant a pass and issue a ‘microcredential’ automatically.
Clearly, we are not quite there yet, with problems such as hallucinations, validation of knowledge, and ethical and regulatory concerns. But the technical problems with AI systems are improving much faster than one might think.
When that happens, automated microlearning has the potential to expand across all levels of learning, globally and exponentially.
The Future of Learning
Clearly, AI's ascendancy doesn't have to spell doom for all types of learning. However, it necessitates a profound reconsideration of the true purpose of education and how to best support learning with technology. For instance, focusing on uniquely human capabilities such as critical thinking, empathy, and complex problem-solving might become more vital than ever. Instead of concentrating on discrete skills that AI excels at, we should be honing what makes us distinctly human.
The future of learning is not merely about keeping pace with AI or mimicking its functions. It's about nurturing our uniquely human capacities and integrating technology in ways that enhance human potential. By reevaluating the purpose of education and the skills we choose to value, we can shape a future where AI is not a threat but a tool that augments human abilities, and transforms, rather than renders, higher education obsolete. This requires both innovation and caution, utilizing AI's strengths while recognizing its limitations, to create a more responsive and enriched educational landscape.