I’ve been writing and speaking about serendipity and lifelong learning for two decades. It’s my absolute favorite topic. Now, with GenAI (generative AI), I’d like to expand on that thought.

Lifelong learning involves a process of learning and unlearning, acquiring new skills and knowledge throughout your life. Formal education forms only a tiny part of this. My friend and favorite Canadian thinker Harold Jarche introduced me to the 70:20:10 Framework*.

The 70:20:10 framework suggests that 70% of our learning comes from experience, practice, and reflection, 20% derives from working with others, and only 10% from formal education.

Now, GenAI and other technological advancements affect our work environment. It is obvious that formal learning isn’t sufficient for today’s complex, dynamic work environment. (Harold has written extensively about networked learning in his blog.) 

Networked learning is crucial, and this is also where GenAI comes into play.

GenAI Supports Lifelong Learning

Building on these cornerstones of lifelong and networked learning, I explored how GenAI fits into this framework. Serendipitous learning is the process of discovering new knowledge or insights by chance or accident—or by making serendipitous encounters possible. If you limit yourself to your company’s intranet or do quick Google searches, it’s unlikely to happen.

GenAI enhances your learning beyond what you can gain from personal experience and formal education alone, although it doesn’t replace your peer group.

True serendipitous learning occurs when you encounter something unexpected, surprising, or relevant to your interests or goals. Ideally, this sparks your curiosity, imagination, and creativity. 

In my bubble, Twitter/X used to be my go-to serendipity machine. It still holds that position in certain areas. However, GenAI has emerged as a powerful tool for serendipitous learning, supporting my learning efforts. 

Some of us criticize GenAI tools as being too generic or suffering from a ”rubbish in, rubbish out” problem. Often true. Here, I say exactly the same as I said about Twitter in the early days: Twitter is chaotic without both a curating structure and your own sense-making process. Similarly, without investing time in learning GenAI, it won’t serve as your serendipity machine. The prompts that GenAI provides for enhancing your learning differ from those you’d use with a plain Google Search.

Sharing Speeds Up Learning

Building on Harold Jarche’s Personal Knowledge Mastery framework, which leans on networked learning, let’s look at three power verbs in this framework through the GenAI lens: seek, sense, share.

Seek 

GenAI can help you discover relevant sources for information. For instance, it can identify research articles, podcasts, blogs, and other resources that enrich your learning. You can ask GenAI to generate novel and useful questions or tasks that can challenge your learning and curiosity.

Sense 

GenAI can assist you in making sense of what you’ve found. It can generate summaries, analyses, evaluations, and recommendations based on your interests. However, your own thinking and experiences are crucial in this process. The more laborious part is to use GenAI to generate experiments or prototypes to test your ideas or methods.

Share 

GenAI can assist in creating content that can be of help when collaborating with your network and community. It can help you write blog posts, tweets, and reports that showcase your skills and share knowledge in your networks. While many of us do this intuitively, GenAI can help those who find it challenging to articulate their thoughts. So it kind of democratizes the sharing effort. 

Remember: Mindset, Environment, and Exposure

GenAI helps you cultivate a mindset and build an environment that fosters serendipity in your creative process. At best, it challenges you with new tasks or questions and exposes you to diverse inputs that enrich your learning efforts.

To answer the question posed in my title: yes, GenAI can serve as a serendipity machine when used in conjunction with your curiosity, intuition, and consideration.

The question I’m pondering now is whether sense-making is becoming easier or more difficult with tools like GenAI. What are your thoughts?

Riitta

P.S.: This postscript was inspired by an important comment from a reader below. It’s imperative to underline that the heart of serendipity lies in our rich interactions with fellow human beings. The conjecture around GenAI acting as a ’Serendipity Machine’ is by no means an attempt to substitute this human essence, but rather a thoughtful exploration of how AI can serve as a tool. A tool that aids in catalyzing serendipitous moments, fostering unexpected discoveries, and augmenting our human experience. The intention is to extend the realm of serendipity by leveraging AI, all while keeping humans at the core of these fortuitous encounters.

*The 70:20:10 learning model was developed by Morgan McCall, Robert Eichinger, and Michael Lombardo at the Center for Creative Leadership in the mid-1990s.