To Make Gen AI Work, Try More Play
Read on to discover how playful, imaginative workshops can prepare us for a rapidly evolving Generative AI future and help us prototype new ways of working and being.
A clear trend on the agendas of innovation-focused corporate learning and development programs over the last year is the rise of the “Generative AI Workshop” – an ostensibly hands-on, learn-by-doing dive into the most promising or hyped technology of the moment. The interest, opportunity, and need are all pretty clear, but the offerings designed to meet the opportunity vary widely, as do the outcomes.
At worst, we’re talking about a workshop in name only—a slides-driven demo that only claims to be hands-on. Then, there’s a serviceable, common model of a workshop that's basically an “I Do, We Do, You Do”-type tutorial. It combines the instructor demo with some facilitated and possibly collaborative learning focused on using specific Gen AI tools to accomplish specific tasks—often tasks chosen to closely align with the roles and functions of the learners in the room.
These workshops get the basic job done: They move beginners from 0 to 1 by providing some exposure to common LLM tools (MidJourney, ChatGPT, Gemini, etc.) and some scaffolded instruction around practical, work-oriented tasks. That’s a win, but we can do better.
In a field evolving as rapidly as Gen AI, where the tools and the scope of possibility are changing weekly and the best practices are emergent, I’d argue that the best workshops need to offer something more. They need to inspire in learners a wider-ranging passion to explore the evolving landscape while remaining engaged, curious, flexible, and playful.
That latter part is important because the tools and techniques taught today are going to change—and quickly. The roles of the leaders and learners in any workshop will also change, as will their respective organizations and industries. But rather than teaching more tools, I think we need to teach the tools more playfully.
A Generative AI future threatens to leave a lot of people feeling overwhelmed, underprepared, and unsure of how—or even whether—they will find a valuable role in that future. Play happens to be a learning modality that’s especially well-suited to exploring shifting roles, new challenges, changing rules, and unfamiliar environments. This was also part of Jane McGonigal’s famous argument for the social value of video games in Reality is Broken.
There’s a reason that play is so adaptive and valuable for children (and other animals!) as they are beginning to understand the world and how to navigate it, and play can be just as useful for adults—still the same animals, after all—who find themselves confronted with a world that is in the process of becoming something new and deeply new to them.
To be clear, I’m not just talking about bringing gamification and high scores to Gen AI workshops here. I’m talking about creating novel, low-stakes environments that encourage curiosity, experimentation, and participant exploration of possibilities that exist beyond (or wildly outside of) present-day, work-determined tasks and functions. Pascal wrote last week about AI as a new “bicycle for the mind,” and I think we all need to be pushing ourselves—and helping others—to embark on deeply imaginative journeys rather than simply running errands on that fancy new bike.
Massively accessible, increasingly multi-modal AI tools offer us a tremendous opportunity for creating first draft versions of just about anything. Shouldn’t we be using them to prototype new and more imaginative ways of working and being—new versions of ourselves as learners and leaders who are ready to embrace the future?
@Jeffrey
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