**Growth Stage**: `= this.stage` **Last Tended**: ``= dateformat(this.file.mtime, "yyyy-MM-dd")`` **Topics**: #AI #CoIntelligence #LLMs #futureproof #conversationswiththemachine --- Sharing my thoughts on [[Co-Intelligence - Ethan Mollick]] >[!Directors commentary] >Gathering my thoughts and reflections on this recommended read 💡 **Reflections on ‘Co-Intelligence’ by Ethan Mollick** 💡 Firstly, thank you Michael Conway for recommending this read. I wrote to Santa and was lucky to find time to get through it between xmas and New Years. Ethan Mollick’s reflection of the current state of AI mirrors my own experience and beliefs on how we interact with Large Language Models (LLMs) and their potential to reshape our work and creativity. Here are my key takeaways: 1️⃣ **We can better predict LLMs, if we get to know them** Large Language Models can feel unpredictable at times. It's interface draws us into conversation and does a really good job of convincing us of both sentience and authority. But, like exploring something we don’t yet fully understand - To truly leverage it, we must engage, experiment, and map its “jagged frontier”—the evolving boundaries of what it excels at (and doesn’t). 2️⃣ **Beyond Prompt Engineering** Unlike traditional computers, LLMs don’t offer repeatable outcomes from set instructions. As the technology advances, the focus will shift from ‘prompt engineering’ to developing intuitive, conversational interactions— as if we’re collaborating with a human partner. I've found in my experience, that engaging this way has produced far greater results, and importantly satisfaction too. 3️⃣ **Creative & Thought-Provoking Opportunities** Rather than immediately presenting opportunities to automate repetitive tasks through data-driven efficiencies, we have witnessed the emergence of 'Machine Creativity' - LLMs have proven to be able to supporting creative, subjective tasks—art, strategy, and ideation. But this isn’t about handing over the reins; it’s about harnessing this new player to amplify our human purpose. 4️⃣ **Collaboration Models** We’re discovering new ways to partner with AI: either by a clear division of labor—some tasks for the AI, others for us - or a more seamless and less defined integration, where human and AI inputs are interwoven in short iterative loops. Personally, I’ve found this more symbiotic mode, my reality and incredibly powerful for refining and enhancing my work. 5️⃣ **A Call for Purposeful Application** Interestingly, LLMs can provide the greatest value not to experts but to those less proficient in a skill, levelling the playing field in unexpected ways. However, this requires careful oversight: experts must guide the application of AI, ensuring we remain vigilant to its limitations and risks. As we navigate this ever advancing frontier, it apparent that continued curiosity and exploration will uncover further hidden potentials, driving yet further development towards more practical and scaleable applications. The key to integrating it thoughtfully into our workflows will begin with determining efficiencies, not by job but at the more nuanced task level, requiring the individual to identify which parts of their day-to-day can either be i) fully automated, ii) done collaboratively, or iii) reserved for themselves alone (because some joys of creation are purely human). Doing so, we unlock opportunities to work smarter, not harder, while preserving the unique essence of our humanity. But what about the implications - on Society, on Work, on Living? - while this emergence is still developing, there are clearly multiple realities to stride towards, some more enticing than others. I'd recommend giving Kevin Roose's *Future Proof* a read to compliment *Co-Intelligence* too. #AI #CoIntelligence #LLMs #futureproof #conversationswiththemachine ## Open Questions & Implications What about the implications - on Society, on Work, on Living? How do we get a head start, in what might inevitably become a race to remain relevant in a decreasing scope of dependency on human work? How to we see into the future to predict where new areas of work will emerge, giving life to new jobs for our next generations? --- *This is a living document in my Digital Garden. It grows and evolves with my thinking and represents my personal thoughts and opinions, and is not part of my work at IBM. However, it is part of my desire to contribute a broader conversation on how we 'get things done' - exploring the impact of tools and techniques aligned to my mission to help individuals and organisations create the settings for sustained growth.* --- ## Growth Log - 2025-01-04: Initial seed planted - 2025-01-04: Major revision - 2025-01-04: Published on https://www.linkedin.com/posts/chrisjmoreton_cooperating-with-the-machine-intelligence-activity-7281242362490630144-oCfR?utm_source=share&utm_medium=member_desktop