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Ethan Mollick in Co-Intelligence

Humans, walking and talking bags of water and trace chemicals that we are, have managed to convince well-organized sand to pretend to think like us.

Why did I pick this book?

I was looking at books on artificial intelligence from a non-technical perspective. Most books currently on the topic of AI either are technical in nature or are focused on prompt engineering. This book came up in a podcast. The cover also caught my eye - the symbolism of AI as a forbidden fruit seemed apt to the topic.

If this book could be summarised into one word, it would be Catalyst.

If this book was a character, it would be a thoughtful mentor who can guide you through the possibilities of human-AI collaboration. This mentor is forward-thinking and possesses a sharp intellect. They acknowledge the potential pitfalls of over-reliance on AI while emphasising the importance of treating AI as a co-intelligence instead of an adversary. This partnership, the book suggests, holds the key to unlocking unprecedented levels of creativity and productivity.

What were the ideas that I liked and want to explore?

There were a few interesting ideas that I really liked and want to explore more:

• co-intelligence: The idea of using AI as a collaborator to achieve a human goal. The book explores how we can look at AIs in the roles of a person 🧑, a creative 🧑‍🎨, a coworker🧑‍💼, a tutor 🧑‍🏫, and a coach 🧢.

• The four co-intelligent principles are:

  1. Always Invite AI to the Table.
  2. Be the Human in the Loop.
  3. Treat AI Like a Person (But Tell It What Kind of Person It Is).
  4. Assume This Is the Worst AI You Will Ever Use.

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• The jagged frontier is the unpredictable and uneven nature of AI capabilities.

• The task classifications when using AI:

  • Just Me Tasks (no AI involvement)
  • Delegated Tasks (full AI involvement)
  • Centaur Tasks (humans and AI working in parallel)
  • Cyborg Tasks (humans and AI constantly collaborating on a single task).

• Using AI Personas for a better collaborative task solving.

• This trend of including AI prompts in books, as seen in Duly Noted and The Two But Rule, excites me.

How did I put this into action?

In the weeks after reading this book, I tried to put these principles into action and found them very useful.

• Reading Duly Noted further solidified the concept of co-intelligence. I used Google’s NotebookLM with my highlights and notes for this book as an input. I could clearly see the benefits as I used the tool to help me synthesis ideas from my notes.
• I’ve embraced the idea of using AI as an amanuensis firmly and I feel it’s an application of AI as a co-intelligence.

This book also piqued a few questions:

• [?] When a human working with an AI co-intelligence outperforms all but the best humans working without an AI, what does that mean for the ‘experts’?
• [?] With the improvements to the GPTs coming at break-neck speed, what’s the impact on human creativity vis-a-vis learning? Will we be engorging on AI-generated content more and more?
• [?] As LLMs improve, will ‘prompt engineering’ go away or get better with muti-modal inputs?
• [?] Is the Turing test really a test for humans not for machines?. If humans can be fooled into thinking that machines are sentient, then a Turing test taken by a machine is to test if the invigilator is human by trying to fool them.

Footnotes

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