#61 - Maybe your kid oughta study literature, after all?
Leaning into the "uniquely human" in the age of AI
What's up, everybody?
This week, a friend and I traded notes on AI and its impact on work. Her take: "AI just is." By which she meant that AI is inevitable; it's here, it's already disruptive, and it will have good and bad impacts. So we may as well figure out how to adapt to it.
We agree, and we believe that our collective response to AI will, also, be what it will be: challenging, flawed, full of ups and downs. And -- like AI itself -- completely beyond our control.
But at TalentStories, we like to focus on what we can control: our individual response. Our understanding of how that response impacts our organizations, and the people we lead.
As curators of a newsletter focused on change at work then, AI poses an interesting challenge. Not writing about it feels negligent to the point of irresponsible. But how much space to give to it? And how to avoid adding to the shrill conversation around its downsides, and upsides?
Well, our guiding principle -- and our commitment to you -- is to bring the same open-minded curiosity to AI that we do to any other topic. To seek to understand it; to take an optimistic approach, by default. And to lean -- early and often -- into the learning to be had. Together. 🤝
In that spirit, today we use our 3 Stories to explore how we can respond to a world in which machines and data are so ubiquitous. A reality that's coming faster and sooner than we can appreciate:
Story #2 - A Harvard professor and expert on work and AI encourages us to "lean into our uniquely human skills"; but also ID's the challenge of doing that in an age of algorithms -- and shares fantastic, practical advice for how to overcome the hurdle. 🙌🏻
Story #3 - How will AI "everywhere, all the time" will impact the role of a manager; and what crucial part will learning play in a workplace that's about to radically transform?
Thanks for reading and exploring with us -- and have a great week!
Aki + Usman
P.S. Our podcast discussion of last week's issue #60 -- "Generational awareness is the new cultural awareness" -- clocks in at a breezy 15 minutes. Check it out right here.
#1
#AI #Disruption #Architect
This breathtaking chart is part of Paul Kedrosky's argument that the large language models (LLMs) which AI like ChatGPT use are going to revolutionize software, by making it more accessible and less complex. Kedrosky explains that because software language is so structured and formal, LLMs can efficiently create code -- even for non-coders. 🙌🏻
Then he goes on to make these observations and predictions:
- All tech breakthroughs occur when something expensive becomes cheap enough to use widely.
- Until now, software creation has been too complicated and pricey for too long, which has led to its underproduction.
- But as the cost and complexity of software production plummets, we can expect a wave of innovation to sweep across the economy.
Our takeaways, in the event he proves right?
First, excitement over democratizing software production, and the innovation that might result. 🙌🏻Second, if software becomes accessible to coders and non-coders alike, then the value we can bring will increasingly be a function of our ability to guide the machines; it will lie in our creativity. And in our ability to apply our uniquely human thinking to them.
This dovetails with the quote we featured in Issue #41, from investor David Friedberg, that is worth re-surfacing:
#2
#AI #Response #LeanHuman
The podcast here is well worth a listen. But if you're pressed for time, these highlights from it are, in a word, stellar. ↓
The guest of the show was Dr. Tomas Chamorro-Premuzic, chief innovation officer at Manpower, a professor at Harvard, and the author of a book: "I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique."
From the show notes:
And, Chamorro-Premuzic says, as work becomes defined by data and automation, humans become more important, not less:
This leads us, though, to the challenge of the quote in the image above: that leaning into our uniquely human skills takes effort. Lest the predictability of algorithms leads to becoming a more distracted, biased and exaggerated version of ourselves. 😳
So what, pray tell, does Dr. Chomorrow-Premuzic recommend we do in that case?
More variety, unpredictability and whimsy --> more creativity. ✅
#3
#AI #Managers #Adaptation
This article in the Harvard Business Review was written in 2018, which feels like eons ago in AI years. 🤣 But it thoughtfully lays out 6 key ways in which a manager's role needs to change in a management context now defined by moving targets. In short, managers need to go from:
- Directive to Instructive
- Restrictive to Expansive
- Exclusive to Inclusive
- Repetitive to Innovative
- Problem solver to Challenger
- Employer to Entrepreneur
To be clear, we are here for all these shifts. But we want to focus on "Directive to Instructive". The authors explain:
Thus the requirement in the quote of our image: that managers think through the impact that Al will have on their work. That they explore and experiment with Al to extend their own knowledge and learning -- and that they model that exploration to their teams.
And this brings us, finally, to the criticality of learning in this process, and the responsibility of a manager to embody it:
Thanks for reading. 🙏🏻