Unless you’ve been under a rock over the past year – or in some discrete corner of the metaverse – it’s been hard to miss the seismic impact that Artificial Intelligence has had on all things tech.
AI has clearly attracted talent, capital, pivoted product roadmaps, reallocated (and laid-off) resources, and pulled in a bunch of VC funding – like a giant magnet in the paperclip 📎 aisle at your local Office Depot.
Even for someone working in the technology space, this all feels pretty fast. Like jump-to-lightspeed fast. Exciting!
What’s interesting is that many of the products folks are already using are simply just getting infused with AI. And there really isn’t an adoption curve. It’s like Digital Transformation 2.0 — but it’s kind of just there; like electricity.
Even terms like “hallucination-free” have entered our daily lexicon via mainstream media product ads.
Now granted, as with any of these types of inflection points, it didn’t happen overnight.
I remember looking at this technology in graduate school thinking that there wasn’t necessarily a there there. At least not yet.
BTW, I still think the most important piece of advice I got in grad school from a professor was based on this simple exchange where I questioned the possibility of the software we were working on:
Me: “Well, can the software do that?”
Wise Professor: “It’s software. It can do anything we want it to.”
Ok, lesson learned. And yeah, I guess the promise of AI finally caught-up, as well.
I’ve been reading a fair amount about the AI space over the past several months (see some notable resources below) trying to look at both sides of the equation: from the promise of Utopian, to the doomsday scenarios.
I’m probably just slightly over-indexing on the positive end of the spectrum.
I’ve also been messing around with the core tools themselves; incorporating them into my daily workflow, building out a few narrow GPTs, and looking at offerings from several leaders in this space.
And so, I’ll aim to write more about this topic in the coming weeks — including usability implications, people’s mental models when using the technology, and maybe even applied considerations for the day-to-day workflow of UX professionals.
Note: Check out a follow-up piece regarding prompts — On AI: Part 2
Marc
Recommended Readings
Essays:
Why AI Will Save the World — Marc Andreesson
Why the Godfather of A.I. Fears What He’s Built — Joshua Rothman
Books:
The Age of AI: And Our Human Future — Daniel Huttenlocher, Eric Schmidt, and Henry Kissenger
Life 3.0: Being Human in the Age of Artificial Intelligence — Max Tegmark
AI Superpowers: China, Silicon Valley, and the New World Order — Kai-Fu Lee
Podcasts:
Making Sense — Sam Harris