Discover more from Prodity: Product Thinking
Product Careers, AI Hype, Catastrophic Risks, Algorithms, and Flashcards
Weekly Roundup of AI, Technology, and UX
Here’s the latest news, resources, and use cases from the world of product, UX, AI and technology. Let’s go:
👨💻 Product Careers
🤖 AI Hype
📚 Learning Machine
🏛️ Executive Orders
☢️ Catastrophic Risks
Product Consulting, Driving Outcomes, and Managing a Product Career
Evie is a product consultant who has taken her experience as a product leader and now works with companies to help them grow their products, refine their product strategies, and shift their focus. On this episode, Kyle and Evie discuss how product managers can grow their careers, both within companies or moving into product consulting roles.
We also discuss managing your career in the context of your broader life vision and goals. And how what makes great product managers and great product teams. As well as bridging the gap between expectations and reality for ourselves and our teams as we align around priorities.
News and Useful Reads
Of all big tech companies, Apple should have been ahead of the curve with AI. Or at least positioned to move more quickly. But, like everyone else, it was caught by surprise and is playing catch up.
Apple was caught flat-footed when ChatGPT and other AI tools took the technology industry by storm. But the company is now preparing its response and plans to develop features for its full range of devices.
Microsoft’s bet on AI, specifically OpenAI, seems to be working, if you use share price as a gauge (which I guess what most business classes will do, though I’m sure we can come up with plenty of examples when that doesn’t work out well, but we digress). For Alphabet, it hasn’t been as good.
Now I’m not one to say that profit should be the determining factor for success, especially in the short-term. You can come at me in the comments all you want. But investors and CEOs will certainly care about share price and profit, so we’ll need to pay attention.
If you’re like me, you’re constantly trying to learn new things and improve your pool of knowledge. I thought this article had some good tips and tricks from someone like us who is continually reading and studying and working to remember all the information they are consuming.
He began to treat his mind like technology infrastructure.
Instead of building systems to optimize server performance, he was optimizing his own brain: he was building himself into a learning machine.
Simon realized that in order to level up fast enough to do his work he needed to read—a lot. And not only that, he needed to retain what he read.
So he built an elaborate system to read, retain, and apply the lessons in hundreds of books. And he didn’t just read about infrastructure—he read literature, and scientific history; he read about politics and philosophy.
Along the way he discovered that reading broadly was the best way to get to the bottom of things—and therefore the best way to get better at his job.
The US government seems like it is going to step into the AI regulation arena:
The Biden Administration is reportedly set to unveil a broad executive order on artificial intelligence next week. According to The Washington Post, the White House’s “sweeping order” would use the federal government’s purchasing power to enforce requirements on AI models before government agencies can use them. The order is reportedly scheduled for Monday, October 30, two days before an international AI Safety Summit in the UK.
If you’re worried about the risks of AI, then you’re not alone. OpenAI is with, and has created a new team to evaluate and protect against the risks of AI, including what it is calling “catastrophic risks.”
The team, called Preparedness, will be led by Aleksander Madry, the director of MIT’s Center for Deployable Machine Learning. (Madry joined OpenAI in May as “head of Preparedness,” according to LinkedIn.) Preparedness’ chief responsibilities will be tracking, forecasting and protecting against the dangers of future AI systems, ranging from their ability to persuade and fool humans (like in phishing attacks) to their malicious code-generating capabilities.
Content creation and algorithms.
The creator economy is projected to be worth $480 billion by 2027. In many ways, that figure represents an enormous redistribution of wealth: a tide of ad dollars and other revenue ebbing away from established studios and publishers, and flooding toward individual creators and the technology giants that host their work. But the corporations are the only ones on a secure footing in this arrangement. If individual creators want to stay afloat for longer than a brief moment, they still need managers to help them navigate the algorithmic churn.
Other Useful Finds
I’ve been testing out using flashcards for remembering things, and putting a few things in Anki:
Anki is a program which makes remembering things easy. Because it's a lot more efficient than traditional study methods, you can either greatly decrease your time spent studying, or greatly increase the amount you learn.
I’ve used flashcards frequently when studying for exams or learning languages, but now this is just for general purpose learning. Probably long overdue.