J-Space, AI Jobs, Urgency Trap, Human-Led Research, and the Iliad
Your Weekly Review of News in Technology, UX and AI
A shift continues to run underneath the news of AI. We’ve gone from “can AI do this?” to “what do we lose when it does?” Anthropic is analyzing its own model’s thoughts. NN/G is insisting that even if AI matches a researchers output quality, it still misses the point. And HBR is warning leaders that urgency is the enemy of good AI strategy (as it is the enemy of most things). Capability isn’t the constraint. Judgement and readiness are.
Here’s the latest news, resources, and use cases from the world of product, UX, AI and technology. Let’s go:
📊 AI in Healthcare
👾 J-Space
👿 GPT-Red
🤖 AI Jobs
⏩ Urgency Trap
🚶➡️ Human-Led Research
🧭 Product Craft
🔱 Iliad
Podcast
Harnessing AI in Healthcare: Insights from RJ Kedziora
In this episode of Product by Design, Kyle Evans interviews RJ Kedziora, co-founder of Estenda, a company specializing in custom software and data analysis for healthcare. We discuss RJ’s journey in technology and entrepreneurship, the importance of energy management over time management, and the role of AI in healthcare. RJ shares insights into the challenges and future of AI applications, the need for ethical considerations, and the potential for personalized healthcare solutions. He also offers advice to aspiring entrepreneurs looking to make a difference in the industry.
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News and Useful Reads
What Anthropic’s latest AI discovery does—and doesn’t—show
An Anthropic team built a tool called the Jacobian lense (J-lens) and used it to uncover a hidden area within Claude (the J-space) which contains words related to the response a model is working on but may not ultimately produce. This was an unknown space for puzzling through problems until Anthropic uncovered it.
Anthropic has been trying to understand how large language models (LLMs) work for a few years now. Anthropic isn’t the only one looking at this, but I think the company has made it part of its core mission more than most. Anthropic’s CEO, Dario Amodei, has said we won’t be able to control LLMs fully unless we learn more about how they work.
Meet GPT-Red: an LLM super-hacker OpenAI built to make its models safer
OpenAI built its own LLM hacker called GPT-Red. As with most other red teams, it tests for vulnerabilities and boost defenses against cyberattacks. This has traditionally been done by human hackers/testers, but unsurprisingly we’re seeing AI companies lean heavily on AI.
As LLMs become more complex and get used in a wider variety of tasks—especially in the form of agents, which can interact with computer files, websites, and third-party code as well as other agents—it’s hard for teams of people by themselves to keep up with all the types of attacks that might take place. “The risk surface grows and the blast radius also grows,” says Nikhil Kandpal, a research scientist at OpenAI who co-created GPT-Red.
A reality check on the AI jobs hysteria
We’ve been hearing warnings for quite some time of the imminent jobs apocalypse (or jobpocalypse) that would destroy most white-collar work in the US and around the world. But so far, there hasn’t been a lot of evidence for that on a large scale (mainly within certain job categories and career stages).
Despite the warning by some of an imminent jobs apocalypse that will destroy much of if not most such work, or the rumblings about a “permanent underclass,” there’s scant evidence that AI has yet had any large-scale impact on the US labor market.
When Developing an AI Strategy, Beware the Urgency Trap
AI promises quick solutions to urgent problems. But that is often not the best place to develop AI for a company or team.
Because of a focus on urgent and immediate challenges, many AI efforts start fast and generate excitement, but ultimately fail to transform organizations in meaningful or lasting ways. Once leaders understand this trap, there are three actions they can take to avoid employing AI as a quick fix and instead use it as a tool for long-term value creation.
Don’t Outsource the Learning: Why Human-Led Research Still Matters in the Age of AI
Even if AI can do a passable job at certain tasks (a big if in most cases), it isn’t a replacement for the actual learning.
A team that outsources research to AI gets a report, but it doesn't get the learning. So even in a world where AI’s outputs are indistinguishable from an expert’s, something essential still goes missing.
Product Craft When AI Changes the Stakes
When it becomes possible to generate designs and even production-ready code in days, any lack of clarity shows up quickly. Teams either realize they are solving a real problem, or discover they have built something impressive that does not meaningfully help customers.
Other Interesting Finds
Archaeologists found Homer’s Iliad inside a 1,600-year-old Egyptian mummy
I just finished reading Circe (which is excellent btw) and am heading to see The Odyssey this week. So Greek stories and mythology are top of mind for me. Which is what makes it fascinating to see that scraps of the Iliad were found in Egypt. It makes me wonder if it was used intentionally, or if it was just like an old newspaper used for packing.
Archaeologists working at the ancient Egyptian site of Oxyrhynchus have made a remarkable discovery: a papyrus containing a passage from Homer's Iliad was found inside a Roman-era mummy dating back about 1,600 years. Researchers say it is the first known case in archaeological history in which a Greek literary text was intentionally incorporated into the mummification process.