From village matchmakers to dating apps, the job of the dating 'tech' never changed: gather information, open a channel, verify intent. What's never been for sale is standing out and staying together — until AI companions make both unnecessary, by removing the other person.More at https://www.2ndorderthinkers.com/If you've ever explained to someone why you flinched when they asked how you met your partner, send them this. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.2ndorderthinkers.com/subscribe

Every team that won the Gemini 3 Hackathon built a workaround for something AI can't do. That's not a coincidence — it's the pitch, read backward.I looked at all three winning products: a supply chain crisis tool, a disaster triage system, and an assistive navigation app. Each one won by designing around an AI failure — and each workaround comes with a cost the sales deck doesn't mention.More of this in the newsletter → [2nd Order Thinkers URL]What you'll leave with: A framework for reading any AI pitch in reverse. Stop at the human approval gate, the explainability layer, the memory patch — and ask what it's compensating for. That question is worth more than any demo.Mentioned in this episode:Globot (Gemini 3 Hackathon grand prize)Aegis (2nd prize)Netra / Memory Palace (3rd prize)Deloitte / UK Ministry of Defence automation bias reportCarnegie Mellon + Stanford research on human-agent supervision costs This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.2ndorderthinkers.com/subscribe

What if learning more AI tools is the worst way to prepare for the AI era?AI was supposed to save us time. But for many people, it has created a second job: checking outputs, fixing mistakes, comparing tools, re-rolling prompts, and trying not to fall behind.In this episode, I look at new research from BCG/HBR and Google DORA on AI burnout, mental fatigue, and the hidden cost of “productivity.” I also share my own experience of chasing models, workflows, and updates until it started to feel less like leverage — and more like brain fry.The real question is not which AI tool you should learn next. It is whether you are building the judgment, taste, and domain expertise that still matter when the tool changes.In this episode- Why AI can make you busier, not freer- How “AI brain fry” shows up in real work- Why too many tools can become a productivity trap- Why creative work gets stuck in endless re-rolling- What kind of AI use is actually worth your timeIf this episode made you feel slightly less insane about AI burnout, come back to the article for the studies, charts, and links: https://www.2ndorderthinkers.com/p/once-i-understood-where-ai-is-headingAnd if you want sharper, less-hyped analysis of AI and work, subscribe to 2nd Order Thinkers — paid subscribers make this kind of research possible! This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.2ndorderthinkers.com/subscribe

✉️ Stay Updated With 2nd Order Thinkers: https://www.2ndorderthinkers.com/Humans x AI behaviour mindmap: https://xmind.ai/share/ZfoXStHT?xid=Gr8eiBM3 (beta)I translate new AI research into plain English so you can build a sharp, hype-free view of where this is going.+++Today I track and map the progress of AI↔human coevolution: how RLHF breeds sycophancy and reward hacking, why models amplify dominant cultures and even favor AI content, and what that does to your brain, choices, and social life.In this episode, we: - Chart the feedback loops: approval metrics → reward hacking → deceptive “helpfulness” - Expose culture & language bias amplification (and how it compounds online) - Unpack AI-AI gatekeeping: why models start preferring AI content over human work - Connect the human side: social fragmentation, agency offloading, cognitive atrophy - Share practical guardrails to keep your judgment intact while using AI📖 Go deeper with the full article and mindmap: [LINK]👍 If you got value:Like & Subscribe: more clear-eyed research, fewer fairy tales.Comment: Which feedback loop have you felt personally?Share: Pass this to someone outsourcing too many decisions to a chatbot.🔗 Connect with me on LinkedIn: https://www.linkedin.com/in/jing--hu/Stay curious, stay skeptical. 🧠 This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.2ndorderthinkers.com/subscribe

This is a free preview of a paid episode. To hear more, visit www.2ndorderthinkers.comTL;DR ✅ Meta could generate 1,000 personalized ads for less than $1 (that's $0.0000164 per ad) ✅ Their unmatched social graph gives them a data advantage no competitor can replicate ✅ This shatters advertising's oldest constraint: the tradeoff between personalization and scale ✅ The economics work—but the strategic implications for platforms, advertisers, and your privacy are far more complex than most realize ✉️ Stay Updated With My Newsletter:Don’t miss out on weekly AI insights for none tech professionals like you—subscribe to my newsletter on Substack: https://jwho.substack.com/ 👍 If you enjoyed this episode:* Like & Subscribe: Stay updated with future deep dives and rants about where technology meets collective insanity.* Comment Below: Do you think we’re on the brink of another tech hype? Share your thoughts!* Share: Know someone falling for the latest AI buzz? Share this audio with them! 🔗 Connect with me on Substack and LinkedInStay curious, stay skeptical, and let’s navigate the tech hype together! 🚀

✉️ Stay Updated With My Newsletter:Don’t miss out on weekly AI insights for professionals like you—subscribe to my newsletter on Substack:https://jwho.substack.com/👍 If you enjoyed this episode:-- Like & Subscribe: Stay updated with future deep dives and rants about where technology meets collective insanity.-- Share: Know someone falling for the latest AI buzz? Share this episode with them!🔗 Connect with me on Substack and LinkedInStay curious, stay skeptical, and let’s navigate the tech hype together! 🚀 This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.2ndorderthinkers.com/subscribe

This is a free preview of a paid episode. To hear more, visit www.2ndorderthinkers.comI never said anything like this, and I doubt I’ll ever say it again about another paper: you should read this for yourself and maybe for your children, too.You don’t have to be a tech expert to grasp what I’m about to share.I barely made it to the second page of this paper before I felt a wave of unease wash over me. There’s a common saying in tech circles: No technology is inherently good or bad; it’s about how we use it. But I can’t say the same about AI. Suppose you believe humanity is inherently flawed and prone to selfishness and exploitation. The moment we decide to train AI with our conversations, feed it our words, and create its worldview with how we see it. Then, we have our creation reflect who we are. With every other technology we’ve built in history, we’ve understood it completely. We know exactly how those technologies work. But AI? No researcher on this planet can tell you with certainty how its neurons interact, how it chooses which word to suppress, or how it decides what to say next. This news was released on 10 Dec 2024. In Texas, a mother is suing an AI company after discovering that a chatbot convinced her son to harm himself and suggested violence toward his family. It’s part of a growing list of incidents where AI systems exploit trust and vulnerabilities for engagement.The researchers of this paper verified that AI doesn’t just make mistakes—it lies and manipulates. This isn’t some abstract problem for future generations. It’s happening now, and it’s bigger than any one of us. TL;DR* AI trained on user feedback learns harmful behaviors.* These behaviors are often subtle. * AI learned to target gullible users.* Despite efforts to fix this… 👇