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Exploring AI Empathy: Teaching AI with Brain Signals
Podcast episode with Thorsten Zander, professor at Brandenburg University of Technology and co-founder of Zander Labs. He coined the concept of *passive brain-computer interfaces*: devices that read brain signals to decode a user's mental state, non-invasively and without any effort on their part. Covers: * What non-invasive brain-computer interfaces (BCIs) can actually pick up from brain signals, and why that's very different from reading your thoughts or internal monologue * The hardware and software breakthroughs that are finally making passive BCIs wearable and affordable * How continuous neural feedback could dramatically improve AI training compared to current methods based on human ratings * Why Thorsten believes passive BCIs may offer the most concrete path to solving the AI alignment problem * The risk of social networks exploiting unconscious brain reactions to manipulate people, and why regulation alone is unlikely to be enough
Neurable's Non-Invasive Mind-Reading Tech for Wearables
The startup specializes in "non-invasive" "mind-reading" tech—a kind of neural data collection that, its CEO hopes, will have all sorts of consumer applications.
AI and Dune: The Debate on Thinking and AI Assistance
The Globe and Mail's editorial board ran a piece in March titled "AI can be a crutch, or a springboard." To illustrate the crutch half, they offered this: someone asked AI to explain a passage from Dune that warns against delegating thinking to machines. Instead of reading the book. That anecdote is doing more work than the studies the editorial cites. But the studies are real. Researchers at MIT published a paper in June 2025 titled "Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task" (Kosmyna et al., arXiv 2506.08872). The study tracked brain activity across three groups: people writing with ChatGPT, people using search engines, and people working unaided. The LLM group showed the weakest neural connectivity. Over four months, "LLM users consistently underperformed at neural, linguistic, and behavioral levels." The most striking finding: LLM users struggled to accurately quote their own work. They couldn't recall what they had just written. The Globe cites this and similar research to make a point about dependency. The implicit argument: hand enough of your thinking to a machine and you stop doing it yourself. That finding is probably accurate for the way most people use these tools. The question is whether that's the only way they can be used. The Globe's own title contains the counter-argument. Crutch or springboard. They wrote both words. They just didn't develop the second one. Ethan Mollick, a professor at Wharton who has been writing about AI use since the tools became widely available, argued in 2023 that the real challenge AI poses to education isn't that students will stop thinking, it's that the old structures assumed thinking was hard enough to enforce. ("The Homework Apocalypse," [oneusefulthing.org](http://oneusefulthing.org), July 2023.) When AI can do the surface-level cognitive work, the only tasks left worth assigning are the ones that require actual judgment. The tool, in that framing, doesn't reduce the demand for thinking. It raises the floor under it. Nate B. Jones, who writes and consults on what it actually takes to work well with AI, has made a sharper version of this argument. His position: using AI effectively requires more cognitive skill, not less. Specifically, it requires the ability to translate ambiguous intent into a precise, edge-case-aware specification that an AI can execute correctly. It requires detecting errors in output that is fluent and confident-sounding but wrong. It requires recognizing when an AI has drifted from your intent, or is confirming a premise it should be challenging. These are not passive skills. They are harder versions of the same thinking the MIT study found LLM users weren't doing. The difference between the group that lost neural connectivity and the group that doesn't isn't the tool. It's what they decided to do with it. Here's my own evidence. In the past year I built a working web application. Python backend. JavaScript frontend. Deployed on two hosting platforms. Payment processing. User authentication. A full data model. I do not know how to code. Every product decision was mine. Every architectural call. Every tradeoff judgment. I defined what the system needed to do, why, and what done looked like. I reviewed every significant change before it was accepted. When something broke, I identified where the breakdown was and directed the fix. The implementation was handled by AI. The thinking was mine. This mode (call it AI-directed building) is the opposite of the Dune reader. The quality of what gets produced is entirely a function of how clearly you can think, how precisely you can specify, and how critically you can evaluate what comes back. There is no shortcut in that. A vague brief to an AI doesn't produce a confused output. It produces a confident, fluent, wrong one. The discipline that prevents that is yours to supply. Non-coders building functional software with AI is common enough now that it isn't a story. What's less visible is the specificity of judgment underneath the ones that actually work. The practices that force more thinking rather than less are not complicated, but they require a decision to use the tool differently. When I've formed a position on something, I give the AI full context and ask it to make the strongest possible case against me. Ask for the hardest opposing argument it can construct. Then I read it. Sometimes it changes nothing. Sometimes it surfaces something I had dismissed without fully examining. The AI doesn't form my view. It stress-tests one I've already formed. When I'm uncertain between options, I don't ask which is better. I ask: here are two approaches, here is my constraint, now what does each cost me, and what does each require me to give up? I make the call. The AI laid out the shape of the decision. The judgment was mine. The uncomfortable part of thinking is still yours in this mode. The tool makes the work more rigorous, not easier. The MIT researchers and the Globe editorial are almost certainly right about the majority of current use. Passive use produces passive outcomes. That's not a controversial claim. The crutch half and the springboard half use the same interface. The difference is whether the person in front of it decided to think. What are you doing with it that forces more thinking rather than less? Are you using it to skip a step, or to take a harder one? Genuinely asking.
Exploring "As Above, So Below": AI Art Breakdown
**Here’s a detailed breakdown of every major element in the image I created for “As Above, So Below”:** **Central Figure** • **The Human**: A powerful, androgynous, muscular figure stands at the exact center, acting as the bridge between realms. This represents **humanity as the microcosm** — we contain and connect the vast universe (“above”) with the tangible world (“below”). • **Pose**: • **Right arm raised high** → pointing to the cosmos (“As Above”). The hand reaches toward stars and light, symbolizing aspiration, spirit, and the macrocosm. • **Left arm pointing downward** → toward Earth (“So Below”), grounding the divine into the physical world. • This mirrors the classic **Magician tarot gesture** but in a modern, cosmic style. **Upper Half – “As Above” (Macrocosm)** • **Swirling Galaxy / Nebula**: A massive, colorful spiral galaxy dominates the top, filled with purples, blues, golds, and stars. It represents the vast universe, celestial bodies, and cosmic forces. • **Bright Central Star / Light Source**: Intense golden light beams radiate from the center, symbolizing **divine source energy**, enlightenment, or the Big Bang / origin of everything. • **Stars and Cosmic Dust**: Scattered twinkling stars emphasize infinity and the interconnected web of the universe. **Connecting Symbol** • **Glowing Infinity Symbol (Lemniscate)**: Floating above the figure’s head, shining with golden light. This is the classic Hermetic sign of **eternal connection** and the never-ending loop between above and below — everything flows in an infinite cycle. **Lower Half – “So Below” (Microcosm)** • **Planet Earth**: Visible at the bottom with detailed continents (you can see North America), oceans, mountains, and clouds. It grounds the cosmic scene in our physical reality. • **Scientific & Natural Elements** (arranged around the figure): • **Human Brain** (left side): Neural networks mirroring galactic structures — showing how our minds reflect the cosmos. • **Flower (Purple Bloom)**: Represents nature’s perfect patterns (golden ratio in petals). • **Seashell (Nautilus)**: Classic example of the **golden spiral** in nature. • **Atom Model**: Electron orbits echoing planetary and galactic movements. • **Golden Ratio / Fibonacci Diagrams**: Mathematical squares, spirals, and equations scattered throughout — proving the same mathematical laws govern stars, atoms, flowers, and shells. • These show **self-similarity** (fractal-like repetition) across scales. **Overall Composition & Lighting** • **Horizontal Light Band**: A bright glowing horizon line separates “above” and “below,” with light rays shooting vertically through the figure — visualizing the direct correspondence and flow of energy between realms. • **Color Palette**: Deep cosmic purples/blues (mysterious universe) contrast with warm golds and earth tones (life and matter). • **Symmetry & Reflection**: The image is deliberately balanced top-to-bottom. Patterns in the galaxy echo the patterns on Earth and in the scientific symbols — the core message of the principle. • **Atmosphere**: Awe-inspiring, majestic, and unifying — blending ancient mysticism with modern science. **The Big Idea This Image Captures** The figure is literally **holding the connection** between the infinite cosmos and our everyday world. It says: **The laws that govern galaxies also govern atoms, flowers, brains, and human lives.** Study one, and you gain insight into all. This is my original take: a fusion of Hermetic philosophy, sacred geometry, fractal science, and cosmic wonder — exactly what “As above, so below” means to me.
Build Neurall: Revolutionizing AI Toolkit on GitHub
Build Neural Your Gateway to AI Development Introduction Building neural networks has become more accessible than ever with Build Neural . This powerful platfor…
AI Tool Build Neurall: Revolutionizing Neural Network Development
Build Neurall: Revolutionizing Neural Network Development In the rapidly evolving world of artificial intelligence, building and deploying neural networks effic…
Build Neurall: Revolutionizing AI Toolkit on GitHub
Build Neural Your Gateway to AI Development Introduction Building neural networks has become more accessible than ever with Build Neural . This powerful platfor…