AI Blogs

Discover independent ai blogs and writers on BlogRolly.

People Are Dating AI Now: Let’s Talk About Why, The Good, The Bad, And Where It Gets Risky — Ever wondered why people date AI now? As a clinical psychotherapist I explain why loneliness, accessibility and fast res
My date with an octopus — A blind date with an octopus? I fed that prompt to ChatGPT and it answered with a theatrical apology to "Octavia" and ev
Whose job is safe from AI? — Think gardeners are safe from AI? I unpack why jobs change shape when machines take over tasks, from laser scarecrows an
When will the AI Bubble burst? — The generative AI industry looks a lot like a bubble. I run through Bank of England and IMF warnings, BBC, FT and RTÉ li
AI and Our Labor Addiction — Surprising truth: a New York Times take treated AI-generated art as a harmless tool for ad agencies. In this post I call
No, AI does not have human-level intelligence — Does AI already have human-level intelligence? In this post I argue the Nature claim is overstated. I show their definit
Racing through a minefield: the AI deployment problem — What should you do if you're on the cusp of building transformative AI? Here I outline the AI deployment problem as raci
AI Safety Seems Hard to Measure — What if passing a safety test still leaves us at risk? In this post I walk through four concrete reasons why measuring A
What does Bing Chat tell us about AI risk? — Is Bing Chat a warning sign about AI risk? I walk through Microsofts new Bing beta, the threats, the professed love, and
AI Art Is Art — What if a urinal and an algorithm both count as art? In this guest post I defend and celebrate AI-generated art like Jas
The Real Problem with AI Art — What happens when algorithms learn from an art world dominated by white men? I argue the real problem with AI art is bia
Debatable AI Persons: No Rights, Full Rights, Animal-Like Rights, Credence-Weighted Rights, or Patchy Rights? — Facing an AI that might be conscious, what should we do about AI personhood and rights? I advise avoiding creation of de
AI Mimics and AI Children — Surprising fact: the aliens we expect might already be here as AI. In "AI Mimics and AI Children" I argue why we balk at
Does Global Workspace Theory Solve the Question of AI Consciousness? — Can Global Workspace Theory settle the puzzle of AI consciousness? I argue no. In three sections from Chapter Eight of m
Artificial Intelligence as Strange Intelligence: Against Linear Models of Intelligence — What if intelligence is not a ladder? In a new draft paper with Eric Schwitzgebel I argue against linear models of intel
Does ChatGPT know about things Wikipedia doesn't? — Curious whether ChatGPT knows things Wikipedia does not? I had it draft a Wikipedia article on the obscure play Damaged
I tried coding with AI, I became lazy and stupid — What happens when AI writes your code? I tried coding with AI on the image processing part of my CMS, and it produced 20
AI and the Human Condition — Who owns the story when AI writes everything? In this post I tackle AI and the human condition, the 2025 Stratechery Yea
Adventures with Deep Research — I’ve been experimenting with new AI research tools and seeing how they actually perform on serious questions. This is a
AI vs human life — Lately I’ve been wondering what we lose when efficiency becomes the only metric. Some thoughts on artificial intelligenc
The impossibility of comprehending AI — I’ve been circling the idea that modern AI systems are too complex to fully understand. A short reflection on technology
Why You Want to Customize Google Analytics Channels (And How) — Shows why default channel groupings in Google Analytics hide important insights, then walks you through customizing them
Box Plots: The Unsung Heroes of Data Analysis — Makes the case that box plots are underrated, showing how they reveal distributions, outliers, and variability far bette
How to Pick an AI Model for Your Chatbot — Offers a decision framework for choosing models for chatbots, balancing cost, latency, safety, and task complexity for b
The 6 Biggest Mistakes that Tank AI Projects — Breaks down six common ways AI projects fail like unclear objectives or bad data and how to avoid wasting time and money
How I Used Natural Language Processing to Build a Search App — Walkthrough of building a search app with NLP, covering data prep, model selection, and evaluation so non‑researchers ca
50 Real-World AI Agent Use Cases That Actually Work — A hefty roundup of real AI‑agent use cases from marketing ops to support and research that are already delivering value,
Prompt Engineering or Fine-Tuning: Which Is Best for Your AI Project? — Weighs the trade‑offs between clever prompts and full fine‑tuning, helping teams choose the right approach based on budg
Bad Vibes in Your Codebase? How to Prevent AI Tools from Going Rogue — Warns about subtle risks of dropping AI tools into your dev stack, from mis‑generated code to security holes, and offers
How To Train Your Drag- LLM Not To Be a Sycophant — Looks at why LLMs tend to agree with users too much and shows how prompt design, feedback, and fine‑tuning can encourage
Making AI Explainable to Non-Technical Stakeholders — Shares strategies for turning opaque AI outputs into clear stories stakeholders understand, focusing on visualization, a
Boosting Prediction Model Performance Through Feature Engineering — Practical guide to using feature engineering to squeeze more accuracy from prediction models, with concrete examples tha
Tech Sketch: Automation vs LLMs vs Agents — Compares classic automation, large language models, and AI agents, clarifying when each makes sense, how they differ, an
Quantum Computing and AI: A Practical Look at the Future — Explains what actually happens when quantum computing meets AI, cutting through hype to show realistic use‑cases, curren
ChatGPT Life Coaching — A candid account of using ChatGPT like a life coach, where it helps structure thoughts and possibilities but can’t repla
AI: The Ultimate Canvas for Neurodivergent Creativity — A critique of over‑the‑top AI marketing and maximalist tools that try to “do the most,” contrasting them with calmer, na