A philosopher at Cambridge published a paper in 2025 arguing something that might seem obvious to most people but actually isn't. We have no way to know whether an artificial intelligence system has become conscious, and we probably won't develop one for a very long time, if ever ( Cambridge, 2025 ). This is not because consciousness is impossible in machines. It is because consciousness is so poorly understood in biological systems that building a test for it anywhere, organ

The traditional path to discovering a new battery material involves chemists coming up with a hypothesis, synthesizing a compound, and then testing it. The result informs the next hypothesis, and so on and so forth.  If they are efficient, they might test a few dozen compounds per year. The discovery of lithium-ion batteries had taken decades of this iterative work. In 2025, Microsoft and the Pacific Northwest National Laboratory approached the problem differently. They used

In 2023, Anthropic posted a Prompt Engineer job with a $375,000 salary and no requirement for a computer science degree. McKinsey had reported that 7% of organizations were hiring Prompt Engineers. The Wall Street Journal called it the job of the future. In 2025, the role has effectively disappeared ( Salesforceben, 2025 ).  Job postings for "Prompt Engineer" peaked at 144 searches per million on Indeed in April 2023. By mid-2025, that number had collapsed to 20-30 per millio

Image generated with Gemini The EU AI Act demands explainability for high-risk systems. ISO 42001 requires documented, repeatable controls over AI decision-making. NIST's AI Risk Management Framework expects you to explain how and why your systems make decisions. The requirement appears in every governance framework published in the last three years. But there is a huge gap between requiring explainability and what companies actually deploy. Companies are shipping AI systems

Image on Unsplash You've probably noticed something strange about your phone. You open it to check one message and thirty minutes vanish. You scroll past something mildly interesting and suddenly your feed feels custom built to keep you in that exact spot. This isn't accidental. It's engineered. Social media platforms use AI algorithms designed specifically to maximize how long you stay on them. These aren't passive recommendation systems that just show you what might be rele

Image on Unsplash The video generation process that used to require a crew of five or six people is now happening in thirty minutes on a smartphone. Not because people are getting particularly skilled in the art, but because AI tools guide us through every step now.  A solo creator can now produce at least a 100 professional-quality videos per month using AI video generation tools ( Clippie AI, 2025 ). Those numbers are not even an exaggeration. With the adoption of improving

Image generated with Gemini Think of a world where a person with visual impairment uses their phone to point at a sign they cannot read. The camera captures it and an AI system reads the text aloud in seconds. The person knows what the sign says without asking anyone. Sounds very helpful, right? Fortunately, AI has actually made this a reality. Accessibility has always been a problem of friction. Suppose a person with visual impairment wants to read a website. Without assista

Image generated with Gemini The New York Times sued Perplexity AI on 5th December for copyright infringement, alleging that the startup scraped millions of Times articles without permission and used them to power its AI products.  The lawsuit joined more than 40 other active copyright disputes between publishers and AI companies, but what makes this one significant is that it reveals the fundamental contradiction embedded in how AI models are built. Perplexity trained its sys

Image on Unsplash Law enforcement has adopted facial recognition technology under the assumption that machines could do what humans struggle with, which is identify suspects accurately and without the biases that come from human judgment. The pitch sounds compelling on its surface. A surveillance camera captures a face. The system checks a database of millions of faces and returns candidates ranked by mathematical similarity. An investigator narrows the list. An eyewitness lo

Image generated with Gemini We've built AI systems that can reason across entire books, code across millions of lines, and converse in ways that feel almost human. Except they can't remember you from one conversation to the next.  Every time you start a new chat, the model forgets everything about you, everything you've told it, everything you've established in previous conversations. This isn't a limitation we're working around anymore. It's the fundamental constraint that's

Image generated with Gemini A study analyzing over 8,885 long-form social media posts from 2018 to 2024 discovered a dramatic acceleration in AI-generated content. Only 5.34% of posts were AI-written before 2023, but after ChatGPT became widely accessible, the average jumped to 24.05% ( IACIS, 2025 ). It is not simply that AI is generating content but that this AI-generated content spreads measurably faster than human-written content, with research showing that AI-generated f

Image on Unsplash When policymakers and technology executives discuss the impact of artificial intelligence on employment, they have developed a particular narrative. It goes like this: yes, jobs will be displaced by automation, but new jobs will be created and workers can retrain for those positions. The net effect over time will be roughly neutral or even positive. However, the data slightly contradicts this narrative. Eighty-five million jobs will be displaced by artificia

Image generated with Gemini Researchers at the University of Pennsylvania conducted an experiment where they asked participants to rate their political candidate preferences on a scale of zero to a hundred. Then, they had them chat with an AI system that was specifically trained to argue for either Kamala Harris or Donald Trump during the 2024 election. After the conversation, the researchers asked participants to rate their candidate preference again. What they found was tha

Image generated with Gemini Research from multiple institutions shows that machine learning models can predict stock market crashes with surprising accuracy, achieving what researchers call out-of-sample predictive power that gives active investors significant advantages. The accuracy is certain because the systems are not just fitting historical patterns but actually identifying preconditions of market crashes in real time ( Science Direct, 2023 ). Organizations using AI for

Image generated with Gemini Professionals using AI tools completed 12.2% more tasks and did them 25.1% faster and produced results with 40% higher quality than those who did not use AI  ( DocuPilot, 2025 ). This is the kind of measurement that gets the attention of law firm partners who are constantly looking for ways to increase billable hours while reducing cost. However, this measurement obscures the fact that lawyers and paralegals have started to notice something troubli