A recent AP-NORC poll found that 64 percent of Americans think artificial intelligence is developing too quickly. I understand the feeling. By the time I figure out what one version can do, somebody has introduced its replacement. Sometimes the version I am using changes without anyone asking me. But I also have a few things I would like it to hurry up with. Sorting out health insurance policies comes to mind. So does finding a suitable alternative place to live without making me read seventeen websites and telephone twelve people. Apparently, I want artificial intelligence to slow down and speed up. Before declaring myself confused, however, I think we need to ask what, exactly, we want to slow down. Better Help Would Be Welcome In…

The useful part begins when AI can take action. So does the risk. Last week I gave an AI agent a real job. I asked it to research housing alternatives for us. It looked at apartments, condos, independent living and other possibilities. It eliminated some choices, narrowed others and produced a report that was useful even though it did not make the decision for us. But I gave it one very important limitation: don’t do anything. Don’t call anyone. Don’t make appointments. Don’t submit applications. Don’t send personal information. Don’t make commitments. Research. Compare. Report back. That worked pretty well. Which raises the next question: what happens when we remove those restrictions? That is where agents become much more interesting — and potentially much more…

Last week I wrote about AI agents and asked a fairly basic question: Why would someone like me want one? I understand why businesses are interested. An agent that can process invoices, answer customer questions, write software or manage inventory might save a company considerable time and money. But I don’t run or try to run a company anymore. I wanted to know whether an AI agent could do something useful for me. So instead of asking another question about agents, I decided to give one a real job. It turns out I had a pretty good one waiting. Where Should We Live? My wife and I live in a house in northwest Reno. At some point, whether soon or several years from now, we…

“Is there a teenager around?” I’ve heard that more times than I can count. Sometimes it’s a television that suddenly refuses to cooperate. Sometimes it’s a smartphone, a streaming service, or a computer that seems to have developed a mind of its own. The assumption is that anyone under twenty-five can solve the problem in a matter of seconds. Sometimes they can and sometimes they can’t. But the times they can leave a lasting impression. But I’ve also noticed something else. Many of my friends have simply stopped experimenting. No social media. No phone-based payment options. No Roomba. And certainly, no AI tools. I think that’s unfortunate, because the people who stop trying are often the very people who could benefit the most. The goal…

Most people imagine artificial intelligence as something floating invisibly across the internet — distributed everywhere, available anytime, almost magical in its reach. But the reality is far more physical. AI increasingly depends on a relatively small number of extraordinarily large and extraordinarily expensive computing centers. Vast buildings filled with specialized processors, cooling systems, backup power systems, networking equipment, and enough electricity consumption to rival small cities. Behind every chatbot, image generator, recommendation engine, autonomous system, or AI “agent” quietly coordinating schedules, purchases, logistics, or data analysis is infrastructure that is surprisingly concentrated. That concentration may become one of the defining technology risks of the next decade. Not because the systems are evil. Not because machines suddenly become self-aware. But because modern society rarely handles concentration…

We’ve become accustomed to systems that simply work. Electricity, communications, cloud services—most of the time they are there when we need them. When they fail, even briefly, the disruption is noticeable, but usually manageable. Backup systems exist. Workarounds exist. People know what to do. Artificial intelligence is starting to become part of that same layer of assumed availability. Not in an obvious way, and not all at once. But gradually, across writing, research, customer support, coding, and planning, it is being woven into the way work gets done. In many cases, it is not replacing entire roles. It is shaping how tasks are performed and how decisions are made. That distinction matters. Because we are not just depending on infrastructure anymore. We are beginning to…