Trump is a master at wielding attention. He’s been owning news cycles and squatting in Americans’ minds for much of the last decade. And for his second term he has an ally in Elon Musk, a man with a similar uncanny skill set. Trump and Musk seem to have figured out something about how attention works in our fragmented media age — and how to use it for political and cultural power — that Democrats simply haven’t. So what is it? What do they understand about attention that their opponents don’t? Chris Hayes is the host of MSNBC’s “All In,” and has written a forthcoming book, “The Sirens' Call: How Attention Became the World's Most Endangered Resource.” And he’s a brilliant thinker on how our modern attention economy works and what it’s doing to our politics. We discuss what Hayes sees as a revolution happening to our attention, which he compares to the Industrial Revolution in its scale and impact; why the old rules about attention in politics no longer apply; the key insight Trump had about attention that fueled his rise; why Musk didn’t really overpay for Twitter; and how Democrats can compete in this new attentional world.

If you talk to many of the people working on the cutting edge of artificial intelligence research, you’ll hear that we are on the cusp of a technology that will be far more transformative than simply computers and the internet, one that could bring about a new industrial revolution and usher in a utopia — or perhaps pose the greatest threat in our species’s history. Others, of course, will tell you those folks are nuts. One of my projects this year is to get a better handle on this debate. A.I., after all, isn’t some force only future human beings will face. It’s here now, deciding what advertisements are served to us online, how bail is set after we commit crimes and whether our jobs will exist in a couple of years. It is both shaped by and reshaping politics, economics and society. It’s worth understanding. Brian Christian’s recent book “The Alignment Problem” is the best book on the key technical and moral questions of A.I. that I’ve read. At its center is the term from which the book gets its name. “Alignment problem” originated in economics as a way to describe the fact that the systems and incentives we create often fail to align with our goals. And that’s a central worry with A.I., too: that we will create something to help us that will instead harm us, in part because we didn’t understand how it really worked or what we had actually asked it to do. So this conversation is about the various alignment problems associated with A.I. We discuss what machine learning is and how it works, how governments and corporations are using it right now, what it has taught us about human learning, the ethics of how humans should treat sentient robots, the all-important question of how A.I. developers plan to make profits, what kinds of regulatory structures are possible when we’re dealing with algorithms we don’t really understand, the way A.I. reflects and then supercharges the inequities that exist in our society, the saddest Super Mario Bros. game I’ve ever heard of, why the problem of automation isn’t so much job loss as dignity loss and much more.