“I just gave this talk at SXSW. It was my first public presentation since starting my new job at The New York Times…this time the topic was AI for journalism. What follows are my slides, script, and references from the talk. Hi, I’m Zach Seward, the editorial director of AI initiatives at The New York Times, where I’m building a newsroom team charged with prototyping potential uses of machine learning for the benefit of our journalists and our readers. Before that, I co-founded and spent more than a decade helping to run the business news startup Quartz, where we built a lot of experimental news products, some with AI. I started at The Times not even three months ago, so don’t expect too much detail today about what we’re working on—I don’t even know yet. What I thought would be helpful, instead, is to survey the current state of AI-powered journalism, from the very bad to really good, and try to draw some lessons from those examples. I’m only speaking for myself today, but this certainly reflects how I’m thinking about the role AI could play in The Times newsroom and beyond. We’re going to start today with the bad and the ugly, because I actually think there are important lessons to draw from those mistakes. But I’ll spend most of my time on really great, inspiring uses of artificial intelligence for journalism—both on uses of what you might call “traditional” machine-learning models, which are excellent at finding patterns in vast amounts of data, and also some excellent recent uses of transformer models, or generative AI, to better serve journalists and readers…”