In a wide-ranging Roundtables conversation for MIT Technology Review subscribers, journalist and author Karen Hao recently spoke about her new book, Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI. She talked with executive editor Niall Firth about how she first covered the company in 2020 while on staff at MIT Technology Review. They discussed how the AI industry now functions like an empire and went on to examine what ethically-made AI looks like. Read the transcript of the conversation, which has been lightly edited and condensed. And, if you're already a subscriber, you can watch the on-demand recording of the event here.

These are our subscriber-only events where you get to listen in to conversations between editors and reporters. Now, I'm delighted to say we've got an absolute cracker of an event today. I'm very happy to have our prodigal daughter, Karen Hao, a fabulous AI journalist, here with us to talk about her new book. Hello, Karen, how are you doing? Thank you so much for having me back, Niall.

More than 1,000 construction workers die on the job each year in the US, making it the most dangerous industry for fatal slips, trips, and falls. A new AI tool called Safety AI could help to change that. It analyzes the progress made on a construction site each day, and flags conditions that violate Occupational Safety and Health Administration rules, with what its creator Philip Lorenzo claims is 95% accuracy. Lorenzo says Safety AI is the first one of multiple emerging AI construction safety tools to use generative AI to flag safety violations. But as the 95% success rate suggests, Safety AI is not a flawless and all-knowing intelligence.

AI journalist Karen Hao's book, Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI, tells the story of OpenAI's rise to power and its far-reaching impact all over the world. Hear from Karen Hao, former MIT Technology Review senior editor, and executive editor Niall Firth for a conversation exploring the AI arms race, what it means for all of us, and where it's headed.

It was meant to be a temporary side job--a way to earn some extra money. Oskarina Fuentes Anaya signed up for Appen, an AI data-labeling platform, when she was still in college studying to land a well-paid position in the oil industry. But then the economy tanked in Venezuela. Inflation skyrocketed, and a stable job, once guaranteed, was no longer an option. Her side gig was now full time; the temporary now the foreseeable future.

Johannesburg, the sprawling megacity once home to Nelson Mandela and Desmond Tutu, is now birthing a uniquely South African surveillance model. In the last five years, the city has become host to a centralized, coordinated, entirely privatized mass surveillance operation. Vumacam, the company building the nationwide CCTV network, already has over 6,600 cameras and counting, more than 5,000 of which are concentrated in Johannesburg. The video footage it takes feeds into security rooms around the country, which then use all manner of AI tools like license plate recognition to track population movement and trace individuals. These tools have been enthusiastically adopted by the local security industry, grappling with the pressures of a high-crime environment.

Defining what is, or isn't artificial intelligence can be tricky (or tough). So much so, even the experts get it wrong sometimes. That's why MIT Technology Review's Senior AI Editor Karen Hao created a flowchart to explain it all. This episode was reported by Karen Hao. It was adapted for audio and produced by Jennifer Strong and Emma Cillekens.

From chess to Jeopardy to e-sports, AI is increasingly beating humans at their own games. But that was never the ultimate goal. We meet the big players in the space, and we take a trip to an arcade. To make this episode, we also spoke to Natasha Regan, Actuary at RPC Tyche, Chess WIM and co-author of "Game Changer". This episode was reported by Jennifer Strong and Will Douglas Heaven and produced by Anthony Green, Emma Cillekens and Karen Hao. Our mix engineer is Garret Lang. Trebeck: Today we're announcing a Jeopardy competition unlike anything we have ever presented before. Jennifer: Ten years ago, the television quiz show Jeopardy unveiled a new player... Well, his name is Watson. Documentary Announcer: [music] Watson is an IBM computer designed to play Jeopardy. Watson understands natural language with all its ambiguity and complexity." Jennifer: And perhaps not surprisingly... given that playing Jeopardy is the thing it was designed to do… Watson was good.

AI is a complex field and there is both hype and hysteria around the subject. To help you explain it clearly to your audience, two community coordinators from the JournalismAI initiative asked four AI experts and tech reporters from across the world for their best tips. Karen Hao, senior AI editor at the MIT Technology Review, started covering AI spending lots of time on YouTube and learning the basics like: what is an algorithm? What are neural networks and how are they trained? What are the key milestones in the history of AI?

Defining what is, or isn't artificial intelligence can be tricky (or tough). So much so, even the experts get it wrong sometimes. That's why MIT Technology Review's Senior AI Reporter Karen Hao created a flowchart to explain it all. This episode was reported by Karen Hao. It was adapted for audio and produced by Jennifer Strong and Emma Cillekens.