The Economics of Generative AI What’s the business model for generative AI, given what we know today about the technology and the market? OpenAl has built one of the fastest-growing businesses in history. It may also be one of the costliest to run. The ChatGPT maker could lose as much as $5 billion this year, according to an analysis by The Information, based on previously undisclosed internal financial data and people involved in the business.

Musings on whether the “AI Revolution” is more like the printing press or crypto. (Spoiler: it’s neither.) I am not nearly the first person to sit down and really think about what the advent of AI means for our world, but it’s a question that I still find being asked and talked about. However, I think most of these conversations seem to miss key factors. Before I begin, let me give you three anecdotes that illustrate different aspects of this issue that have shaped my thinking lately.

Courts are preparing to decide whether generative AI violates copyright—let’s talk about what that really means Copyright law in America is a complicated thing. Those of us who are not lawyers understandably find it difficult to suss out what it really means, and what it does and doesn’t protect. Data scientists don’t spend a lot of time thinking about copyright, unless we’re choosing a license for our open source projects.

On deepfakes, authenticity, and the President’s Executive Order on AI One of the many interesting ethical issues that comes with the advances of generative AI is detection of the product of models . It’s a practical issue as well, for those of us who consume media. Is this thing I am reading or looking at the product of a person’s thoughtful work, or just words or images probabilistically generated to appeal to me?