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.

Thinking about the intersection of people and technology in the creative process in the AI era Understanding art is challenging for lots of people, and it can often seem inaccessible. However, I have long been a lover of art (to the point where I almost majored in Art History in college) and eagerly seek out art to better understand human conditions past and present. As a result, bringing people to art and art to people is important to me.

What would you say it is you do here? Now that many of us are returning to the office and getting back into the swing after a winter break, I have been thinking a bit about the relationship between machine learning functions and the rest of the business. I have been getting settled in my new role at DataGrail since November, and it has reminded me how much it matters for machine learning roles to know what the business is actually doing and what they need.

On the use of machine learning in healthcare and the United Healthcare AI scandal Some of you may know that I am a sociologist by training — to be exact, I studied medical sociology in graduate school. This means I focused on how people and groups interact with illness, medicine, healthcare institutions, and concepts and ideas around health.* I taught undergraduates going into healthcare fields about these issues while I was an adjunct professor, and I think it’s really important for people who become our healthcare providers to have insight into the ways our social, economic, and racial statuses interact with our health.

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?

Much of the division between technology and human activity is artificial — how do people make our work possible? We don’t talk enough about how much manual, human work we rely upon to make the exciting advances in ML possible. The truth is, the division between technology and human activity is artificial. All the inputs that make models are the result of human effort, and all the outputs in one way or another exist to have an impact on people.