Here are some of my most recent Medium posts - I write twice a month about the intersection of ML and society. Subscribe at Medium or on https://medium.com/feed/@s.kirmer to see the posts when they come out.

April 17, 2024

How Do We Know if AI Is Smoke and Mirrors?

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.

April 1, 2024

The Coming Copyright Reckoning for Generative AI

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.

March 14, 2024

Uncovering the EU AI Act

The EU has moved to regulate machine learning. What does this new law mean for data scientists? The EU AI Act just passed the European Parliament . You might think, “I’m not in the EU, whatever,” but trust me, this is actually more important to data scientists and individuals around the world than you might think. The EU AI Act is a major move to regulate and manage the use of certain machine learning models in the EU or that affect EU citizens, and it contains some strict rules and serious penalties for violation.

March 2, 2024

Seeing Our Reflection in LLMs

When LLMs give us outputs that reveal flaws in human society, can we choose to listen to what they tell us? Machine Learning, Nudged By now, I’m sure most of you have heard the news about Google’s new LLM*, Gemini, generating pictures of racially diverse people in Nazi uniforms . This little news blip reminded me of something that I’ve been meaning to discuss, which is when models have blind spots, so we apply expert rules to the predictions they generate to avoid returning something wildly outlandish to the user.

February 17, 2024

Art and AI

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.

January 29, 2024

Using Poetry and Docker to Package Your Model for AWS Lambda

An accessible tutorial for one way to put a model into production, with special focus on troubleshooting and hiccups you might encounter along the way As promised, this week I’m coming with a more technical topic and taking a little break from all the discussions of business. I recently had an opportunity to deploy a new model using AWS Lambda, and I learned a few things when combining my usual development tooling (Poetry) with the infrastructure of Lambda.

January 13, 2024

Closing the Gap Between Machine Learning and Business

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.

December 15, 2023

How Much Data Do We Need? Balancing Machine Learning with Security Considerations

For a data scientist, there’s no such thing as too much data. But when we take a broader look at the organizational context, we have to balance our goals with other considerations. Data Science vs Security/IT: A Battle for the Ages Acquiring and keeping data is the focus of a huge amount of our mental energy as data scientists. If you ask a data scientist “Can we solve this problem?” the first question most of us will ask is “Do you have data?

November 30, 2023

What Role Should AI Play in Healthcare?

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.

November 15, 2023

Detecting Generative AI Content

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?