Within the Creator Highlight sequence, TDS Editors chat with members of our neighborhood about their profession path in knowledge science and AI, their writing, and their sources of inspiration. Right this moment, we’re thrilled to share our dialog with Stephanie Kirmer.
Stephanie is a Employees Machine Studying Engineer, with nearly 10 years of expertise in knowledge science and ML. Beforehand, she was a better schooling administrator and taught sociology and well being sciences to undergraduate college students. She writes a month-to-month submit on TDS about social themes and AI/ML, and offers talks across the nation on ML-related topics. She’ll be talking on methods for customizing LLM analysis at ODSC East in Boston in April 2026.
You studied sociology and the social and cultural foundations of schooling. How has your background formed your perspective on the social impacts of AI?
I feel my educational background has formed my perspective on all the pieces, together with AI. I discovered to suppose sociologically via my educational profession, and meaning I take a look at occasions and phenomena and ask myself issues like “what are the social inequalities at play right here?”, “how do completely different sorts of individuals expertise this factor in another way?”, and “how do establishments and teams of individuals affect how this factor is going on?”. These are the sorts of issues a sociologist needs to know, and we use the solutions to develop an understanding of what’s occurring round us. I’m constructing a speculation about what’s occurring and why, after which earnestly in search of proof to show or disprove my speculation, and that’s the sociological methodology, primarily.
You might have been working as an ML Engineer at DataGrail for greater than two years. How has your day-to-day work modified with the rise of LLMs?
I’m truly within the strategy of writing a brand new piece about this. I feel the progress of code assistants utilizing LLMs is admittedly fascinating and is altering how lots of people work in ML and in software program engineering. I take advantage of these instruments to bounce concepts off, to get critiques of my approaches to issues or to get different concepts to my strategy, and for scut work (writing unit checks or boilerplate code, for instance). I feel there’s nonetheless loads for folks in ML to do, although, particularly making use of our expertise acquired from expertise to uncommon or distinctive issues. And all this isn’t to reduce the downsides and risks to LLMs in our society, of which there are various.
You’ve requested if we will “save the AI financial system.” Do you consider AI hype has created a bubble just like the dot-com period, or is the underlying utility of the tech sturdy sufficient to maintain it?
I feel it’s a bubble, however that the underlying tech is admittedly to not blame. Individuals have created the bubble, and as I described in that article, an unimaginable amount of cash has been invested underneath the idea that LLM expertise goes to provide some type of outcomes that can command income which might be commensurate. I feel that is foolish, not as a result of LLM expertise isn’t helpful in some key methods, however as a result of it isn’t $200 billion+ helpful. If Silicon Valley and the VC world have been prepared to simply accept good returns on a average funding, as an alternative of demanding immense returns on a huge funding, I feel this could possibly be a sustainable house. However that’s not the way it has turned out, and I simply don’t see a manner out of this that doesn’t contain a bubble bursting ultimately.
A 12 months in the past, you wrote concerning the “Cultural Backlash In opposition to Generative AI.” What can AI corporations do to rebuild belief with a skeptical public?
That is powerful, as a result of I feel the hype has set the tone for the blowback. AI corporations are making outlandish guarantees as a result of the subsequent quarter’s numbers all the time want to indicate one thing spectacular to maintain the wheel turning. Individuals who take a look at that and sense they’re being lied to naturally have a bitter style about the entire endeavor. It received’t occur, but when AI corporations backed off the unrealistic guarantees and as an alternative targeted onerous on discovering affordable, efficient methods to use their expertise to folks’s precise issues, that might assist loads. It could additionally assist if we had a broad marketing campaign of public schooling about what LLMs and “AI” actually are, demystifying the expertise as a lot as we will. However, the extra folks study concerning the tech, the extra practical they are going to be about what it could and might’t do, so I anticipate the massive gamers within the house additionally is not going to be inclined to try this.
You’ve coated many various matters up to now few years. How do you resolve what to jot down about subsequent?
I are likely to spend the month in between articles serious about how LLMs and AI are displaying up in my life, the lives of individuals round me, and the information, and I discuss to folks about what they’re seeing and experiencing with it. Typically I’ve a particular angle that comes from sociology (energy, race, class, gender, establishments, and so forth) that I need to use as framing to check out the house, or typically a particular occasion or phenomenon provides me an concept to work with. I jot down notes all through the month and once I land on one thing that I really feel actually fascinated by, and need to analysis or take into consideration, I’ll choose that for the subsequent month and do a deep dive.
Are there any matters you haven’t written about but, and that you’re excited to sort out in 2026?
I truthfully don’t plan that far forward! Once I began writing just a few years in the past I wrote down a giant listing of concepts and matters and I’ve fully exhausted it, so today I’m at most one or two months forward of the web page. I’d like to get concepts from readers about social points or themes that collide with AI they’d like me to dig into additional.
To study extra about Stephanie’s work and keep up-to-date together with her newest articles, you may comply with her on TDS or LinkedIn.
