Stephanie Kirmer

AI

The Cultural Impact of AI Generated Content: Part 2

What can we do about the increasingly sophisticated AI generated content in our lives? Stephanie Kirmer · Follow Published in Towards Data Science · 9 min read · 9 hours ago — Photo by Meszárcsek Gergely on Unsplash In my prior column, I established how AI generated content is expanding online, and described scenarios to illustrate why it’s occurring. (Please read that before you go on here!) Let’s move on now to talking about what

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AI

The Cultural Impact of AI Generated Content: Part 1

What happens when AI generated media becomes ubiquitous in our lives? How does this relate to what we’ve experienced before, and how does it change us? Stephanie Kirmer · Follow Published in Towards Data Science · 7 min read · 9 hours ago — Photo by Annie Spratt on Unsplash This is the first part of a two part series I’m writing analyzing how people and communities are affected by the expansion of AI generated

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AI

Writing a Good Job Description for Data Science/Machine Learning

Things to do and things to avoid in order to find the right candidates for your open position Stephanie Kirmer · Follow Published in Towards Data Science · 13 min read · 11 hours ago — Photo of a very good candidate by Thomas Butler on Unsplash I’ve probably been involved in the hiring process for data scientists a dozen times or more over my career, while never being the hiring manager myself, and I

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AI

Economics of Generative AI

What’s the business model for generative AI, given what we know today about the technology and the market? Stephanie Kirmer · Follow Published in Towards Data Science · 6 min read · 10 hours ago — Photo by Ibrahim Rifath on Unsplash 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

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AI

The Meaning of Explainability for AI

Do we still care about how our machine learning does what it does? Stephanie Kirmer · Follow Published in Towards Data Science · 8 min read · 1 hour ago — Today I want to get a bit philosophical and talk about how explainability and risk intersect in machine learning. Photo by Kenny Eliason on Unsplash What do we mean by Explainability? In short, explainability in machine learning is the idea that you could explain

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AI

Environmental Implications of the AI Boom

The digital world can’t exist without the natural resources to run it. What are the costs of the tech we’re using to build and run AI? Stephanie Kirmer · Follow Published in Towards Data Science · 8 min read · 6 hours ago — Photo by ANGELA BENITO on Unsplash There’s a core concept in machine learning that I often tell laypeople about to help clarify the philosophy behind what I do. That concept is

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AI

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.) Stephanie Kirmer · Follow Published in Towards Data Science · 10 min read · 6 hours ago — Photo by Daniele Levis Pelusi on Unsplash 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

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AI

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 Stephanie Kirmer · Follow Published in Towards Data Science · 14 min read · 8 hours ago — Photo by Annelies Geneyn on Unsplash 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

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