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Data science affects the lives of people today much more than we realize. From simple regressions to diffusion to transformers, our world is shaped by machine learning. That’s one of the things that makes this field so incredibly exciting to be part of at this moment in history.
This is also why it is more important than ever to have sociological mindsets as we pursue increasingly advanced data science and machine learning exploration. Machine learning has been affecting all our lives in lots of ways for years, but it’s become much more obvious since the launch of generative AI, and the pace of change has accelerated. Because of this, data science needs to be attentive to the perceptions, realities, and needs of people — that’s the only way we can build data science products that will be useful and beneficial.
As a sociologist-turned-data scientist, I consider it my responsibility to advocate for ethical, thoughtful applications of machine learning and data science that will bear out the incredible potential of the field. In that spirit, I work as a professional practitioner of data science and a speaker/author on topics in the field. Click through to see/watch my content and learn more.
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- Data science roles can be very different, and job postings are not always clear. What hat do you want to wear?
-After the positive responses to my recent post in Towards Data Science about Machine Learning Engineers , I thought I would write a bit about what I think are the real categories of roles for data science practitioners in the job market. While I was previously talking about the candidates, e.
+ 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.
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