Taking a different tack with this episode, a wonderful chat with the remarkable Mark Stickells, AM, CEO of Pawsey Supercomputing Research Centre, on AI and the role of Humanities in STEM. "I fundamentally believe knowledge is a human insight. And we work with these tools that are incredibly powerful, but can be incredibly stupid." "We… Continue reading Mark Stickells on AI & the role of Humanities in STEM
Tag: data science education
Dr Kat Ross on Astrophysics, Bias in Science, and Including Diverse Scientists in Education
I might ask the same questions every time, but there's no knowing where the conversations will go! A fabulous episode with the incredible Dr Katherine Ross. Check it out! "So I think my favorite part about data is that it is completely unpredictable. And that may also be my least favorite part about it." "That’s… Continue reading Dr Kat Ross on Astrophysics, Bias in Science, and Including Diverse Scientists in Education
Dr Emily Kahl on pretty much everything!
Amazing conversation with Dr Emily Kahl from Pawsey Supercomputing Research Centre, on everything from the need for a humanities education in STEM, the application of Marxist and Feminist Lenses to Data Science, and a whole lot more. This was an absolute delight. Check it out! "I wanted to use the tools of maths and science… Continue reading Dr Emily Kahl on pretty much everything!
Darren Mansfield on Sleep, Data, and Sleep Tracking Devices
A super interesting episode with Professor Darren Mansfield on sleep, data, and sleep tracking devices. "imagine if you go and run a one hour documentary on something that's inconclusive. Here's all the evidence for you is the evidence against and we can't really don't know. That's not great television." " the truth is not always… Continue reading Darren Mansfield on Sleep, Data, and Sleep Tracking Devices
Scaling scams
It's important, when you're making graphs, to think about the story you want to tell with the data, and what type of graph, and what features of the graph, will help you tell that story. Likewise, when you're looking at someone else's graph, we all need to apply that critical data literacy and look at the scale on the y axis, as well as checking the labels, finding out the origin of the data, and considering whether the graph is accurate, a valid way to display that data, and what story it might be trying to tell you.