Hello ebc–
We are entering a brave new world. Have you seen that movie? If not, it’s a wonderful spectacle (and book). That being said, what are we going to do with the wild, wild, west that is artificial intelligence (AI), especially in science, technology, engineering, and math (STEM) fields.
In today’s episode, we discuss our perspectives and experiences with AI including our current understanding, how we use it within our research workflows, and important caveats to consider. More specifically, we firstly break down how AI models are derived from supervised and unsupervised machine learning, the importance of understanding how these models are built from datasets, and this concept of “crap data in, crap data out.” We then explore the utility of using AI, across individuals, ranging from programmers all the way to lay users, removing previous barriers of entry in asking questions and speeding up the discovery process that would otherwise require a technical background.
We also discuss how we use AI in our scientific workflows to help with writing code, writing, and making plots and figures. Finally, we discuss all the caveats of AI including problem-solving, critical thinking, ground truth, the energy and ecological impact, regulation and democratization of AI.
This all begs the question… When will we reach a symbiosis with AI, and what will that world look like? Stay tuned for Part 2!
Next episode topic: Wrapping up the 5th year in our Neuroscience PhDs
As always, stay educated and seek confusion!
-A&Y
Get connected with us:
Contact us for educated thoughts or general confusions at [email protected] & follow us on instagram @ebcpod :)