CAS 1733 A (CRN: 15536)
Arts & Sciences: Sci Tech Studies: AI & Bio Sys (A)
3 credit hours
About CAS 1733 A
Topics exploring themes in Science and Technology Studies from a natural science perspective. May repeat for credit with different content. Topics vary by offering; periodic offering at intervals that may exceed four years.
Notes
Open to degree and PACE students
Section Description
What does it mean to "think"? Can a machine model the cognitive abilities of the human mind? And how well can these predictive models help us decode the complex biological systems of life?
This introductory course explores the intersection of artificial intelligence and the natural world, beginning with a comparative study of artificial intelligence systems and human cognitive processes. We will experiment with different types of training data and simulations to see for ourselves how different models work and evaluate how these models are used in our everyday world. Collaborative research projects will explore how specific AI technologies are employed within the natural sciences; potential topics range in scope from how molecules interact (e.g. drug development) to how ecosystems change over time (e.g. biodiversity monitoring). Project work will describe the mechanics of the AI model, analyze and summarize type of model output, and present findings to the class, ultimately allowing us all to learn from each other on the wide-ranging applications of AI.
Section Expectation
Compare major types of AI with human cognition (perception, learning, memory, decision-making)
Analyze AI training data and biological data, and critically evaluate the conclusions they support
Identify how AI models are currently used to predict changes in natural systems
Work as a team to evaluate an AI tool in the natural sciences and effectively communicate its outputs
Evaluation
Readings from A Brief History of Intelligence: Evolution, AI, and the Five Breakthroughs That Made Our Brains
In class simulations and discussions
Evaluation of case studies
Independent research, data analysis and scientific communication
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Resources
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