Chris Franck, Changing Roles of Statistical Analysis, Computation, & AI in Behavior Science, SQAB скачать в хорошем качестве

Chris Franck, Changing Roles of Statistical Analysis, Computation, & AI in Behavior Science, SQAB

Chair: Federico Sanabria (Arizona State University) Computational approaches continue to grow in power and widespread use, providing incredible opportunities and posing new challenges for the field of behavior science. A century ago humans resorted to pen-and paper calculations to tabulate basic statistical summaries. Today, our students routinely use modern software to easily fit sophisticated data models that were mostly beyond the reach of the experts from several decades ago. Simulation-based approaches promise to augment empirical data collection, potentially rendering new insights. Going forward, the proliferation of generative artificial intelligence models has unclear implications for the future of scientific writing in our field. At each level of technological development, we expect a learning curve, growing pains, missteps, progress, and hopefully a breakthrough or two. The purpose of this tutorial is to review the increasing role statistical and computational approaches have played in our field with an eye towards the future. This tutorial precedes a panel discussion whose goal is to have a community-wide dialog on best practices surrounding some of the following questions. What role does computer-simulated data play in the analysis of behavioral data? What is the proper balance between visual analysis and statistical analysis in behavior science? What is the current interface between AI and research ethics and what threats to data integrity, scientific practice, etc. might loom on the horizon?