Blogs (19) >>
Thu 16 Mar 2023 14:35 - 15:00 at 715 - AI/ML Literacy, Activities, and Fairness Chair(s): Jill Westerlund

Machine learning (ML) models are often included in high-risk algorithmic decision making software, making them a particularly important facet of ethics education for those creating them to make sure they are unbiased and fair to all users. Natural Language Processing (NLP) specifcally functions on text, a human produced artifact, making it even more prone to inheriting fawed biases. However, teaching about ethics in machine learning courses is lacking. To address this issue, we created three interventions in an NLP course to introduce students to biases in existing machine learning models. We employed a combination of hands-on programming activity, lecture, programming quiz, and a project that discuss machine learning fairness at diferent levels and for different populations including gender bias and disability bias. Each of the teaching interventions included a refection question on students’ learning about bias. After the completion of the course, we interviewed six students to further understand the impact of the interventions. The answers to the refection questions and the interviews were qualitatively analyzed. We found that integrating fairness topics throughout the NLP course with repeated discussions led to an overall positive shift in students’ attitudes and awareness towards ML fairness and biases.

Thu 16 Mar

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13:45 - 15:00
AI/ML Literacy, Activities, and FairnessPapers at 715
Chair(s): Jill Westerlund University of Alabama
13:45
25m
Paper
Developing Machine Learning Algorithm Literacy with Novel Plugged and Unplugged ApproachesK12In-PersonGlobal
Papers
Ruizhe Ma University of Massachusetts Lowell, Ismaila Temitayo Sanusi University of Eastern Finland, Vaishali Mahipal University of Massachusetts Lowell, Joseph Gonzales University of Massachusetts Lowell, Fred Martin University of Massachusetts Lowell
DOI
14:10
25m
Paper
Make-a-Thon for Middle School AI EducatorsK12In-Person
Papers
Daniella Dipaola MIT Media Lab, Katherine S. Moore MIT, Safinah Ali MIT, Beatriz Perret MIT, Xiaofei Zhou University of Rochester, Helen Zhang Boston College, Irene Lee Massachusetts Institute of Technology
DOI
14:35
25m
Paper
Towards Machine Learning Fairness Education in a Natural Language Processing CourseK12In-Person
Papers
Samantha Dobesh Western Washington University, Tyler Miller Western Washington University, Pax Newman Western Washington University, Yudong Liu Western Washington University, Yasmine Elglaly Western Washington University
DOI