skip to main content
10.1145/3626253.3635405acmconferencesArticle/Chapter ViewAbstractPublication PagessigcseConference Proceedingsconference-collections
abstract

Accessing and Democratizing AI for Whom? Student Learning through an Algorithm-Centered Supply Chain Case Study

Published:15 March 2024Publication History

ABSTRACT

Questioning who has access to knowledge, skills, tools, and data becomes paramount as algorithms and the artificial intelligence (AI) systems they support find widespread applications. To address these concerns, "AI democratization" has become a prominent goal. In broad strokes, democratization allows more people to understand and work with AI, but a central question remains: for whom is AI being democratized? As the phrase can represent different meanings and stakeholders, grounding the concept of democratization for undergraduate students can be challenging. This ongoing work explores student engagement with the definitions of democratizing AI through a case study highlighting a fictional (but realistic) isolated community at risk of losing its last local grocery store and the potential for technology to address the supply chain fallout. Using role-play as the instructional activity for participants to engage in a collaborative peer-learning environment, students were immersed in a verisimilar discussion, envisioning the forms democratization can take. Seventy students participated in a course focused on technology's global and social impact, and their responses were analyzed before and after participating in the role-play activity. Overall, by being primed to the discussion on democratization through pre-assigned resources, students highlighted a nuanced understanding for whom democratization was relevant even before participating in the role-play. Results from statistical analysis showed significant improvement in recognizing the democratization of AI development, profits, and governance. Additionally, most students highlighted the role-play discussion as having strengthened the concepts they highlighted initially, but some described a broader view and recognition of other levels of democratization.

Index Terms

  1. Accessing and Democratizing AI for Whom? Student Learning through an Algorithm-Centered Supply Chain Case Study

                      Recommendations

                      Comments

                      Login options

                      Check if you have access through your login credentials or your institution to get full access on this article.

                      Sign in
                      • Published in

                        cover image ACM Conferences
                        SIGCSE 2024: Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 2
                        March 2024
                        2007 pages
                        ISBN:9798400704246
                        DOI:10.1145/3626253

                        Copyright © 2024 Owner/Author

                        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

                        Publisher

                        Association for Computing Machinery

                        New York, NY, United States

                        Publication History

                        • Published: 15 March 2024

                        Check for updates

                        Qualifiers

                        • abstract

                        Acceptance Rates

                        Overall Acceptance Rate1,595of4,542submissions,35%

                        Upcoming Conference

                        SIGCSE Virtual 2024
                      • Article Metrics

                        • Downloads (Last 12 months)0
                        • Downloads (Last 6 weeks)0

                        Other Metrics