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Creators: Barrett, The Honors College

AI in Radiology: How the Adoption of an Accountability Framework can Impact Technology Integration in the Expert-Decision-Making Job Space

Description

Rapid advancements in Artificial Intelligence (AI), Machine Learning, and Deep Learning technologies are widening the playing field for automated decision assistants in healthcare. The field of radiology offers a unique platform for this technology due to its repetitive work structure, ability to leverage large data sets, and high position for clinical and social impact. Several technologies in cancer screening, such as Computer Aided Detection (CAD), have broken the barrier of research into reality through successful outcomes with patient data (Morton, Whaley, Brandt, & Amrami, 2006; Patel et al, 2018). Technologies, such as the IBM Medical Sieve, are growing excitement with the potential for increased impact through the addition of medical record information ("Medical Sieve Radiology Grand Challenge", 2018). As the capabilities of automation increase and become a part of expert-decision-making jobs, however, the careful consideration of its integration into human systems is often overlooked. This paper aims to identify how healthcare professionals and system engineers implementing and interacting with automated decision-making aids in Radiology should take bureaucratic, legal, professional, and political accountability concerns into consideration. This Accountability Framework is modeled after Romzek and Dubnick’s (1987) public administration framework and expanded on through an analysis of literature on accountability definitions and examples in military, healthcare, and research sectors. A cohesive understanding of this framework and the human concerns it raises helps drive the questions that, if fully addressed, create the potential for a successful integration and adoption of AI in radiology and ultimately the care environment.

ContributorsGilmore, Emily Anne (Author) / Chiou, Erin (Thesis director) / Wu, Teresa (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor, Contributor) / Barrett, The Honors College (Contributor)

Created2019-05

The Women’s Power and Influence Index: Early Reactions to an Equity Ranking Methodology

Description

The following paper builds upon version one of The Women’s Power and Influence Index (WPI). The WPI Index is a product created by The Difference Engine, a center at ASU, to address gender inequality in the workplace. The WPI Index ranks Fortune 500 companies on various criteria and releases the information to the public in an easy-to-understand manner. Following the first release in 2021, we aim to help the WPI Index continue to grow by researching social movements that can inspire the Index, suggesting additional criteria for version 1.5, and raising awareness through events and social media. Part I of the paper details how social movements have utilized social pressure and social media to create broad change, setting the stage for the WPI Index’s public rankings to incentivize change. Part II provides research on new criteria we propose to be added to the Index for the next release. Lastly, part III covers how we used TikTok, events, and partnerships to help the Index gain notoriety. Altogether the paper suggests new directions and provides scientific research to further the goals of the WPI Index.

ContributorsAmare, Esete (Author) / Zaffar, Ehsan (Thesis director) / Gel, Esma (Thesis director) / Devries, Alexis (Committee member) / Holly, Sydney (Committee member) / Lee, Shania (Committee member) / Barrett, The Honors College (Contributor) / School of Social Transformation (Contributor) / Department of English (Contributor)

Created2023-05