Presenter Information

Theresa FisterFollow

Major

Communication

Anticipated Graduation Year

2023

Access Type

Open Access

Abstract

With increasing developments in technology, many sectors of society implement artificial intelligence into their structures with the goal of eliminating discriminatory practices and enhancing productivity. Artificial intelligence, while sometimes considered neutral by its proponents, can perpetuate the implicit and explicit biases of the engineers and designers responsible through the process of machine learning. Despite the risks, companies and organizations increasingly utilize artificial intelligence in their hiring processes, from recruiting to interviewing. As this technology shapes hiring decisions, further career-specific algorithmic bias research work rooted in human experience proves essential. Focusing on the applicants’ perspectives can identify whether this software provides a more equitable and inclusive interview environment than current in-person interviewing methods.

Faculty Mentors & Instructors

Dr. George K. Thiruvathukal

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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The Importance of Human Perceptions of Algorithmic Bias in Video Interviewing Software

With increasing developments in technology, many sectors of society implement artificial intelligence into their structures with the goal of eliminating discriminatory practices and enhancing productivity. Artificial intelligence, while sometimes considered neutral by its proponents, can perpetuate the implicit and explicit biases of the engineers and designers responsible through the process of machine learning. Despite the risks, companies and organizations increasingly utilize artificial intelligence in their hiring processes, from recruiting to interviewing. As this technology shapes hiring decisions, further career-specific algorithmic bias research work rooted in human experience proves essential. Focusing on the applicants’ perspectives can identify whether this software provides a more equitable and inclusive interview environment than current in-person interviewing methods.