Session: The Algorithm Is the Instrument: Artificial Intelligence and Qualitative Research (Society for Social Work and Research 28th Annual Conference - Recentering & Democratizing Knowledge: The Next 30 Years of Social Work Science)
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124 The Algorithm Is the Instrument: Artificial Intelligence and Qualitative Research

Schedule:
Friday, January 12, 2024: 2:00 PM-3:30 PM
Archives, ML 4 (Marriott Marquis Washington DC)
Cluster:
Organizer:
Ceema Samimi, PhD, MSSW, MPA, University of Minnesota-Twin Cities
Speakers/Presenters:
Michael Massey, Ph.D, The Catholic University of America, Channel Lowery, MSW, University of Minnesota-Twin Cities and Erin Sugrue, PhD, Augsburg University
Artificial intelligence (AI) is ushering in new challenges and opportunities for academics at an ever-quickening pace. Researchers are beginning to explore the intervention of AI and academia by examining the ethics of using Chat GPT as a co-author in research manuscripts, calling for AI in the evaluation of journal quality, and the examination of AI's impact on disabled people (Lillywhite, A., & Wolbring; 2019, Lund & Wang, 2023; Steingard & Linacre, 2023). The qualitative software company Atlas.ti recently launched its own AI interface; one that will conduct qualitative analysis on data without humans.

The idea of a qualitative research process that does not involve human interpretation is antithetical to the concept of Ëœresearcher as instrument in qualitative interviewing, and the constructivist paradigm (Stewart, 2010). Patton (1999) states that qualitative analysis is "a creative process, depending on the insights and conceptual capabilities of the analyst" (p. 1190). The act of coding is not a precursor to analysis, it is an integral part of an iterative, analytical process. While coding, the research is not simply identifying codes, they are deepening their connection with the entire set of data, and the codes emerge in that context. One of the most important concepts in qualitative research is positionality. Prior to coding, a researcher's social location, interviewing style, questions asked, the identities held by participants, and researcher interplay with participant responses all impact the coding process, (Saldania, 2013). Additionally, AI has been found to be biased in many ways, including perpetuating systemic racism (Fountain, 2022; Kundi et al., 2022). Algorithmic bias reflects human bias. With no awareness of positionality or social location, it is impossible for AI to produce trustworthy research findings that are context-bound.

Objectives:

Discuss the ethics of using AI in social work research

Provide concrete examples of the differences between AI-generated and human-generated research findings

Examine the ways in which AI impacts the social constructivist research paradigm

The first presenter will pose questions regarding the nature of qualitative research and how human meaning-making is essential to the inductive research process. The second and third presenters will provide overviews of the coding processes used in two phenomenological qualitative research projects, and compare their human processes and conclusions with the process and results determined through using the AI coding feature in Atlas.ti software. The final presenter will discuss the ways in which AI has been shown to perpetuate systemic oppression, including racism, homophobia, and sexism.

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