Jeffrey Basoah: Lead Ph.D. Researcher
Erica Adams: Graduate Researcher
Alisha Bose: Undergraduate Researcher
Aditi Jain: Graduate Researcher
Kaustubh Yadav: Graduate Researcher
Goal
Our goal was to explore how Black users engage with digital technology, focusing on aspects that reflect their real-life experiences and highlighting areas where current digital tech design may fall short. The study delved into Black users' perspectives through interviews, imagined scenarios (design fiction), and firsthand observations, particularly in relation to AI-driven text technologies used in conversations.
Interviews
In-depth discussions were held through interviews to gauge the integration of AI-supported text technologies with the lived experiences of Black users. The aim was to grasp the participants' perspectives on the Black lived experience, its portrayal (or lack thereof) in their tech interactions, and how AI text tools either aligned with or overlooked their lived realities.
In a subsequent phase, participants engaged in a brief writing exercise using Google Docs to express themselves naturally, followed by reflections on the impact of grammar and spelling suggestions. This was followed by utilizing ChatGPT prompts to continue writing, allowing for examination of how well ChatGPT captured their communication style.
Speculative Design Fiction Workshop
Employing a workshop format, participants engaged in speculative design exercises aimed at reenvisioning the functionality of these technologies. The objective was to foster discussions on their existing deficiencies and explore pathways to enhance their effectiveness for Black users. Through creative brainstorming, participants sought to conceptualize innovative solutions that address the specific needs and experiences of Black users in digital spaces.
Thematic Coding
To understand how participants perceive and experience ASWT, I conducted a thematic analysis of the interview data gathered by our team. We began by cleaning the Zoom audio transcriptions using Otter.AI. Then, we performed inductive coding on two interviews, ensuring a blind coding process for each. This generated an initial list of codes. Next, we collected all the generated codes and merged similar ones. We utilized an affinity map to create broader coding groups.
Impact
We hope that this research will be used to make AI tools more inclusive in the future, and we address the problem of placing excessive trust in AI.
This work has been accepted to CSCW 2024
Explores the intricacies of text-based digital interactions facilitated by AI-supported writing technologies (AISWT) that have become inherent in our daily lives. This investigation primarily focuses on unraveling the cultural assumptions ingrained in the design of AISWT. Its overarching goal is to gain valuable insights into how Black users perceive the alignment of their lived experiences with AISWT, shedding light on potential shortcomings in the current design of digital technology that warrant careful consideration.