Civil War Twin: Exploring Ethical Challenges in Designing an Educational Face Recognition Application

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Virginia Tech


Facial recognition systems pose numerous ethical challenges around privacy, racial and gender bias, and accuracy, yet little guidance is available for designers and developers. We explore solutions to these challenges in a four-phase design process to create Civil War Twin (CWT), an educational web-based application where users can discover their lookalikes from the American Civil War era (1861-65) while learning more about facial recognition and history. Through this design process, we synthesize industry guidelines, consult with scholars of history, gender, and race, evaluate CWT in feedback sessions with diverse prospective users, and conduct a usability study with crowd workers. We iteratively formulate design goals to incorporate transparency, inclusivity, speculative design, and empathy into our application. We found that users' perceived learning about the strengths and limitations of facial recognition and Civil War history improved after using CWT, and that our design successfully met users' ethical standards. We also discuss how our ethical design process can be applied to future facial recognition applications.



Human-AI Interaction, Facial Recognition, Digital History, Ethical Design