Data Shed: Interactive Art in the Service of Data Fluency

As data continues to permeate all aspects of our lives, the need for data fluency becomes paramount. The “Data Shed” project explores the intersection of interactive art, machine learning, and data visualization to facilitate experiential learning about data and its pervasive influence in our digital age. Grounded in the metaphor of shedding, akin to a snake’s skin, the installation portrays the implicit generation and shedding of latent data in our digital interactions. The paper delves into related work, emphasizing the accelerating role of algorithms, motivated by the challenges posed by data misuse and potential for bias. It draws on the concepts of data fluency and critical data studies, exploring the paradox of privacy in the face of increasing concerns about data handling by organizations. The study reviews generative artworks and human-AI collaboration before addressing the ability of machine learning to address surveillance and data-shedding concerns. The paper details research creation, the development methodology, and highlights gaps where the “Data Shed” approach can bring focus to these issues. Evaluative insights are provided, emphasizing technical goals, interactivity levels, and assessment of achievement of data fluency objectives. The research underscores the importance of interactive art works, user engagement, and ethical considerations, in fostering a deeper understanding of data in our digital landscape. The project invites users to reflect on the shaping influence of data in our lives and its potential impact on our collective future.