This panel examines the rhetorical ethics of algorithmic data collection in medical and educational contexts. We investigate the multifaceted ways that algorithms and databases function as persuasive and sometimes coercive agents as well as the extent to which ethical issues are disclosed to users. Our analysis focuses on two widely available technologies: Turnitin and the Starkey Halo Hearing Aid. Both of these complex, networked sites of study yield insights into nuanced elements of surveillance, ethical dimensions of data production and analytics, human/machine collaboration, tensions in interpretations of intellectual property doctrine, and the ways that these issues are (and importantly, are not) disclosed to users. We discuss the myriad ways that design persuasively demonstrates the political dimensions of these technologies. Ultimately, we ask what best practices might evolve for designing persuasive systems that bring users into intimate contact with algorithmic data collection, processing, transmission, and deployment.
Our discussions are concerned with the ways that algorithms function as persuasive arguments. Often, the procedures and processes through which algorithms operate are obscured from users even as those algorithms are active participants in shaping users’ pathways, access to knowledge, and daily engagement with the world around them. The politics of algorithms, then, are evident in their design and deployment. This is particularly true in algorithmic systems that collect data through surveillance of the user’s daily activities, whether those involve navigating social situations as a d/Deaf wearer of a smart hearing aid or submitting a required class essay. Our panel provides three extensive, grounded case studies whose data reveal the nuances and implications of algorithmically-driven surveillance.
