ETHOS Push: An Approach toward Empathetic Orchestration of Scrutable Push - Fraser, Kieran (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2021)
There was a time, not so long ago, when our physical world would have seemed unfathomably large. But thanks, in part, to the meteoric rise of technology and its ability to connect far reaching parts of the universe, it has since diminished in size. The space and silence that was once infinite is now fast filling up with a noisy clamour borne of the virtual world, which is quickly expanding and, unless tempered, threatens to reduce the size of our physical world further, until it exists solely behind a softly glowing screen. Mobile devices are ubiquitous in the modern world and rarely leave our side. Subsequently, interruptions are more frequent and attention increasingly difficult to protect. Push-notifications are an extremely valuable tool for disseminating useful and timely information, but their current use lacks the intelligence to tactfully adapt to the transient physical and cognitive contextual needs of subscribers, to whom they are delivered. Those pushing notifications resort to increasingly persuasive strategies to entice engagement and, at times, do so without empathy for the human to whom they are pushing. Therefore, subscribers of this technology require tools for protection, awareness and empowerment to retain ownership of their attention and make informed engagement decisions. This thesis presents ETHOS-Push, an approach for creating, delivering and presenting notifications which are empathetic to subscribers and promote scrutability. The requirements of the ETHOS-Push approach were informed through a rigorous review of literature and observational studies of push-notification engagements in-the-wild. A sustainable, data-driven approach toward intelligent delivery was evaluated; well-defined principles of persuasion were used to engineer features for scrutability; and finally, overtly enticing text was moderated at the point of creation to reduce the exploitative influence of notifications employing information-gap strategies.
APPROVED
Keywords: Generative Modeling; Ethical AI; Human-computer Interaction; Push-notification; Mobile Computing