Emotional Trauma, Machine Learning and the Internet

Politics & Society
re:publica 2017

Short thesis: 

This is a talk on machine learning, emotional data, and how design affects behavior, specifically around online harassment. Can design and data affect behavior, and mitigate online harassment? The talk will cover two topics- the possibility of creating emotional data corpuses in machine learning, and using machine learning along with users in social media platforms to create transparent, open systems that focus on emotions and conversations. 


How do we create, code and make emotional data inside of systems? And how do we create the necessary context t in larger systems that use data. Is it possible to use machine learning to solve very hard problems around conversation? For the past two years, I’ve been studying internet culture, online conversations, memes, and online harassment. I also worked as a user researcher at IBM Watson helping design and layout systems for chat bot software. As a designer and researcher interested in all of the nuances of human conversations and emotions, from humor to sadness, to memes and harassment, I wonder is it possible to code in emotions for machine learning systems? And what are the ethical implications of that? Can we design systems to mitigate harassment, to elevate humor? And can these systems promote human agency, and allow for participation from users to help decide and structure the system the talk in- can design and user participation help set what is harassment and what is not? 

With machine learning, often the creators of the system are deciding what norms of the system and the users are left out of the collaboration. How do we create systems that are transparent for users, that also facilitate user participation? With online communities, communication, and culture, users make, users, do, users are the community. 

Stage 1
Tuesday, May 9, 2017 - 16:15 to 17:15