In an age of ubiquitous data collecting, analysis and processing, how can citizens judge the trustworthiness and fairness of systems that heavily rely on algorithms? News feeds, search engine results and product recommendations increasingly use personalization algorithms to help us cut through the mountains of available information and find those bits that are most relevant, but how can we know if the information we get really is the best match for our interests?
There is no such thing as a neutral algorithm. As anyone who has ever created something knows, even something as simple as a meal, the act of creating inevitably involves choices that will affect the properties of the final product. Despite this truism recommendations and selections made by algorithms are commonly presented to consumers as if they are inherently free from (human) bias and ‘fair’ because the decisions are ‘based on data’. During the recent controversy about possible political bias in Facebook’s Trending Topics for instance the focus was almost exclusively on the role of the human editors even though 95% or more of the news selection process is done by algorithms. Human judgements however are ultimately also based on data.
Starting in September 2016 the EPSRC funded project “UnBias: Emancipating Users Against Algorithmic Biases for a Trusted Digital Economy” will look at the user experience of algorithm driven internet services and the process of algorithm design. A large part of this work will include user group studies to understand the concerns and perspectives of citizens. UnBias aims to provide policy recommendations, ethical guidelines and a ‘fairness toolkit’ co-produced with young people and other stakeholders that will include educational materials and resources to support youth understanding about online environments as well as raise awareness among online providers about the concerns and rights of young internet users. The project is relevant for young people as well as society as a whole to ensure trust and transparency are not missing from the internet. The project is led by the University of Nottingham in collaboration with the University of Oxford and University of Edinburgh. More information about project activities can be found here.