RT info:eu-repo/semantics/bookPart
T1 Visual Monitoring of Complex Algorithms
A1 Invernizzi, Michele
A1 Mauri, Michele
A1 Ciuccarelli, Paolo
K1 Data Visualization
K1 Algorithmic Accountability
K1 Visualizing complexity
AB Purchases, conversations, access to information, music and movies:more and more of our online life is mediated by complex algorithms that aredesigned to make the experience of the Web customized and more “personal”.These algorithms can process an amount of heterogeneous data that would takeenormous resources for the human mind to cope with, and find valuablepatterns in it. Their use is not limited to our online experience as similaralgorithms have been also implemented, for example, to inform policymakers:suggesting where to deploy police forces around the urban context, assessingcriminality risk scores of offenders, or allocating high school students to themost suited school.While the consequences of the decisions made by algorithms have a greatimpact on people’s lives, the way they are built and designed makes them defacto “black boxes”: a series of legal and technical barriers prevents fromaccessing and understanding how a certain input influences a given output.Overseeing their decision processes becomes then of the utmost importance.This paper argues that visualizations can become a powerful tool to monitoralgorithms and make their complexity accessible and usable by visually showingthe relation between the inputs and the outputs in a manner that mimics anobservational study approach. The paper analyzes a case study developed as anexperiment to test opportunities and criticalities in using visualization torepresent the presence and the activity of algorithms.This represents a shift from the main purpose of visualizations and DataVisualization in general: since its strong suit is to support human decision-making processes by transforming data into knowledge, the substitution ofpeople by machines in this activity seems to make visualizations obsolete. Acomputer doesn’t need to “see” the data to make a decision – or at least not inthe same way as people do – no matter how multidimensional and hetero-geneous the data is. With the diffusion of algorithms, the need to inspect theiraccountability and performance will simply move visualizations at a later stage.From a decision-making tool visualization becomes a monitoring and awarenesstool.
PB Vicerrectorado de Docencia. Universidad de La Laguna. Servicio de Publicaciones de la Universidad de La Laguna
SN 978-84-09-10171-9
YR 2020
FD 2020
LK http://riull.ull.es/xmlui/handle/915/18465
UL http://riull.ull.es/xmlui/handle/915/18465
LA en
DS Repositorio institucional de la Universidad de La Laguna
RD 22-nov-2024