{"title":"Box","authors":"Tomás Laurenzo, Katia Vega","doi":"10.1145/3414686.3427178","DOIUrl":null,"url":null,"abstract":"BOX is an interactive installation, consisting on an everyday object augmented by artificial intelligence. The piece reflects on the power asymmetries that technology instantiates, aiming at providing with a reflection on the aesthetics of our relationship with it. The artwork also aims to showcasing the advancements and limitations in computer vision and artificial intelligence, allowing the public to experience in person its power as well as its inherent biases. Recent advances in computer vision and artificial intelligence, have allowed the creation of systems able to infer (predict) information on a person from camera data, including facial recognition, facial expressions, ethnicity, among others. Nowadays, several companies provide image processing services that include these predictions, among several others. In spite of potential benefits that face recognition proposes, its widespread application entails several risks, from privacy breaches to systematic discrimination in areas such as hiring, policing, benefits assignment, marketing, and other purposes. BOX consists of a gumball machine that, using computer vision and machine learning, predicts its user's ethnicity, delivering free candy only to white users. The artwork showcases a possible use of computer vision making explicit the fact that every technological implantation crystallises a political worldview, allowing the general public to experience in person the power of these new technologies, while simultaneously providing a tool for participatory observation, as well as ethnographic and technographic research. Our project aims to raise awareness on discrimination, ethics, and accountability in AI among practitioners and the general public.","PeriodicalId":376476,"journal":{"name":"SIGGRAPH Asia 2020 Art Gallery","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIGGRAPH Asia 2020 Art Gallery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3414686.3427178","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
BOX is an interactive installation, consisting on an everyday object augmented by artificial intelligence. The piece reflects on the power asymmetries that technology instantiates, aiming at providing with a reflection on the aesthetics of our relationship with it. The artwork also aims to showcasing the advancements and limitations in computer vision and artificial intelligence, allowing the public to experience in person its power as well as its inherent biases. Recent advances in computer vision and artificial intelligence, have allowed the creation of systems able to infer (predict) information on a person from camera data, including facial recognition, facial expressions, ethnicity, among others. Nowadays, several companies provide image processing services that include these predictions, among several others. In spite of potential benefits that face recognition proposes, its widespread application entails several risks, from privacy breaches to systematic discrimination in areas such as hiring, policing, benefits assignment, marketing, and other purposes. BOX consists of a gumball machine that, using computer vision and machine learning, predicts its user's ethnicity, delivering free candy only to white users. The artwork showcases a possible use of computer vision making explicit the fact that every technological implantation crystallises a political worldview, allowing the general public to experience in person the power of these new technologies, while simultaneously providing a tool for participatory observation, as well as ethnographic and technographic research. Our project aims to raise awareness on discrimination, ethics, and accountability in AI among practitioners and the general public.