{"title":"Genealogies of online content identification - an introduction","authors":"Maria Eriksson, Guillaume Heuguet","doi":"10.1080/24701475.2021.1878649","DOIUrl":null,"url":null,"abstract":"In today’s digital landscape, cultural content such as texts, films, images, and recorded sounds are increasingly subjected to automatic (or semi-automatic) processes of identification and classification. On a daily basis, spam filters scan swaths of emails in order to separate legit and illegitimate textual messages (Brunton, 2013), algorithms analyze years of user-uploaded film on YouTube in search for copyright violations (Heuguet, 2019), and software systems are deployed to scrutinize millions of images on social media sites in order to detect sexually offensive content (Liao, 2018). These examples reveal how machines and algorithmic systems are increasingly utilized to make complex judgments regarding cultural content. Indeed, it could be argued that the wideranging adoption of content identification systems is constructing new ontologies of culture and regimes of truth in the online domain. When put to action, content identification systems are trusted with the ability to separate good/bad and legal/illegal forms of communication and used to secure the singularity, value, authenticity, origin, and ownership of content. Such efforts are deeply embedded in constructions of knowledge, new forms of political governance, and not least global market transactions. Content identification tools now make up an essential part of the online data economy by protecting the interests of rights holders and forwarding the mathematization, objectification, and commodification of cultural productions. Parallel to their increased pervasiveness and influence, however, content identification systems have also been increasingly contested. Debates regarding automatic content identification tools recently gained momentum due to the European Union’s decision to update its copyright laws. A newly adopted EU directive encourages all platform owners to implement automatic content filters to safeguard copyrights (Spangler, 2019) and critics have argued that such measures run the risk of seriously hampering the freedom of speech and stifling cultural expressions online (e.g., Kaye, 2018). A wide range of high profile tech figures (such as Tim Berners Lee, commonly known as one of the founders of the World Wide Web) have even warned that the widespread adoption of pre-emptive content identification systems could effectively destroy the internet as we know it (Cerf et al., 2018). Content identification systems, then, are not neutral devices but key sites where the moral, juridical, economical, and","PeriodicalId":52252,"journal":{"name":"Internet Histories","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2021-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24701475.2021.1878649","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet Histories","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/24701475.2021.1878649","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMMUNICATION","Score":null,"Total":0}
引用次数: 1
Abstract
In today’s digital landscape, cultural content such as texts, films, images, and recorded sounds are increasingly subjected to automatic (or semi-automatic) processes of identification and classification. On a daily basis, spam filters scan swaths of emails in order to separate legit and illegitimate textual messages (Brunton, 2013), algorithms analyze years of user-uploaded film on YouTube in search for copyright violations (Heuguet, 2019), and software systems are deployed to scrutinize millions of images on social media sites in order to detect sexually offensive content (Liao, 2018). These examples reveal how machines and algorithmic systems are increasingly utilized to make complex judgments regarding cultural content. Indeed, it could be argued that the wideranging adoption of content identification systems is constructing new ontologies of culture and regimes of truth in the online domain. When put to action, content identification systems are trusted with the ability to separate good/bad and legal/illegal forms of communication and used to secure the singularity, value, authenticity, origin, and ownership of content. Such efforts are deeply embedded in constructions of knowledge, new forms of political governance, and not least global market transactions. Content identification tools now make up an essential part of the online data economy by protecting the interests of rights holders and forwarding the mathematization, objectification, and commodification of cultural productions. Parallel to their increased pervasiveness and influence, however, content identification systems have also been increasingly contested. Debates regarding automatic content identification tools recently gained momentum due to the European Union’s decision to update its copyright laws. A newly adopted EU directive encourages all platform owners to implement automatic content filters to safeguard copyrights (Spangler, 2019) and critics have argued that such measures run the risk of seriously hampering the freedom of speech and stifling cultural expressions online (e.g., Kaye, 2018). A wide range of high profile tech figures (such as Tim Berners Lee, commonly known as one of the founders of the World Wide Web) have even warned that the widespread adoption of pre-emptive content identification systems could effectively destroy the internet as we know it (Cerf et al., 2018). Content identification systems, then, are not neutral devices but key sites where the moral, juridical, economical, and