Uncertain Archives

Scholars from a range of disciplines interrogate terms relevant to critical studies of big data, from abuse and aggregate to visualization and vulnerability.This pathbreaking work offers an interdisciplinary perspective on big data, interrogating key terms. Scholars from a range of disciplines interrogate concepts relevant to critical studies of big data--arranged glossary style, from from abuse and aggregate to visualization and vulnerability--both challenging conventional usage of such often-used terms as prediction and objectivity and introducing such unfamiliar ones as overfitting and copynorm. The contributors include both leading researchers, including N. Katherine Hayles, Johanna Drucker and Lisa Gitelman, and such emerging agenda-setting scholars as Safiya Noble, Sarah T. Roberts and Nicole Starosielski.

1 Abuse 292 Affect 373 Aggregation 474 Algorithmic Racism 575 Bots 656 Care 757 Complicity 878 Conversational Agents 999 Cooling 10910 Copynorms 11511 Database 12512 Demo 13313 Detox 14114 Digital Assistants 151 15 Digital Humanities 16116 DNA 17117 Drone 17918 Error 19119 Ethics 20120 Executing 20921 Expertise 21722 Field 22723 Figura 235 24 File 24125 Flesh 249 26 Glitch 25927 Hashtag Archiving 27128 Hauntology 27929 Instrumentality 28930 Interface 29931 Intersectionality 305 32 Latency 31333 Metadata 32134 Migrationmapping 33135 (Mis)gendering 33936 Misreading 34737 Natural 35338 Obfuscation 35939 Organization 36940 Outlier 37741 Performative Measure 38942 Pornography 397 43 Prediction 403 44 Proxies 41945 Quantification 42746 Remains 43347 Reparative 44348 Self-Tracking 45749 Shifters 469 50 Sorting 47751 Stand-In 48552 Supply Chain 49353 Technoheritage 499 54 Throbber 51355 Time.now 52356 Unpredictability 53357 Unthought 54158 Values 55159 Visualization 56160 Vulnerability 56961 Word 579Contributors 585Index 597