  {"id":18994,"date":"2016-11-18T16:50:27","date_gmt":"2016-11-18T21:50:27","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/our-modern-surveillance-society\/"},"modified":"2016-11-18T16:50:27","modified_gmt":"2016-11-18T21:50:27","slug":"our-modern-surveillance-society","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/our-modern-surveillance-society\/","title":{"rendered":"Our Modern Surveillance Society"},"content":{"rendered":"<p><strong>They\u2019re Watching<\/strong><\/p>\n<p>In cities across the world, governments are investing heavily in Closed Circuit Television (CCTV), a form of video surveillance that transmits a <a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2016\/11\/images-8.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-19072 alignright\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2016\/11\/images-8.jpg\" alt=\"images\" width=\"275\" height=\"183\" \/><\/a><br \/>\ndigital feed to a limited set of monitors. Most recently with the emergence of the cloud, companies offer video surveillance as a service (VSaaS), whereby a user can automatically set and adjust capabilities, access footage via multiple devices, and rapidly scale video capabilities. <a href=\"#_ftn1\" name=\"_ftnref1\">[1]<\/a>\u00a0 As the price of video surveillance decreases, the prevalence of surveillance cameras has increased dramatically. While London with estimates of over 1.9 million installed cameras ranks as the most surveilled city, other metropolises across the globe are investing heavily in video surveillance. Worldwide revenue from sale of video surveillance technology reached $15 billion in 2014 and is expected to increase up to over $23.6 billion by 2018.<a href=\"#_ftn2\" name=\"_ftnref2\">[2]<\/a><\/p>\n<p><strong>Video Surveillance and the Prevalence of Crime<\/strong><\/p>\n<p>Most cities laud the surveillance technology as a way to prevent crime and increase public safety. While the presence of a camera in a parking lot or <a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2016\/11\/download-1-3.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"size-medium wp-image-19073 alignleft\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2016\/11\/download-1-3-300x166.jpg\" alt=\"download-1\" width=\"300\" height=\"166\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2016\/11\/download-1-3-300x166.jpg 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2016\/11\/download-1-3.jpg 302w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a>on public transportation may deter a potential criminal from committing a crime, the cameras have no effect on experienced offenders.\u00a0\u00a0 Despite the ability to store and compare vast quantities of video footage, after a crime has been committed, facial recognition software is not yet capable of dissecting video footage and identifying possible criminals.<a href=\"#_ftn3\" name=\"_ftnref3\">[3]<\/a> \u00a0In order for facial recognition software to ever work, a computer must be equipped with a database of faces against which to compare video footage. Many worry that such a catalog would infringe on privacy rights of law abiding citizens. While law enforcement organizations can use mug shots of past perpetrators, facial recognition is not yet advanced enough to match a clear image to the grainy video footage of a CCTV camera that is taken from an angle. The FBI\u2019s Next Generation Identification (NGI) system, only guarantees an 85% chance of returning a suspect\u2019s name on a ranked list of 50 names after viewing a picture of a suspect\u2019s face, and that will only happen if the suspect\u2019s name is already in the database. Even amongst software developers, many believe that facial recognition software will never deliver \u201cnear human\u201d recognition capabilities.<a href=\"#_ftn4\" name=\"_ftnref4\">[4]<\/a><\/p>\n<p><strong>Working around Technological Limitations<\/strong><\/p>\n<p><iframe loading=\"lazy\" title=\"London police using crime-fighting &quot;super recognizers&quot;\" width=\"640\" height=\"360\" src=\"https:\/\/www.youtube.com\/embed\/_lcEhZm8iUE?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/p>\n<p>Recognizing these limitations, some law enforcement agencies have developed processes that pair their digital libraries with the power of the human brain. The London Metropolitan Police Service created a specialized force of \u201csuper-recognizers\u201d to work with computer outputs in order to identify criminals. Officers at Scotland Yard developed this unit after hearing about research from a 性视界 postdoctoral student studying prosopagnosia, a condition where a person is unable to recognize human faces.\u00a0 The research showed that humans are capable of a spectrum of recognition ability.\u00a0 While a person with prosopagnosia cannot even recognize himself, super-recognizers can remember the face of a person with whom they have minimally interacted. To become a member of the Met super-recognizer unit, an individual must pass a series of recognition tests.<a href=\"#_ftn5\" name=\"_ftnref5\">[5]<\/a><\/p>\n<p>To identify a criminal, first, software determines the images that contain faces within a stream of video footage. Normal police officers then enter these images of the perpetrator into a database and tag the images with categorical metadata such as age, race\/ethnicity, type of crime, and other physical characteristics like tattoos, missing teeth, etc. The database also includes images and mug shots of known criminals tagged with metadata. Using the computer\u2019s algorithm, super-recognizers narrow the number of images in the database to compare against the video footage. They then can determine which images in the database match the perpetrator. In 2015, this unit was able to solve 2,500 crimes using imagery.\u00a0 This method of identification has also proven far less expensive and more accurate than traditional identification techniques like DNA and finger print matching. <a href=\"#_ftn6\" name=\"_ftnref6\">[6]<\/a><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-19386 alignright\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2016\/11\/images-1-4.jpg\" alt=\"images-1\" width=\"350\" height=\"233\" \/><\/p>\n<p><strong>Ethical Implications<\/strong><\/p>\n<p>While use cases, like London\u2019s team of super-recognizers, prove that video surveillance can effectively improve security, there are still many ethical quandaries that need further exploration. Governments must balance civil liberty and safety. As evidenced by the revelations of Edward Snowden, most law-abiding citizens do not feel comfortable submitting to government surveillance. As technology becomes more advanced, societies must constantly assess the freedoms they forsake by living in a digital world.<\/p>\n<p>Word Count: 799<\/p>\n<p><a href=\"#_ftnref1\" name=\"_ftn1\">[1]<\/a>\u201cA Detailed Comparison of VSaaS vs. Internet-Connected Traditional Security Camera Systems\u201d, Dean Drako. <em>Eagle Eye Networks<\/em>.<\/p>\n<p><a href=\"#_ftnref2\" name=\"_ftn2\">[2]<\/a> <a href=\"http:\/\/cjr.sagepub.com\/content\/early\/2013\/07\/05\/0734016813492415\">\u201cHere\u2019s Looking at You: An Evaluation of Public CCTV Cameras and Their Effects on Crime and Disorder\u201d<\/a>, McLean, Sarah J.; Worden, Robert E.; Kim, MoonSun.\u00a0<em>Criminal Justice Review.<\/em><\/p>\n<p><a href=\"#_ftnref3\" name=\"_ftn3\">[3]<\/a> \u201cFrom Drones to Body Cams, Tech is Changing the Fight Against Crime\u201d, Simon Hill, <em>Digital Trends<\/em>.<\/p>\n<p><a href=\"#_ftnref4\" name=\"_ftn4\">[4]<\/a> \u201cWhy Facebook is Beating the FBI at Facial Recognition\u201d, Russell Brandom, <em>The Verge<\/em>.<\/p>\n<p><a href=\"#_ftnref5\" name=\"_ftn5\">[5]<\/a> \u201cThe Super Recognisers of Scotland Yard\u201d, Xan Rice, <em>New Statesman.<\/em><\/p>\n<p><a href=\"#_ftnref6\" name=\"_ftn6\">[6]<\/a> \u201cThe Detectives who Never Forget a Face\u201d, Patrick Raden Keefe, <em>The New Yorker<\/em>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>While the prevalence of surveillance cameras in metropolitan areas continues to increase, the technology does not always deliver on its promise to prevent crime. As law enforcement agencies rethink the use of video surveillance, societies must assess the trade off between increased security and decreased civil liberty.<\/p>\n","protected":false},"author":2621,"featured_media":19552,"comment_status":"open","ping_status":"closed","template":"","categories":[],"class_list":["post-18994","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/digitization-challenge-2016\/","yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Our Modern Surveillance Society - Technology and Operations Management<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/our-modern-surveillance-society\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Our Modern Surveillance Society - Technology and Operations Management\" \/>\n<meta property=\"og:description\" content=\"While the prevalence of surveillance cameras in metropolitan areas continues to increase, the technology does not always deliver on its promise to prevent crime. 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