{"id":70,"date":"2018-09-28T14:26:03","date_gmt":"2018-09-28T18:26:03","guid":{"rendered":"https:\/\/sites.bu.edu\/emsconf\/?page_id=70"},"modified":"2018-12-11T13:46:21","modified_gmt":"2018-12-11T18:46:21","slug":"face-off-facial-recognition-technologies-and-humanity-in-an-era-of-big-data","status":"publish","type":"page","link":"https:\/\/sites.bu.edu\/emsconf\/past-conferences\/face-off-facial-recognition-technologies-and-humanity-in-an-era-of-big-data\/","title":{"rendered":"April 18, 2018 – Face-Off: Facial Recognition Technologies and Humanity in an Era of Big Data"},"content":{"rendered":"

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About the Event<\/h3>\n

As facial recognition technology becomes increasingly sophisticated, and the presence of such devices proves ubiquitous in both public and private spheres, it is critical for researchers to examine the potential effects on both individuals and society as a whole. To this end, the Division of Emerging Media Studies of Boston University\u2019s College of Communication is holding an international symposium to bring together diverse perspectives from social scientists, philosophers, policy-makers, and computer scientists to explore the social, behavioral, and psychological dimensions of this new technological terrain. This unique collection of voices intends to illuminate the various and often competing dimensions of a challenging, complex area of research. Ultimately, it hopes to trace out the implications for society, and the choices that we must collectively and individually make.<\/p>\n

Organized and chaired by:
\nJames E. Katz, Boston University <\/p>\n

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Speakers & Abstracts<\/h3>\n

Margrit Betke, Boston University<\/h4>
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How Does the Face Recognition Technology Work?<\/em><\/strong>
\nFace recognition is the task of identifying or verifying a person from an image or video. In recent years, the advances in artificial intelligence, in particular, the use of deep neural networks have produced astonishingly accurate face recognition systems. This talk will present a high-level introduction to how current face recognition systems work and what they are capable of. <\/p>\n

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Mark Frank, University at Buffalo<\/h4>
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The Biology of Facial Recognition<\/em><\/strong>
\nA very underappreciated aspect of facial recognition is that it was important for survival throughout our evolutionary history. This presentation will discuss the history, the reasons, and the social importance of our hard-wired abilities to recognize others. It will then extend those findings and ideas to suggest that any new technology that moderates this role would have important implications for our social interaction and internal feelings. The presentation will end with informed speculation as to what those implications may be. <\/p>\n

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Vanessa Nurock, Epidapo CNRS-UCLA & Universit\u00e9 Paris 8<\/h4>
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The Risks and Benefits of Facial Recognition? A New Direction Needed<\/em><\/strong>
\nWhat are the risks and benefits of facial recognition? This question is usually considered as the most relevant and efficient way to deal with ethical and political issues about facial recognition. This talk suggests that a different approach may be useful to propose a fuller analysis of the ethical issues of facial recognition. I develop two different but related arguments. First, I argue that it is both necessary and urgent to go beyond this risk\/benefit stance in order to examine facial recognition as a particular case of an emerging technology. Second, I rely on philosophy and cognitive science to argue that a full-fledged ethics of facial recognition should deal with the three meanings of recognition. ‘Recognition’ means, first, a form of identification, but second, it is also an act of intellectual apprehension and third, it is an act of acknowledging or respecting someone. Together, these two arguments will contribute to suggest a few directions for an ethics of facial recognition. <\/p>\n

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Laura Spector-Sullivan, Harvard Medical School\u2019s Center for Bioethics <\/h4>
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The Ethical Significance of the Face and AI Facial Recognition<\/em><\/strong>
\nMany analyses of facial recognition focus on how to use this technology without ethical missteps. Some of these real and potential issues include biases in data sets making their way into algorithm operation, consent for the use of a face as a piece of biometric data, privacy of faces as intimate information that are nevertheless externally apparent, and accountability for facial recognition algorithms to be transparent and fair. While these are all very real and pressing issues, I would like to take a slightly different approach. I will consider the effects that facial recognition technology might have on ethics itself, where ethics is understood as a social practice of caring for and considering each other. I argue that part of this social practice is attunement and sensitivity to the nuances of other humans\u2019 facial expressions. I will then consider two questions: whether algorithms can be trained to interpret facial expressions in the same way, and the implications of offloading human facial recognition practices onto artificial systems. <\/p>\n

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Derek Christensen, Accenture<\/h4>
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An Industry Perspective on Facial Recognition Technology<\/em><\/strong>
\nFacial recognition and cognitive services are advancing at a rapid pace and driving real change in industry. This segment will explore industry applications of facial, image, and video recognition, the underlying trend of mass personalization, and the combinatory power of facial recognition with adjacent technologies.<\/p>\n

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Pierre Piazza, Cergy-Pontoise University<\/h4>
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Alphonse Bertillon: Issues in the \u201cScientific\u201d Identification of Persons by Means of Facial Features at the Turn of the 20th Century<\/em><\/strong>
\nAuthorities had been attempting to determine the true identity of individuals based on written descriptions of their faces since the Middle Ages at least, as evidenced by the development of various forms of descriptions and wanted notices at the time. Attempts at formalizing and\/or codifying this can be observed in the early 19th century. Reliance on facial features by policing authorities to identify individuals was not, however, the most rigorous of processes yet, as both its terminology and practices focused essentially on the most conspicuous physical characteristics\u2014even going as far as assessing an individual\u2019s degree of dangerousness from certain elements of their facial morphology. This talk specifically explores the portrait parl\u00e9 (French for \u201cspoken portrait\u201d), the real \u201crevolution\u201d in the field, which was a method for describing facial features developed and implemented by Alphonse Bertillon over the last three decades of the 19th century \u2013 initially as he worked for the Paris pr\u00e9fecture de police (police department). The signalement descriptif (\u201cdescriptive portrayal\u201d), as it was also called, was intended to supplement the anthropometric measurements that were already being relied upon to discriminate among individuals. The objective was to capture human physiognomy as accurately as possible, and the tool soon proved extremely useful as an evidence-based method for establishing the uniqueness of each repeat offender\u2019s identity.\n<\/p>\n

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Clare Garvie and Alvaro Bedoya, Georgetown Center for Privacy and Technology Jonathan Frankle, Massachusetts Institute of Technology <\/h4>
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The Perpetual Line-Up: Unregulated Police Face Recognition in America.<\/em><\/strong>
\nPeople often think of face recognition technology as some science fiction future. In reality, half of all American adults are in a police or FBI face recognition network. Police face recognition technology is much more pervasive than people realize – yet it is not subject to any meaningful system of regulation. In this talk, Clare Garvie, Alvaro Bedoya and Jonathan Frankle will discuss The Perpetual Line-Up: Unregulated Police Face Recognition in America, the Center’s year-long investigation into police use of face recognition. In a world where we have no (formal) reasonable expectation of privacy in public, how should the law protect Americans’ privacy, civil liberties, and civil rights?<\/p>\n

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Luke Stark, Dartmouth College<\/h4>
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Emotion, Classification, and Race in Facial Recognition Systems <\/em><\/strong>
\nFacial recognition systems are increasingly common components of commercial smartphones such as the iPhone X and the Samsung Galaxy S9. These technologies are also increasingly being put to use in consumer-facing social media video-sharing applications, such as Apple\u2019s animoji, Facebook Messenger\u2019s masks and filters and Samsung\u2019s AR Emoji. These animations serve as technical phenomena translating moments of affective and emotional expression into mediated socially legible forms. Through an analysis of company patents, technical and promotional materials, and broader literature on digital animation, this paper considers the ways these facial recognition systems classify and categorize racial identities in human faces. The paper considers the potential both for racializing logics as part of these systems of classification, and how data regarding emotional expression gathered through these systems might interact with identity-based forms of classification. <\/p>\n

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Daniel Halpern, Pontifical Catholic University of Chile<\/h4>
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Public Perceptions and Concerns: A View from Chile<\/em><\/strong>
\nThis experiment, conducted with 2,380 Chilean professionals, aimed to understand how individuals react to positive and negative scenarios about the impact of facial recognition technologies, and which psychological factors affect subjects’ attitudes toward the acceptance of this technology. Results showed that in the negative condition individuals are less willing to accept its use, and this relationship is mediated by the attitude to this technology (Cyber-Utopism and Dystopianism) and the level of security elicited by the experiment. The study also confirmed how several predictors such as exposition to sci-fi series or movies, recognition of human characteristics in Artificial Intelligence, religiosity and conspiracy mentality impact the acceptance of facial recognition.<\/p>\n

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Lora Appel, OpenLab University Health Network, Toronto; York University, Toronto<\/h4>
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Putting a Face to a Name in Clinical Settings: Recognizing Faces in Manifestation and Outcomes of Clinician Anonymity.<\/em><\/strong>
\nHealthcare is characterized by \u201cmore to do, more to know, more to manage, and more people involved than ever before.\u201d This reality brings challenges to staff working in rapidly changing teams and stressful environments. The inability to recognize colleagues (by face for example) and the general lack of familiarity within teams undermines the effective collaboration that is critical to the delivery of patient care. This phenomenon, termed \u2018clinician anonymity,\u2019 was neither well defined nor understood, and few studies focused on interventions that addressed its causes and effects. This study focused on two novel elements: studying the phenomenon of \u2018clinician anonymity\u2019 and its effects on inter-professional communication in hospital practice and applying design science theory and methodology to understand and address communication problems\n<\/p>\n

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Speaker Biographies<\/h4>\n

Lora Appel<\/strong><\/em> is an assistant professor of Health Informatics at the Faculty of Health at York University, and a Research Scientist at OpenLab, and innovation Centre housed at University Health Network, the largest medical research organization in Canada. She leads \u201cPrescribing Virtual Reality (VRx)\u201d a collection of studies that introduce and evaluate AR\/VR\/MR interventions for patients, caregivers, and healthcare providers. Lora has received several grants from the Centre for Aging in Brain Health innovation (CABHI) to pursue this work in aging and dementia care. She is also involved in the design of a new curriculum incorporating VR for the School of Nursing at York University. Lora received her PhD from the School of Communication and Information at Rutgers University and was awarded the Gerald R. Miller Outstanding Doctoral Dissertation Award in 2017 for her work defining clinician anonymity and designing \u201cFace2Name\u201d a tool to improve interprofessional communication in clinical settings. Her expertise is in applying design thinking and science methodologies to healthcare innovation; she is passionate about designing new technological interventions that provide care in the pursuit of a cure. www.PrescribingVR.com<\/p>\n

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