The spectrum of how much or how little organizational processes should be automated has long been debated. As the world undergoes a digital transformation where contactless and frictionless are promoted as two aspects that should be honored, many academics are questioning both the frenetic deployment of digital transformation in learning and teaching environments (e.g., face-to-face classrooms, library and academic office spaces, and laboratories, virtual/hybrid modalities, etc.) and its corresponding validity to students. Indeed, little consultation seems to have taken place with the necessary stakeholders, such as academics, students, instructional designers and pedagogical experts, during and after the COVID-19 pandemic. Rather, discussions and decisions appear to have been reactive regarding which modalities of teaching delivery might be the best in a given context, based on operational scenarios directly linked to financials, such as student recruitment trends, and local legislative changes affecting international students. Furthermore, many academic faculty and a great number of corresponding auxiliary staff have found themselves in the unemployment queue. This paper seeks to present the possibilities that AI-based systems may bring to higher education, but in so doing, point to the harmonization required to offer the most appropriate solutions to the needs of both students and teachers, as well as university administration. Education is not a commodity, although it has been treated as one. We are not advocating for an open market which offers “free education” for all, though we wish for everyone to have adequate access to education. But we are certainly advocating for a future in which students and teachers are central to the learning and teaching environment, not relegated to a passive role nor exploited. This article uses Shiv Ramdas’ short science fiction story, “The Trolley Solution”, to work through the future possibilities of AI in higher education.
{"title":"Automating Higher Education Through Artificial Intelligence?","authors":"Katina Michael;Jeremy Pitt;Jason Sargent;Eusebio Scornavacca","doi":"10.1109/TTS.2024.3450694","DOIUrl":"https://doi.org/10.1109/TTS.2024.3450694","url":null,"abstract":"The spectrum of how much or how little organizational processes should be automated has long been debated. As the world undergoes a digital transformation where contactless and frictionless are promoted as two aspects that should be honored, many academics are questioning both the frenetic deployment of digital transformation in learning and teaching environments (e.g., face-to-face classrooms, library and academic office spaces, and laboratories, virtual/hybrid modalities, etc.) and its corresponding validity to students. Indeed, little consultation seems to have taken place with the necessary stakeholders, such as academics, students, instructional designers and pedagogical experts, during and after the COVID-19 pandemic. Rather, discussions and decisions appear to have been reactive regarding which modalities of teaching delivery might be the best in a given context, based on operational scenarios directly linked to financials, such as student recruitment trends, and local legislative changes affecting international students. Furthermore, many academic faculty and a great number of corresponding auxiliary staff have found themselves in the unemployment queue. This paper seeks to present the possibilities that AI-based systems may bring to higher education, but in so doing, point to the harmonization required to offer the most appropriate solutions to the needs of both students and teachers, as well as university administration. Education is not a commodity, although it has been treated as one. We are not advocating for an open market which offers “free education” for all, though we wish for everyone to have adequate access to education. But we are certainly advocating for a future in which students and teachers are central to the learning and teaching environment, not relegated to a passive role nor exploited. This article uses Shiv Ramdas’ short science fiction story, “The Trolley Solution”, to work through the future possibilities of AI in higher education.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"5 3","pages":"264-271"},"PeriodicalIF":0.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10666816","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-04DOI: 10.1109/TTS.2024.3446183
Kevin R. McKee
In recent years, research involving human participants has been critical to advances in artificial intelligence (AI) and machine learning (ML), particularly in the areas of conversational, human-compatible, and cooperative AI. For example, roughly 9% of publications at recent AAAI and NeurIPS conferences indicate the collection of original human data. Yet AI and ML researchers lack guidelines for ethical research practices with human participants. Fewer than one out of every four of these AAAI and NeurIPS papers confirm independent ethical review, the collection of informed consent, or participant compensation. This paper aims to bridge this gap by examining the normative similarities and differences between AI research and related fields that involve human participants. Though psychology, human-computer interaction, and other adjacent fields offer historic lessons and helpful insights, AI research presents several distinct considerations—namely, participatory design, crowdsourced dataset development, and an expansive role of corporations—that necessitate a contextual ethics framework. To address these concerns, this manuscript outlines a set of guidelines for ethical and transparent practice with human participants in AI and ML research. Overall, this paper seeks to equip technical researchers with practical knowledge for their work, and to position them for further dialogue with social scientists, behavioral researchers, and ethicists.
近年来，有人类参与者参与的研究对于人工智能（AI）和机器学习（ML）的进步至关重要，尤其是在对话式、人类兼容和合作式人工智能领域。例如，在最近的 AAAI 和 NeurIPS 会议上，约有 9% 的出版物表明收集了原始人类数据。然而，人工智能和 ML 研究人员缺乏对人类参与者进行伦理研究的指导方针。在这些 AAAI 和 NeurIPS 论文中，每四篇中只有不到一篇确认了独立的伦理审查、知情同意书的收集或参与者补偿。本文旨在通过研究人工智能研究与涉及人类参与者的相关领域在规范方面的异同来弥补这一差距。虽然心理学、人机交互学和其他相邻领域提供了历史教训和有益的启示，但人工智能研究提出了几个独特的考虑因素--即参与式设计、众包数据集开发和企业的广泛作用--这就需要一个背景伦理框架。为了解决这些问题，本手稿概述了一套在人工智能和 ML 研究中对人类参与者进行伦理和透明实践的指导方针。总之，本文旨在为技术研究人员的工作提供实用知识，并为他们与社会科学家、行为研究人员和伦理学家的进一步对话奠定基础。
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Pub Date : 2024-09-04DOI: 10.1109/TTS.2024.3446860
Shiv Ramdas
The Trolley Solution is a speculative fiction short story that can be used as a single teaching case study in the classroom to discuss and debate the emergent issues related to the introduction of artificial intelligence, specifically in the higher education sector. The short story squares off humans against machines, provides poignant ideas on the future of work, describes organizational operational efficiencies that are being considered in the higher education sector, triggers critical thinking in identifying what it means to be human, points to the disconnectedness felt by everyday people in society, and considers how humans will learn in the future, among other themes addressed. The Trolley Solution points to broader impacts and social implications of AI, as it considers who or what is more ethical in a variety of circumstances. For those who have studied the Trolley Problem in depth, it is known that the philosophical problem has purposefully been designed with no real solution but instead is an attempt at thinking through various avenues of response to a moral dilemma.
{"title":"The Trolley Solution: Speculative Fiction Addressing the Trolley Problem in the Context of AI in Education","authors":"Shiv Ramdas","doi":"10.1109/TTS.2024.3446860","DOIUrl":"https://doi.org/10.1109/TTS.2024.3446860","url":null,"abstract":"The Trolley Solution is a speculative fiction short story that can be used as a single teaching case study in the classroom to discuss and debate the emergent issues related to the introduction of artificial intelligence, specifically in the higher education sector. The short story squares off humans against machines, provides poignant ideas on the future of work, describes organizational operational efficiencies that are being considered in the higher education sector, triggers critical thinking in identifying what it means to be human, points to the disconnectedness felt by everyday people in society, and considers how humans will learn in the future, among other themes addressed. The Trolley Solution points to broader impacts and social implications of AI, as it considers who or what is more ethical in a variety of circumstances. For those who have studied the Trolley Problem in depth, it is known that the philosophical problem has purposefully been designed with no real solution but instead is an attempt at thinking through various avenues of response to a moral dilemma.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"5 3","pages":"272-278"},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-30DOI: 10.1109/TTS.2024.3448506
Vasilis Stavrou;Anastasia Griva;Cleopatra Bardaki
Location-based services have been increasingly used to support various decisions in retail such as coupon recommendation, indoor advertisement, smart targeting, etc. However, effectively tracking user’s position to provide extra value embeds several challenges ranging from technical and infrastructure to business, user acceptance and social. This paper presents a location-based coupon recommendation service deployed in a retail store, using Bluetooth Low Energy (BLE) Beacons technology to track the customers. We aim to share the challenges we encountered, and the factors that affected our system’s quality and performance; and show how we handled the issues that arose. Our study moves beyond the technical challenges and discusses the business and user acceptance challenges, highlighting the role of the application context. This paper aspires to provide realistic and more holistic, not just technical, guidelines on prospective researchers and designers of location-based services for retail stores and other contexts. The outcome of the paper highlights new directions for existing challenges and introduces new ones related to beacon configuration, the choice of the unit of analysis, the definition of areas of interest, and acceptance by employees.
{"title":"Deploying a Location-Based Coupon Recommendation Service in Retail: Challenges and Lessons Learnt","authors":"Vasilis Stavrou;Anastasia Griva;Cleopatra Bardaki","doi":"10.1109/TTS.2024.3448506","DOIUrl":"https://doi.org/10.1109/TTS.2024.3448506","url":null,"abstract":"Location-based services have been increasingly used to support various decisions in retail such as coupon recommendation, indoor advertisement, smart targeting, etc. However, effectively tracking user’s position to provide extra value embeds several challenges ranging from technical and infrastructure to business, user acceptance and social. This paper presents a location-based coupon recommendation service deployed in a retail store, using Bluetooth Low Energy (BLE) Beacons technology to track the customers. We aim to share the challenges we encountered, and the factors that affected our system’s quality and performance; and show how we handled the issues that arose. Our study moves beyond the technical challenges and discusses the business and user acceptance challenges, highlighting the role of the application context. This paper aspires to provide realistic and more holistic, not just technical, guidelines on prospective researchers and designers of location-based services for retail stores and other contexts. The outcome of the paper highlights new directions for existing challenges and introduces new ones related to beacon configuration, the choice of the unit of analysis, the definition of areas of interest, and acceptance by employees.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"5 4","pages":"368-376"},"PeriodicalIF":0.0,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10660595","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-27DOI: 10.1109/TTS.2024.3443540
Luca Turchet
This paper proposes a paradigm shift from the current wave of Internet of Musical Things (IoMusT) research, which is mostly centered on technological development, towards the new wave of the Internet of Musical Things and People (IoMusTP). This wave focuses not only on musical stakeholders’ values, needs, behaviors and diversity, but also on their mutual entanglement with networked musical devices, services and environment. In the IoMusTP, technology is not only aware of the users and their surrounding context, but is also compliant to ethical and sustainable principles that will make it possible more inclusive, personalized, and socially acceptable experiences for the 21st-century musical stakeholders and beyond. The move from the IoMusT to the IoMusTP is a move from a network of musical devices to a network of musical stakeholders, whose interactions with musical resources as well as other stakeholders are empowered by devices. To this end, we propose a framework that can concretely guide designers of IoMusT technologies in considering the human and non-human factors relevant in the IoMusTP vision. We illustrate our framework by analyzing a set of case studies, showing how existing systems are insufficient to comply with the IoMusTP vision. Finally, we reflect on the challenges ahead of us, identifying a set of promising future directions that can inform the development of the next generation of IoMusT technologies.
{"title":"Entangled Internet of Musical Things and People: A More-Than-Human Design Framework for Networked Musical Ecosystems","authors":"Luca Turchet","doi":"10.1109/TTS.2024.3443540","DOIUrl":"https://doi.org/10.1109/TTS.2024.3443540","url":null,"abstract":"This paper proposes a paradigm shift from the current wave of Internet of Musical Things (IoMusT) research, which is mostly centered on technological development, towards the new wave of the Internet of Musical Things and People (IoMusTP). This wave focuses not only on musical stakeholders’ values, needs, behaviors and diversity, but also on their mutual entanglement with networked musical devices, services and environment. In the IoMusTP, technology is not only aware of the users and their surrounding context, but is also compliant to ethical and sustainable principles that will make it possible more inclusive, personalized, and socially acceptable experiences for the 21st-century musical stakeholders and beyond. The move from the IoMusT to the IoMusTP is a move from a network of musical devices to a network of musical stakeholders, whose interactions with musical resources as well as other stakeholders are empowered by devices. To this end, we propose a framework that can concretely guide designers of IoMusT technologies in considering the human and non-human factors relevant in the IoMusTP vision. We illustrate our framework by analyzing a set of case studies, showing how existing systems are insufficient to comply with the IoMusTP vision. Finally, we reflect on the challenges ahead of us, identifying a set of promising future directions that can inform the development of the next generation of IoMusT technologies.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"5 4","pages":"355-367"},"PeriodicalIF":0.0,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10649611","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-29DOI: 10.1109/TTS.2024.3430940
Dayoung Kim;Qin Zhu;Hoda Eldardiry
There has been a trend among various stakeholders for AI governance, such as the government, industry, and academia, that advocates for a shift from traditional ethics approach to more recent policy-oriented approach. This paper starts by briefly introducing the motivation for such a change. To further help AI ethics researchers ground their discussion about how to operationalize abstract AI ethics into actionable policy, it introduces existing literature about AI policy development efforts with ethics focus. We also discuss the implications of the policy approach to normative AI governance for training the next generation of AI professionals. More specifically, this paper introduces two approaches that AI educators can employ to encourage their students to participate in policy discussions and practical exercises in AI-related courses. The insights derived from this paper hold particular significance for AI professionals, educators, and policymakers aiming to translate general AI ethics principles into operationalizable action items with broader policy implications in the design of AI systems.
{"title":"Toward a Policy Approach to Normative Artificial Intelligence Governance: Implications for AI Ethics Education","authors":"Dayoung Kim;Qin Zhu;Hoda Eldardiry","doi":"10.1109/TTS.2024.3430940","DOIUrl":"https://doi.org/10.1109/TTS.2024.3430940","url":null,"abstract":"There has been a trend among various stakeholders for AI governance, such as the government, industry, and academia, that advocates for a shift from traditional ethics approach to more recent policy-oriented approach. This paper starts by briefly introducing the motivation for such a change. To further help AI ethics researchers ground their discussion about how to operationalize abstract AI ethics into actionable policy, it introduces existing literature about AI policy development efforts with ethics focus. We also discuss the implications of the policy approach to normative AI governance for training the next generation of AI professionals. More specifically, this paper introduces two approaches that AI educators can employ to encourage their students to participate in policy discussions and practical exercises in AI-related courses. The insights derived from this paper hold particular significance for AI professionals, educators, and policymakers aiming to translate general AI ethics principles into operationalizable action items with broader policy implications in the design of AI systems.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"5 3","pages":"325-333"},"PeriodicalIF":0.0,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-04DOI: 10.1109/TTS.2024.3408085
Ashish Hingle;Aditya Johri
Case studies are among the most popular and effective pedagogical techniques in ethics education. In this paper, we present a framework to develop and effectively use one type of case study: role-plays. We argue that role-plays are particularly effective for allowing students to think through complex problems and bridge multi-level issues, a core concern of ethics education. The fictional case implemented in the study presented here focuses on the use of algorithms for making lending decisions. The case narrative and its associated roles highlight and emphasize the interdependent and intertwined individual and societal perspectives. Thirty-six students consented to the research study in the course where the role-plays were implemented. Student responses related to their engagement with the role were analyzed. We found that participants moved between the multi-level perspectives in the case, identified ethical principles at each level, and connected case examples to real-world occurrences. Overall, using role-plays strongly encouraged students to appreciate the complexity of technology. This work is part of a larger project on using role-play case studies, and in our conclusions, we draw implications from our overall findings.
{"title":"A Framework to Develop and Implement Role-Play Case Studies to Teach Responsible Technology Use","authors":"Ashish Hingle;Aditya Johri","doi":"10.1109/TTS.2024.3408085","DOIUrl":"https://doi.org/10.1109/TTS.2024.3408085","url":null,"abstract":"Case studies are among the most popular and effective pedagogical techniques in ethics education. In this paper, we present a framework to develop and effectively use one type of case study: role-plays. We argue that role-plays are particularly effective for allowing students to think through complex problems and bridge multi-level issues, a core concern of ethics education. The fictional case implemented in the study presented here focuses on the use of algorithms for making lending decisions. The case narrative and its associated roles highlight and emphasize the interdependent and intertwined individual and societal perspectives. Thirty-six students consented to the research study in the course where the role-plays were implemented. Student responses related to their engagement with the role were analyzed. We found that participants moved between the multi-level perspectives in the case, identified ethical principles at each level, and connected case examples to real-world occurrences. Overall, using role-plays strongly encouraged students to appreciate the complexity of technology. This work is part of a larger project on using role-play case studies, and in our conclusions, we draw implications from our overall findings.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"5 3","pages":"306-315"},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-01DOI: 10.1109/TTS.2024.3427816
Yvonne Apolo;Katina Michael
THE CAPTURE is a mystery thriller series, that completed its second season on Peacock and BBC One. The British television drama revolves around the alteration of direct audiovisual evidence on the command of a special unit that believes there is enough circumstantial evidence to either convict or acquit an individual of a felony. Based on the plot of the television series, this paper explores the potential for a variety of AI-enabled applications to be used in the course of criminal proceedings. The implications of evidence tampering are considered through AI manipulation toward the realization that deepfake evidence may well be admitted in court dependent on the human decision-maker. Will the future demand the interpolation of visual evidence for high profile criminal cases, and what does the existence of Generative AI and deepfakes mean for the forensic analysis of audiovisual evidence? After contemplating the socio-technical plausibility of the central premise of THE CAPTURE, this paper then turns to its legal implications. Drawing on examples from U.S. and Australian legal frameworks, the paper considers the consequences of AI-corrected, augmented or generated audiovisual evidence on three facets of natural justice: (1) the presumption of innocence; (2) the fair trial; and (3) lawyers’ ethical duties of competence and to the administration of justice. The key takeaways of the paper are that: (1) deepfake evidence will continue to proliferate; (2) that the law will need to address both the substantive and procedural impacts of such evidence, and (3) that the legal profession must continue to educate its lawyers and practitioners, and associated stakeholders, of the nature, uses and risks posed by deepfake audiovisual artefacts to maintain public trust in the legal system.
THE CAPTURE》是一部悬疑惊悚剧集，第二季已在孔雀和 BBC One 频道播出。这部英国电视剧围绕着一个特别小组在其指挥下篡改直接视听证据的故事展开，该小组认为有足够的间接证据证明某人有罪或无罪。本文以该电视剧的情节为基础，探讨了在刑事诉讼过程中使用各种人工智能应用的可能性。本文通过人工智能的操作来考虑篡改证据的影响，从而认识到深度伪造证据很可能会被法庭采纳，而这取决于人类决策者。未来是否需要在备受瞩目的刑事案件中对视觉证据进行插值处理，以及生成式人工智能和深度伪造的存在对视听证据的法证分析意味着什么？在思考了《捕获》的核心前提在社会技术上的合理性之后，本文转而探讨其法律意义。本文以美国和澳大利亚的法律框架为例，探讨了人工智能校正、增强或生成的视听证据对自然正义三个方面的影响：(1) 无罪推定；(2) 公平审判；(3) 律师的能力道德义务和司法行政。本文的主要观点如下(1) 深度伪造证据将继续扩散；(2) 法律将需要解决此类证据在实体和程序上的影响；(3) 法律界必须继续教育其律师和从业人员以及相关利益方，使其了解深度伪造视听人工制品的性质、用途和风险，以维护公众对法律制度的信任。
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Pub Date : 2024-06-01DOI: 10.1109/TTS.2024.3413268
Katina Michael;Joseph R. Carvalko;Clinton J. Andrews;Lucy Batley
The June issue incorporates a double special issue bringing together the areas of Generative AI, ingenuity and the law; and separately the unintended consequences of emerging technologies aligned to artificial intelligence and subset areas, such as biometrics. The first special issue is led by Joseph Carvalko Jr., Chairperson, Technology and Ethics, Yale Interdisciplinary Center for Bioethics, Institution for Public and Social Policy Studies [1] ; and the second special issue is led by Clinton Andrews of the Edward J. Bloustein School of Planning and Public Policy at Rutgers University and previously the President of the IEEE Society on Social Implications of Technology [2] . In this guest editorial we provide a brief Introduction to the special issues and an overview of each of the accepted papers. We also invite Lucy Batley of Traction Industries located in Newcastle on the Tyne in England to join us, as the inspiration behind the cover design of this issue [3] .
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Pub Date : 2024-06-01DOI: 10.1109/TTS.2024.3416344
Gabriella Pangelinan;Aman Bhatta;Haiyu Wu;Michael C. King;Kevin W. Bowyer
Concerns related to the proliferation of automated face recognition technology with the intent of solving or preventing crimes continue to mount. The technology being implicated in wrongful arrest following 1-to-many face identification has heightened scrutiny in the media and spawned lawsuits. We analyze the accuracy of 1-to-many face identification across African-American and Caucasian demographic groups and in the presence of blur and reduced resolution in the probe image, as might occur in “surveillance camera quality” images. Because of the high accuracy of modern face recognition algorithms with “government ID quality” images and the size of available datasets, we use the following indirect metrics to assess the relative propensity for false positive identifications: (1) the traditional d-prime statistic between mated and non-mated score distributions, (2) absolute score difference between thresholds in the high-similarity tail of the non-mated distribution and the low-similarity tail of the mated distribution, and (3) distribution of (mated – non-mated rank-one scores) across the set of probe images. We find that demographic variation patterns in 1-to-many accuracy largely, but not perfectly, follow that observed in 1-to-1 accuracy. We show that, different from the case with 1-to-1 matching accuracy, demographic comparison of 1-to-many accuracy can be affected by different numbers of identities and images across demographics. We also show that increased blur or reduced resolution of the face in the probe image can significantly increase the false positive identification rate. This point is important because the reputation of modern face recognition algorithms for high accuracy in 1-to-many face identification comes from statistics based on analyzing “government ID quality” rather than “surveillance camera quality” images.
{"title":"Analyzing the Impact of Demographic and Operational Variables on 1-to-Many Face ID Search","authors":"Gabriella Pangelinan;Aman Bhatta;Haiyu Wu;Michael C. King;Kevin W. Bowyer","doi":"10.1109/TTS.2024.3416344","DOIUrl":"https://doi.org/10.1109/TTS.2024.3416344","url":null,"abstract":"Concerns related to the proliferation of automated face recognition technology with the intent of solving or preventing crimes continue to mount. The technology being implicated in wrongful arrest following 1-to-many face identification has heightened scrutiny in the media and spawned lawsuits. We analyze the accuracy of 1-to-many face identification across African-American and Caucasian demographic groups and in the presence of blur and reduced resolution in the probe image, as might occur in “surveillance camera quality” images. Because of the high accuracy of modern face recognition algorithms with “government ID quality” images and the size of available datasets, we use the following indirect metrics to assess the relative propensity for false positive identifications: (1) the traditional d-prime statistic between mated and non-mated score distributions, (2) absolute score difference between thresholds in the high-similarity tail of the non-mated distribution and the low-similarity tail of the mated distribution, and (3) distribution of (mated – non-mated rank-one scores) across the set of probe images. We find that demographic variation patterns in 1-to-many accuracy largely, but not perfectly, follow that observed in 1-to-1 accuracy. We show that, different from the case with 1-to-1 matching accuracy, demographic comparison of 1-to-many accuracy can be affected by different numbers of identities and images across demographics. We also show that increased blur or reduced resolution of the face in the probe image can significantly increase the false positive identification rate. This point is important because the reputation of modern face recognition algorithms for high accuracy in 1-to-many face identification comes from statistics based on analyzing “government ID quality” rather than “surveillance camera quality” images.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"5 2","pages":"217-230"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141964820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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