IEEE transactions on technology and society最新文献

{"title":"2022 Index IEEE Transactions on Technology and Society Vol. 3","authors":"","doi":"10.1109/TTS.2022.3230198","DOIUrl":"https://doi.org/10.1109/TTS.2022.3230198","url":null,"abstract":"Presents the 2022 author/subject index for this issue of the publication.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"3 4","pages":"333-339"},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8566059/9987552/10004495.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50226289","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}

{"title":"Analyzing Human Observer Ability in Morphing Attack Detection—Where Do We Stand?","authors":"Sankini Rancha Godage;Frøy Løvåsdal;Sushma Venkatesh;Kiran Raja;Raghavendra Ramachandra;Christoph Busch","doi":"10.1109/TTS.2022.3231450","DOIUrl":"10.1109/TTS.2022.3231450","url":null,"abstract":"Morphing attacks are based on the technique of digitally fusing two (or more) face images into one, with the final visage resembling the contributing faces. Morphed images not only pose a challenge to Face-Recognition Systems (FRS) but also challenge experienced human observers due to high quality, postprocessing eliminating any visible artifacts, and further the printing and scanning process. Few studies have concentrated on examining how human observers can recognize morphing attacks, even as several publications have examined the susceptibility of automated FRS to morphing attacks and offered morphing attack detection (MAD) approaches. MAD approaches base their decisions either on a single image with no reference to compare against (Single-Image MAD (S-MAD)) or using a reference image (Differential MAD (D-MAD)). One prevalent misconception is that an examiner’s or observer’s capacity for facial morph detection depends on their subject expertise, experience, and familiarity with the issue. No works have reported the specific results of observers who regularly verify identity (ID) documents for their jobs. As human observers are involved in checking ID documents having facial images, a lapse in their competence can result in significant societal challenges. To assess the observers’ proficiency, this research first builds a new benchmark database of realistic morphing attacks from 48 different subjects, resulting in 400 morphed images. Unlike the previous works, we also capture images from Automated Border Control (ABC) gates to mimic realistic border-crossing scenarios in the D-MAD setting with 400 probe images, to study the ability of human observers to detect morphed images. A new dataset of 180 morphing images is also produced to research human capacity in the S-MAD environment. In addition to creating a new evaluation platform to conduct S-MAD and D-MAD analysis, the study employs 469 observers for D-MAD and 410 observers for S-MAD who are primarily governmental employees from more than 40 countries, along with 103 control group members who are not examiners. The analysis offers intriguing insights and highlights the lack of expertise and failure to recognize a sizable number of morphing attacks by experienced observers. Human observers tend to detect morphed images to a lower accuracy as compared to the four automated MAD algorithms evaluated in this work. The results of this study are intended to aid in the development of training programs that will prevent security failures while determining whether an image is bona fide or altered.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"4 2","pages":"125-145"},"PeriodicalIF":0.0,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8566059/10153436/09997091.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49232822","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}

{"title":"After COVID-19: Crises, Ethics, and Socio-Technical Change","authors":"Rafael A. Calvo;Sebastian Deterding;Catherine Flick;Christoph Lütge;Alison Powell;Karina V. Vold","doi":"10.1109/TTS.2022.3218500","DOIUrl":"10.1109/TTS.2022.3218500","url":null,"abstract":"Crises like the COVID-19 pandemic accelerate social and technological changes and put new political and public demands on science, technology, and innovation systems. Their urgency clashes with the deliberate slowness of existing responsible innovation and technology ethics practices and processes, while many fast and ad-hoc changes and infrastructures brought about during a crisis become permanent fixtures. This special issue brings together work reflecting in different ways how COVID-19 as an exemplary crisis is creating new challenges for technology ethics. From epidemiological models to contact tracing, biometric recognition, and machine learning-based assisted diagnosis, the different articles show the quandaries of our increasingly datafied health systems.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"3 4","pages":"248-251"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8566059/9987552/09987572.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42891389","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}

{"title":"What Happens to COVID-19 Data After the Pandemic? Socio-Technical Lessons","authors":"Katina Michael;Roba Abbas","doi":"10.1109/TTS.2022.3226119","DOIUrl":"10.1109/TTS.2022.3226119","url":null,"abstract":"The COVID-19 global pandemic outbreak meant a complete reevaluation of societal interactions, business processes, and government policies. For decades, the scientific and technical communities had contemplated the possibility of an all-out air-borne virus and had postulated how technology might be used in response, for example, in the reduction of transmission rates. In this paper, we examine the Australian COVID-19 technological response, focused initially on using a contact tracing app that would continually be broadcasting for known recorded cases, one nearby smartphone to another, and to the successive deployment of a QR-code-based solution requiring checking in and checking out of a place of congregation, like a closed or open campus setting. Despite the lackluster outcomes of the high-fidelity solutions, government continued, and in some instances, persisted in relying on QR codes for a considerable period. These solutions necessitated the collection of data pertaining to an individual for functioning, prompting a series of questions regarding the collection, storage, dissemination, and use of this data, both at the height of the pandemic and presently. On reflection, was the data effectively used or integrated into the proposed processes? Could the data be utilized in an unauthorized manner? And how might we circumvent its unauthorized use moving forward? Are there any potentially positive use cases that we could envisage? And, significantly, in the context of this piece, what are the broader socio-technical lessons or learnings that could be derived from such implementations that can be reinstituted into the design of future health-oriented systems? This paper provides an overview of Australia’s contact tracing app, from here on referred to as COVIDSafe, and the subsequent use of QR Codes that were state based and governed by the Services arm of the Australian Government, to present design insights relevant to both the Australian context and beyond.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"3 4","pages":"242-247"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8566059/9987552/09987511.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49501178","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}

{"title":"IEEE Transactions on Technology and Society Publication Information","authors":"","doi":"10.1109/TTS.2022.3206925","DOIUrl":"https://doi.org/10.1109/TTS.2022.3206925","url":null,"abstract":"Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"3 4","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8566059/9987552/09987514.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50226292","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}

{"title":"tts-index-3230198","authors":"","doi":"10.1109/tts.2022.3230198","DOIUrl":"https://doi.org/10.1109/tts.2022.3230198","url":null,"abstract":"","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47493575","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}

{"title":"Computing and Modeling After COVID-19: More Responsible, Less Technical","authors":"Ehsan Nabavi","doi":"10.1109/TTS.2022.3218738","DOIUrl":"10.1109/TTS.2022.3218738","url":null,"abstract":"The COVID-19 pandemic brought into focus the crucial role of computational modeling and simulation in informing and/or advising governments and societies, demonstrating the profound influence that modelers can have, particularly in times of crisis. This global experience has (re)shaped political and public demands on science and technology and the ways in which we incorporate scientific findings in our everyday lives. Through a brief review of models developed for COVID-19, this paper discusses the urgent need to move towards ‘responsible modeling’ in which social, ethical, and cultural issues claim the same importance as technical aspects. This includes a new social contract between modeler and society on one hand, and science and policy on the other hand. The characteristics of modeling work under this new paradigm, however, are still not well understood and are a topic of debate. This paper aims to fill this gap by proposing a new research agenda that can facilitate the discussion about ‘responsible modeling’ and the overarching principles that underpin the concept’s aims and objectives.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"3 4","pages":"252-261"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44937467","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}

{"title":"Individuality and Fairness in Public Health Surveillance Technology: A Survey of User Perceptions in Contact Tracing Apps","authors":"Ellen Hohma;Ryan Burnell;Caitlin C. Corrigan;Christoph Luetge","doi":"10.1109/TTS.2022.3211073","DOIUrl":"10.1109/TTS.2022.3211073","url":null,"abstract":"Machine learning algorithms are playing an increasingly important role in public health measures, accelerated by the Covid-19 pandemic. It is therefore vital that machine learning algorithms are applied in ways that are generally considered fair. However, the question of how to define fairness in a public health context is still an open one. In this study, we investigated people’s attitudes towards two ways of defining fairness in the context of Covid-19 contact tracing apps. In the first, ‘high-individuality’ approach, the likelihood of an algorithm asking a person to self-isolate would depend on the person’s individual characteristics, such as their risk of spreading the virus through regular contacts. In the second ‘low individuality’ approach, these individual characteristics would not be used to come to a decision. For each approach, participants rated its fairness, overall quality, and their privacy concerns, and answered questions about basic psychological need satisfaction. Participants rated the high-individuality approach as fairer and better overall compared to the low-individuality approach, despite having greater privacy concerns. Further, we found a strong correlation between the participants’ fairness perceptions and their overall impression of the tracking tool. Together, these findings suggest that people prefer individualised approaches in some contexts and perceive them as fairer. However, policy makers should consider the privacy trade-off of employing such measures.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"3 4","pages":"300-306"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8566059/9987552/09906425.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49226007","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}

{"title":"The Semantic Attack Surface: A Systems-Dynamic Model of Narrative in Cyberspace","authors":"Catherine B. Smith","doi":"10.1109/TTS.2022.3210782","DOIUrl":"10.1109/TTS.2022.3210782","url":null,"abstract":"Influence operations in cyberspace have raised questions about how narratives are strategically disseminated and circulated online, and in particular, whether state-of-the-art machine learning (ML) techniques for narrative understanding and automated narrative generation are or will soon become part of adversarial nation-states’ arsenal. However, until we clarify some fundamental ambiguities surrounding narratives in cyberspace, we cannot accurately assess the threat of ML. For instance, how do we define “narrative” in a way that makes sense across all the various organizations and academic disciplines that must be involved in defending against disinformation? What blind spots in our shared lexicon have stymied the United States’ response to disinformation attacks so far? This paper aims to take a step towards alleviating the confusion by analyzing the usage of some common terminology, summarizing some recent contributions in the realm of disinformation, positing a new systems-dynamic model of narrative in cyberspace, and demonstrating the use of the model in the context of an existing case study in disinformation.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"4 2","pages":"146-157"},"PeriodicalIF":0.0,"publicationDate":"2022-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43592392","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}

{"title":"Social Sensing for Personalized Orienteering Mediating the Need for Sociality and the Risk of COVID-19","authors":"Giovanni Pilato;Fabio Persia;Mouzhi Ge;Daniela D’Auria","doi":"10.1109/TTS.2022.3210882","DOIUrl":"10.1109/TTS.2022.3210882","url":null,"abstract":"Orienteering or itinerary planning applications aim to optimize travel routes exploiting user preference and other constraints, such as time budget or traffic conditions. For these algorithms, it is essential to explore the user preference to predict potential Points-Of-Interest (POI) or touristic routes. However, user preference has been significantly affected by the COVID-19, since health concern plays a key trade-off role now. For example, people may try to avoid crowdedness, even if there is a strong social desire. However, most orienteering applications just focus on user preferences, thus paying less attention to the variety of the data inputs, which has become an essential factor for the utility of the application in the COVID-19 era. Therefore, this paper proposes a social sensing system that considers the trade-off between user preference and various factors, such as crowdedness, fear of being infected, knowledge of the COVID-19, POI features, and desire for socialization. The experiments are conducted on profiling user interests with Doc2Vec and FastText based on the Yelp dataset. Furthermore, the proposed system is modular and can be efficiently adapted to different applications for COVID-aware itinerary planning.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"3 4","pages":"323-332"},"PeriodicalIF":0.0,"publicationDate":"2022-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46291287","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}