Pub Date : 2026-01-09DOI: 10.1109/TTS.2026.3651875
{"title":"2025 Index IEEE Transactions on Technology and Society Vol. 6","authors":"","doi":"10.1109/TTS.2026.3651875","DOIUrl":"https://doi.org/10.1109/TTS.2026.3651875","url":null,"abstract":"","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 4","pages":"495-505"},"PeriodicalIF":0.0,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11345138","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145929461","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 : 2025-12-24DOI: 10.1109/TTS.2025.3626074
Lindsay J. Robertson;Clinton J. Andrews;Lucy Resnyansky
{"title":"Special Issue Editorial: Imagining Tomorrow’s Infrastructure","authors":"Lindsay J. Robertson;Clinton J. Andrews;Lucy Resnyansky","doi":"10.1109/TTS.2025.3626074","DOIUrl":"https://doi.org/10.1109/TTS.2025.3626074","url":null,"abstract":"","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 4","pages":"338-341"},"PeriodicalIF":0.0,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11314487","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145814501","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 : 2025-12-24DOI: 10.1109/TTS.2025.3621784
Xuanyan Zhu;Si Min Liu;Shashank Vaid;Daniel Gozman;Katina Michael
{"title":"Editorial Betting on Dual-Use Technology: How AI and Marketing Rewires Modern Gambling","authors":"Xuanyan Zhu;Si Min Liu;Shashank Vaid;Daniel Gozman;Katina Michael","doi":"10.1109/TTS.2025.3621784","DOIUrl":"https://doi.org/10.1109/TTS.2025.3621784","url":null,"abstract":"","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 4","pages":"326-334"},"PeriodicalIF":0.0,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11314187","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145814489","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 : 2025-12-24DOI: 10.1109/TTS.2025.3620515
{"title":"IEEE Transactions on Technology and Society Publication Information","authors":"","doi":"10.1109/TTS.2025.3620515","DOIUrl":"https://doi.org/10.1109/TTS.2025.3620515","url":null,"abstract":"","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 4","pages":"C2-C3"},"PeriodicalIF":0.0,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11314189","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145814493","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 : 2025-12-24DOI: 10.1109/TTS.2025.3621785
K. Michael
Recounts the career and contributions of Lindsay James Robertson.
叙述林赛·詹姆斯·罗伯逊的职业生涯和贡献。
{"title":"In Memoriam","authors":"K. Michael","doi":"10.1109/TTS.2025.3621785","DOIUrl":"https://doi.org/10.1109/TTS.2025.3621785","url":null,"abstract":"Recounts the career and contributions of Lindsay James Robertson.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 4","pages":"335-337"},"PeriodicalIF":0.0,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11314486","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145814496","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 : 2025-12-12DOI: 10.1109/TTS.2025.3630817
Mallory James;Daniel S. Schiff;Heather A. Love;Iven Mareels;Ketra Schmitt;Greg Adamson
In August 2025, Australia’s Productivity Commission acknowledged that “large AI models are already being trained on copyrighted materials without consent or compensation” [1, p. 25]. In doing so, they cited evidence already documented by numerous scholars and advocates regarding how traditional expectations about safeguarding the ownership of completed work could no longer be assured. Yet, shocking authors and artists, the commission continued onwards to propose that the legal concept of “fair use” can be interpreted as allowing tech companies to freely use copyrighted material to train artificial intelligence (AI) models even without explicit consent [2]. Even while raising the possibility that this concession for tech companies would come at the expense of copyright owners, the commission acknowledged that the local economies of AI innovation might still feel no benefit whatsoever: “At present, large AI models are trained overseas, not in Australia. It is unclear whether the introduction of a [text and data mining] TDM exception would change this trend” [1, p. 28]. It is easy to see the injustice of giving away the rights of authors and artists to their work and (meagre) livelihoods, especially when doing so doesn’t even promise direct payoffs back to Australian workers. But how can we move beyond this initial critical reaction towards also contextualizing such transfers of intellectual property (IP) within a more robust understanding of how work and its products are currently governed in the age of AI?
{"title":"Special Issue Editorial: Extraction by Design—AI, Value, and the Future of Work","authors":"Mallory James;Daniel S. Schiff;Heather A. Love;Iven Mareels;Ketra Schmitt;Greg Adamson","doi":"10.1109/TTS.2025.3630817","DOIUrl":"https://doi.org/10.1109/TTS.2025.3630817","url":null,"abstract":"In August 2025, Australia’s Productivity Commission acknowledged that “large AI models are already being trained on copyrighted materials without consent or compensation” [1, p. 25]. In doing so, they cited evidence already documented by numerous scholars and advocates regarding how traditional expectations about safeguarding the ownership of completed work could no longer be assured. Yet, shocking authors and artists, the commission continued onwards to propose that the legal concept of “fair use” can be interpreted as allowing tech companies to freely use copyrighted material to train artificial intelligence (AI) models even without explicit consent [2]. Even while raising the possibility that this concession for tech companies would come at the expense of copyright owners, the commission acknowledged that the local economies of AI innovation might still feel no benefit whatsoever: “At present, large AI models are trained overseas, not in Australia. It is unclear whether the introduction of a [text and data mining] TDM exception would change this trend” [1, p. 28]. It is easy to see the injustice of giving away the rights of authors and artists to their work and (meagre) livelihoods, especially when doing so doesn’t even promise direct payoffs back to Australian workers. But how can we move beyond this initial critical reaction towards also contextualizing such transfers of intellectual property (IP) within a more robust understanding of how work and its products are currently governed in the age of AI?","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 4","pages":"421-429"},"PeriodicalIF":0.0,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11299073","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145814495","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 : 2025-11-14DOI: 10.1109/TTS.2025.3630666
Chelsea McCullough;Jessica P. Needle;Haley Triem;Kenneth R. Fleischmann;Sherri R. Greenberg
This paper reports findings from a mixed-methods study examining the perspectives of apprentices in skilled trade labor unions about artificial intelligence (AI). Findings emerge from 148 surveys with apprentices and 15 interviews with apprentices and union leaders (150 total participants). Participants expressed a general concern about AI displacing jobs but lacked fear that AI will replace their jobs. Interviews revealed that the manual, hands-on nature of participants’ work combined with the complexity of on-the-job technical judgement required removes anxiety that AI could automate these tasks. However, participants expressed concern about AI’s surveillance capacity (e.g., reporting working hours or time spent using a specific tool). Participants expressed support for how smart hand tools could improve their on-the-job safety. These findings provide support for human-centered AI (HCAI) practices by emphasizing a relationship between skilled trade work and AI.
{"title":"“AI Is Not Gonna Take Our Jobs”: Perspectives From Skilled Trade Labor Union Apprentices","authors":"Chelsea McCullough;Jessica P. Needle;Haley Triem;Kenneth R. Fleischmann;Sherri R. Greenberg","doi":"10.1109/TTS.2025.3630666","DOIUrl":"https://doi.org/10.1109/TTS.2025.3630666","url":null,"abstract":"This paper reports findings from a mixed-methods study examining the perspectives of apprentices in skilled trade labor unions about artificial intelligence (AI). Findings emerge from 148 surveys with apprentices and 15 interviews with apprentices and union leaders (150 total participants). Participants expressed a general concern about AI displacing jobs but lacked fear that AI will replace <italic>their</i> jobs. Interviews revealed that the manual, hands-on nature of participants’ work combined with the complexity of on-the-job technical judgement required removes anxiety that AI could automate these tasks. However, participants expressed concern about AI’s surveillance capacity (e.g., reporting working hours or time spent using a specific tool). Participants expressed support for how smart hand tools could improve their on-the-job safety. These findings provide support for human-centered AI (HCAI) practices by emphasizing a relationship between skilled trade work and AI.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 4","pages":"471-480"},"PeriodicalIF":0.0,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11247937","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145814499","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 : 2025-10-28DOI: 10.1109/TTS.2025.3621860
V. Sridhar;Amrita Mishra;Asheef Iqubbal
Sixth-generation (6G) mobile networks and services are expected to be standardized by 2030. While they will offer enhanced human-machine and machine-machine connectivity, they will also introduce unique challenges, in the areas of cybersecurity, privacy, and ethical use. This research project was funded by the Australia-India Cyber and Critical Technology Partnership - Grants Round 2 in 2021 awarded by the Australian Department of Foreign Affairs and Trade. Here we present a brief paper that utilized a two-thronged approach: 1) an extensive literature review of which the outcomes have been summated only; and 2) 46 semi-structured interviews that were conducted between August 2022 and February 2024, including experts from Australia and India from technical and non-technical fields, inclusive of academics, policy advocates, industry, industry associations and government regulators. This paper highlights the challenges in these areas and provides technology and regulatory guidelines in order to be well-prepared to deploy sustainable and socially beneficial 6G networks and services for the next decade, mitigating risks that may arise.
{"title":"Analysis of Techno-Social and Regulatory Challenges in Future 6G Networks and Services","authors":"V. Sridhar;Amrita Mishra;Asheef Iqubbal","doi":"10.1109/TTS.2025.3621860","DOIUrl":"https://doi.org/10.1109/TTS.2025.3621860","url":null,"abstract":"Sixth-generation (6G) mobile networks and services are expected to be standardized by 2030. While they will offer enhanced human-machine and machine-machine connectivity, they will also introduce unique challenges, in the areas of cybersecurity, privacy, and ethical use. This research project was funded by the Australia-India Cyber and Critical Technology Partnership - Grants Round 2 in 2021 awarded by the Australian Department of Foreign Affairs and Trade. Here we present a brief paper that utilized a two-thronged approach: 1) an extensive literature review of which the outcomes have been summated only; and 2) 46 semi-structured interviews that were conducted between August 2022 and February 2024, including experts from Australia and India from technical and non-technical fields, inclusive of academics, policy advocates, industry, industry associations and government regulators. This paper highlights the challenges in these areas and provides technology and regulatory guidelines in order to be well-prepared to deploy sustainable and socially beneficial 6G networks and services for the next decade, mitigating risks that may arise.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 4","pages":"374-376"},"PeriodicalIF":0.0,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145814504","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 : 2025-10-27DOI: 10.1109/TTS.2025.3617543
Jan Przybyszewski;Jiajing Li;Paul Cuffe
This paper is energised by the emergence of powerful generative artificial intelligence tools. We ask: can these tools administer some overdue shock treatment to the neglected domain of electricity grid aesthetics? At a moment when artificial intelligence’s role in mainstream creative professions is hotly debated, we target instead the uncontested design backwater that is the aesthetics of physical energy infrastructure. Can these destablising new tools of visual propaganda upend the negligent status quo within electrical engineering; might they infuse (some artificial approximation of) creativity, beauty and panache into the staid paradigm of “least cost/technically acceptable” grid infrastructure design? Creative professionals seem largely uninterested in the question of how to construct attractive energy infrastructure; how might we deploy generative artificial intelligence against this aesthetic abdication, to (synthetically) imagine power systems beyond the drab hegemony of grey steel? Can flawed artificial imagination goad human designers into applying authentic creativity?
{"title":"Shock Treatment: Can Generative Artificial Intelligence Defibrillate the Dead Aesthetics of Electricity Infrastructure?","authors":"Jan Przybyszewski;Jiajing Li;Paul Cuffe","doi":"10.1109/TTS.2025.3617543","DOIUrl":"https://doi.org/10.1109/TTS.2025.3617543","url":null,"abstract":"This paper is energised by the emergence of powerful generative artificial intelligence tools. We ask: can these tools administer some overdue shock treatment to the neglected domain of electricity grid aesthetics? At a moment when artificial intelligence’s role in mainstream creative professions is hotly debated, we target instead the uncontested design backwater that is the aesthetics of physical energy infrastructure. Can these destablising new tools of visual propaganda upend the negligent status quo within electrical engineering; might they infuse (some artificial approximation of) creativity, beauty and panache into the staid paradigm of <italic>“least cost/technically acceptable”</i> grid infrastructure design? Creative professionals seem largely uninterested in the question of how to construct attractive energy infrastructure; how might we deploy generative artificial intelligence against this aesthetic abdication, to (synthetically) imagine power systems beyond the drab hegemony of grey steel? Can flawed artificial imagination goad human designers into applying authentic creativity?","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 4","pages":"411-420"},"PeriodicalIF":0.0,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145814494","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 : 2025-10-14DOI: 10.1109/TTS.2025.3615624
Le Nam Hai Pham;Ashish Shrestha;Charu Sharma;Francisco Gonzalez-Longatt
Digital twins (DTs) and Cyber-physical systems (CPSs) are forerunner technologies for the digital transformation of power and energy systems (PESs), which directly and indirectly affect human society. These technologies introduce innovative methods for the monitoring, controlling, and optimising of complex infrastructures by facilitating a comprehensive and broader view of physical PESs. DTs and CPSs share some core similarities, both are fundamentally based on data, and both have simulation capabilities. However, they differ in their specific applications and developmental approaches in PESs. Correct understanding of these differences is crucial in order to utilise their individual advantages and tackle their individual challenges. Therefore, this paper provides a systematic review of DTs and CPS, focusing on their distinct capabilities, applications, benefits, and challenges. Further, this paper describes the roles of these technologies in digitalisation of PESs, along with the impacts and considerations necessary for their effective implementation. This paper aims to provide detailed information for researchers, experts, policymakers, and industry stakeholders about the DT and CPS technologies. It will enable them to make proactive decision-making, enhancing the ongoing digital transformation of PESs.
{"title":"Digital Twins and Cyber–Physical Systems Toward the Digitalization of Power and Energy Systems","authors":"Le Nam Hai Pham;Ashish Shrestha;Charu Sharma;Francisco Gonzalez-Longatt","doi":"10.1109/TTS.2025.3615624","DOIUrl":"https://doi.org/10.1109/TTS.2025.3615624","url":null,"abstract":"Digital twins (DTs) and Cyber-physical systems (CPSs) are forerunner technologies for the digital transformation of power and energy systems (PESs), which directly and indirectly affect human society. These technologies introduce innovative methods for the monitoring, controlling, and optimising of complex infrastructures by facilitating a comprehensive and broader view of physical PESs. DTs and CPSs share some core similarities, both are fundamentally based on data, and both have simulation capabilities. However, they differ in their specific applications and developmental approaches in PESs. Correct understanding of these differences is crucial in order to utilise their individual advantages and tackle their individual challenges. Therefore, this paper provides a systematic review of DTs and CPS, focusing on their distinct capabilities, applications, benefits, and challenges. Further, this paper describes the roles of these technologies in digitalisation of PESs, along with the impacts and considerations necessary for their effective implementation. This paper aims to provide detailed information for researchers, experts, policymakers, and industry stakeholders about the DT and CPS technologies. It will enable them to make proactive decision-making, enhancing the ongoing digital transformation of PESs.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 4","pages":"393-410"},"PeriodicalIF":0.0,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11203246","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145814492","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}
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