Pub Date : 2025-04-08DOI: 10.1109/TTS.2025.3556355
Christos Bormpotsis;Michael Nanos;Asma Patel
Financial decision-making, a cornerstone of individual prosperity and global economic stability, is hard to comprehend because it is a complex cognitive process concerned with emotional state and behavioural bias. This paper aims to decode the neural mechanisms behind financial behaviour to advance theoretical and empirical progress in neurofinance. Thus, to better capture financial behaviour, this article proposes an innovative framework that bridges neurofinance, neuroscience, and bio-inspired computational models, like the MCoRNNMCD-ANN. Key research areas include the role of neural processes driving decisions, the effect of cognitive preferences on judgment, and the potential of bio-inspired AI models to enhance understanding. The societal implications of this research seek to encourage equitable, stable and informed financial systems while addressing challenges at the intersection of neurofinance and neuroscience-informed AI.
{"title":"A Neuroscience-Informed AI Framework to Decode the Complexities of Neurofinance","authors":"Christos Bormpotsis;Michael Nanos;Asma Patel","doi":"10.1109/TTS.2025.3556355","DOIUrl":"https://doi.org/10.1109/TTS.2025.3556355","url":null,"abstract":"Financial decision-making, a cornerstone of individual prosperity and global economic stability, is hard to comprehend because it is a complex cognitive process concerned with emotional state and behavioural bias. This paper aims to decode the neural mechanisms behind financial behaviour to advance theoretical and empirical progress in neurofinance. Thus, to better capture financial behaviour, this article proposes an innovative framework that bridges neurofinance, neuroscience, and bio-inspired computational models, like the MCoRNNMCD-ANN. Key research areas include the role of neural processes driving decisions, the effect of cognitive preferences on judgment, and the potential of bio-inspired AI models to enhance understanding. The societal implications of this research seek to encourage equitable, stable and informed financial systems while addressing challenges at the intersection of neurofinance and neuroscience-informed AI.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 3","pages":"305-313"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144657524","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 : 2025-03-27DOI: 10.1109/TTS.2025.3549931
Adrian Bermudez-Villalva;Maryam Mehrnezhad;Ehsan Toreini
Online hate speech can harmfully impact individuals and groups, specifically on non-moderated platforms such as 4chan where users can post anonymous content. This work focuses on analysing and measuring the prevalence of online hate on 4chan’s politically incorrect board (/pol/) using state-of-the-art Natural Language Processing (NLP) models, specifically transformer-based models such as RoBERTa and Detoxify. By leveraging these advanced models, we provide an in-depth analysis of hate speech dynamics and quantify the extent of online hate non-moderated platforms. The study advances understanding through multi-class classification of hate speech (racism, sexism, religion, etc.), while also incorporating the classification of toxic content (e.g., identity attacks and threats) and a further topic modelling analysis. The results show that 11.20% of this dataset is identified as containing hate in different categories. These evaluations show that online hate is manifested in various forms, confirming the complicated and volatile nature of detection in the wild.
{"title":"Measuring Online Hate on 4chan Using Pre-Trained Deep Learning Models","authors":"Adrian Bermudez-Villalva;Maryam Mehrnezhad;Ehsan Toreini","doi":"10.1109/TTS.2025.3549931","DOIUrl":"https://doi.org/10.1109/TTS.2025.3549931","url":null,"abstract":"Online hate speech can harmfully impact individuals and groups, specifically on non-moderated platforms such as 4chan where users can post anonymous content. This work focuses on analysing and measuring the prevalence of online hate on 4chan’s politically incorrect board (/pol/) using state-of-the-art Natural Language Processing (NLP) models, specifically transformer-based models such as RoBERTa and Detoxify. By leveraging these advanced models, we provide an in-depth analysis of hate speech dynamics and quantify the extent of online hate non-moderated platforms. The study advances understanding through multi-class classification of hate speech (racism, sexism, religion, etc.), while also incorporating the classification of toxic content (e.g., identity attacks and threats) and a further topic modelling analysis. The results show that 11.20% of this dataset is identified as containing hate in different categories. These evaluations show that online hate is manifested in various forms, confirming the complicated and volatile nature of detection in the wild.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 2","pages":"200-209"},"PeriodicalIF":0.0,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117419","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 : 2025-03-26DOI: 10.1109/TTS.2025.3563812
Evan Selinger;Tom Carroll
The expression of empathy is an important part of effective and humane medical care. Modern medicine faces a significant challenge in this area, at least in part due to the ever-increasing demands on clinicians’ time. When empathic responses to patient emotions are lacking, the quality of care suffers, including a patient’s ability to understand important information and willingness to trust their doctor. This article asks whether AI can help address this challenge. We approach the question by presenting and critically analyzing three novel scenarios that represent fundamentally different approaches, including (1) AI-powered “doctor” avatars directly interacting with patients, (2) AI editors and co-authors helping clinicians find the right words, and (3) AI simulated patients helping to provide communication training. In each case, we identify fundamental AI and medical ethics considerations, including those that warrant further consideration.
{"title":"The Ethics of Empathetic AI in Medicine","authors":"Evan Selinger;Tom Carroll","doi":"10.1109/TTS.2025.3563812","DOIUrl":"https://doi.org/10.1109/TTS.2025.3563812","url":null,"abstract":"The expression of empathy is an important part of effective and humane medical care. Modern medicine faces a significant challenge in this area, at least in part due to the ever-increasing demands on clinicians’ time. When empathic responses to patient emotions are lacking, the quality of care suffers, including a patient’s ability to understand important information and willingness to trust their doctor. This article asks whether AI can help address this challenge. We approach the question by presenting and critically analyzing three novel scenarios that represent fundamentally different approaches, including (1) AI-powered “doctor” avatars directly interacting with patients, (2) AI editors and co-authors helping clinicians find the right words, and (3) AI simulated patients helping to provide communication training. In each case, we identify fundamental AI and medical ethics considerations, including those that warrant further consideration.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 3","pages":"276-282"},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144657523","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 : 2025-03-22DOI: 10.1109/TTS.2025.3558573
Katina Michael;George Roussos;Jordan Richard
{"title":"Senior Editors of IEEE Transactions on Technology and Society Announcement","authors":"Katina Michael;George Roussos;Jordan Richard","doi":"10.1109/TTS.2025.3558573","DOIUrl":"https://doi.org/10.1109/TTS.2025.3558573","url":null,"abstract":"","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 2","pages":"115-119"},"PeriodicalIF":0.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11010828","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117230","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 : 2025-03-22DOI: 10.1109/TTS.2025.3555363
{"title":"IEEE Transactions on Technology and Society Publication Information","authors":"","doi":"10.1109/TTS.2025.3555363","DOIUrl":"https://doi.org/10.1109/TTS.2025.3555363","url":null,"abstract":"","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 2","pages":"C2-C3"},"PeriodicalIF":0.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11010829","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117423","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 : 2025-03-22DOI: 10.1109/TTS.2025.3553212
Paulo F. Ribeiro;Katina Michael
{"title":"Editorial: Pride and Jealousy in Academia","authors":"Paulo F. Ribeiro;Katina Michael","doi":"10.1109/TTS.2025.3553212","DOIUrl":"https://doi.org/10.1109/TTS.2025.3553212","url":null,"abstract":"","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 2","pages":"120-128"},"PeriodicalIF":0.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11010825","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117232","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 : 2025-03-22DOI: 10.1109/TTS.2025.3558350
John Impagliazzo
{"title":"George Roussos and Jordan Schoenherr Appointed New EIC/Co-EIC at IEEE TTS 2026–2028","authors":"John Impagliazzo","doi":"10.1109/TTS.2025.3558350","DOIUrl":"https://doi.org/10.1109/TTS.2025.3558350","url":null,"abstract":"","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 2","pages":"113-114"},"PeriodicalIF":0.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11010827","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117418","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 : 2025-03-20DOI: 10.1109/TTS.2025.3567143
Lucas Wiese;Sonali Subbu Rathinam;Matthias Oschinski;Bryan DeWitt;Daniel S. Schiff
Demand for an AI-literate workforce has surged, in large part to counter a growing skills gap. Meanwhile, expertise in ethical and governance dimensions of AI is increasingly deemed crucial to handle various organizational, regulatory, and social concerns. However, the focus of AI literacy efforts to date has been primarily technical. This paper helps close this gap by providing the first large-scale analysis of AI ethics and governance skills sought by employers in the labor market. Drawing on more than four million job postings for AI-related professions over the years 2018-2023, we provide an empirically-grounded characterization of AI ethics and governance competencies and perform associated descriptive analyses. We find that professionals with AI ethics and governance competencies are requested by employers to hold diverse skill sets, covering technical, managerial, and regulatory domains, though the two professions remain distinct. Moreover, the demand for expertise in these domains has grown rapidly, both in absolute terms and as a proportion of AI-related job postings. More than 100,000 professionals with expertise in AI ethics and governance are now requested annually, with the concentration highest in the financial and information sectors. These findings can help individuals, employers, and institutions of higher education better design job requirements, educational programs, and individual learning pathways, closing the career competency gap in AI ethics and governance.
{"title":"AI Ethics and Governance in the Job Market: Trends, Skills, and Sectoral Demand","authors":"Lucas Wiese;Sonali Subbu Rathinam;Matthias Oschinski;Bryan DeWitt;Daniel S. Schiff","doi":"10.1109/TTS.2025.3567143","DOIUrl":"https://doi.org/10.1109/TTS.2025.3567143","url":null,"abstract":"Demand for an AI-literate workforce has surged, in large part to counter a growing skills gap. Meanwhile, expertise in ethical and governance dimensions of AI is increasingly deemed crucial to handle various organizational, regulatory, and social concerns. However, the focus of AI literacy efforts to date has been primarily technical. This paper helps close this gap by providing the first large-scale analysis of AI ethics and governance skills sought by employers in the labor market. Drawing on more than four million job postings for AI-related professions over the years 2018-2023, we provide an empirically-grounded characterization of AI ethics and governance competencies and perform associated descriptive analyses. We find that professionals with AI ethics and governance competencies are requested by employers to hold diverse skill sets, covering technical, managerial, and regulatory domains, though the two professions remain distinct. Moreover, the demand for expertise in these domains has grown rapidly, both in absolute terms and as a proportion of AI-related job postings. More than 100,000 professionals with expertise in AI ethics and governance are now requested annually, with the concentration highest in the financial and information sectors. These findings can help individuals, employers, and institutions of higher education better design job requirements, educational programs, and individual learning pathways, closing the career competency gap in AI ethics and governance.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 4","pages":"458-470"},"PeriodicalIF":0.0,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145814498","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 : 2025-03-05DOI: 10.1109/TTS.2025.3564840
Marta Beltrán
Understanding and regulating addictive patterns is essential for protecting users’ rights and freedoms in the digital age. A strong framework is necessary to identify these patterns, ensuring that digital providers operate in ways that respect users’ privacy, autonomy, and well-being. This paper aims to contribute to this effort by developing the FoSIP framework, which defines addictive design strategies, classifies them into a new three-level taxonomy, and proposes guidelines for identifying their presence in user interfaces. This framework will assist providers in designing ethical products and help users recognize these addictive patterns. Additionally, it will support supervisory, oversight, and enforcement authorities in monitoring compliance with regulations such as the General Data Protection Regulation or the Digital Services Act. By addressing the challenges posed by addictive patterns, the FoSIP framework promotes a safer, fairer, and more transparent digital environment.
{"title":"Defining, Classifying and Identifying Addictive Patterns in Digital Products","authors":"Marta Beltrán","doi":"10.1109/TTS.2025.3564840","DOIUrl":"https://doi.org/10.1109/TTS.2025.3564840","url":null,"abstract":"Understanding and regulating addictive patterns is essential for protecting users’ rights and freedoms in the digital age. A strong framework is necessary to identify these patterns, ensuring that digital providers operate in ways that respect users’ privacy, autonomy, and well-being. This paper aims to contribute to this effort by developing the FoSIP framework, which defines addictive design strategies, classifies them into a new three-level taxonomy, and proposes guidelines for identifying their presence in user interfaces. This framework will assist providers in designing ethical products and help users recognize these addictive patterns. Additionally, it will support supervisory, oversight, and enforcement authorities in monitoring compliance with regulations such as the General Data Protection Regulation or the Digital Services Act. By addressing the challenges posed by addictive patterns, the FoSIP framework promotes a safer, fairer, and more transparent digital environment.","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 3","pages":"314-323"},"PeriodicalIF":0.0,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10985886","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144657425","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 : 2025-02-28DOI: 10.1109/TTS.2024.3477828
David Kolevski;Katina Michael;Mark Freeman
{"title":"In This Special Issue: Data Breaches in the Cloud—Business Security and Risk Management","authors":"David Kolevski;Katina Michael;Mark Freeman","doi":"10.1109/TTS.2024.3477828","DOIUrl":"https://doi.org/10.1109/TTS.2024.3477828","url":null,"abstract":"","PeriodicalId":73324,"journal":{"name":"IEEE transactions on technology and society","volume":"6 1","pages":"2-14"},"PeriodicalIF":0.0,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10908511","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521567","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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