Ethical Considerations in Emotion Recognition Research
The deployment of emotion-recognition technologies expands across healthcare education and gaming sectors to improve human–computer interaction. These systems examine facial expressions together with vocal tone and physiological signals, which include pupil size and electroencephalogram (EEG), to de...
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| Format: | Article |
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MDPI AG
2025-05-01
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| Series: | Psychology International |
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| Online Access: | https://www.mdpi.com/2813-9844/7/2/43 |
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| author | Darlene Barker Mukesh Kumar Reddy Tippireddy Ali Farhan Bilal Ahmed |
| author_facet | Darlene Barker Mukesh Kumar Reddy Tippireddy Ali Farhan Bilal Ahmed |
| author_sort | Darlene Barker |
| collection | DOAJ |
| description | The deployment of emotion-recognition technologies expands across healthcare education and gaming sectors to improve human–computer interaction. These systems examine facial expressions together with vocal tone and physiological signals, which include pupil size and electroencephalogram (EEG), to detect emotional states and deliver customized responses. The technology provides benefits through accessibility, responsiveness, and adaptability but generates multiple complex ethical issues. The combination of emotional profiling with biased algorithmic interpretations of culturally diverse expressions and affective data collection without meaningful consent presents major ethical concerns. The increased presence of these systems in classrooms, therapy sessions, and personal devices makes the potential for misuse or misinterpretation more critical. The paper integrates findings from literature review and initial emotion-recognition studies to create a conceptual framework that prioritizes data dignity, algorithmic accountability, and user agency and presents a conceptual framework that addresses these risks and includes safeguards for participants’ emotional well-being. The framework introduces structural safeguards which include data minimization, adaptive consent mechanisms, and transparent model logic as a more complete solution than privacy or fairness approaches. The authors present functional recommendations that guide developers to create ethically robust systems that match user principles and regulatory requirements. The development of real-time feedback loops for user awareness should be combined with clear disclosures about data use and participatory design practices. The successful oversight of these systems requires interdisciplinary work between researchers, policymakers, designers, and ethicists. The paper provides practical ethical recommendations for developing affective computing systems that advance the field while maintaining responsible deployment and governance in academic research and industry settings. The findings hold particular importance for high-stakes applications including healthcare, education, and workplace monitoring systems that use emotion-recognition technology. |
| format | Article |
| id | doaj-art-06013d92ef1f43efb2455f59cfcd7def |
| institution | DOAJ |
| issn | 2813-9844 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Psychology International |
| spelling | doaj-art-06013d92ef1f43efb2455f59cfcd7def2025-08-20T03:16:38ZengMDPI AGPsychology International2813-98442025-05-01724310.3390/psycholint7020043Ethical Considerations in Emotion Recognition ResearchDarlene Barker0Mukesh Kumar Reddy Tippireddy1Ali Farhan2Bilal Ahmed3Research and Development, DB Attic Studios, LLC, Bedford, NH 03110, USADepartment of Computer Science, Rivier University, Nashua, NH 03060, USADepartment of Management Information Systems, Keimyung University, Daegu 42601, Republic of KoreaDepartment of Biomedical Engineering, College of Engineering, Keimyung University, Daegu 42601, Republic of KoreaThe deployment of emotion-recognition technologies expands across healthcare education and gaming sectors to improve human–computer interaction. These systems examine facial expressions together with vocal tone and physiological signals, which include pupil size and electroencephalogram (EEG), to detect emotional states and deliver customized responses. The technology provides benefits through accessibility, responsiveness, and adaptability but generates multiple complex ethical issues. The combination of emotional profiling with biased algorithmic interpretations of culturally diverse expressions and affective data collection without meaningful consent presents major ethical concerns. The increased presence of these systems in classrooms, therapy sessions, and personal devices makes the potential for misuse or misinterpretation more critical. The paper integrates findings from literature review and initial emotion-recognition studies to create a conceptual framework that prioritizes data dignity, algorithmic accountability, and user agency and presents a conceptual framework that addresses these risks and includes safeguards for participants’ emotional well-being. The framework introduces structural safeguards which include data minimization, adaptive consent mechanisms, and transparent model logic as a more complete solution than privacy or fairness approaches. The authors present functional recommendations that guide developers to create ethically robust systems that match user principles and regulatory requirements. The development of real-time feedback loops for user awareness should be combined with clear disclosures about data use and participatory design practices. The successful oversight of these systems requires interdisciplinary work between researchers, policymakers, designers, and ethicists. The paper provides practical ethical recommendations for developing affective computing systems that advance the field while maintaining responsible deployment and governance in academic research and industry settings. The findings hold particular importance for high-stakes applications including healthcare, education, and workplace monitoring systems that use emotion-recognition technology.https://www.mdpi.com/2813-9844/7/2/43emotion recognitionresearch ethicsdata autonomyalgorithmic discriminationobserver biasdual-use bias |
| spellingShingle | Darlene Barker Mukesh Kumar Reddy Tippireddy Ali Farhan Bilal Ahmed Ethical Considerations in Emotion Recognition Research Psychology International emotion recognition research ethics data autonomy algorithmic discrimination observer bias dual-use bias |
| title | Ethical Considerations in Emotion Recognition Research |
| title_full | Ethical Considerations in Emotion Recognition Research |
| title_fullStr | Ethical Considerations in Emotion Recognition Research |
| title_full_unstemmed | Ethical Considerations in Emotion Recognition Research |
| title_short | Ethical Considerations in Emotion Recognition Research |
| title_sort | ethical considerations in emotion recognition research |
| topic | emotion recognition research ethics data autonomy algorithmic discrimination observer bias dual-use bias |
| url | https://www.mdpi.com/2813-9844/7/2/43 |
| work_keys_str_mv | AT darlenebarker ethicalconsiderationsinemotionrecognitionresearch AT mukeshkumarreddytippireddy ethicalconsiderationsinemotionrecognitionresearch AT alifarhan ethicalconsiderationsinemotionrecognitionresearch AT bilalahmed ethicalconsiderationsinemotionrecognitionresearch |