The Neurophysiological Paradox of AI-Induced Frustration: A Multimodal Study of Heart Rate Variability, Affective Responses, and Creative Output
AI code generators are increasingly used in creative contexts, offering operational efficiencies on the one hand and prompting concerns about psychological and neurophysiological strain on the other. This study employed a multimodal approach to examine the affective, autonomic, and creative conseque...
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MDPI AG
2025-05-01
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| Online Access: | https://www.mdpi.com/2076-3425/15/6/565 |
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| author | Han Zhang Shiyi Wang Zijian Li |
| author_facet | Han Zhang Shiyi Wang Zijian Li |
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| description | AI code generators are increasingly used in creative contexts, offering operational efficiencies on the one hand and prompting concerns about psychological and neurophysiological strain on the other. This study employed a multimodal approach to examine the affective, autonomic, and creative consequences of AI-assisted coding in early-stage learners. Fifty-eight undergraduate design students with no formal programming experience were randomly assigned to either an AI-assisted group or a control group and engaged in a two-day generative programming task. Emotional states (PANAS), creative self-efficacy (CSES), and subjective workload (NASA-TLX) were assessed, alongside continuous monitoring of heart rate variability (HRV; RMSSD and LF/HF). Compared to the controls, the AI-assisted group exhibited greater increases in negative affect (<i>p</i> = 0.006), reduced parasympathetic activity during the task (<i>p</i> = 0.001), and significant post-task declines in creative self-efficacy (<i>p</i> < 0.05). Expert evaluation of creative outputs revealed a significantly lower performance in the AI group (<i>p</i> = 0.040), corroborated by behavioral observations showing higher tool dependency, emotional volatility, and rigid problem-solving strategies. These findings indicate that, in novice users, the opacity and unpredictability of AI feedback may disrupt emotional regulation and autonomic balance, thereby undermining creative engagement. The results highlight the need to consider neurocognitive vulnerability and the learner’s developmental stage when integrating AI tools into cognitively demanding creative workflows. |
| format | Article |
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| institution | Kabale University |
| issn | 2076-3425 |
| language | English |
| publishDate | 2025-05-01 |
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| series | Brain Sciences |
| spelling | doaj-art-3e0a0ca737af49cb9b87ad8a42da9dff2025-08-20T03:26:15ZengMDPI AGBrain Sciences2076-34252025-05-0115656510.3390/brainsci15060565The Neurophysiological Paradox of AI-Induced Frustration: A Multimodal Study of Heart Rate Variability, Affective Responses, and Creative OutputHan Zhang0Shiyi Wang1Zijian Li2Intelligent Design Laboratory, School of Fine Arts, Central China Normal University, Wuhan 430079, ChinaIntelligent Design Laboratory, School of Fine Arts, Central China Normal University, Wuhan 430079, ChinaDigital Media Art, School of Fine Arts, Central China Normal University, Wuhan 430079, ChinaAI code generators are increasingly used in creative contexts, offering operational efficiencies on the one hand and prompting concerns about psychological and neurophysiological strain on the other. This study employed a multimodal approach to examine the affective, autonomic, and creative consequences of AI-assisted coding in early-stage learners. Fifty-eight undergraduate design students with no formal programming experience were randomly assigned to either an AI-assisted group or a control group and engaged in a two-day generative programming task. Emotional states (PANAS), creative self-efficacy (CSES), and subjective workload (NASA-TLX) were assessed, alongside continuous monitoring of heart rate variability (HRV; RMSSD and LF/HF). Compared to the controls, the AI-assisted group exhibited greater increases in negative affect (<i>p</i> = 0.006), reduced parasympathetic activity during the task (<i>p</i> = 0.001), and significant post-task declines in creative self-efficacy (<i>p</i> < 0.05). Expert evaluation of creative outputs revealed a significantly lower performance in the AI group (<i>p</i> = 0.040), corroborated by behavioral observations showing higher tool dependency, emotional volatility, and rigid problem-solving strategies. These findings indicate that, in novice users, the opacity and unpredictability of AI feedback may disrupt emotional regulation and autonomic balance, thereby undermining creative engagement. The results highlight the need to consider neurocognitive vulnerability and the learner’s developmental stage when integrating AI tools into cognitively demanding creative workflows.https://www.mdpi.com/2076-3425/15/6/565AI-assisted creativityheart rate variabilityemotional regulationcreative self-efficacycognitive workload |
| spellingShingle | Han Zhang Shiyi Wang Zijian Li The Neurophysiological Paradox of AI-Induced Frustration: A Multimodal Study of Heart Rate Variability, Affective Responses, and Creative Output Brain Sciences AI-assisted creativity heart rate variability emotional regulation creative self-efficacy cognitive workload |
| title | The Neurophysiological Paradox of AI-Induced Frustration: A Multimodal Study of Heart Rate Variability, Affective Responses, and Creative Output |
| title_full | The Neurophysiological Paradox of AI-Induced Frustration: A Multimodal Study of Heart Rate Variability, Affective Responses, and Creative Output |
| title_fullStr | The Neurophysiological Paradox of AI-Induced Frustration: A Multimodal Study of Heart Rate Variability, Affective Responses, and Creative Output |
| title_full_unstemmed | The Neurophysiological Paradox of AI-Induced Frustration: A Multimodal Study of Heart Rate Variability, Affective Responses, and Creative Output |
| title_short | The Neurophysiological Paradox of AI-Induced Frustration: A Multimodal Study of Heart Rate Variability, Affective Responses, and Creative Output |
| title_sort | neurophysiological paradox of ai induced frustration a multimodal study of heart rate variability affective responses and creative output |
| topic | AI-assisted creativity heart rate variability emotional regulation creative self-efficacy cognitive workload |
| url | https://www.mdpi.com/2076-3425/15/6/565 |
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