From Biometrics to Bioethics: Governing Emotional Data in Digital Health

This project aims to critically examine how emotion biosensing technologies are integrated into healthcare and the ethical, legal, and governance challenges they present. The key objectives include:

1. Mapping the Regulatory Landscape: a) analyze how regulatory bodies such as the EU AI Act, WHO, and FDA approach emotion AI in medical applications.
   b) Identify regulatory gaps and inconsistencies in how affective computing is governed across different regions. c) Examine the role of corporations, healthcare institutions, and policymakers in shaping the governance of emotional data.
    
2. Exploring Ethical and Societal Implications: a) Investigate how emotion biosensing reconfigures patient rights, consent, and data privacy in healthcare. b) Analyze bias and discrimination risks in biometric emotion recognition systems, particularly in mental health applications. c) Examine how patients and healthcare providers interpret and respond to emotion AI technologies, exploring their impact on medical decision-making.
    
3. Speculating Future Governance Models: a) Develop speculative design scenarios that envision alternative ethical frameworks for governing emotion biosensing in medicine. b) Organize workshops with scholars, policymakers, and designers to critically reflect on how emotion AI should be regulated in healthcare.
   c) Produce a policy white paper and academic publication outlining recommendations for responsible governance of affective computing in medicine.
   These objectives will contribute to broader discussions on AI governance, bioethics, and digital health policy, ensuring that emotion biosensing technologies are developed and deployed in ways that prioritize human rights, patient well-being, and ethical accountability.