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Confronting the Ethics of A.I. 2007 : 2nd Annual International Interdisciplinary Conference on Confronting the Ethics of Artificial Intelligence

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Link: https://www.scranton.edu/academics/wml/ai/index.shtml
 
When Apr 29, 2027 - May 1, 2027
Where Scranton, Pennsylvania, USA
Submission Deadline Nov 6, 2026
Notification Due Dec 18, 2026
Final Version Due Apr 29, 2027
Categories    artificial intelligence   ethics   interdisciplinary
 

Call For Papers

We invite submissions that engage with the ethics of artificial intelligence in both specific and general applications. Topics may include, but are not limited to:

Arts & Humanities: AI in creativity, authorship, performance, and cultural identity.
Business: Automation, labor ethics, and corporate responsibility.
Education: AI in teaching, learning, and research integrity; utilizing AI for student success initiatives and learning accommodations; ethical applications and questions related to AI in scholarly activity; AI in K-12 education.
Environmental Impact: AI and sustainability, climate modeling, and AI resource consumption.
Healthcare & Medicine: Projection models for patient disease development; treatment individuation; individualized medicine; bias in treatment.
Law & Policy: Privacy and data usage; the legitimacy of AI in government.
Library & Information Science: AI and the new digital divide; algorithmic bias; AI accuracy, mis- and dis-information.
Philosophy: AI as moral agents; AI's effect on human autonomy and decision making; human-AI interfaces and the locus of moral responsibility.
Science: AI fabrication of scientific data or references; legitimacy of sources for AI training; drug discovery; intellectual property of data from AI discoveries.
Theology: AI in moral theology and bioethics; AI applications in healthcare; theological responses to AI development, including those offered in light of Antiqua et nova (2025) and Magnifica Humanitas (2026).
Social Justice & Equity: Accessibility, bias, and discrimination in AI systems.
Social Sciences: AI as a research tool for data analysis and methodology; AI systems as social entities and their behavioral impacts; algorithmic bias in social research; AI's effects on human social structures and interactions.

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