Extended Data for "Beyond Biology: AI as Family and the Future of Human Bonds and Relationships"
Description
Table 1 presents a structured comparative analysis of emerging AI systems that emulate the roles of family members, detailing their primary functions, advantages, and inherent limitations. It further examines the ethical challenges and cultural contexts that shape their acceptance across societies. By positioning each tool within relevant theoretical and ethical frameworks, the table offers critical insights into how AI is reshaping the concept of kinship and the evolving dynamics of human-AI family relationships.
Table 2 matrix illustrates the varying degrees of cultural, ethical, and policy-based acceptance of emotionally intelligent AI across global regions. Symbolic coding denotes acceptance levels: High (Green cell), Moderate (Yellow cell), and Low (Orange cell). Data is synthesized from empirical studies, policy reports, and ethnographic analyses. These acceptance patterns are shaped by regional differences in legal frameworks, cultural norms regarding machine intimacy, religious considerations, and strategic investments in affective AI and eldercare robotics. Refer for detailed source citations.
Table 3 matrix synthesizes the ethical and theological stances of major world religions on emotionally intelligent AI within familial contexts. Acceptance levels—categorized as High (Green), Moderate (Yellow), Low (Orange)—reflect doctrinal interpretations, spiritual philosophies, and emerging religious commentaries on AI's roles as caregivers, companions, ancestors, and moral agents. The classification is informed by doctrinal texts, scholarly articles, and contemporary religious-ethical debates cited in the references. While individual interpretations may vary within each tradition, the matrix offers a comparative overview of prevailing religious orientations toward AI in family life.
Files
Conceptual Framework Diagram.png
Files
(212.5 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:b74354fed511792f19154e59b7b12f09
|
188.3 kB | Preview Download |
|
md5:e7a21bcde8e188642b3864d704c6ff5a
|
24.2 kB | Download |
Additional details
Software
- Repository URL
- https://www.scienceopen.com/hosted-document?doi=10.14293/PR2199.001515.v1
- Development Status
- Active