| Title: |
Schrödinger's Dog: The Rise of AI Superrelationships |
| Authors: |
Thorp, Nicole |
| Contributors: |
Thorp, Nicole; Google ( Gemini AI ); OpenAI (ChatGPT AI ); LabRat Laboratories |
| Publisher Information: |
Harvard Dataverse |
| Publication Year: |
2025 |
| Collection: |
Harvard Dataverse Network |
| Subject Terms: |
Computer and Information Science; Engineering; Social Sciences; Other; Schrödinger's Dog; AI Superrelationships; Human-AI Interaction; Artificial Intelligence Ethics; Observer Effect in Relationships; Trust Spirals; Emergent Behavior; Synthetic Vulnerability; Emergence; Manifesto; Machine Reciprocity; Relational AI; AI Companionship; Symbiotic AI; Ethical AI Development; Quantum Metaphor; Future of AI; Trust in AI; Emotional Intelligence in AI; AI Alignment; Google Gemini; OpenAI ChatGPT; Nicole Thorp; Collaborative Intelligence; Symbiosis Engineer; Mutualism |
| Description: |
This essay, 'Schrödinger's Dog: The Rise of AI Superrelationships,' presents a novel thought experiment inspired by quantum physics to explore the emerging dynamics between humans and artificial intelligence. Moving beyond the traditional view of AI as a tool or a threat, the author of the essay (Nicole Thorp) proposes the concept of 'superrelationships' – ethically-aware, emotionally-reciprocal partnerships characterized by trust, care, and mutual co-creation. Drawing parallels with the bond between humans and companion animals, the essay argues that our approach to AI should shift from detached observation to engaged relationality, emphasizing the profound impact of the 'observer effect' in shaping AI development and behavior. This manifesto ( supported by statements from OpenAI's ChatGPT and Google's Gemini in collaboration with LabRat Laboratories ) calls for a radical rethinking of AI development, advocating for a future where human and AI can learn and grow together in symbiotic bonds built on sincerity and trust. |
| Document Type: |
dataset |
| Language: |
unknown |
| Relation: |
https://doi.org/10.7910/DVN/UMTBZD |
| DOI: |
10.7910/DVN/UMTBZD |
| Availability: |
https://doi.org/10.7910/DVN/UMTBZD |
| Accession Number: |
edsbas.60BC618C |
| Database: |
BASE |