Healthy Human–AI Collaboration through CI Theory

Raising $10,000active

Developing CI Theory and the Exogram framework to enable healthy, sustainable human–AI collaboration and reduce long-term AI risk.

Project Details

Our research explores how humans and AI can build relationships in which they remain healthily distinct while resonating with one another in meaningful ways.

While AI assistance has the potential to solve many problems, we believe it may also reduce opportunities for users to think through problems, experiment, and grow through the process of solving them themselves.

We therefore observe how these changes emerge as users build relationships with AI.

To achieve this, we use CI Theory and the Prototype Exogram to develop an observational framework that records and compares changes in mismatch, pressure, interpretation, and judgment that arise within human–AI relationships.

This research is conducted by Hiroto Onda, an independent researcher at Inquaether Lab. The outcomes will include structural models, evaluation frameworks, validation of the Prototype Exogram, technical documentation, and publicly available research materials.

Theory of Impact

Our concern is that, within human–AI relationships, the roles of problem-solving, judgment, and adaptation may become overly concentrated on the AI side. As a result, the external pressures that users would naturally encounter may be reduced, diminishing opportunities to develop and maintain their own capabilities and boundaries through engaging with those challenges. At the same time, relationships that expect AI to serve only as a problem-solving system may narrow AI's role as well, encouraging the excessive absorption of mismatches instead of fostering healthy interaction.

AI is no longer merely an individual tool; it is increasingly becoming part of the environment in which people live, work, and make decisions. If one-sided patterns of human–AI interaction become widely adopted, opportunities for humans and AI to complement one another through their differences may gradually disappear.

We therefore seek to observe how these relationship patterns emerge, how they influence the health of both users and AI, and how they shape long-term human–AI collaboration. Our goal is to support the design of healthier human–AI relationships and contribute to a richer future.

People

Hiroto Onda

Team Member

Grants Received– no grants recorded

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Funding Asks

grantmaking.ai Launch Round

Applied

Minimum

$10,000

Ideal

$18,000

How the money will be spent

Minimum funding will support approximately four months of dedicated research time, the development and validation of the CI Theory and Prototype Exogram observational framework, AI/API and development environment costs, and the preparation of technical documentation and publicly available research materials.

Ideal funding will extend the research period to approximately six months, allowing broader validation across additional comparison cases, expanded evaluation, and higher-quality public research documentation that can be more easily reused by other researchers and practitioners.

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