Introduction

genusAI is an artificial intelligence-powered platform designed by genusConnect to provide personalized health engagements and care coordination. Built on the revolutionary principles of carePhysics, genusAI aims to understand each patient holistically across medical, emotional, behavioral, and social dimensions in order to deliver more compassionate, equitable care tailored to individual needs and preferences.

2. Core Principles

• Holistic Care: genusAI collects comprehensive data on patients' circumstances, preferences, challenges, motivations, and goals in order to craft holistic care plans. This may include physical and mental health information, demographics, family/community resources, values, and more, as permitted by patients. The AI uses insights from this data to address the whole person.
• Unbiased Approach: We utilize rigorous debiasing techniques in developing AI models, including diverse training data, bias testing, and mitigation protocols. Ongoing audits help ensure impartiality. We also incorporate human oversight and community feedback loops that flag problematic recommendations for correction.
• Compassionate Interactions: genusAI is designed to converse empathetically, with appropriate tone, language, and sensitivity to each engagement context. Patient surveys provide ongoing input to refine interactions and nurture compassion.
• Care Equity: Our AI delivers engagements tailored to patients' unique needs and backgrounds, without discrimination. We continually assess care equity gaps and refine personalization approaches to overcome barriers faced by disadvantaged groups.

3. Privacy and Data Protection

• Data Collection: genusAI only collects personal health data needed to understand the patient and coordinate care, as permitted by patients to authorized providers. We obtain clear consent on information gathered and its usage.
• Data Usage: Patient data is exclusively used to personalize and improve care engagements. It is not shared, sold, or used for any other purpose. We comply fully with HIPAA and inform patients how data guides care.
• Data Storage and Security: Patient data is encrypted and stored only on HIPAA-compliant secure servers. Access is limited to essential staff under strict confidentiality agreements and data use monitoring.
• User Control: Patients can access their profile and data via their account dashboard at any time. They can request changes, restrictions, or deletion of their information if desired, with full transparency into data practices.

4. Feedback and Human Evaluation

• Feedback Mechanism: Patients are encouraged to share feedback on AI interactions via embedded surveys, reviews, or direct email. This input is systematically analyzed to continuously enhance genusAI's performance and sensitivity.
• Human Oversight: A team of professionals oversees a portion of AI engagements to evaluate quality, accuracy, and appropriateness. Errors prompt immediate diagnosis and corrections, with model retraining to prevent recurrences.

5. Behavioral Science and Ethics

• Behavioral Techniques: Motivational interviewing, goal setting, reinforcement, and other evidence-based techniques are judiciously built into engagements to support behavior change. Implementation follows established clinical guidelines.
• Ethical Use: Behavioral principles are applied transparently and appropriately, empowering patient autonomy. Techniques aim to educate and activate, not manipulate. Ongoing ethics reviews help ensure responsible use.
• Transparency: We openly share details on behavioral science foundations and techniques used by genusAI. Patients understand how the AI personalizes interactions to motivate healthy behaviors.

6. Ensuring Unbiased AI

• Training Data: genusAI models are trained on diverse, balanced datasets representative of global populations. Problematic data is systematically identified and removed.
• Bias Detection: Rigorous testing methodologies help detect algorithmic biases. Detected issues trigger immediate review, root cause analysis, and model adjustments to mitigate bias.
• Continuous Improvement: Our team is devoted to continuously strengthening our debiasing framework, refining data and models to further reduce the potential for algorithmic bias and inequity.

7. Safety and Reliability

• Safety Protocols: Multiple validation checkpoints ensure genusAI responds safely, appropriately, and non-harmfully. Simulations gauge reactions to harmful input. Patient wellbeing is the top priority.
• Error Handling: Rigorous monitoring enables early error identification. All errors prompt urgent human review, diagnosis, bug fixes, and model updates to resolve issues and prevent recurrences.
• Reliability: With robust infrastructure, failover systems, and extensive testing, we ensure consistent 24/7 availability and reliability patients can trust.

8. Conclusion

Our unwavering commitment is to ethical, compassionate AI that enhances healthcare accessibility, quality, and equity. This policy reflects our dedication to honorable principles that put people first in everything we do.

9. Contact Information