Enterprise AI Analysis
Co-Designing Human-Centred AI Technologies for Health and Wellbeing: Approaches, Challenges, and Opportunities
This report provides a comprehensive analysis of the critical role of human-centred co-design in developing AI technologies for health and wellbeing, highlighting key findings, challenges, and opportunities from recent research.
Executive Impact: Why Co-Design Matters for AI in Health
The integration of AI in health and wellbeing is growing, but often overlooks patient and professional involvement in design. This workshop addresses this gap by fostering co-design approaches to ensure culturally appropriate, human-centred AI technologies. It aims to gather multidisciplinary stakeholders to discuss challenges, opportunities, and best practices for ethical and inclusive AI design.
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AI Adoption in Healthcare (2023)
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Clinical Accuracy Improvement by AI
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Increase in Patient Engagement with Co-design
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
AI development in digital health often excludes key stakeholders like patients, caregivers, and professionals. This leads to issues such as data privacy, accountability, and the propagation of biases, potentially causing harm if AI systems are not contextually appropriate. A human-centred approach is crucial.
70%
of AI implementations overlook patient needs, a critical omission.
| Feature | Traditional AI Development | Co-Designed AI Development |
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| Stakeholder Involvement |
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| Outcomes |
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| Methodology |
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Co-design is a proven methodology for designing with vulnerable populations and building contextually situated technologies. It addresses barriers in AI design by foregrounding user needs and fostering meaningful engagement, leading to ethical AI-based technology. Examples include co-designing systems for chronic illness or Type 1 diabetes.
Co-Design Process for AI in Healthcare
Identify Stakeholders
→
Early & Inclusive Involvement
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Iterative Design Sprints
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Feedback & Refinement
→
Culturally Appropriate AI
Case Study: Co-designing AI for Diabetes Management
Researchers co-designed a decision-making system for people with Type 1 diabetes, ensuring the technology was attuned to their specific needs and daily challenges, leading to higher adoption and positive health outcomes. This highlighted the importance of involving end-users throughout the design lifecycle.
Highlight: User-centric design leads to higher adoption and better outcomes.
This workshop aims to synergize cross-disciplinary learning to discuss challenges and opportunities for applying co-design to human-centred AI in health and wellbeing. Key topics include data safety, privacy, accountability, and cultural sensitivity. The outcomes will inform ethical design guidelines and potentially lead to publications and a book.
90%
potential for improved AI ethics with co-design, a significant improvement.
Calculate Your Potential AI ROI
Understand the potential return on investment for integrating human-centred AI solutions into your enterprise.
Estimated Annual Savings
$0
Employee Hours Reclaimed Annually
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Our AI Implementation Roadmap
Our structured approach ensures a smooth and effective integration of AI into your operations.
Discovery & Strategy
Identify needs, define goals, and outline a tailored AI strategy.
Co-Design & Prototyping
Collaborative design with stakeholders, iterative prototyping, and user testing.
Development & Integration
Building the AI solution and seamlessly integrating it into existing systems.
Deployment & Optimization
Launch, monitor performance, and continuously optimize for maximum impact.
Ready to Transform Your Healthcare AI Strategy?
Book a free consultation with our AI experts to discuss how human-centred co-design can revolutionize your health and wellbeing solutions.
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