Global Initiatives

GHDIF supports collaborative initiatives that explore how artificial intelligence can strengthen public health systems and help societies respond to emerging challenges, including climate-related health risks.

Through the IEEE Standards Association, we initiated and lead a multidisciplinary programme that brings together experts from healthcare, technology, research, and policy to explore how generative AI can support more inclusive and resilient health systems.

This work includes convening international dialogues, contributing to the development of open standards that support responsible AI and health data governance, and advancing practical approaches to implementing emerging regulatory frameworks.

As part of this effort, we are also exploring how AI models can integrate environmental, geospatial, and health data to better understand how climate change affects disease patterns and health outcomes. These approaches aim to improve early detection of risks, strengthen public health preparedness, and support more resilient health systems.

We support the development of open industry standards that bring together society and technology. These frameworks help ensure that AI and digital health systems are designed with human needs, safety, ethics, and real-world healthcare practice in mind. By connecting innovators, clinicians, policymakers, and communities, we promote governance approaches that allow innovation to advance while protecting public trust and societal benefit.

Working with partners including the IEEE Standards Association, European institutions, and the World Health Organization, we contribute to initiatives that support the practical implementation of emerging AI governance frameworks, including the EU AI Act and related regulatory developments affecting health innovation.

Through these collaborations we help translate regulatory principles into practical action by:

• supporting standards development and responsible AI guidance,
• facilitating dialogue between innovators, clinicians, regulators, and policymakers,
• exploring new approaches to validating AI systems in real-world healthcare environments,
• contributing to collaborative initiatives that promote ethical, safe, and socially beneficial innovation.
   

Our aim is to help ensure that new regulatory frameworks not only manage risks but also enable responsible innovation that improves healthcare outcomes and strengthens trust in digital technologies.

GHDIF contributes to public policy discussions on the responsible use of artificial intelligence and digital technologies in healthcare. Through our participation in the IEEE European Public Policy Committee (EPPC), the IEEE Global Policy Caucus, and volunteering with WHO working groups and knowledge communities on artificial intelligence and digital technologies, we collaborate with experts from across sectors to develop policy recommendations that support equitable and trustworthy innovation.

Our recent work focuses on advancing equitable innovation in digital health and AI. We have provided guidance on safely and fairly advancing AI in precision medicine and preventive care, improving health outcomes and supporting the healthcare workforce. 

These efforts build on European initiatives such as the European Health Data Space (EHDS) regulation, the Medical Device Regulation (MDR) and the AI Act.

We also contribute to policy discussions on the implementation and scaling of collaborative regulatory sandboxes—environments where innovators, clinicians, and regulators can safely test new digital health technologies and data practices. 

In particular, we focus on evidence sandboxes, which help improve the pathways for AI model training, validation, and adaptation in real-world settings. These approaches enable responsible experimentation while maintaining public trust.

Through these efforts, GHDIF works with international partners to align policy, standards, and innovation, helping ensure that emerging technologies support broad industry participation in building equitable, anticipatory, and resilient healthcare systems.

We are developing several technological innovations to advance our mission, with DorothAI™ at the core. 

This next-generation platform brings artificial intelligence safely into healthcare by leveraging the idea that AI has its own digital DNA.

DorothAI™ is designed for non-AI experts, providing a governed core architecture that allows AI systems to learn, adapt, and grow safely within clinical environments under expert supervision.

Acting as an AI factory, DorothAI™ offers a sandboxed, rapid-prototyping environment that produces micro-models™ powered by Safe Language Models™ at the workflow interface. 

Startups, scale-ups, and AI-powered companies can use it to develop patient-safety AI faster, while systematically de-risking clinical deployment and regulatory pathways.

The AI for Public Benefit Challenge empowers young innovators and multidisciplinary teams to tackle real-world healthcare and societal challenges using artificial intelligence. Participants collaborate with clinicians, policymakers, and community organisations to design solutions that are ethically responsible, evidence-informed, and scalable.

Through a combination of challenge-based learning, prototyping, and iterative testing, teams develop tangible outputs such as AI-powered tools, digital platforms, and policy recommendations. 

Online guidance from regulators and clinical experts using the DorothAI™ platform ensures solutions are safe, transparent, and aligned with emerging standards.

By connecting talent, technology, and real-world impact, the Challenge demonstrates how AI can advance equitable, anticipatory, and resilient healthcare systems worldwide.

ASCEND (Adaptive Safety & Clinical Evaluation Network) provides the regulatory and translational expertise that ensures AI innovations emerging from DorothAI™ and the AI Factory are safe, compliant, and scalable. It supports teams in:

Clinical and regulatory guidance: Aligning AI prototypes with GDPR, MDR, MHRA, and other standards/regulation and preparing evidence packages for clinical evaluation.
 

Structured evidence generation: Advising on trial design, real-world data collection, and validation, supporting teams in the Trusted Evidence Ecosystem to generate investment- and regulatory-ready evidence.
 

Translational acceleration: Bridging academic research and venture acceleration to make prototypes clinically viable, scalable, and ready for deployment.
 

Together, ASCEND and DorothAI™ form a safe and structured environment for innovation, while the AI for Public Good Challenge introduces new talent and ideas into this ecosystem.