Our mission
In an era of accelerating technological changes and exponential growth of data production, addressing the inherent complexities and epistemic ambiguities of Artificial Intelligence (AI) is essential.
Our core mission is to responsibly integrate AI across industry, life sciences, and healthcare, to drive efficiency, minimize waste, and ensure ethical growth, ultimately building trust and increasing stakeholder value.
Explainambiguity Think Tank supports organizations in navigating the challenges of AI adoption by promoting a vision for technology that minimizes regulatory and reputational risk. This approach simultaneously aims to establish a robust foundation for market-leading innovation while fostering health and human dignity.
Our Core Principles
Ethics at the Core – Convinced that technological innovation must be inseparable from responsibility, we advocate for AI systems that uphold human and patient autonomy and rights, safeguard data privacy, and ensure equitable access to technological resources.
Clarity and Transparency – AI must be rendered intelligible to all stakeholders: researchers, executives, healthcare professionals, patients, and public decision-makers alike. Hence the centrality of explainability, which elucidates the rationale behind the determinations and predictions produced by AI models.
Regulatory Compliance – The implementation of AI in industrial and especially healthcare settings requires stringent regulatory standards to guarantee fairness and safety. We work to identify solutions that align technological progress with social dynamics and regulatory mechanisms.
Applied Potential and Tangible Impact – Our research targets the diverse domains in which AI can make a meaningful difference in solving real-world problems. We focus on varied contexts of applicability, including decision-making processes, and driving measurable organizational and societal outcomes across all sectors.
Rigor and Objectivity – Our recommendations are grounded in scientific methodologies, empirical evidence, and critical analysis that eschews simplification. Our investigations are not only rigorous but also transparent and replicable, ready to challenge both human preconceptions and biases, and committed to pursuing knowledge as a public good.
Multidisciplinary Collaboration – The complexity of AI and its responsible deployment in industry and healthcare demands a broad spectrum of overlapping expertise. When working in silos, important nuances are lost. A multidisciplinary approach creates a flywheel effect, multiplying its impact from one use case to the next. Our think tank, therefore, brings together specialists in business, social sciences, ethics, epistemology, economics, computer science, biology, cognitive science, medicine, and biopharmacology.
Epistemic Reliability – AI must operate on the basis of well-established scientific knowledge. This necessitates rigorous validation and oversight by domain experts, both in relation to the data used to train AI models and the outputs they generate.
Virtuous Human–Machine Collaboration – AI must not replace but rather assist humans in high-risk tasks and decision-making processes that affect health and quality of life. We promote the study and deployment of AI systems designed to operate in synergy with professionals, always ensuring that final decisions remain in human hands.
Our Commitment
We are dedicated to:
We are dedicated to:
Developing guidelines and standards for the implementation of interpretable AI systems in healthcare;
Conducting cutting-edge research on explainability methodologies with a specific focus on medical and pharmaceutical applications;
Building bridges of dialogue among technology developers, managers, healthcare professionals, regulators, and end users;
Providing training and educational resources to foster competencies in explainable AI;
Collaborating with regulatory authorities to define frameworks that balance innovation and safety
Our Vision for the Future
We envision a future in which:
We envision a future in which:
Companies implement innovative technological solutions that meet the highest standards of quality and safety;
Patients understand and trust the AI technologies that contribute to their diagnoses and treatments;
Physicians employ clinical decision-support systems with full awareness of their mechanisms and limitations;
Pharmaceutical researchers accelerate scientific discovery through transparent and verifiable AI models;
Regulators possess the conceptual and practical tools needed to adequately assess AI systems.
Join Us
Explainambiguity Think Tank is a space for dialogue and exchange for all who believe in a more effective, transparent, and secure AI—one oriented toward the betterment of the human condition. We especially invite stakeholders in the healthcare and pharmaceutical sectors to join us in advancing AI that serves human health: one that is comprehensible, trustworthy, and ethical. Ambiguity in AI is not an isolated technical issue—it is a collective challenge that demands collective commitment. Only through shared effort can we transform complexity into opportunity, uncertainty into clarity, and promises into concrete realities.
Explainambiguity Think Tank is a space for dialogue and exchange for all who believe in a more effective, transparent, and secure AI—one oriented toward the betterment of the human condition. We especially invite stakeholders in the healthcare and pharmaceutical sectors to join us in advancing AI that serves human health: one that is comprehensible, trustworthy, and ethical. Ambiguity in AI is not an isolated technical issue—it is a collective challenge that demands collective commitment. Only through shared effort can we transform complexity into opportunity, uncertainty into clarity, and promises into concrete realities.