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Exploring uncertainty's impact on financial markets and economic policy design, focusing on long-term growth limitations and climate change implications through decision theory and uncertainty quantification methods.
Explores reduced-form market models with financial assets and life insurance liabilities under model uncertainty, focusing on mortality intensities and longevity bonds. Discusses arbitrage-free pricing and contingent claims in this framework.
Experts discuss AI's role in UK society, addressing climate change, resilience, mental health, diversity, and skills development while exploring strategies to build public trust and make actionable impact.
Exploring UK's role in responsible AI innovation, covering safety, ethics, governance, and practical applications like tactile robotics. Insights from experts on fostering trust and creating impactful AI solutions.
Exploring AI's limited impact on pandemic response, challenges in health data science, and lessons from COVID-19. Experts discuss AI strengths, weaknesses, and future potential in healthcare.
Explore digital human rights challenges in AI era: privacy, free speech, security. Discuss threats, policies, and regulatory frameworks for protecting individual rights in the digital age.
Explore real-world AI applications in healthcare through startup experiences and investor insights. Gain valuable perspectives on deploying academic research in the medical market.
Explore innovative methods for monitoring and predicting climate change, from Antarctic sea ice to forest ecosystems, with leading environmental scientists using AI and data science.
Experts discuss responsible AI, diversity in data science, and creating fair, inclusive AI systems. Explore challenges and opportunities in algorithmic fairness, team diversity, and equitable AI access across society.
Explore trustworthy communication of COVID-19 statistics and risks, focusing on official releases, background actuarial risk, and lessons for effective public understanding during crises.
Exploring the role of data science in policy-making during COVID-19, emphasizing open data methods, interdisciplinary collaboration, and the challenges of deploying AI expertise to address real-world problems.
Explore deep learning techniques for analyzing mobile network traffic, enhancing urban data interpretation and smart city development.
Explore urban modeling scenarios using AI, focusing on smart cities, deep learning for mobility data, and building resilient systems for future urban challenges.
Explore causal inference in AI prediction, enhancing algorithms with 'what if' capabilities for decision-making and fairness. Learn about counterfactual prediction challenges and methodologies.
Exploring causal inference in AI prediction algorithms for decision-making, focusing on 'what if' scenarios in healthcare and insurance, with applications to COVID-19 pandemic response.
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