Discovery

Thematic series of technical talks on AI/Machine learning.

The AI for Good Discovery Series digs deeper into thematic areas transformed by AI/ML and addresses key challenges in the field. Structured into 14 Discovery streams, each one-hour Discovery episode features a researcher presenting their latest findings, offering deep insights into cutting-edge advancements and real-world applications of AI/ML.

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OnlineGOAL 12GOAL 4+1
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Future robots need to be robust and adaptable, and new...
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AI for Earth and Sustainability Science

AI and Climate Science

AI and Manufacturing

GeoAI

ML5G

Trustworthy AI

AI and Robotics

AI and Health

AI for Biodiversity

AI and Finance

AI and Work

Open Source AI for Digital Public Goods

AI in Humanitarian Action

From Molecules to Models

AI for Earth and Sustainability Science

The AI for Earth and Sustainability Science webinar series highlights seminal and recent progress in AI-enabled modelling and understanding of the Earth system from local to global scale and AI-science based diagnosis, prediction and remedy of environmental crises. Interdisciplinary researchers from academia, industry, UN and government agencies as well as NGOs will talk about tackling systemic real-world challenges with AI, including disaster risk reduction and preparedness, environmental degradation, climate change, societal impacts and dynamics, and the sustainable and responsible use of natural resources such as water and energy.

The webinar series is curated by the ELLIS Unit Jena and the ELLIS program “Machine Learning for Earth and Climate Sciences”. ELLIS is the European Laboratory for Learning and Intelligent Systems.”

Enjoy and learn how to make our planet a better place and our future more sustainable through AI!

Curators

Director & Professor
,
Max Planck Institute for Biogeochemistry
Markus Reichstein is Director at the Max-Planck-Institute for Biogeochemistry, and Professor for Global Ecology at the University of Jena. He is founding co-director of the ELLIS (<a href="http://www.ellis.eu">www.ellis.eu</a>) program “Machine Learning for Earth and Climate Science” and the recently established ELLIS Unit Jena (<a href="http://www.ellis-jena.ai">www.ellis-jena.ai</a>) within the Michael-Stifel-Center Jena for Data-driven and Simulation Science Jena. and member of the German National Committee Future Earth for Sustainability research. He has been serving as lead author for the IPCC, as member of the German Committee Future Earth on Sustainability Research, and the Thuringian Panel on Climate for advising the state on climate protection and adaptation. Markus’s main research interests revolve around the response and feedback of ecosystems (vegetation and soils) to climatic variability with an Earth system perspective. Of specific interest is the interplay of climate extremes with ecosystem and societal resilience. He is addressing these topics with a combination of artificial intelligence and classical modelling approaches to exploit the wealth of experimental, ground- and satellite-based Earth observations together with theoretical knowledge. Recent awards for his research include the Piers J. Sellers Mid-Career Award by the American Geophysical Union (2018), and the Gottfried Wilhelm Leibniz Preis by the German Science Foundation (2020). He is also Principal Investigator in the European Research Council Synergy Grant USMILE dedicated to the development and application of machine learning for a better Earth system understanding and modelling. Furthermore, Markus is chairing the Global Research Program and Knowledge-Action Network “Emergent Risks and Extreme Events – Reducing Disaster Risks under Environmental Change” (<a href="http://www.risk-kan.org">www.risk-kan.org</a>). Markus is excited about linking system thinking with data-driven science and artificial intelligence for understanding complex systems, such as the climate-environmental-societal system and believes that such approaches can help societies become more resilient and sustainable.
Senior Researcher
,
Universitat de València
<p class="CDt4Ke zfr3Q" dir="ltr">Maria is currently a <em>Ramón y Cajal</em> Senior Researcher at the <span class=" aw5Odc"><a class="XqQF9c" href="http://www.google.com/url?q=http%3A%2F%2Fisp.uv.es&sa=D&sntz=1&usg=AOvVaw2YiCbIliB2mb9YEEvBkfTE" target="_blank" rel="noopener">Image & Signal Processing group (ISP)</a></span>, <em>Universitat de València</em>, in <em>València</em>, Spain. Her research interests include microwave remote sensing, estimation of soil moisture and vegetation biogeophysical parameters, and development of multisensor techniques for enhanced retrievals with focus on agriculture, forestry, wildfire prediction, extreme detection, and climate studies.</p> <p class="CDt4Ke zfr3Q" dir="ltr">She is deeply involved in research projects that use machine learning to exploit Earth Observation data in Earth and Climate Sciences. She is particularly interested in the development of data-driven models that respect physical laws, in causal inference and in learning and explaining feature representations. She is IEEE senior member (2019) and ELLIS Fellow (2021).</p>
Professor in Electrical Engineering
,
Universitat de València
Gustau Camps-Valls (born 1972 in <a href="https://en.wikipedia.org/wiki/Valencia">València</a>) is a Physicist and Full Professor in Electrical Engineering in the <a href="https://en.wikipedia.org/wiki/University_of_Valencia">Universitat de València</a>, Spain, where lectures on machine learning, remote sensing and signal processing. He is the Head of the <a href="http://isp.uv.es/">Image and Signal Processing (ISP) </a>group, an interdisciplinary group of 40 researchers working at the intersection of AI for Earth and Climate sciences. Prof. Camps-Valls published over 250+ peer-reviewed international journal papers, 350+ international conference papers, 25 book chapters, and 5 international books on remote sensing, image processing and machine learning. He has an h-index of 78 with 29000+ citations in <a href="https://scholar.google.com/citations?user=6mgnauMAAAAJ">Google Scholar</a>. He was listed as a Highly Cited Researcher in 2011, 2020 and 2021; currently has 13 «Highly Cited Papers» and 1 «Hot Paper», Thomson Reuters ScienceWatch identified his activities as a <a href="http://archive.sciencewatch.com/dr/fmf/2011/11mayfmf/11mayfmfCamp/">Fast Moving Front research (2011)</a> and the most-cited paper in the area of Engineering in 2011, received the <a href="https://scholar.google.com/citations?view_op=list_classic_articles&hl=en&by=2006&vq=eng_remotesensing">Google Classic paper award (2019)</a>, and <a href="https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000918">Stanford Metrics</a> includes him in the top 2% most cited researchers of 2017-2020. He publishes in both technical and scientific journals, from IEEE and PLOS One to Nature, Nature Communications, Science Advances, and PNAS. He has been Program Committee member of international conferences (IEEE, SPIE, EGU, AGU), and Technical Program Chair at <a href="https://www.igarss2018.org/">IEEE IGARSS 2018</a> (2400+ attendees) and general at AISTATS 2022. He served in technical committees of the IEEE GRSS & IEEE SPS, as Associate Editor of 5 top IEEE journals, and in the prestigious <a href="https://www.grss-ieee.org/community/distinguished-lecturers/">IEEE Distinguished Lecturer</a> program of the GRSS (2017-2019) to promote «AI in Earth sciences» globally. He has given 100+ talks, keynote speaker in 10+ conferences, and (co)advised 10+ PhD theses. He coordinated/participated in 60+ research projects, involving industry and academia at national and European levels. He assisted the aerospace industry in Advisory Boards; Fellow Consultant of the <a href="https://blogs.esa.int/philab/">ESA PhiLab</a> (2019) and member of the EUMETSAT MTG-IRS Science Team. He is compromised with open source/access in Science, and is habitual panel evaluator for H2020 (ERC, FET), NSF, China and Swiss Science Foundations. He coordinates the ‘Machine Learning for Earth and Climate Sciences’ research program of <a href="https://ellis.eu/programs/machine-learning-for-earth-and-climate-sciences">ELLIS</a>, the top network of excellence on AI in Europe. He was elevated to <a href="https://www.uv.es/gcamps/cv.html">IEEE Fellow member (2018)</a> in two Societies (Geosciences and Signal Processing) and to ELLIS Fellow (2019). Prof. Camps-Valls is the only researcher receiving two European Research Council (ERC) grants in two different areas: an <a href="https://cordis.europa.eu/project/id/647423">ERC Consolidator (2015, Computer Science)</a> and <a href="https://cordis.europa.eu/project/id/855187">ERC Synergy (2019, Physical Sciences)</a> grants to advance AI for Earth and Climate Sciences. In 2021 he became a Member of the ESSC panel part of the European Science Foundation (ESF), and in 2022 was elevated to Fellow of the European Academy of Sciences (EurASc), Fellow of the Academia Europeae (AE), and Fellow of Asia-Pacific Artificial Intelligence Association (AAIA).
Professor of Computer Vision
,
University of Jena
Joachim Denzler is a full Professor of Computer Vision at the University of Jena. He has been the founding Director of the Michael-Stifel-Center Jena for Data-driven and Simulation Science and recently established the ELLIS Unit Jena (<a href="http://www.ellis-jena.ai">www.ellis-jena.ai</a>) as well as the Director of the Institute of Data Science of the German Aerospace Center (DLR). Joachim's main research interests revolve around the analysis, prediction and understanding of complex dynamical systems, including applications from medicine, psychology and earth system sciences. Fine-grained object classification, active learning and causal inference for time-series analysis are of particular interest. He addresses these topics with the development and application of machine learning methods, including deep learning, and aspects from explainable AI. Joachim is a member of the board of the Thuringia Center for Learning Systems and Robotics (<a href="http://www.tzlr.de">www.tzlr.de</a>) with the mission to transfer research results from AI to industry. Joachim is excited about the potential of using applications as drivers for basic research, especially to contribute to our society's urgent and pressing problems, like climate change and biodiversity loss. Joachim published more than 500 papers at international conferences and journals with around 10000 citations and an h-index of 45, according to google scholar. He is a PC member and reviewer of major conferences (NeurIPS, ICCV, ECCV, CVPR, ICLR) and Journals (IEEE TPAMI, IJCV, etc.). His group consists of 15 PhD students and receives funding from the German Research Foundation (DFG), Federal Ministry of Science (BMBF), and EU, as well as from industrial projects. He is a member of IEEE and IEEE Computer Society.

AI and Climate Science

For many years climate scientists have used comparatively simple statistical approaches to try and discern subtle changes in observational datasets, or to interpret abundant climate model data output. The opportunity now presents itself for climate science to exploit advances in Machine Learning to answer some of the most pressing challenges of our time – while they are still relevant for policy makers. This acceleration will be built upon: supervised and un-supervised learning of features and patterns in the vast amounts of Earth observation and climate model data that is now available, transforming our ways to constrain climate models and the detection of climate change; robust emulation of existing climate models and their components; and causal detection and attribution of regional climatic changes.

Climate scientists have begun to enthusiastically explore these possibilities, but scaling these novel approaches to the exabytes of data that will be created over the next decade to answer urgent scientific and policy relevant questions in a timely manner will require a concerted collaboration between academia, industry and policy makers. Industrial partners in particular can play a leading role in bringing in their extensive expertise and know-how but also in ensuring that climate data is accessible and interoperable with the latest ML algorithms and the specialized computational hardware required to run them.

This series provides a forum for leading voices in these fields and across sectors to outline a vision for how we will achieve this – with the aim of Accelerating Climate Science with AI.

Curators

Professor of Atmospheric Physics
,
University of Oxford
Philip Stier is Professor of Atmospheric Physics and Head of Atmospheric, Oceanic and Planetary Physics in the Department of Physics at the University of Oxford. He also heads the <a href="https://www2.physics.ox.ac.uk/research/climate-processes">Climate Processes Group</a> and serves on the steering group of the Oxford Climate Research Network. Philip's research addresses physical climate processes in the context of anthropogenic perturbations to the earth system as the underlying cause of climate change and air pollution. His key interests lie in aerosol and cloud physics, their interactions and their role in the climate system. Aerosols are small liquid or solid particles suspended in air of both anthropogenic and natural origin. Cloud droplets form on aerosol particles, so man-made changes in aerosol (precursor) emissions also affect the physics of clouds. He is also Principal Investigator for a <a href="https://www2.physics.ox.ac.uk/research/climate-processes/projects/recap">European Research Council</a> project on the highly uncertain effects of aerosols on precipitation, and he leads the new Marie Skłodowska-Curie Innovative Training Network <a href="https://imiracli.web.ox.ac.uk/">iMIRACLI</a>, which brings together leading climate and machine learning scientists from academia and industry across Europe to educate a new generation of climate data scientists. Philip is passionate about the power of interdisciplinary approaches to address complex questions around the causes and impacts of climate change. Through the Climate Processes Group, Phillip combines work on global climate models, earth observations from satellites and surface and aircraft based in-situ measurements, as well as detailed process models with theory to improve our understanding of the climate system.
Assistant Professor
,
University of California San Diego
Duncan Watson-Parris is an atmospheric physicist working at the interface of climate research and machine learning to investigate the effect of anthropogenic aerosols on the climate. Using cutting-edge machine learning techniques to combine global aerosol models with novel observational constraints he looks to better understand complex aerosol-climate interactions and improve projections of climate change. He is also keen to foster the application of machine learning to climate science questions more broadly and convenes the Machine Learning for Climate Science session at the European Geosciences Union (EGU), and co-convenes the UN AI for Good ‘Climate Science’ Discovery series. Duncan is an Assistant Professor at the University of California San Diego.

AI for Manufacturing

Manufacturing is an integral and huge part of the economy and plays an essential and fundamental role in accelerating progress toward the United Nations Sustainable Development Goals (SDGs). With the rapid development of information technology and the continuous deepening of the digital transformation process, AI is gradually applied in the whole lifecycle of manufacturing and this trend is expanding.

Together with the United Nations Industrial Development Organization (UNIDO), ITU launches the AI and Manufacturing series to provide a forum for leading research works, policies, and best practices in different sectors.

The AI and Manufacturing series focuses on how AI technologies can be used to benefit the manufacturing domain, not only product lifecycle management level, but also smart factory level and intelligent supply chain level, drawing from a variety of techniques such as modeling and simulation, digital twin, blockchain, 5G, and edge computing.

Curator

Professor and Chair of Sustainable Manufacturing
,
KTH Royal Institute of Technology
Lihui Wang is a Professor and Chair of Sustainable Manufacturing at KTH, Sweden. He is also the Director of Centre of Excellence in Production Research (XPRES) - one of the five national strategic research centres at KTH. He has served as the President (2020-2021) of North American Manufacturing Research Institution (NAMRI) of Society of Manufacturing Engineers (SME), and the Chairman (2018-2020) of Swedish Production Academy. In 2020, he was elected one of the 20 Most Influential Professors in Smart Manufacturing by Society of Manufacturing Engineers. He received his PhD and MSc from Kobe University (Japan) in 1993 and 1990, respectively, and BSc in China in 1982. He was an Assistant Professor of Kobe University and Toyohashi University of Technology (Japan) prior to joining National Research Council of Canada (NRC) in 1998, where he was a Senior Research Scientist before moving to Sweden in 2008. His research interests are presently focused on real-time monitoring and control, human-robot collaboration, brain robotics, digital twin, cyber-physical and sustainable production systems. His research work has won one Best Poster Award in Switzerland (2003), four Best Paper Awards in Germany (2002), USA (2016), Serbia (2020) and Sweden (2020), and two Outstanding Paper Awards in Mexico (2008) and USA (2016). In 2021, he received the Best Paper Award of Journal of Manufacturing Systems. He is also an eight-time winner of NRC Institute Awards on Excellence and Leadership in R&D, Multidisciplinary Collaborative Research, Global Reach, and Outstanding People. Professor Wang has published 10 books, 15 conference proceedings and 32 journal special issues. He has authored or co-authored in excess of 600 scientific articles in archival journals, books, and peer-reviewed conference proceedings in the above research areas. In addition to the research work, he is actively engaged in various committee and community activities. He was the Conference Chair of FAIM 2004 and CIRP CMS 2018, a member of Grant Selection Committee (GSC-20 for Industrial Engineering) of Natural Sciences and Engineering Research Council of Canada (2004-2007), the Chair of the Scientific Committee of NAMRI/SME during 2016-2018, and a member of Technical Committee 282 (Machinery Safety) of Swedish Standards Institute (2014-2017). He is the Editor-in-Chief of International Journal of Manufacturing Research, Editor-in-Chief of Journal of Manufacturing Systems, Editor-in-Chief of Robotics and Computer-Integrated Manufacturing, Editor of Journal of Intelligent Manufacturing (2007-2019), Associate Editor of International Journal of Production Research, and an Editorial Board Member of other 17 international journals. He is also a Fellow of The Canadian Academy of Engineering (CAE), a Fellow of The International Academy for Production Engineering (CIRP), a Fellow of SME, a Fellow of ASME, and a registered Professional Engineer in Canada.

GeoAI

Geospatial AI (GeoAI), the emerging scientific discipline at the intersection of geospatial data and artificial intelligence, is the new frontier of technological innovation that promises to transform entire business industries.

Geographic information systems (GIS) have been used widely to present a view of our world based on geographic and geospatial data. Started as the basic capability to visualize information on maps to improve efficiency and decision-making, GIS has conceptually evolved to include the Digital Twin Earths for revisiting the past, understanding the present and predicting the future.

Nowadays we are undergoing significant new developments expanding the use of geographic data in a way that promises to disrupt entire sectors as energy, transportation, healthcare, agriculture, insurance and institutions in the public/private sector (weather centres, national labs)

Behind the rise of geospatial AI are three trends: increased availability of geospatial Earth Observation data both from flying (satellites, airplanes, and UAVs (unmanned aerial vehicle)) and on the ground sensors , the advancement of AI (particularly machine and deep learning), and the availability of massive computational power.

This series provides a forum for leading voices in the fields of geospatial and AI across various sectors (private sector, academia, governments, national and international organizations) to describe latest research and real applications of GeoAI to meet the Sustainable Development Goals.

Curators

Professor
,
Politecnico di Milano
Degree with honours in Physics, PhD in Geodesy and Cartography. She is Professor of “GIS” and “The Copernicus Green Revolution for sustainable development” at Politecnico di Milano (PoliMI) and a member of the School of Doctoral Studies in Data Science at “Roma La Sapienza” University. From 2006 to 2011 she lectured GIS at the ETH of Zurich and from 1997 to 2011 she was the Head of the Geomatics Laboratory of PoliMI (Campus Como). From 2011 to 2016 she was the Vice-Rector of PoliMI for the Como Campus. Currently, she is the coordinator of the Copernicus Academy Network for the PoliMI and the Head of the GEOLab, the Interdepartmental Lab to which 7 Departments of POLIMI are contributing.   She is Vice President of the  ISPRS Technical Commission on Spatial Information Science, a former member of ESA ACEO (Advisory Committee of Earth Observation); co-chair of the United Nations Open GIS Initiative, chair of the UN-GGIM (Global Geospatial Information Management) Academic Network, mentor of the PoliMI Chapter of YouthMappers (PoliMappers), one of the three curators of the geospatial series of the AI for Good, organized by ITU in partnership with 40 UN Sister Agencies.   Her research activity is in the field of geomatics. Her interests have been various, starting from geodesy, radar-altimetry and moving later to GIS, webGIS, geospatial web platform, VGI, Citizen Science, Big Geo Data, geoAI. She is participating and leading research on these topics within the frameworks of both national and international projects and scientific networks. One of her main interests is in Open-Source GIS, where she plays a leading worldwide role.

ML5G

Many stakeholders in the information and communication technology (ICT) domain are exploring how to make best use of AI/ML. But applying AI/ML in communication networks poses different challenges than applying machine learning in, say, image recognition or natural language processing. The reasons are:

  1. Time scales vary a lot in communication networks, from annual (e.g. your subscription to a telecom provider) to millisecond timescales. If your network parameters changes on a millisecond timescale, you need to (re)train your ML model on a similar timescale.
  2. The network environment is noisy.
  3. Computing resources in a network are limited.

5G, combined with AI, will speed up the advancement of the UN Sustainable Development Goals with significant contributions in healthcare, education, agriculture, energy, manufacturing and transportation, among others. The technology will transform these sectors by providing significantly higher speed and lower latency for people, devices and applications.

ITU has been at the forefront to explore how to best apply AI/ML in future networks including 5G networks. Please see the “AI (Pre-)Standardization Section”

Curator

Independent Research Consultant
,
Consultant
Vishnu has hands-on experience in the field of Telecom industry for more than 25 years, developing and implementing standards, and holds many international granted patents. Vishnu currently works as an independent consultant, is a Vice Chair of ITU Focus Group on Autonomous Networks and the co-convener of ITU Correspondence Group on datasets. Previously, he was a co-editor of ITU-T Focus Group specifications on Machine learning in 5G. His current passion includes coordinating standards initiatives, industry bodies, open source and academia, mentoring student projects and coordinating the ITU “AI/ML in 5G“ Challenge across the globe. He also curates and moderates webinars under the ITU Machine learning 5G webinar series and AI for Good. Vishnu was nominated as Scientific Advisory Board Associate (SABA) member of Motorola Networks and is a senior member of IEEE. He holds a Masters degree in Computer Science and Engineering from Indian Institute of Technology, Delhi.

AI and Robotics

Advances in AI are driving the creation of more sophisticated, autonomous and specialized robots that can not only perform multiple tasks with great ease, but also analyze, learn and self-improve in dynamic environments. The AI and Robotics webinar series focuses on how intelligent autonomous systems, which are developed by integrating AI with robotics, can help advance the Sustainable Development Goals.

This expert talk series discusses the latest innovations and trends in robotics and AI, and how they can be harnessed to address some of the world’s most pressing societal challenges in fields such as ageing and health, smart transport, working in hazardous environments, sustainable food production and consumption, green energy, climate change, safety, and equality. Speakers address the technical aspects of robotics and AI, such as machine learning, computer vision, natural language processing, robotics hardware design, human-robot interaction.

This series provides a forum for cataclysmic collaboration around AI and robotics for the benefit of humankind.  Learn about some of the most impactful areas of robotics from the leading experts themselves, and voice your thoughts, questions and ideas on how we can shape a better future, together.

Curator

AI and Robotics Programme Officer
,
International Telecommunication Union (ITU)
<p class="x_MsoNormal"><span lang="EN-US" data-olk-copy-source="MessageBody">Guillem is the Artificial Intelligence (AI) and Robotics Programme Officer at the International Telecommunication Union (ITU), the United Nations specialized agency for digital technologies. His mission is to connect AI and robotics innovators with problem owners to collectively advance the United Nations Sustainable Development Goals.</span></p> <p class="x_MsoNormal"><span lang="EN-US">With over a decade of experience in robotics, Guillem has participated in major international robotics tournaments across Asia, Europe, and North America. At just 15 years old, he co-founded ROBOCAT, an educational robotics competition that promotes learning in robotics and coding among youths from diverse backgrounds, irrespective of their gender, socio-economic status, or academic ability. He led it for over 8 years, nurturing it from a grassroots project into a leading open-source robotics championship that engages thousands of young students annually.</span></p> <p class="x_MsoNormal"><span lang="EN-US">Before joining ITU at the age of 23, he served as the EU Policy Assistant at the Delegation of the Government of Catalonia to the European Union, and as the International Relations Assistant at the Delegation of the Government of Catalonia to Switzerland. He also worked as a legal trainee at Montesinos Abogados.</span></p> <p class="x_MsoNormal"><span lang="EN-US">Guillem is a European Commission Expert Evaluator and Reviewer, a Global Shaper, a Sigma Squared Society Fellow, and a Nova member. He has been an Ambassador for EU Careers (European Personnel Selection Office), EUTOPIA European University, POLITICO's EU Studies and Career Fair (POLITICO Europe), and UNICAT (Ministry of Research and Universities) and a member of the 1st EUSALP Youth Council. He has also been a DIPLOCAT Scholar.</span></p> <p class="x_MsoNormal"><span lang="EN-US">On the academic front, Guillem holds a double bachelor's degree in Law and Business Management and Administration from Universitat Pompeu Fabra, Barcelona. He also participated in the one-year Swiss-European Mobility Program in Law at the University of Geneva, where he earned the Certificate in Transnational Law. He also completed a master’s degree in International Law from the Graduate Institute for International and Development Studies (IHEID), Geneva, and the 59th Graduate Study Program at the United Nations Office in Geneva.</span></p> <p class="x_MsoNormal"><span lang="EN-US">He has been a speaker at leading global tech, AI and robotics events, such AI and Big Data Congress Barcelona, AI Expo Africa, AI Policy Summit, AI House Davos, European Robotics Forum, EmpoderaLIVE, GAIN Summit, Geneva IP and Digital Law Career Forum, Smart City Expo World Congress, WSIS, Swiss Robotics Day, iREX, and Youth Mobile Festival.</span></p>

Trustworthy AI

Artificial Intelligence (AI) systems have steadily grown in complexity, gaining predictivity often at the expense of interpretability, robustness and trustworthiness. Deep neural networks are a prime example of this development. While reaching “superhuman” performances in various complex tasks, these models are susceptible to errors when confronted with tiny (adversarial) variations of the input – variations which are either not noticeable or can be handled reliably by humans. This expert talk series will discuss these challenges of current AI technology and will present new research aiming at overcoming these limitations and developing AI systems which can be certified to be trustworthy and robust.

Curator

Professor of Electrical Engineering and Computer Science
,
Technical University Berlin
Wojciech Samek is a professor in the Department of Electrical Engineering and Computer Science at the Technical University of Berlin and is jointly heading the Department of Artificial Intelligence at Fraunhofer Heinrich Hertz Institute (HHI), Berlin, Germany. He studied computer science at Humboldt University of Berlin, Heriot-Watt University and University of Edinburgh and received the Dr. rer. nat. degree with distinction (summa cum laude) from the Technical University of Berlin in 2014. During his studies he was awarded scholarships from the <a href="https://www.studienstiftung.de/en/">German Academic Scholarship Foundation</a> and the DFG Research Training Group GRK 1589/1, and was a visiting researcher at <a href="https://www.nasa.gov/ames">NASA Ames Research Center</a>, Mountain View, USA. Dr. Samek is associated faculty at the <a href="https://bifold.berlin/">BIFOLD - Berlin Institute for the Foundation of Learning and Data</a>, the <a href="https://ellis.eu/units/berlin">ELLIS Unit Berlin</a> and the <a href="https://bioqic.de/">DFG Graduate School BIOQIC</a>, and member of the scientific advisory board of <a href="https://ideas-ncbr.pl/">IDEAS NCBR</a>. Furthermore, he is a senior editor of <a href="https://cis.ieee.org/publications/t-neural-networks-and-learning-systems">IEEE TNNLS</a>, an editorial board member of <a href="https://journals.plos.org/plosone/">PLoS ONE</a> and <a href="https://www.journals.elsevier.com/pattern-recognition">Pattern Recognition</a>, and an elected member of the <a href="https://signalprocessingsociety.org/community-involvement/machine-learning-signal-processing/mlsp-tc-home">IEEE MLSP Technical Committee</a>. He is recipient of multiple best paper awards, including the 2020 Pattern Recognition Best Paper Award, and part of the expert group developing the <a href="https://www.mpegstandards.org/standards/MPEG-7/17/">ISO/IEC MPEG-17 NNR standard</a>. He is the leading editor of the Springer book <a href="https://www.springer.com/gp/book/9783030289539">"Explainable AI: Interpreting, Explaining and Visualizing Deep Learning"</a> (2019), co-editor of the open access Springer book “xxAI – Beyond explainable AI” (2022), and organizer of various special sessions, workshops and tutorials on topics such as explainable AI, neural network compression, and federated learning. Dr. Samek has co-authored more than 150 peer-reviewed journal and conference papers; some of them listed by Thomson Reuters as "Highly Cited Papers" (i.e., top 1%) in the field of Engineering.

AI and Health

The health sector, one of the most important sectors for societies and economies worldwide, is particularly interesting for AI applications, given the ongoing digitalization of health data and the promise for an improved quality of health and healthcare.

Many investigators from the machine learning community are driven to applying their methodological tool kits to improve patient care, inspired by the impressive successes in image analysis (e.g. in radiology, pathology and dermatology).

However, due to the complexity of AI models, it is difficult to distinguish good from bad AI-based solutions and to understand their strengths and weaknesses. ITU and the World Health Organization established the ITU/WHO Focus Group on “AI for Health” to clarify responsibilities and building trust among AI developers, AI regulators and AI users.

Curators

Chair of the Department of Biomedical Informatics
,
Harvard Medical School
Isaac Kohane, MD, PhD is the inaugural Chair of the Department of Biomedical Informatics and the Marion V. Nelson Professor of Biomedical Informatics at Harvard Medical School. He develops and applies computational techniques to address disease at multiple scales—from whole healthcare systems as “living laboratories” to the functional genomics of neurodevelopment with a focus on autism. Kohane’s i2b2 project is currently deployed internationally to over 120 major academic health centers to drive discovery research in disease and pharmacovigilance (including providing evidence on drugs which ultimately contributed to “boxed warning” by the FDA). Dr. Kohane has published several hundred papers in the medical literature and authored a widely-used book on Microarrays for an Integrative Genomics. He is a member of the Institute of Medicine and the American Society for Clinical Investigation.
Resident physician
,
Charité - Berlin University of Medicine
Matthias Groeschel graduated with an MD-PhD from the University of Groningen, The Netherlands. He conducted his PhD thesis at the Institut Pasteur in Paris and the Research Center Borstel which comprised experimental work and genomic analyses of pathogenic bacteria. He then joined the Department of Biomedical Informatics at Harvard Medical School to study <span lang="EN-US">antimicrobial resistance and transmission of</span> tuberculosis <span lang="EN-US">causing bacteria</span>. Dr Groeschel supports several AI for Health projects at ITU, including AI for Good webinars and the Focus Group on AI for Health. <span lang="EN-US">He is currently a resident physician in pulmonary medicine at Charité – Universitätsmedizin Berlin, Germany, and a research fellow in biomedical informatics at Harvard Medical School.</span>

AI for Biodiversity

While almost 25% of all species are at risk of going extinct mainly because of unsustainable human activities, biodiversity is essential for humanity and for achieving the Sustainable Development Goals. As more species face the risk of becoming endangered, restoring and preserving nature requires urgent and massive investment, effort and innovation. AI can play a vital role in protecting wild animals and plants in new and innovative ways, from AI-based cameras and drones to monitor populations and track poachers, AI models for animal recognition via images or sounds, or algorithms to estimate environmental degradation and ocean health over time – and more. Artificial Intelligence is, for example, also used as a new approach for biodiversity conservation (see Silvestro, Goria, Sterner, & Antonelli, 2022) to identify conservation priorities in space and time, within budget limitations. This technique allows to integrate multidimensional biodiversity data and can more efficiently use the information at hand compared to state-of-the-art methods.

Highlighting the importance of biodiversity and the urgent need to accelerate action to halt the unprecedented degradation of natural habitats, this series brings the AI and biodiversity community together to identify potential scope for collaboration to overcome challenges and strengthen efforts to mobilize, create and drive solutions for progress towards SDG 14 (Live Below Water) and SDG 15 (Life On Land) and beyond.

Curators

Director
,
NatureServe’s Biodiversity Indicators Program
Mike Gill is the Director of NatureServe’s Biodiversity Indicators Program, an Honorary Fellow of UN Environment’s World Conservation Monitoring Centre, and the former Co-Chair of the Group on Earth Observations – Biodiversity Observation Network. For the past three decades, Mike has led the design and implementation of user-driven and results-oriented biodiversity conservation, research, and monitoring programs.  These programs have spanned the planet and have involved partnerships with aboriginal, national and sub-national governments, academia, industry and NGOs. Mike has advised multiple governments, senior officials, and Environment Ministers on biodiversity conservation policy and published over 60 scientific publications. His current work focuses on the design and implementation of biodiversity monitoring and reporting systems in Southeast Asia, the Caribbean, the Tropical-Andes, sub-Saharan Africa and the Arctic.
Senior Researcher, Biodiversity Assessment and Monitoring Program
,
Humboldt Institute
María Cecilia Londoño is a biologist from the Universidad de los Andes in Colombia, with a Master’s degree and PhD from the Universidad Nacional Autónoma de México. Her professional trajectory has focused on the use of environmental data for supporting decision-making process for different stakeholder groups, focusing on the achievement of three main objectives: 1) Identify and monitor essential variables for understanding socioecological change, 2) implement an observation systems for socioecological monitoring, and 3) lead comprehensive analysis for guiding the production of transformative knowledge. Maria Cecilia work is built on the principle of participatory process with heterogeneous stakeholders that share and build knowledge leading to social appropriation of biodiversity. María Cecilia Londoño works as a researcher in the Biodiversity Assessment and Monitoring Program at the Humboldt Institute in Colombia since 2012 and co-chairs the Group of Earth Biodiversity Observation Networks (GEO BON).

AI and Finance

Artificial intelligence promises to transform every aspect of our lives, from the way we communicate to how we drive, learn, consume energy, and obtain healthcare. There is no area where this is more true than financial services. However, the disruption of the finance sector by AI has only just begun. While AI models are being used in trading and portfolio management, and large language models are being used for information consumption and image generation, artificial intelligence is just on the cusp of stimulating changes in lending, investing, insurance, cybersecurity, infrastructure, and much more. This series provides an important forum for leading experts in finance, economics, law, policy, and engineering to discuss the transformative impact of AI on finance and in support of the Sustainable Development goals.

Curator

Executive Director, The Wharton School
,
The University of Pennsylvania Law School
Professor Sarah Hammer is Executive Director at the Wharton School of the University of Pennsylvania, leading financial technology initiatives as well as Wharton Cypher Accelerator, which supports leading global businesses that are leveraging financial technology. Hammer is also Adjunct Professor at the University of Pennsylvania Law School. Hammer is also Affiliated Scholar at the Penn Program on Regulation.   Previously, Hammer was Managing Director of the Center for Innovation in Finance and Senior Director of the Alternative Investments Program at Wharton. Hammer also led the launch of the University of Pennsylvania’s first digital asset, unique 3D intellectual property that memorializes the invention of the mRNA technology which enabled the COVID-19 vaccines.   Hammer is also a board member of the International Telecommunications Union (ITU) at the United Nations. The ITU is the UN specialized agency responsible for information and communication technology. She is also an advisor at the World Economic Forum, the Dubai International Finance Centre, and the Digital Dollar Project for Central Bank Digital Currency.   Previously, Hammer was Acting Secretary of the Department of Banking and Securities for Pennsylvania, having led the Department through the banking crisis of March 2023. The Department regulates and supervises ~290,000 bank and non-bank financial entities, totaling $3.5 trillion in AUM.   Hammer was also previously Acting Deputy Assistant Secretary for Financial Institutions and Director of the Office of Financial Institutions Policy at the US Department of the Treasury. In this role, she led the Department’s policy responsibilities involving financial institutions, as well as oversaw the Federal Insurance Office and the Office of Critical Infrastructure Protection and Compliance Policy (cybersecurity).   While at U.S. Treasury, Hammer also led the cross-functional team conducting a full review and report on the financial regulatory framework. Hammer also served on the board of the Securities Investor Protection Corporation (SIPC) and assisted the U.S. Treasury Secretary in fulfilling responsibilities on the board of the Pension Benefit Guaranty Corporation (PBGC).   Hammer has held various leadership positions throughout financial services in general management, portfolio management, trading, marketing, research, and analytics at the Vanguard Group, PIMCO, JP Morgan Chase, BlackRock, and Tudor Investments.   Hammer earned a J.D. from the University of Pennsylvania Law School, an M.B.A. from the Wharton School, and a Master of Studies from Oxford University.

AI and Work

While past fears over automation primarily concerned blue-collar workers, recent advancements in AI have revealed the potential for automating cognitive tasks. It is thus not surprising that many of today’s workers report fearing for their job or for the jobs of their children. But the effects of AI at the workplace go beyond potential redundancy, as the more likely outcome is the transformation of jobs, with important implications for job quality.

Together with the International Labour Organization (ILO), this series on AI & Work will explore the opportunities and challenges presented by AI in the workplace. With invited speakers from economics, law, industry and labour studies, the series will delve into how AI technologies are reshaping jobs and skills requirements, the use of AI-driven decision-making in hiring and management, and the implications for productivity, inequality and the nature of work itself.

Curators

Senior Economist
,
International Labour Organization (ILO)
Janine Berg is a Senior Economist and Head of the Effective Labour Institutions unit. Since joining the ILO in 2002, she has conducted research on the economic and social effects of labour laws as well as provided technical assistance to ILO constituents on policies for generating jobs and improving working conditions. She is the author of several books and numerous articles on employment, labour market institutions and the digital transformation of work. Janine received her Ph.D. in economics from the New School for Social Research in New York, USA. <span style="text-decoration: underline;">Recent publications:</span> <ul> <li>Janine Berg, Francis Green, Laura Nurski and David Spencer,<em> ‘Risks to Job Quality from Digital Technologies: Are Industrial Relations in Europe Ready for the Challenge?’</em>, European Journal of Industrial Relations, 26 May 2023, <span style="color: #0000ff;"><a style="color: #0000ff;" href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.1177%2F09596801231178904&data=05%7C02%7Cjulien.smith%40itu.int%7C91f4e2ccbb614701bf8e08dc4cabef15%7C23e464d704e64b87913c24bd89219fd3%7C0%7C0%7C638469548630663207%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=dXZW11twguMIOzebvEdzRmp47axjjON%2FgzDgMM4lxuU%3D&reserved=0">https://doi.org/10.1177/09596801231178904 </a></span>.</li> <li>Pawel Gmyrek, Janine Berg and David Bescond, “<a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.ilo.org%2Fglobal%2Fpublications%2Fworking-papers%2FWCMS_890761%2Flang--en%2Findex.htm&data=05%7C02%7Cjulien.smith%40itu.int%7C91f4e2ccbb614701bf8e08dc4cabef15%7C23e464d704e64b87913c24bd89219fd3%7C0%7C0%7C638469548630669410%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=1Dek0oyJlH0qeOcZtGnJcj8D6f9qlhqm0eUYRqe8ph0%3D&reserved=0"><span style="color: #0000ff;">Generative AI and Jobs: A global analysis of potential effects on job quantity and quality</span> </a>,” ILO Working Paper no. 96.</li> <li><span style="color: #0000ff;"><a style="color: #0000ff;" href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.ilo.org%2Fglobal%2Fresearch%2Fglobal-reports%2Fweso%2FWCMS_871016%2Flang--en%2Findex.htm&data=05%7C02%7Cjulien.smith%40itu.int%7C91f4e2ccbb614701bf8e08dc4cabef15%7C23e464d704e64b87913c24bd89219fd3%7C0%7C0%7C638469548630675562%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=RUZmAAJXxWniU6c0cYWNFsqvA8ub1evXu%2BE2SpQ3TmY%3D&reserved=0">World Employment and Social Outlook 2023: The value of essential work </a></span>, ILO, Geneva, 2023.</li> </ul> <em>For a full list of publications, <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fscholar.google.ch%2Fcitations%3Fhl%3Den%26user%3DZkUSxwgAAAAJ%26view_op%3Dlist_works%26sortby%3Dpubdate&data=05%7C02%7Cjulien.smith%40itu.int%7C91f4e2ccbb614701bf8e08dc4cabef15%7C23e464d704e64b87913c24bd89219fd3%7C0%7C0%7C638469548630655593%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=s41TZ%2F0QtW2zCjIOo%2Fu7AQpeE3P%2B%2Bk01qe0RdwoTNxM%3D&reserved=0"><span style="color: #0000ff;">see Google Scholar</span></a></em>
Senior Researcher
,
International Labour Organization (ILO)
Pawel Gmyrek is a Senior Researcher in the Effective Labour Institutions unit of ILO’s Research Department. His current work is focused on the impact of generative AI on employment and occupational structures and on the use of generative AI tools and large unstructured datasets for research purposes. He holds a Ph.D. in Political Science and International Relations from University of Geneva, Switzerland, and a Master’s degree from Warsaw School of Economics, Poland. He has been staff member of the International Labour Office since 2008 and published on topics related to multilateral funding, aid effectiveness, human rights and technology and jobs. <span style="text-decoration: underline;">Recent publications:</span> Gmyrek, P., Lutz, C., Newlands, G. 2024. A Technological Construction of Society: Comparing GPT-4 and Human Respondents for Occupational Evaluation in the UK, ILO Working Paper 102 (Geneva, ILO). <span style="color: #0000ff;"><a style="color: #0000ff;" href="https://doi.org/10.54394/UQOQ5153">https://doi.org/10.54394/UQOQ5153</a></span> Paweł Gmyrek, Janine Berg, David Bescond. 2023. Generative AI and jobs: A global analysis of potential effects on job quantity and quality, ILO Working Paper 96 (Geneva, ILO). <span style="color: #0000ff;"><a style="color: #0000ff;" href="https://doi.org/10.54394/%20FHEM8239">https://doi.org/10.54394/ FHEM8239</a></span> Paweł Gmyrek. 2023. “Who Cares About Workers' Rights? The Effects of Violations of Trade Unions' Rights on Donors' Funding Decisions in the ILO”. Journal of Global Trade, Ethics and Law 1, no. 2 (July 23, 2023): 135–82. <a href="https://doi.org/10.5281/zenodo.8175710"><span style="color: #0000ff;">https://doi.org/10.5281/zenodo.8175710</span></a> Paweł Gmyrek. 2021. Trade interests and UN funding: commercial earmarking of multi-bi aid. Routledge. DOI: <a href="http://dx.doi.org/10.4324/9781003089711"><span style="color: #0000ff;">10.4324/9781003089711</span></a>. ISBN: 9781003089711

Open Source AI for Digital Public Goods (OSAI4DPG)

With the recent advances in AI, and in particular generative AI, there is a growing interest from the public sector to invest in AI developments to facilitate and improve public services. AI usages in the public sector span from simple redundant tasks automation, to more advanced chatbots to serve citizens and to decision support tools to improve public policies, investment and services.

With less than 10 years to achieve the Sustainable Development Goals (SDGs), AI holds great promise in supporting better country public services. ITU is actively contributing to raising awareness and providing education and training on the potential uses and risks of AI in public services to help countries build capacities and move forward. Under the patronage of its EU-funded Open Source Ecosystem Enabler (OSEE) project and the ITU OSPO, this webinar will discuss the compelling requirements of trustable, auditable and equitable AI-based public services.

A key focus of this discussion will be on the importance of Retrieval Augmented Generation (RAG) and the fine-tuning of open-source AI for Low and Middle-Income Countries (LMICs), particularly when resources are scarce. RAG techniques can significantly enhance the efficiency and effectiveness of AI implementations in these contexts, making them more viable and impactful.

This track will discuss the impact of (open source) AI on SDG 4, SDG 8, and SDG 9. A particular focus will be set on SDG 9 target 9.5, which involves the upgrading of technological capabilities of industrial sectors in all countries, and 9.b, which emphasizes domestic technology development, research, and innovation in developing countries.

Curators

Senior Project Coordinator of the EC-funded OSEE project
,
International Telecommunication Union (ITU)
<span data-contrast="none">Dr David MANSET is Senior Project Coordinator of the EC-funded OSEE project (Open Source Ecosystem Enablement for Public Services Innovation) at United Nations ITU.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":259}"> </span><span data-contrast="none"> </span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":259}"> </span> <span data-contrast="none">Formerly researcher-entrepreneur, Dr David MANSET created 4 IT companies at the international level specialized in deeptech (artificial intelligence, blockchain and big data) and sensitive data processing. Over the last decade, he architected large-scale international big data and blockchain platforms for various market sectors, including e.g., www.MyHealthMyDaya.eu. He received 15 awards, amongst which the gold medal at the International Exhibition of Inventions of Geneva, in 2007; the Best Exhibit 1st Prize at European Commission’s largest conference on Information and Communication Technologies in 2008 and in 2013; and in 2016 ranked 2nd Best at the Global SME Award competition of the United Nations ITU Telecom World conference, in Bangkok.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":259}"> </span> <span data-contrast="none">Dr David MANSET holds a Habilitation thesis to conduct research (HDR) from Paris 1 Pantheon-Sorbonne and a DPhil in Model Driven Engineering of Distributed Computing Systems, from the University of the West of England in Bristol, as well as an Executive Master of Business Administration from the Geneva School of Economics and Management, specialized in digital transformation, crypto-currencies, digital trust, big data and data privacy.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":259}"> </span> <span data-contrast="none">As of 1st January 2019, Dr. David MANSET has been nominated as a Knight of the French Order of Academic Palms by the Minister of Education in France.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":259}"> </span>
Digital Services Project Officer
,
International Telecommunication Union (ITU)
Roman Chestnov works with the Digital Services Division of the ITU Telecommunication Development Sector (ITU-D) on innovative applications of digital technologies and digital public goods (DPGs). Since joining ITU in 2020, he has collaborated with more than a dozen countries and public sector entities on projects and initiatives in the areas of digital health, digital public services, digital agriculture, and digital rural development, among others. He has been part of the <a href="https://www.itu.int/en/ITU-D/ICT-Applications/Pages/mhealth-for-ncd-behealthy-bemobile.aspx">WHO-ITU inter-agency team</a> working on health communication and telemedicine solutions for non-communicable diseases (NCDs). As part of this work, he contributed to the implementation of <a href="https://www.itu.int/en/ITU-D/ICT-Applications/Pages/Diabetic%20Retinopathy%20Screening%20in%20Senegal.aspx">a pilot AI telemedicine application</a> for remote diabetic retinopathy screening in Senegal. Working with the ITU-led <a href="https://www.itu.int/en/ITU-D/ICT-Applications/Pages/Initiatives/ASP/Smart-Islands/Smart-Islands-Initiative.aspx">Smart Villages and Smart Islands initiative</a>, he has also supported needs assessment for rural digital infrastructure for essential service delivery in remote rural areas, including health and agriculture needs. As part of the <a href="https://www.govstack.global/">GovStack Global Initiative</a>, he has been supporting regional cooperation on digital government for Central Asia and the Caucasus countries, involving knowledge exchange for better digital public services design and architecture. Through his engagement in projects involving the development and use of digital public goods, Roman developed a strong interest in open-source technology and its applications. He also has a strong interest in machine learning and conducted research on AI implications for international relations and law between 2019 and 2022. Prior to joining ITU, Roman worked with the United Nations Development Programme and the International Labour Organization on impact assessment, data-driven research, and analysis of access to essential services in developing countries.
AI advisor
,
GIZ
Daniel Brumund is an AI advisor for GIZ’s initiative “<a title="" href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.bmz-digital.global%2Fen%2Foverview-of-initiatives%2Ffair-forward%2F&data=05%7C02%7Celanthi.lumani%40itu.int%7Cb0cc386cde3f4e2dd8c408dc1804c87b%7C23e464d704e64b87913c24bd89219fd3%7C0%7C0%7C638411656021509501%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=PBWdPew%2BPBaKoL33qynwsD%2BLdhOdIxUHydQ662PtLMg%3D&reserved=0" target="_blank" rel="noopener noreferrer" data-auth="VerificationFailed" data-linkindex="1">FAIR Forward – Artificial Intelligence for All</a>” which promotes a more inclusive, open and sustainable approach to AI at an international level, together with partners from government, civil society and academia in Africa and Asia. He is working with Mozilla Common Voice and African partners to create open AI training data for under-resourced languages; as well as supporting Kenyan partners with creating open-source chatbots to simplify access to government services; and working on licensing and business models for open-source AI systems.
AI & Country Policy Lead
,
Digital Public Goods Alliance (DPGA)
<span class="TextRun SCXW186683097 BCX8" lang="EN-US" xml:lang="EN-US" data-contrast="none"><span class="NormalTextRun SCXW186683097 BCX8">Lea Gimpel is the lead for country policy and AI at the Digital Public Goods Alliance (DPGA). Previously, Lea co-led the GIZ initiative "FAIR Forward", which aims to democratize AI development worldwide. Lea holds an Executive </span><span class="NormalTextRun ContextualSpellingAndGrammarErrorV2Themed SCXW186683097 BCX8">Master's in Public Administration</span><span class="NormalTextRun SCXW186683097 BCX8">, specializing in big data and digital governance from the </span><span class="NormalTextRun SpellingErrorV2Themed SCXW186683097 BCX8">Hertie</span><span class="NormalTextRun SCXW186683097 BCX8"> School, where she is also a lecturer. She is a board member of the Open Knowledge Foundation Germany and supports the initiative on AI technologies for Civil Climate Action of the German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety, and Consumer Protection in an advisory role. She also holds an advisory role with the German UNESCO Commission, focusing on digital governance topics.</span></span><span class="EOP SCXW186683097 BCX8" data-ccp-props="{"201341983":0,"335559739":0,"335559740":259}"> </span>

AI in Humanitarian Action

The humanitarian sector has been actively exploring the integration of AI, with each organization independently experimenting and deriving valuable insights. These efforts span technical, data management, financial, cultural, and linguistic dimensions. However, the broader humanitarian community has yet to fully benefit from these dispersed findings. To maximize the potential of AI in humanitarian contexts, it is crucial to foster a more integrated approach that consolidates these lessons and promotes collaborative learning.

The AI in Humanitarian Action discovery series, in collaboration with AI for Good, seeks to bring together a wide range of stakeholders to share their experiences and learned lessons. Coordinated by UNOCHA and the IASC secretariat, this series aims to foster a more cohesive and integrated approach to AI in humanitarian contexts, enhancing the collective impact and effectiveness of AI-driven initiatives.

Curators

Research Fellow
,
The Distributed AI Research (DAIR) Institue
<span class="TextRun SCXW186495237 BCX0" lang="EN-US" xml:lang="EN-US" data-contrast="none"><span class="NormalTextRun SpellingErrorV2Themed SCXW186495237 BCX0">Nyalleng</span> <span class="NormalTextRun SpellingErrorV2Themed SCXW186495237 BCX0">Moorosi</span><span class="NormalTextRun SCXW186495237 BCX0"> is a research fellow at The Distributed Artificial Intelligence Research (DAIR) institute, where her research concentrates on developing models that prioritize the global majority. Prior to her position at DAIR, she was a research software engineer at Google and a senior researcher at the South African Council for Scientific and Industrial Research. </span><span class="NormalTextRun SpellingErrorV2Themed SCXW186495237 BCX0">Nyalleng</span><span class="NormalTextRun SCXW186495237 BCX0"> is also a co-founder of the Deep Learning Indaba, the largest machine learning consortium of AI/ML practitioners in Africa and a Board Member of CDAC Alliance and Colossal Biosciences.</span></span><span class="EOP SCXW186495237 BCX0" data-ccp-props="{"134233117":false,"134233118":false,"335551550":0,"335551620":0,"335559738":240,"335559739":240}"> </span>
Founder of the Humanitarian AI Advisory and Senior Artificial Intelligence Advisor
,
United Nations Office for the Coordination of Humanitarian Affairs (OCHA)
<div class="x_elementToProof">Michael Tjalve is Senior AI Advisor to UNOCHA. He brings more than two decades of experience with AI, from applied science and research to tech sector AI product development, most recently serving as Chief AI Architect at Microsoft Philanthropies where he helped humanitarian organizations leverage AI to amplify their impact.</div> <div></div> <div></div> <div class="x_elementToProof">In 2024, he left the tech sector to found Humanitarian AI Advisory, dedicated to helping humanitarian organizations and stakeholders understand how to harness the potential of AI while navigating its pitfalls.</div> <div></div> <div></div> <div class="x_elementToProof">Michael is Assistant Professor at University of Washington where he teaches AI in the humanitarian sector. He holds a PhD in Artificial Intelligence from University College London.</div> <div></div> <div></div> <div class="x_elementToProof">Michael serves as Board Chair and technology advisor for Spreeha Foundation, working to improve healthcare and education in underserved communities in Bangladesh.</div> <div class="x_elementToProof">Michael is also part of the recently launched SAFE AI initiative which aims to promote the safe and responsible use of AI in humanitarian action.</div>

From Molecules to Models

Join us for the From Molecules to Machines webinar series, where leading experts from the ELLIS Programs will present their cutting-edge research and innovations in AI. This is a unique opportunity to engage with high-impact topics across various AI fields, from semantic and symbolic learning to breakthrough applications that are shaping the future of technology.

What is ELLIS?
The European Laboratory for Learning and Intelligent Systems (ELLIS) is a top-tier initiative dedicated to advancing AI research in Europe. ELLIS unites some of the brightest minds in AI across Europe’s leading institutions, fostering a collaborative, interdisciplinary network of researchers. Its mission is to address the most pressing challenges in AI, from deep learning to interpretable AI, and to ensure that European research remains at the forefront of AI development.

The ELLIS Programs are a network of cutting-edge research programs focused on high-impact AI challenges. Led by distinguished researchers and supported by leading Program Fellows, these programs drive collaboration across Europe to push the boundaries of modern AI. Inspired by the CIFAR Program model, ELLIS Programs also collaborate with the CIFAR LMB (Learning in Machines and Brains) Program, creating an environment for intensive scientific exchange.

Register now and join us for these transformative sessions!

Curators

Senior Project Coordinator
,
Friedrich Schiller University Jena
Conrad Philipp is the coordinator of the ELLIS Unit Jena, where he facilitates collaboration across a network of leading institutions, including the Friedrich Schiller University Jena, the Max Planck Institute for Biogeochemistry, and the German Aerospace Center. The unit's research focuses on using machine learning and AI to tackle challenges in environmental and climate sciences, aiming to deepen the understanding of Earth’s dynamic systems and guide evidence-based decision-making for policy and society. Before joining ELLIS, Conrad worked in the public relations team at the Max Planck Institute for Biogeochemistry, where he helped communicate groundbreaking research to broader audiences. He also coordinated the "Cooling Singapore" project at the Singapore-ETH Zurich Centre and worked as a postdoctoral research fellow in Australia. As part of the pan-European ELLIS network, which consists of 43 units across 17 countries, Conrad works to promote human-centered AI, ensuring that Europe leads the way in this field. He holds a Ph.D. in Environmental Sciences from the University of Duisburg-Essen and has broad international experience in both scientific research and project coordination.

AI for Good Discovery Past Curators

CEO
,
Open Geospatial Consortium (OGC)
Executive Director
,
World Geospatial Industry Council (WGIC)

AI for Good Discovery partners