​​​Workshops and Seminars

• Joint ITU/WHO Workshop on safe listening in video gaming and esports: Updates (2)
  Geneva, ITU HQs, 4-5 July 2024
  
• Joint ITU/WHO Workshop on safe listening in video gaming and esports: Updates
  Rennes, France, 16 April 2024
  
• Joint ITU/WHO Workshop on safe listening in video gaming and esports
  Geneva, 30-31 January 2024
  
• ITU Workshop on the future of television for the Americas
  Bogotá, Colombia, 17 November 2023 (with ITU-T SG9 and ITU-R SG6)
  
• Joint ITU/WHO Workshop on developing standards for safe listening in video gaming and esports activities
  Geneva, 28-29 Sep 2023
  
• ITU Workshop on voice recognition implementation in vehicles
  Geneva, 11 July 2023
  
• ITU-T/WHO Workshop on safe listening standards for personal listening devices and systems
  Geneva, 9 June 2023
  
• ITU Workshop on multimedia in the metaverse
  Geneva, 18 October 2022
  
• ITU Workshop on the future of television for Europe (2021 edition)
  Online, 19 November 2021 (with ITU-T SG9 and ITU-R SG6)
  
• Joint ITU/WHO Workshop on safe listening in e-sports and video gaming: identifying use cases and requirements
  Online, 2 December 2021
  
• 2nd Joint ITU/WHO Workshop on Digital COVID-19 Certificates
  Online, 26 November 2021
  
• ITU/WHO Workshop "Digital Vaccination Certificates"
  Online, 11 August 2021
  
• ITU/WHO workshop "Role of industry in making telehealth accessible for persons with disabilities"
  Online, 23 June 2021
  
• ITU Workshop "The future of television for Asia & Pacific"
  Online, 23 April 2021 (with ITU-T SG9 and ITU-R SG6)
  

---

• ITU DLT meetup series
  Regular episodes happen on the 1st Wednesday of the month, 13:00-15:00 (Geneva time)
  

---

• ITU Autonomous and Assisted Driving workshop series (part of FG-AI4AD events)
  2019-09 (Online) | 2020-01 (London) | 2020-09 (Online) | 2020-10 (Online) | 2020-12 (Online) | 2021-03 (Online) | 2021-06 (Online) | 2021-10 (Online)
  

---

• ITU Vehicular Multimedia workshop series (part of FG-VM events)
  2018-10 (Blackberry, Ottawa) | 2019-01 (TTC, Tokyo) | 2019-09 (ITU/Telecom, Budapest) | 2020-12 (Online) | 2021-04 (Online)
  2022-04 (Online) | 2022-06 (Online)
  

---

• ITU/WHO AI for health workshop series (part of FG-AI4G events)
  2018-09 (WHO, Geneva) | 2018-11 (Columbia Univ., New York) | 2019-01 (EPFL, Lausanne) |
  2019-04 (CAICT, Shanghai) | 2019-05 (AI for Good, Geneva) | 2019-09 (Zanzibar) | 2019-11 (New Delhi) |
  2020-01 (Fraunhofer HHI, Berlin) | 2020-01 (Brasilia) | 2022-05 (Berlin) | 2022-09 (Helsinki) | 2022-12 (Cameroon) | 2023-03 (MIT Media Labs, Cambridge, MA, USA) | 2023-07 (​Geneva)​
  

ITU AI for Health segment of the AI for Good webinars ... ^{(click to expand)}


Seeing the future: AI-based risk assessment models, Naomi Lee (The Lancet Journal), Regina Barzilay (Massachusetts Institute of Technology (MIT)), 26 May 2021


Ignoring the mirage of the disposable clinician for the successful deployment of AI in medicine, Isaac Kohane (Harvard Medical School), Maha Farhat (Harvard Medical School), 22 June 2021​


Making neural nets uncool again, Jeremy Howard (fast.ai), 16 July 2021

Ethics in AI for health: the quest for global governance, Effy Vayena (ETH Zurich), 15 September 2021

Contextualizing progress in the AI revolution, David Shaywitz (Astounding HealthTech), 22 September 2021

Dissecting algorithmic bias, Ziad Obermeyer (Berkeley School of Public Health), 7 October 2021

The disorderly world of diagnostic and prognostic models for covid-19, Laure Wynants (Maastricht University), Maarten van Smeden (University Medical Center Utrecht), 8 November 2021

AI for Health in developing countries, Hugo Morales (Robô Laura), 22 November 2021

Fairness of machine learning classifiers in medical image analysis, Enzo Ferrante (Argentina's National Research Council (CONICET)), 6 December 2021


Bringing machine learning to clinical use safely, ethically and cost-effectively, Nigam Shah (Stanford University), Isaac Kohane (Harvard Medical School), 17 December 2021

Refusing AI Contact: Autism, Algorithms and the Dangers of 'Technopsyence', Os Keyes (University of Washington), 13 January 2022

AI-Enabled Public Health from a Marginalized Perspective, Lelia Marie Hampton (Massachusetts Institute of Technology (MIT)), 19 January 2022


Scalable AI for Good solutions in genomics and health, Colby T. Ford (Tuple), 11 February 2022


How to harness AI for genomic insights in drug-resistant tuberculosis?, Anna G. Green (Harvard Medical School), Chang Ho Yoon (Oxford University’s Big Data Institute), 25 February 2022


AI and regenerative medicine: AI-enabled manufacturing of stem-cell based therapies, Nabiha Saklayen (Cellino), 9 March 2022


The Pitfalls and Potential of Using Machine Learning to Personalize Patient Treatments, Uri Shalit (Technion - Israel Institute of Technology, Faculty of Industrial Engineering and Management), 30 March 2022


Beyond bias: Algorithmic unfairness, infrastructure, and genealogies of data, Alex Hanna (Distributed AI Research Institute (DAIR)), 13 April 2022


AI in health and medicine, Isaac Kohane (Harvard Medical School), Eric Topol (Scripps Research Translational Institute), 27 April 2022


The gift from yesterday: Medical data as a public good, Matthew Lungren (AWS World Wide Public Sector Healthcare), 4 May 2022


How could we improve mental health for 100 million people within 5 years?, Matthias Groeschel (International Telecommunication Union (ITU)), Andrew Welchman (Ieso), 8 June 2022


Digital and the Future of Disease Surveillance, John Brownstein (Boston Children’s Hospital), 22 June 2022


GeoAI and Health, Nadine Alameh (Open Geospatial Consortium (OGC)), Anthony Arce (San Bernardino County Department of Public Health), Jay R Etherton (HSR.health), 27 June 2022


Human-centered AI for dangerous mental health behaviors online, Stevie Chancellor (University of Minnesota), 6 July 2022


Designing machine learning processes for equitable health systems, Marzyeh Ghassemi (Massachusetts Institute of Technology (MIT)), Luis Oala (Fraunhofer Heinrich Hertz Institute (HHI)), 14 July 2022

Responsible AI and MLOPs for healthcare – bias reduction and fair modeling, every algorithm, every time, Enzo Ferrante (Argentina's National Research Council (CONICET)), Maia Hightower (University of Utah), 7 September 2022

Bringing machine learning models to the bedside, Isaac Kohane (Harvard Medical School), Karandeep Singh (University of Michigan), 8 November 2022