Contributed by Florian Teichert, WMO.
The WMO HydroHub has partnered with the organizers of the Open Seventeen Challenge to publish challenges around the topic of “Artificial Intelligence (AI) for Operational Hydrology”, to which students from all over the world can submit solutions. Contributions from the developing and least-developed world would be especially welcomed to give students a chance to make a difference.
This is part of the University of Geneva organized Open Seventeen (O17) Challenges targeting one or more of the Sustainable Development Goals (SDGs). Challenges have been chosen according to their relevance to the operational hydrology and the implementation of SDGs; the potential benefit to Least Developed Countries (LDCs) and Small Island Developing States (SIDS) and the potential number of people that could address the challenge.
If all goes well then you will be able to see the results of the challenges at the AI for Good Global Summit taking place in Geneva (Switzerland) from 4 to 8 May 2020, where the project outputs are presented to the public. For more details visit openseventeen.org – application deadline 9th March 2020.
CHALLENGE 1: Estimating river flows
Predicting river flows is critical for managing global water resources. How could you combine AI open data sources and measurements made by citizens to predict river flow in your region?
CHALLENGE 2: Predicting landslides
Forecasting rainfall-induced landslides is challenging. How can AI improve the landslide predictions in your region by using historical landslide datasets as well as crowdsourced data?
CHALLENGE 3: Reducing the gender bias of algorithms
There is increasing concern that datasets used to train AI algorithms are gender biased. How could public participation in data gathering reduce that bias?
CHALLENGE 4: Recycling food more intelligently
Every day food is wasted in some parts of the world, while people go hungry elsewhere. How could AI and citizen science help to reduce waste and hunger?
CHALLENGE 5: Tracking SDGs through history
The UN is digitizing the archives of its predecessor the League of Nations. How could the study of historical trends in topics such as pollution, peace or poverty, be assisted with AI?
CHALLENGE 6: Responding to emergencies
The analysis of social media streams following a natural disaster such as an earthquake can provide vital information for first responders. How can AI be used to accelerate such analysis?
I am very happy that we could attract two strong partners, ECMWF and Deltares, to volunteer as mentors to work with the students. With their expertise and experience, I am sure, we will see a strong push towards adding value for the SDGs and operational hydrology.