Fighting COVID19 with AI – How to build and deploy solutions we trust? – WS 14 2020
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The COVID-19 pandemic has resulted in an unprecedented situation which has called for unprecedented solutions, including a rapid development of applications based on Artificial Intelligence (AI) and data. These solutions are essential in tackling the pandemic, as applications can benefit treatment as well as generate a specific overview of the spread. However, these solutions could be introducing potential risks such as biases and privacy issues.
Such examples display the dilemmas surrounding the application of AI and data in general. The question is how to address these serious risks and to ensure the trustworthy use of AI and data, while reaping the benefits and opportunities stemming from the new technologies? This session aims at looking at the regulatory as well as non-regulatory toolbox for AI and data by discussing practical models and tools on how to ensure secure, ethical and trustworthy usage of AI and data without stifling innovation.
Across the globe, new AI solutions have been built and deployed in order to fight the COVID-19 pandemic – and more innovative solutions are being created, as we speak. These solutions can both benefit disease prevention, diagnosis and treatment and varies from spotting specific patterns in x-rays to tracking people diagnosed with COVID-19. However, such applications raise questions such as: Are the AI solutions able to take autonomous decisions? Are the AI solutions protecting existing rights and values, such as privacy and data ethics? Are results from AI safe and reproducible? Are the AI solutions trained on representative data in order not to discriminate?
These are extraordinary times which call for extraordinary measures, but the pandemic will surely also leave its mark on jobs, mobility, consumption patterns, markets, businesses etc., thereby giving way to new AI solutions in the long-term. As these solutions increasingly become a central part of our everyday life, the question is how to address the potential risks and challenges related to AI and instead build trust in innovative AI solutions.
Already before COVID-19, there was awareness of the challenges brought by AI, such as bias, transparency and privacy, which spurred the debate whether the race for AI should also include regulatory responses. While some intergovernmental institutions and countries are working on developing guidelines, others are drafting regulation. Experience within the regulatory landscape is still scarce and the technology is rapidly evolving - thereby, leaving a range of questions unresolved:
- Which are the best tools in order to ensure trustworthy AI?
- Which requirements for the development and deployment of AI should be instated?
- How do we strike the right balance between trust and innovation?
These are some of the questions this session will touch upon in order to come one step closer to defining how the regulatory as well as non-regulatory toolbox can help ensure secure, ethical and trustworthy usage of AI and data without stifling innovation.
Until 11 May 2020.
Please try out new interactive formats. EuroDIG is about dialogue not about statements, presentations and speeches. Workshops should not be organised as a small plenary.
- ITU AI/ML in 5G Challenge 
Until 27 April 2020.
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- Julia Katja Wolman
- Maria Danmark Nielsen
Organising Team (Org Team) List them here as they sign up.
- Nadia Tjahja
- Narine Khachatryan
- Moritz Schleicher
- Amali De Silva-Mitchell
- André Melancia
- Ashwini Sathnur
- Marie-Noemie Marques
- João Pedro Martins
- Martin Ulbrich, DG CONNECT, European Commission. Martin is part of the team in charge of the AI White Paper process in the EC.
- Mikael Jensen, CEO for the new Danish labelling scheme and seal for IT-security and responsible use of data, which is planned to launch by the end of 2020
- Dr. Sebastian Hallensleben, AI Ethics Impact Group (led by VDE and BertelsmannStiftung) who has recently published the report ”From principles to practice – An interdisciplinary framework to operationalise AI ethics”
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