Sharing data
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Data Sharing
No AI machine learning is possible without data. The more relevant data is available, the better the predictive value becomes and thus the utility of machine learning AI applications is improved. Access to data is therefore crucial. In the Netherlands, data is often kept locked away. Usually for legal or commercial reasons. To break these barriers, data sharing must be organized in a good and responsible way, much faster and better than we are used to now. More access to data means accelerated AI implementation and higher accuracy, resulting in better service. Trust, insight, more knowledge and our democratic principles are the basis.
Approach
For organizations and businesses, the opportunities and risks must be properly considered and organized. To protect business interests and ensure that the data they share is not misused. The question is: how are we going to provide the AI applications with data if these constraints are there?
The Dutch AI Coalition aims to simplify data sharing as a crucial element of AI by researching, developing and deploying privacy enhancing techniques (PETs). Knowledge about what is and is not allowed should be readily available. In addition, ecosystems around a particular sector or in a region should be encouraged to include data sharing solutions in their portfolio.
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Yvonne Kooi - Program Manager
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