AI Governance and Neuroinformatics: Privacy and Data Sharing
Author Information
Author(s): Alsaigh Roba, Mehmood Rashid, Katib Iyad, Liang Xiaohui, Alshanqiti Abdullah, Corchado Juan M., See Simon
Hypothesis
How can AI governance regulations be harmonized with neuroinformatics practices to address privacy and data sharing challenges?
Conclusion
The study emphasizes the need for standardized data sharing and robust ethical frameworks to enhance global research and ensure ethical innovation.
Supporting Evidence
- The integration of neuroinformatics within global AI governance frameworks reveals a robust alignment, especially in privacy and data protection.
- Technological advancements such as federated learning and blockchain are emphasized for enhancing data security.
- Significant gaps persist in data standardization and interoperability across international borders.
Takeaway
This article talks about how we need to make rules for using AI in brain research that keep people's data safe and help scientists share information better.
Methodology
The article is based on a comprehensive analysis of over 4,000 research articles and AI regulation documents.
Limitations
The article does not present the topic in full depth due to a word limit.
Digital Object Identifier (DOI)
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