Overcoming the Challenges of Data Sharing in Artificial Intelligence Systems: A Comprehensive Review of Techniques and Best Practices

Artificial Intelligence (AI) systems rely heavily on data sharing to develop more accurate and effective algorithms. However, data sharing presents several challenges, including privacy concerns, security risks, and ownership issues. To address these challenges, organizations must implement effective data sharing strategies that maintain data privacy and security while leveraging the strengths and expertise of other organizations. This paper provides a comprehensive review of techniques and best practices for overcoming the challenges of data sharing in AI systems. The research concludes that there is no such dataprivacy technique one-size-fits-all solution. The choice of technique will depend on several factors, such as the sensitivity of the data being shared, the regulatory environment, and the desired level of data privacy.