Data is the new oil, lubricating the engines of Artificial Intelligence (AI) and Machine Learning (ML), ceaselessly driving us towards an era of automated enlightenment. However, as we guzzle down this invaluable resource, there's a lingering side effect of ethical indigestion. Reality hits hard when we realize that amidst this data binge, we might be inadvertently serving up generous portions of personal or sensitive information on the platter of AI/ML training and applications.
The endless stories of data breaches that decorate the headlines testify to how vital robust data security frameworks are. Amidst an array of data protection mechanisms, Data Masking and Data Tokenization emerge as prominent players. These data security tools are not only pivotal in safeguarding sensitive information but also play a crucial role in ensuring compliance with evolving data privacy laws.