CTO Connection

Data privacy for technology leaders

• Geeta Chauhan

• slides:

Privacy Challenges in AI

• Privacy Tradeoff between protecting data privacy and training AI/ML models

• Tensions associated with data minimization and retention

• Proliferation of AI/ML models heighten lack of public understanding

• As artificial intelligence evolves, it magnifies the ability to use information in ways that can intrude on privacy interests

• Increasingly sensitive nature of data used for research raises other privacy challenges

• Sourcing of data that is free of bias

Privacy Challenges

Data input needs of the AI need to be balanced against the needs and concerns of consumers and regulations

• Data for AI Model: Collected data need business justifications for best performance

• Consumer needs and regulations

  • Consumer Concerns and Benefits: more proactive user-centric approach to know what the consumers are needed and comfortable with

  • Government Regulations: GDPR, CCPR

  • Business Concerns: explicitly not to collect certain types of data out of concerns for privacy

Privacy Preserving ML Techniques

Homomorphic Encryption