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

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