# CTO Connection

## Data privacy for technology leaders

* Geeta Chauhan
* slides:

{% embed url="<https://www.slideshare.net/geetachauhan/building-ai-with-security-and-privacy-in-mind>" %}

![](/files/-MfUwBpVMslZ9vVdhtgp)

### 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**

![](/files/-MfUwGDwnTEp50HhJ1BL)

### 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&#x20;

![](/files/-MfUwTRdzP_lGgP-D-5d)

### Privacy Preserving ML Techniques

![](/files/-MfUzLBtegZU2JWvBTyI)

#### Homomorphic Encryption

![](/files/-MfUzVH2Hxxxf_yGGBEs)

![](/files/-MfUzjt94UZdSWwwlIR-)


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