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Prepare to Privacy-Proof Your AI Technology

Make your privacy program the enabler of your AI projects.

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to this Blueprint

  • The pace set by rapid advancements in technology, and the increased prevalence of AI forces IT and business leaders to engage in a state of constant evolution.
  • Simultaneously, data privacy regulations have become increasingly stringent in an attempt to safeguard personal information from manipulation.
  • AI relies on analysis of large quantities of data, and more often than not involves personal data within the data set, posing an ethical and operational dilemma when considered alongside data privacy law.

Our Advice

Critical Insight

Data privacy first, AI second. Your organization’s internal and external environment impact not only the integration of AI-based technology but govern the approach to data privacy. By understanding your data privacy environment, you lay the foundation for a streamlined AI implementation.

Impact and Result

  • Perspective from a privacy lens on mitigating data privacy risk through IT best practices.
  • Guidance on completion of impact assessments that validate the integration of AI technology within the organization’s environment.
  • Knowledge around core AI vendor solutions that maintain a privacy-first approach based on integration of explainability.
  • Data privacy best practices and how AI technology can support a privacy-proof environment.
  • Understanding of the scope of data privacy regulations within the context of the organization.
  • Comprehensive outlook around data privacy best-practices that enable effective AI integration.

Research & Tools

Start here – read the Executive Brief

Learn how to carefully balance the implications of data privacy adherence with adoption of AI technologies to drive efficiencies in the context of your business.

1. Evaluate AI through a data privacy lens

Take a deep dive into AI technologies through the review of ethical AI techniques including Explainability and Differential Privacy, as well as the application of AI in the context of data privacy.

2. Identify the data privacy posture

Evaluate the current state of data governance and data privacy within the business as you prepare to integrate AI technologies.

Guided Implementations

This guided implementation is a five call advisory process.

Guided Implementation #1 - Evaluate AI through a data privacy lens

Call #1 - Scope requirements, objectives, and your specific challenges.
Call #2 - Discuss AI project pipeline.
Call #3 - Review organization’s privacy and AI drivers.

Guided Implementation #2 - Identify the data privacy posture

Call #1 - Assess current data governance approach.
Call #2 - Review and make modifications to current data privacy program and identify privacy posture.

Search Code: 94965
Published: November 4, 2020
Last Revised: November 4, 2020

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