Ethical Data Principles

Learn About Our 5 Core Ethical Data Principles

Across the data lifecycle - from data collection to retention – five core ethical data principles will enable trust without stifling innovation:


First and foremost, sensitive and personal data must be collected conscientiously – and used and protected with care. If personal data is no longer relevant to the purpose for which it was collected, it should be erased.

Read our introduction to the principle of Privacy.


To preserve data dignity, people should be given choice and control over how their data is used, and have the power to change their decision at any time – and those choices should been forced across all the data systems that process that data.

Read our introduction to the principle of Agency.


Businesses must communicate, in simple language, how they will use data they collect, who it will share that data with, and how long they plan on storing the data.

Read our introduction to the transparency principle.


Businesses must measure and mitigate over the impact of data systems and the outputs in machine learning, intelligent systems, and artificial intelligence that may have disparate impact or bias in application.

Read our introduction to the fairness principle.


A business’s technology and its employees must do what it says it will do system and organization-wide. We envision a world where if entities don’t do right by people, businesses are held accountable.

Read our introduction to the accountability principle.

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