Ethical Data Principles Scorecard

So, you’ve earned strategic buy-in by leveraging the Data Stewardship Assessment. Now what? Start by empowering individual practitioners across your organization with the resources they need with our essential tool - the Ethical Data Principles Scorecard.

Ask individual practitioners to compare their department and role’s performance against the Ethical Data Principles Scorecard to identify where to improve.

Here's why you need to leverage this tool today:

  • Precision: Evaluate your department's compliance with ethical data principles, spotlighting focus areas.
  • Progress: Use the Scorecard to highlight growth areas and monitor advancements in data ethics.
  • Catalyst: Ignite team discussions on data ethics, fostering a more conscientious workforce.

Review the Ethical Data Principles Scorecard Now⬇


Review the scorecard below, aligned to our 5 principles for Ethical Data Use that form the bedrock of ethical tech guidelines.

Ask yourself: is your department Exceptional, Average, or Poor?

Be honest. If you score poorly, you can get the help you need - whether technical or strategic - from the Ethical Tech Project Partner Program.

Review the scorecard now:


Exceptional Performance

Average Performance

Poor Performance


Your team conscientiously collects minimal personal data with clear consent, uses it strictly for the intended purpose, protects it effectively against breaches, and promptly erases it once it's no longer needed.

Your team collects personal data with consent, usually uses it for the intended purpose, has some protection measures, and occasionally erases data that is no longer needed. However, these processes could be made more rigorous and consistent.

Your team collects personal data without clear consent, sometimes uses it beyond the intended purpose, lacks robust protection measures, and infrequently erases data, even when it's no longer relevant.


You ensure individuals have full control over their data with user-friendly tools for managing preferences. Their decisions are enforced promptly across all your systems with data orchestration technology.

You allow individuals to control their data, with some options for managing preferences. However, there could be delays or inconsistencies in enforcing their decisions across all systems.

Users lack meaningful control over their data due to limited options and inconsistencies in enforcing their decisions across your systems.


Your team clearly, simply, and unambiguously communicates how it will use collected data, with whom it will be shared, and the duration of storage. This information is easily accessible and understandable, leaving no room for obfuscation.

Your team provides information about how it uses collected data, its sharing partners, and storage duration, but the language can be complex and hard to understand. Improvements can be made to simplify and clarify this communication.

Your team's communication about its data usage, sharing, and storage is unclear, hard to understand, or inaccessible. The language is complex, and key information may be obfuscated or missing. Users are left in the dark about changes and third-party data access.


You actively work to mitigate biases in data and AI systems, ensuring fair outcomes for all users. You conduct regular impact assessments and correct identified disparities.

Your team checks for biases in data and AI systems but there are gaps. Regular impact assessments may not be conducted, leading to occasional unfair outcomes.

Your team lacks measures to mitigate biases in data and AI systems. Fair outcomes are not consistently achieved due to rare or non-existent impact assessments.


You hold your team accountable for data stewardship, conducting regular audits to ensure adherence to policies. Data ethics are integral to your team's culture.

Your team has some accountability measures, but strict enforcement or regular audits may be lacking. There's room to improve the integration of data ethics into your team's culture.

Accountability mechanisms in your team are weak or lacking. Audits are irregular or non-existent, leading to an inconsistent approach to data ethics.

Customer/User Satisfaction

Customers/users are very satisfied because they feel their data dignity is respected. They feel empowered to manage their data, resulting in high trust and a positive relationship. As a result, customers/users are more loyal and likely to recommend the product.

Customers/users are moderately satisfied. They generally feel their data is handled respectfully, but occasional concerns or lack of empowerment may create trust issues. If left unaddressed or unimproved, customer/user concerns could snowball into a problem for the business.

Customers/users are dissatisfied, frequently raising concerns about data handling. Their sense of data dignity is compromised, resulting in low trust in your team's data stewardship and a negative impact on the company as a result.

Overall Data Stewardship Posture

Your team is a standout in data stewardship, pioneering the comprehensive implementation of ethical data principles. You're not just responsible with people's data—you're a model of integrity, thereby securing unwavering consumer trust. Your bold organizational and technological shifts ensure these principles are deployed at scale, making you a trailblazer prepared for any AI advancements.

Your team is on the path to better data stewardship. You're implementing ethical data principles but the approach can be more consistent or far-reaching. Greater commitment to these principles will enhance consumer trust and better equip your team for AI disruptions.

Your team is significantly lagging in data stewardship, which jeopardizes consumer trust. You're barely embarking on the journey of implementing ethical data principles at scale. Without a drastic shift in your approach, your readiness for the impact of AI advancements is at stake.