Using your Data Responsibly and Ethically

Data is a powerful resource that many organizations have but it needs to be managed and stewarded with care. We must ensure that our data practices are in alignment with our overall organizational values, and that we do not increase the vulnerability of the people that we serve.

Guide Details

Last Updated On

January 11, 2022


It seems like every week there are new data breaches, concerns about our privacy, and stories about data science gone wrong. We hear about banks giving credit to customers they know can’t afford it, casinos using data science and behavioral economics to keep customers coming back for more and driving them into bankruptcy, and on and on…

These kinds of behaviors aren’t limited to private sector actors in search of greater profits. Nonprofits can also be irresponsible with their data, or fall victim to unintended consequences. Blackbaud suffered a data breach and ended up paying ransom to hackers that were in their system for months. The United Nations shared data about Rohingya refugees without their consent, possibly increasing their vulnerability in returning to Myanmar.

In this Guide
  • Simple, practical tools and principles to help your organization use data responsibly. 
  • Checklist created by the DrivenData team for data scientists to assess the risk of a project at the outset.
  • A tool developed by IDEO to support ethical design with data.
  • How Salesforce developed the first office of Ethical & Humane Use.
  • Help an organization develop a mindset for collecting and using data responsibly.

What does responsible data mean? What is irresponsible data?

What do we mean by responsible use? The Internet Society defines it as “applying ethical principles of transparency, fairness, and respect to how we treat the data that affects people’s lives”. The Responsible Data project defines it as “the collective duty to account for unintended consequences of working with data by prioritizing people’s rights to consent, privacy, security, and ownership when using data and implementing values and practices of transparency and openness”.

Think of responsible use as ensuring that our data practices align to our values. For example, many nonprofit organizations work with what would be described as vulnerable people. Our data efforts should never increase that vulnerability. We shouldn’t collect information that we are unable to protect. Here are some helpful resources on responsible data.

Data Science Projects

While the potential ethical issues that might arise when using data science and artificial intelligence have certainly been in the popular press recently, there has not been as much discussion with respect to how a data science team should incorporate ethics within a project. To help ensure ethics is considered during a data science project, below are resources to identify and address data science ethical conundrums.

Design Principles

Design firm IDEO has developed 4 Ethical Data Design Principles to help those developing data tools. The principles are useful guardrails and reminders as you’re using data to develop products and analysis. They’ve also created a series of Blind Spot Checks that can be used during group brainstorming design sessions to ensure your design process is responsible.

Ethical and Humane Use Leadership

Salesforce developed an Office of Ethical & Humane Use to develop principles and practices for ensuring that their technology is being used in ways that align with the company’s values. It has enabled employees to report unethical uses by customers, developed a toolkit to help teams build with intention, and pushed other technology companies to develop similar offices. 


The resources above will help you implement responsible data use for your organizations. We also suggest reaching out to peer organizations, whose challenges and learning may provide direct and current examples of ways forward. Please feel free to suggest any other guides you found helpful by contacting us and we may incorporate them.

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