Core Learning Stream

Operationalising Data Ethics

Why does operationalising data ethics matter?

Although data ethics is a relatively new focus for most organisations, “formal” initiatives appear to have had little positive impact on consumer trust. In fact, Pew Research Centre’s 2019 privacy study shows that US consumers are more concerned than ever about how public and private organisations are using data about them. Study respondents believe their data is less secure, that data collection poses more risks than benefits, and that it is not possible to navigate their daily lives without being surveilled.

This consumer discomfort has led to a data trust deficit, so that the trust an individual places in a brand and the trust they place in its data practices are different. In most cases, data trust is lower than brand trust.

Although this is a complex issue, we believe that the limited scope of the common principles-based approaches to data ethics – which are primarily limited to the ethics of data collection and use – make it difficult for organisations to improve the trustworthiness of their practices. It’s a relatively narrow approach that shifts focus away from the bigger issues that have an impact on trust, like incentives misalignment. Perhaps this is why many are calling out Big Tech for ethics washing. Or why we are calling out Responsible Innovation for ethics washing.

We’ve, therefore, extended the scope of data ethics initiatives to focus on an organisation’s entire operating model, considering the ways in which data has an impact on decision making, specific actions and real-life outcomes. This includes everything from an organisation’s business model and incentives structures, through to product design and development, marketing and customer support and even employee training.

In addition to this extension of scope, we propose that organisations should move beyond feel-good statements and commit to operationalising data ethics frameworks. A data ethics framework, as we define it, is the consistent process an organisation executes to decide, document and verify that its data processing activities – both the intent and real-life outcomes of those activities – are socially preferable.

If we are to close the data trust gap and design a more socially preferable future, organisations must become more adept at data ethics. If you believe this too, you’ve come to the right place.


Operational approaches to data ethics make ethical decision making and follow through action easier to do for people, regardless of their functional role or where they ‘sit’ in an organisation.

This stream is for:

  1. Executives
  2. Applied Ethicists
  3. ‘Tethicists’ (yup, Gavin Belson, we’re looking at you)
  4. AI Ethicists
  5. Responsible Innovation practitioners
  6. Data Scientists
  7. Machine Learning Engineers
  8. Designers
  9. Researchers
  10. Product Managers
  11. Software Engineers
  12. Marketers
  13. Privacy practitioners
  14. Data Protection practitioners
  15. Lawyers
  16. Students, and
  17. Anyone else who wants to help design a more socially preferable future where tech really is a force for good

Your Instructors For This Stream

Nathan Kinch

Nathan is a 3x entrepreneur, impact focused startup investor, speaker, writer and educator.

He’s spent most of his career designing organisations for the qualities of trustworthiness. Most of his days revolve around finding effective pathways to scale activities that have positive impact.

He lives on the sunny Gold Coast. 

Mathew Mytka

Mat is an autodidact, adept generalist and co-founder of Greater Than Learning. He’s spent 26 years working across diverse roles and exploring the systems levers that catalyse positive change.

He’s led cross functional product teams, and trustworthiness and data ethics initiatives with everything from complex fortune 500 companies through to early stage start ups.

Course Difficulty Levels

Across the platform you’ll find courses to suit your skill and knowledge level. These will support you in getting started with new approaches that support you and the organisations you work with to enhance the qualities of trustworthiness.



These courses are aimed to get you started. They are appropriate for someone just starting out on the ethical change journey through to seasoned change makers. They get you hands on with the basics of new models, methods and techniques to making the world a better place.



These courses are aimed to take you deeper. They build on primer courses and take you deeper into concepts and the practicalities of using different toolkits. They support you in expanding your working knowledge of a subject area and enhancing the practical skills you already have.



These courses are for the seasoned practitioner. They build on primer and fundamentals courses but require extensive experience in the field. They bring additional subject matter experts to dive into the day to day challenges of making change happen in a modern business environment.

A Primer To Operationalising Data Ethics

This course supports you in your journey to move beyond feel good statements and principles.

It covers some of the market context to why so many initiatives are failing. The overlaps, the duplication of effort and the frameworks that have fallen short of creating real positive change.

You’ll get to explore a tangible and concrete approach to operationalising data ethics with other practitioners.

You’ll reflect and make sense of this with a community of people like you all working towards making the world better.

This primer course has 5 lessons with each lesson taking about 20 minutes each. These lessons are designed to be done every 2 days and are combined with short reflection and reinforcement activities in between.


Each lesson will:

  • Introduce you to a new concept
  • Help you reinforce what you’ve learned
  • Support you in practically applying what you’ve learned, and
  • Encourage active community engagement and social learning.

Here’s a brief overview of each lession in this Primer Course.

The Market Context

You’ll learn the definition of data ethics, develop a better understanding of the shortcomings of current approaches and get a clearer sense of the impact these shortcomings have on people, society and markets. You’ll walk away with more confidence to have productive discussions and a sense that you’re not alone.

Why Initiatives Are Failing

You’ll learn more about the shortcomings of principles based approaches and the various considerations that must be factored into whole of organisation approaches. You’ll walk away better prepared to identify common pitfalls and how to overcome them.

An Operational Approach
This is your first introduction to the concept of an operational Data Ethics Framework, its definition and its key functions. You’ll begin learning about social preferability as the benchmark and how you can meaningfully engage diverse stakeholders to test for it. You’ll wrap up with more confidence to talk about these approaches to your colleagues.
The Ideal Core Team
Although ethics is everyone’s job, you’ll be introduced to an ideal cross-functional data ethics team composition. You’ll learn simple tips to communicate with these team members and walk away ready to discuss how you can work with them to get started.
Operationalising data ethics isn’t always easy. There will be push back. Perhaps a lot of it. This lesson will help you understand common challenges and pitfalls. It’ll also help you prepare to define the tiny first steps you’ll need to take to start the journey and demonstrate meaningful progress.

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