Systemic Data Ethics Framework

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SDE Strategy Guide

The Systemic Data Ethics Guide

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The Guide is a work in progress. Created from distilled, aggregate information from multiple sources, this represents an example of the kind of insight that a structured franework makes possible.

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The Systemic Data Ethics Guide

The Systemic Data Ethics framework is a stable, whole system, view of data ethics. Instead of defining principles, it establishes a set of 12, interconnected, areas of practice called “domains”.

Select a domain to explore (Strategy is the only complete option right now)

level

Intention

Implementation

Information

Implication

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Strategy

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The organization’s principles, and it’s approach to the opportunity and risks related to using and commercialising data.

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Systemic framework attributes

Within the Systemic Data Ethics framework, the

Strategy

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domain is defined by combining these different attributes.

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Level:

Governance

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The work required at an organizational level to use and manage data and AI within an economic or social context. This includes a business decisions and it’s strategy to commercialise data, an organization’s structure, the way in which it communicates (and listens to) the public as well as the long term, social and environmental impact of any data or AI use.

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(Matrix rows)

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Dimension:

Intention

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The ethical decisions required to achieve goals and objectives, at an individual/design level, day-to-day operations and strategy.

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(Matrix columns)

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Overview

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Tags

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legitimate interestespurposeimproper userisksdata practicescultural valuescompliancelawethicsfuture-proofpublic trustbenefitAIchangetechnologyengagementmisconductwork environmentresponsibilitygovernancedecentralisationresponsible innovationanticipationreflexivitybehaviourresiliencefeedback loopsmanagementdisagreementalignment Show 7 more

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Where to start

First steps

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Compliance actions

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Document your “legitimate interests”

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Relevant regulations

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GDPR

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Understanding the

Strategy

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domain

Ethical challenges

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What are we willing to sacrifice for our principles and values? It’s all very well shouting about our values, but, when it comes down to a real decision between principles or profit.... at which point do we choose to take the money? When something does go wrong, how will we act? Assume that you will miss something, and that a data breach or ethical failure will happen, no matter how well you prepare. How will your organization respond? Are we choosing to build tools that could be used to harm people or society? How clearly can we articulate the commercial value of data ethics to our business? How will we respond in the event of a major data breach? Do we know what “ethical data use” looks like in our sector/industry?

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The big questions to answer

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How does data, and it’s ethical use, relate to our business model and commercial interests? How do we provide guidance to our staff on what ethical conduct and data use looks like in our context? What impact will technology and data have on the way in which we do business and make decisions? How do does an organization successfully evolve to integrate data ethics at it’s core? How do we approach the uncertainty and risks related to working and innovating with data and AI? How does data ethics impact our business ecosystem?

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The primary benefits

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Employee engagement Competitive advantage Increased public trust

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Further development

Actions

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Document and communicate the positive value of data ethics in your organization. Define a set of data ethics principles. Know the purposes for collecting and the value you seek to deliver with data. Establish a requirement to regularly review data purpose and need at every level. Articulate levels of risks and model your response to different situations

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Projects

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Establish a long term, iterative, data ethics transformation strategy Develop your leadership’s ability to see how technology will change your business Cultivate ecosystem wide ethical standards

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Considerations

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Ensure that leadership are seen to embody your values and principles Data ethics is a culture shift, not a technology or compliance project Establish a frameworks for unknown risks

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Dive into the detail

Our foundations go deep. Select a question from the list below to explore the key recommendations for the

Strategy

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domain. Once selected, scroll past this table to read on.

Select a question to dive into

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Action: select big

Summary

Recommendations

sources

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Recommendations

recommendation

detail

sources

Effort

Timescale

benefits

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Benefits

Benefit

Summary

Source

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Cultural behaviours

behaviour

description

Admit mistakes

Feel comfortable admitting when you’re are wrong and when things have not gone to plan.

Open to ideas

Don’t assume you know the answers before you understand the detail

Being allowed to fail

Feel that you are able to safely try something new, even if you are not sure if it will work.

Honesty

Be able to say the scary things

Transparency

Being open and accountable

Self responsibility

Taking responsibility for one’s actions

Social awareness

Being aware of the impact of actions on society

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Resources

Tools

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Description

Author/Organization

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Sources

The Systemic Data Ethics structure allows us to categorise “aspects” of other data ethics frameworks and systems to build a big, whole system picture of each domain, and data ethics in general.

As we process each of our sources, we identify key sections of text, and assign each to a level and dimension. This process is, by definition, a little blurry. Ideas will often apply to multiple domains, but we are generally able to be sufficiently accurate.

Principle sources

These sources focus primarily on this domain.