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Recommendation playbook
A summary of recommendations with an indication of the effort and timescales involved.
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level
Intention
Implementation
Information
Implication
1
Governance
Strategy
Accountability
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Recommendations
First steps
Document and communicate the positive value of data ethics in your organization.
Be clear of the positive reasons for developing data ethics, and ensure that these are seen as having real value. If ethics are only seen as a restricting factor then it will be difficult to find any real commitment to them over time.
Work with your leadership and employees to explore why ethics really makes a positive difference.
Document and communicate this value, and commit to regularly reviewing it to ensure that it remains relevant.
Effort: 1 Timescale: 1
Know the purposes for collecting and the value you seek to deliver with data.
Provide high level guidance to your organization by clarifying the purposes of your data collection. Communicate the value that you deliver for your customers and users through the use of data and AI.
How would ethical standards impact this potential? Do your ethical principles, or regulatory standards, lead you to avoid specific use cases? Document any specific limits to potential applications.
Effort: 1 Timescale: 1
Document your “legitimate interests”
There are three elements to the legitimate interests basis for data collection. GDPR expects you to:
The legitimate interests can be your own interests or the interests of third parties. They can include commercial interests, individual interests or broader societal benefits. The processing must be necessary. If you can reasonably achieve the same result in another less intrusive way, legitimate interests will not apply. You must balance your interests against the individual’s. If they would not reasonably expect the processing, or if it would cause unjustified harm, their interests are likely to override your legitimate interests.
Keep a record of your legitimate interests assessment (LIA) to help you demonstrate compliance if required.
You must include details of your legitimate interests in your privacy information.
Effort: 1 Timescale: 1
Define a set of data ethics principles.
Take the time to define a set of values and principles that make sense within your organization.
Develop these values and principles with all levels of staff to ensure that they are relevant and resonate with the actual work that people do.
Have a plan to keep your principles up to date.
Effort: 2 Timescale: 2
Getting warmer
Ensure that leadership are seen to embody your values and principles
Ethical standards need to be driven by an organization’s leadership. Leaders must be seen to set the example and champion their principles.
When leadership is seen to ignore the principles and values espoused by the organization, they can actively incentivise unethical behaviour in employees.
Effort: 2 Timescale: 3
Establish a requirement to regularly review data purpose and need at every level.
The understanding of purpose and need should be revisited regularly at every level.
The pace of change in data driven environments requires us to constantly keep an eye on any guidance to ensure that it remains relevant.
Effort: 2 Timescale: 3
Articulate levels of risks and model your response to different situations
There will be different levels of risk involved, depending upon the application, so the levels of risk need to be clearly articulated to allow different responses from the organisation’s ethical protocols.
Effort: 2 Timescale: 2
Establish a long term, iterative, data ethics transformation strategy
Data ethics implementation and operationalisation can never be completed. Data ethics exists on the cutting edge - of technology, business and culture, and to stay effective, any strategy must constantly evolve to incorporate changes.
Adopt an iterative approach to data ethics implementation. Regularly review all your policies and practices, incorporate new ideas and values, pay attention to what is not working.
Data ethics is a lens on your whole organization. Successfully implementing data ethics, at a deep level, is a transformational undertaking. Data ethics should inform, and be imbedded within, any and all transformation projects.
Effort: 3 Timescale: 3
Data ethics is a culture shift, not a technology or compliance project
Data ethics is primarily a culture shift, involving changes in the mindset that drives day-to-day interactions and decision making across your whole organization.
Effort: 3 Timescale: 3
Larger scale efforts
Develop your leadership’s ability to see how technology will change your business
An organization’s leadership cannot effectively establish a strategy to embrace the ethical use of data without an understanding of the impact of technology on it’s future.
Effort: 3 Timescale: 3
Establish a frameworks for unknown risks
Responsible innovation requires a new, anticipatiory and collaborative approach to the risk.
Effort: 3 Timescale: 3
Cultivate ecosystem wide ethical standards
Your ethical policies and standards are only as strong as those you share data with. Work with all your suppliers and partners to establish common ethical standards.
Effort: 3 Timescale: 3
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