Data Ethics Framework
Data ethics is an emerging branch of applied ethics which describes the value judgements and approaches we make when generating, analysing and disseminating data. This includes a sound knowledge of data protection law and other relevant legislation, and the appropriate use of new technologies. It requires a holistic approach incorporating good practice in computing techniques, ethics and information assurance.
The Data Ethics Framework consists of 3 parts:
Your project, service or procured software should be assessed against the 7 data ethics principles.
1. Start with clear user need and public benefit
Using data in more innovative ways has the potential to transform how public services are delivered. We must always be clear about what we are trying to achieve for users - both citizens and public servants.
2. Be aware of relevant legislation and codes of practice
You must have an understanding of the relevant laws and codes of practice that relate to the use of data. When in doubt, you must consult relevant experts.
3. Use data that is proportionate to the user need
The use of data must be proportionate to the user need. You must use the minimum data necessary to achieve the desired outcome.
4. Understand the limitations of the data
Data used to inform policy and service design in government must be well understood. It is essential to consider the limitations of data when assessing if it is appropriate to use it for a user need.
5. Ensure robust practices and work within your skillset
Insights from new technology are only as good as the data and practices used to create them. You must work within your skillset recognising where you do not have the skills or experience to use a particular approach or tool to a high standard.
6. Make your work transparent and be accountable
You should be transparent about the tools, data and algorithms you used to conduct your work, working in the open where possible. This allows other researchers to scrutinise your findings and citizens to understand the new types of work we are doing.
7. Embed data use responsibly
It is essential that there is a plan to make sure insights from data are used responsibly. This means that both development and implementation teams understand how findings and data models should be used and monitored with a robust evaluation plan.
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The Data Ethics Framework consists of 3 parts:
- the data ethics principles
- additional guidance for each principle in the framework
- a workbook to help your team record the ethical decisions you’ve made about your project
Your project, service or procured software should be assessed against the 7 data ethics principles.
1. Start with clear user need and public benefit
Using data in more innovative ways has the potential to transform how public services are delivered. We must always be clear about what we are trying to achieve for users - both citizens and public servants.
2. Be aware of relevant legislation and codes of practice
You must have an understanding of the relevant laws and codes of practice that relate to the use of data. When in doubt, you must consult relevant experts.
3. Use data that is proportionate to the user need
The use of data must be proportionate to the user need. You must use the minimum data necessary to achieve the desired outcome.
4. Understand the limitations of the data
Data used to inform policy and service design in government must be well understood. It is essential to consider the limitations of data when assessing if it is appropriate to use it for a user need.
5. Ensure robust practices and work within your skillset
Insights from new technology are only as good as the data and practices used to create them. You must work within your skillset recognising where you do not have the skills or experience to use a particular approach or tool to a high standard.
6. Make your work transparent and be accountable
You should be transparent about the tools, data and algorithms you used to conduct your work, working in the open where possible. This allows other researchers to scrutinise your findings and citizens to understand the new types of work we are doing.
7. Embed data use responsibly
It is essential that there is a plan to make sure insights from data are used responsibly. This means that both development and implementation teams understand how findings and data models should be used and monitored with a robust evaluation plan.
Details >>
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