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Glossary

Data ethics

Data ethics covers the ethical and moral obligations of collecting, sharing, and using data, focused on ensuring that data is used fairly, for good.

What is data ethics?

Data ethics covers the ethical and moral implications of collecting, sharing, and using data, especially personally identifiable information. It is particularly focused on any negative impacts that data projects might have on individuals, groups or wider society. It aims to ensure that data is used fairly, in a non-discriminatory way.

Adopting a data ethics approach at the beginning of any data project requires understanding all ethical considerations around the data being used, and putting in place good practice to demonstrate that these considerations are being met. Data ethics requires a responsible, holistic approach that brings together technology, ethics and strong information governance practices.

While data ethics is related to legislation around personal information (such as GDPR and CCPA), it is not limited to achieving regulatory compliance. Being ethical about data use goes beyond meeting legislation – it covers employee/company conduct around how data is collected, shared and used. For example, it may be legal to use freely-given consumer data to segment your customer base, but unethical if it is then used to deliver different levels of service dependent on factors such as race, sex or location.

Why is data ethics important?

Using information ethically within decision-making has always been important. However, two factors have made data ethics business-critical:

  • Data volumes. There has been an explosion in the amount of data available to organizations, both collected themselves, and sourced from third-parties. It is not always clear where this information has come from, particularly in the case of personal information, and what permissions have been provided for its reuse.
  • Artificial intelligence. Organizations are increasingly using machine learning and artificial intelligence algorithms to make sense of data and take automated decisions based on data analysis without involving human oversight. This can lead to issues around fairness and discrimination, even if these are unintended consequences of how data is used.

What are the principles of data ethics?

Everyone who handles data should be well-versed in the basic principles of data ethics and apply them at all stages of a data project:

  • Transparency – is it clear what data is being used for, how and where it is being stored, and is this information freely available to all?
  • Accountability – is there strong oversight and management of data within the project to ensure it is used ethically?
  • Fairness – will your use of data have discriminatory consequences for particular groups, even if this is unintended?
  • Ownership – individuals have ownership over their data and how it is used. Have you received their informed consent for its use in your particular context?
  • Privacy – is personal data being protected and kept secure, so that any identifiable information is not available to unauthorized users? Has it been anonymized to further protect privacy?
  • Intention – do you have a clear reason for using particular datasets? Is all the information you have collected relevant, necessary, and appropriate to your stated intention?
  • Outcomes – have you investigated any potentially negative, harmful or discriminatory outcomes from your use of particular data? It is vital to address this at the beginning of a project, not when any impacts have occurred.

What are the advantages of focusing on data ethics?

Data analysis and reuse provides organizations with the opportunity to deliver a better experience to customers and citizens, to increase innovation and to meet public/societal needs. However, if this data is not used ethically all of these benefits will be undermined.

The advantages of taking an ethical approach include:

  • Greater trust and higher revenues. Showing that you use customer/citizen data responsibly strengthens trust and increases loyalty. In turn, customers indicate that they are more willing to buy from companies that they trust, boosting the bottom line.
  • Meet legislative requirements. Data ethics supports organizations in meeting their regulatory requirements around data use. It therefore helps ensure compliance and the avoidance of legal challenges and punitive fines.
  • Protect organizational reputation. There is increasing awareness and concerns around how personal data is used by businesses and other organizations. Even if it does not break any regulations, failing to use data ethically and fairly has a significant impact on corporate reputation, impacting sales, staff retention and share price.

How can organizations embrace data ethics?

While it is an emerging discipline, there are multiple sources of best practice for organizations looking to embrace data ethics. These include clear frameworks for the private and public sector, including:

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