Data ethics

While it may seem like the fields of data and ethics might not have much in common, in reality, they do. Despite tough regulations, data security and privacy breaches have become common in today’s world owing to the extensive availability of data. For instance, on April 14 2020, the credentials of over 5,000,000 Zoom teleconferencing accounts were found on the dark web for sale. [1] This context has prompted the induction of data ethics into data science.

What is data ethics?

According to Oxford professors and philosophers Luciano Floridi and Mariarosaria Taddeo:

’Data ethics is a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing and use), algorithms (including artificial intelligence, artificial agents, machine learning and robots) and corresponding practices (including responsible innovation, programming, hacking and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values).’ [2]

In simple terms, data ethics involves the study of the ethical concerns that arise during the use of data.

The need for data ethics

With the extensive availability of free data, there is an increased possibility for data privacy and security concerns. The General Data Protection Regulation (GDPR) passed by the European Union (EU) on data protection and privacy is an initiative specifically designed to ensure data privacy and security on the internet. Similar to Governments, organisations also deal with large amounts of customer data, making them susceptible to issues pertaining to data ethics.

In any organisation, people decide what data is collected, included, used, and excluded. This gives enormous power to the people who are handling data. However, with great power comes great responsibility. Hence, organisations must have a clear moral and ethical position for data governance supported by a set of centralised rules and regulations to avoid any form of data abuse, both conscious or unconscious.

The role of the data scientist in data ethics

In a 2016 report titled Building Digital Trust, [3] Accenture recommended a universal code of data ethics. The 12 principles in this code drive data ethics holistically at an organisational level, and integrate the imperative of data ethics into a data scientist’s role.

The 12 principles are as follows:

1. The highest priority is to respect the persons behind the data.
2. Account for the downstream uses of data sets.
3. The consequences of utilising data and analytical tools today are shaped by how they’ve been used in the past.
4. Seek to match privacy and security safeguards with privacy and security expectations.
5. Always follow the law, but understand that the law is often a minimum bar.
6. Be wary of collecting data just for the sake of having more data.
7. Data can be a tool of both inclusion and exclusion.
8. As far as possible, explain methods for analysis and marketing to data disclosures.
9. Data scientists and practitioners should accurately represent their qualifications (and limits to their expertise), adhere to professional standards, and strive for peer accountability.
10. Aspire to design practices that incorporate transparency, configurability, accountability, and auditability.
11. Products and research practices should be subject to internal (and potentially external) ethical review.
12. Governance practices should be robust, known to all team members, and regularly reviewed.

Now that you’ve learned about data ethics and the role of a data scientist in establishing data governance within an organisation, you’ll have an opportunity to share your thoughts on data ethics.

References

1. Abrams L. Over 5000,000 Zoom accounts sold on hacker forums, the dark web [internet]. Bleeping computer; 2020 Apr 13. Available from: https://www.bleepingcomputer.com/news/security/over-500-000-zoom-accounts-sold-on-hacker-forums-the-dark-web/
2. Floridi L, Taddeo M. What is Data Ethics? [Internet]. Rochester, NY: Social Science Research Network; 2016 Nov 14. Report No.: ID 2907744. Available from: https://papers.ssrn.com/abstract=2907744
3. Building digital trust: The role of data ethics in the digital age [PDF]. Accenture; 2016. Available from: https://apo.org.au/sites/default/files/resource-files/2016-06/apo-nid71946.pdf