Professional Ethics for Statistical Practice in Europe

24 September 2024

Introduction

Statistical methods are powerful tools that have the potential to generate great benefits in various areas of application. They can provide information, help prepare decisions based on the best evidence, advance the empirical foundation of science and objectify public discourse. However, they can also be misapplied and misused to create confusion, to fabricate false 'alternative facts' and to create doubt in enlightenment, rationality and institutions. Statistical methods use data of individuals, families, companies whose interests in sensitive information must be protected. At the same time, the aim is to provide access to data, facts and figures to as many people as possible in a way that is FAIR (GOFAIR 2016; Wilkinson 2016) in the spirit of open data. Recognised ethical principles apply to scientific research, which can be of a procedural nature (reproducibility, no falsification or plagiarism, etc.) or also address intrinsic duties of ethically sound research conduct (choice of equations and variables, analysis of data, handling of error) or extrinsic risks (impact of research results on others, risks and side effects in application, dual use) (Tuana 2010).

As soon as statistics meets applications, the practitioner, be he or she from the statistics profession or from other scientific disciplines or professional areas, therefore has a great responsibility. Statistical practitioners should be prepared for this, which means that the ethical dimension with its values and principles must be taught in professional education alongside methodological knowledge and skills training. The Federation of European National Statistical Societies FENStatS is taking a step in this direction and presenting its initiative for professional statistical ethics in Europe. The approach draws on the corresponding Declaration of the International Statistical Institute (ISI) and promotes it for use in Europe.

The Purpose of Statistical Ethics - FENStatS' Ethical Mission

The key question is, why do statisticians need (professional) ethics at all? In the course of the rapid change in the data ecosystem, this question is being raised anew. Luciano Floridi / Mariarosaria Taddeo (Floridi and Taddeo 2016) and David Hand (Hand 2018) have developed convincing thoughts on this and have provided useful pointers, such as

"Navigating between the Scylla of social rejection and the Charybdis of legal prohibition in order to reach solutions that maximize the ethical value of data science to benefit our societies, all of us and our environments is the demanding task of data ethics." (Floridi and Taddeo 2016: 2)

"As far as ethical codes for data collection, manipulation, and use are concerned, these have various functions, including things such as the following:
• providing guidance on how to behave in difficult circumstances;  
• preserving privacy in a way that users and the public will find acceptable;  
• ensuring that data are used in such a way as to benefit the public;  
• reassuring customers, the public, and others about an organization’s integrity; and  
•reassuring employees that they work for a trust-worthy organization." (Hand 2018: 178)

 And

"However, the context of data science is so vast and diverse, and is changing so rapidly over time, that we cannot hope to put in place precise regulations. There cannot be a single and simple universal set of rules, and unexpected and unforeseen circumstances are certain to arise. The best we can hope for are some ethical principles that have to be interpreted or instantiated in particular applications. That is, the principles must be mapped to low-level guidance, and this is likely to be application specific." ... "At the highest level, the principles include such things as integrity, honesty, objectivity, responsibility, trustworthiness, impartiality, nondiscrimination, transparency, accountability, fairness, robustness, resilience, usability, efficiency, and independence. All good and desirable characteristics. These are then refined into lower, but still high-level principles." (Hand 2018: 179)

Obviously, these ethical values and principles are to be understood hierarchically, in such a way that the fundamental ones (i.e. values) should be as general as possible and thus robust against changes (e.g. through technologies) over time, while the guidelines derived from them are more precise, but also more in need of evolution/adaptation; similar to the situation in legal systems.

Depending on the area of application in which statisticians work, they will also encounter the ethical guidelines and specifications that are relevant there, be they general guidelines for scientific research (Tuana 2010), rules for professional conduct in the neurosciences (Society for Neurosciences 2024) or official statistics (United Nations 2023), to name but a few.

Which level of the ethical hierarchy and which characteristics are suitable depends on the intended purpose: Whether a relatively open conveying of values is intended (e.g. in statistics training) or whether, as in the Code of Practice of the European Statistical System (Eurostat 2018), binding rules are required with regard to compliance with which reviews and certifications are to be carried out.

FENStatS is focussing on the first level. The following objectives are being pursued:

• to support practitioners from a wide range of professions in dealing with questions and dilemmas as professionally and ethically correct as possible,
• to promote the awareness of professional ethics in European statistics (in research, teaching and all areas of application),
• to establish a binding European reference framework for certification by the European Statistical Accreditation,
•  to foster and facilitate international co-operation between scientists and teachers of statistics in Europe and outside Europe.
• Last but not least, FENStatS is also committed to enhancing the reputation of statistics and statisticians by promoting high professional standards.

Alignment and Harmonisation with the International Standard

FENStatS ensures that its objectives are compatible with international standards. For this reason, reference is made to the ISI Declaration of Professional Ethics (International Statistical Institute (ISI) 2023). This Declaration of Ethics dates back to the 1980s with a current version from 2010, which was updated in 2023 during the World Statistical Congress in Ottawa.

The ISI’s Declaration on Professional Ethics consists of a statement of Shared Professional Values and a set of Ethical Principles that derive from these values. The Declaration emphasises the responsibility of statisticians:

“Although not explicitly stated, the Principles inherently reflect the obligations and responsibilities of – as well as the resulting conflicts faced by – statisticians to forces and pressures outside of their own performance, namely to and from:
• Society,
• Employers, Clients, and Funders,
• Colleagues,
• Subjects.
In carrying out his/her responsibilities, each statistician must be sensitive to the need his/her actions are consistent with the interests of each group and do not favour any group at the expense of any other, or conflict with any of the Principles.” (International Statistical Institute (ISI) 2023)

Ethical Principles – Declaration on Professional Ethics

In parallel to the ISI Declaration, the Ethical Guidance for Statistical Practice of the American Statistical Association ASA (American Statistical Association (ASA) 2022) and the Code of Conduct of the Royal Statistical Society (Royal Statistical Society 2014) are well known in the statistical community and used by scientists. However, there should hardly be any difficulties, as these guidelines are very much in line with the content of the ISI Declaration. “Two documents from two professional statistical organizations should align closely, and these do. There is strong alignment between the ASA EG and the ISI DPE.” (Tractenberg and Park 2023: 17)

Next steps towards a FENStatS Declaration on Professional Ethics (DPE)

This approach were presented to the FENStatS General Assembly in September 2024 with the request that it be supported and approved. Following this formal decision, the Executive Committee will develop and deploy proposals for implementation, communication and promotion of the FENStatS DPE. This will also involve cooperating closely with the ISI in order to utilise synergies as far as possible. Finally, the content of the ethics statement will be used in future activities relating to the training of statisticians.

 References

American Statistical Association (ASA). 2022. 'Ethical Guidance for Statistical Practice', ASA. https://www.amstat.org/docs/default-source/amstat-documents/ethicalguidelines.pdf.

Eurostat. 2018. "European Statistics Code of Practice - For the National Statistical Authorities and Eurostat." In, 20. Luxembourg: Publications Office of the European Union.

Floridi, Luciano, and Mariarosaria Taddeo. 2016. 'What is data ethics?', Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374: 20160360.

GOFAIR. 2016. 'FAIR PRINCIPLES', GOFAIR, Accessed 24.06.2024. https://www.go-fair.org/fair-principles/.

Hand, David J. 2018. 'Aspects of Data Ethics in a Changing World: Where Are We Now?', Big Data, 6.

International Statistical Institute (ISI). 2023. 'Declaration on Professional Ethics', ISI, Accessed 14.03.2024. https://isi-web.org/declaration-professional-ethics.

Royal Statistical Society. 2014. 'Code of Conduct', RSS, Accessed 04.07.2024. https://rss.org.uk/about/policy-and-guidelines/code-of-conduct/.

Society for Neurosciences. 2024. 'Professional Conduct', SfN, Accessed 24.06.2024. https://www.sfn.org/about/professional-conduct.

Tractenberg, Rochelle E., and Jennifer Park. 2023. "How does international guidance for statistical practice align with the ASA Ethical Guidelines for Statistical Practice?" In arXiv pre-print server.

Tuana, Nancy. 2010. 'Leading with ethics, aiming for policy: new opportunities for philosophy of science', Synthese, 177: 471-92.

United Nations. 2023. 'Fundamental Principles of National Official Statistics', UN, Accessed 01.02.2024. https://unstats.un.org/unsd/dnss/gp/fundprinciples.aspx.

Wilkinson, Mark D., et al. 2016. 'The FAIR Guiding Principles for scientific data management and stewardship', Scientific Data, 3: 160018.