In the fifth instalment of the ‘Switzerland as a Hub for Innovation’ series, Philip Michel of Swiss Post Advertising and Dr Stefan Oglesby, President of Swiss Insights, demonstrate how companies can use data responsibly. The focus is on Swiss Insights’ Data Fairness Label, which is designed specifically to help SMEs critically scrutinise data-driven decisions.
Using Swiss Post Advertising as an example, the authors explain how data fairness considerations can be integrated into existing workflows. The article also demonstrates why data protection and data security alone are not enough, and how even simple screening questions can contribute to more responsible data use.
This article in KMU-Magazin forms part of the series ‘Switzerland as a Hub for Innovation’, which emerged as a follow-up to the SATW publication ‘AI Orientation: Challenges and Opportunities for Swiss SMEs’.
The content was developed in collaboration with stakeholders from the SAIROP (Swiss AI Research Overview Platform) network and the SATW’s network of experts. SAIROP promotes collaboration between research, industry and public administration and supports knowledge transfer within the Swiss AI ecosystem.
Fair use of data means that organisations must not only check that it is legally permissible, but must also take into account the purpose, the data basis and the potential implications of any use. This includes, in particular, the question of whether individual people or groups might be unintentionally disadvantaged or excluded.
The Data Fairness Label provides a framework for the responsible handling of data. It helps organisations to systematically scrutinise assumptions, risks and responsibilities in data-driven applications and to document decisions in a transparent manner.
Models based on existing customer data may incorporate any biases present in that data. Furthermore, calculated interests or affinities are often based on probabilities rather than on established knowledge. This creates a risk that certain groups of people may be unintentionally disadvantaged or excluded.
Data protection and data security deal, amongst other things, with the lawful handling of data, access rights and protection against misuse. Data fairness complements these perspectives and examines why data is used for a particular purpose, what assumptions underlie this, and what consequences may result.
SMEs can start by using a simple questionnaire. It is crucial to clarify the purpose and origin of the data before each use, to assess any potential impacts and to define responsibilities. These questions can be integrated into existing workflows without the need to set up additional, comprehensive governance structures.
| Role | Title + Name |
|---|---|
| Text by | Philip Michel, Stefan Oglesby |
