Entreprises put data at the heart of their strategies and this place is more and more important in the daily life of consumers and citizens.
In order to avoid any downward slide, entreprises must define their stance on an ethical data usage. Anne-Eole, Senior Consultant in Data Management at Wewyse, explains in this post what a data ethics framework is within an entreprise.
1. The Limits of the Legal Framework: Towards an Ethical Usage of Data by Entreprises
Nowadays, entreprises are alerted of potential ethical risks regarding their data. The issue of setting boundaries for data usage isn’t new. For example, regarding personal data: In France, the ‘’Informatique et Libertés’’ law dates back from 1978. It was reinforced in 2018 with the General Data Protection Regulation (GDPR), which brings in a legal framework for the usage of citizens’ personal data.
The exponential growth of data and its usage (from entreprises, among others) makes those risks even more significant and makes necessary to build a joint set of rules regarding those new issues, such as artificial intelligence. The European Commission has led a project on the matter since March 2018, and published an Artificial Intelligence regulation proposition (AI Act) in spring 2021.
The existence of a legal framework (such as the GDPR today, and the AI Act tomorrow) doesn’t exempt entreprises from thinking about an ethical data usage, as legal doesn’t especially mean ethical.
Moreover, those two major issues – personal data and artificial intelligence – are not the sole issues covered by the ethical side of data. For example, a few other questions should be raised: Can an entreprise be allowed to sell data to a third person who doesn’t share the same values?
Therefore, respecting the GDPR and limiting risks regarding artificial intelligence are necessary, but insufficient conditions to an ethical usage of data within an entreprise.
2. What Is a Data Ethics Framework for an Entrepise?
Let’s get back to basics, without being too academic. The Britannica Encyclopedia describes ethics as ‘’what is morally good and bad, and what is morally right and wrong’’.
An ethical framework therefore defines what is considered as right or wrong behaviour within a group of individuals.
We should highlight the fact that ethics are by nature associated with a culture, a society, a group of individuals. The Chinese social credit system could shock some in Europe, where individual freedom is a founding value, but it actually leans on a strong value of the Chinese society: Harmony of relations in the community – a harmony that is reached by the regulation of individual behaviours, in this case.
Regarding the complexity of the matter, our post will suggest what such a framework could be within an entreprise. In our opinion, a data ethics framework within an entreprise should include values (and principles) the entreprise wants to abide to and promote as well as an operational part for each actor to be able to get involved in the respect of those values.
Despite the complexity of the issue of ethics, we advise entreprises to define a data ethics framework according to their values, and to set internal rules to apply it. Well done is better than well said.
3. Data Ethics Framework and Entreprise: How Does It Work?
A data ethics framework will therefore be based on the values the entreprise wants to promote and abide to.
Entreprise values are the basic go-to
Every entreprise will naturally refer to its own values. For example, French group La Poste promotes six historical values: Openness, consideration, equity, accessibility, proximity, and sense of service. Those values are the reflection of the group’s position, a fully state-owned group also known as the biggest proximity organisation in France.
A data ethics framework can also be based on more collective values, wether they are taken from the culture the entreprise lives in, or from multiple cultures in the case of a multinational organisation. Here, at Wemanity, our culture inspires this tryptic of values: Customer love, spirit of Ubuntu, and agility. They give birth to specific values for Wewyse, the Data Department of Wemanity: Excellence, sharing, creativity, ethics.
Express those values with data in mind
Those values express a more general stance and can rarely be interpreted or used by the enterprise’s collaborators in their daily data usage. For example, a data
processing algorithm can greatly improve a service for most customers, but also have the exact opposite effect on other customers. Must this algorithm be optimized so that the service given to customers as a whole is improved – or corrected in order to limit the bias and allow for a better equity between customers?
Such enlightened decisions are not always possible to make for collaborators if they only look at the entreprise’s values. This is the reason why a framework should be defined and shared.
Collaborators must apply those values on a daily basis
Giving an operational application of those values in a data ethics framework will give every actor several tools to help them apply those values on a daily
basis and in their projects – from the Board of Directors to the data-collecting officer. This could include ethical risk analysis grids, validation processes, alert processes, …always adapted to the collaborator’s responsibility level in the decision-making process.
Within a Data Science squad, each Data Scientist can therefore respect the values by checking the potential risk coming from the new model being developed thanks to an ethical risk analysis grid made for algorithmic uses. In consequence, they can take every measure necessary according to the process defined by the entreprise, which might be discussing the matter with the Head of Data Science, the Product Owner, or even an ethics committee, for example.
4. A Data Ethics Framework Eventually Adds Value to Entreprises
Many entreprises include a department in charge of ethic issues in their organisation. This often takes the form of an ethics committee, even sometimes of a Chief Ethics Officer. Entreprises will use various tools: An ethics chart, a conduct code, a reporting process, the training of collaborators, …
One of the reasons entreprises often refer to for an ethics committee to be put in place is performance. Artelia is convinced that ‘’ethical exemplariness is a key factor to performance and sustainability’’; SANOFI promotes ethics as a true lever for added value. Eric Ducasse, Country Leader at Wemanity France, explains in this post why he’s convinced of the link between ethics and financial results.
But the main reason remains reputation. In order to ‘’preserve their reputation’’, EDF do not impose only a chart, but an ethical conduct as absolute rule for their
employees. Véolia even admit their “reputation, image, and cohesion largely depend on their capacity to act according to their values“.
An entreprise’s reputation has many dimensions: Reputation among their clients, their partners (entreprises or administrations), and collaborators and potential
employees.
Reputation stakes can be seen as risks, but also as opportunities: Promoting the data ethics approach to strengthen clients’ trust; Opting for partnerships (public or private) with organisations with high demands; Improving collaborators’ involvement by granting them a role and responsibility in the entreprise’s reputation.
Defining a data ethics framework can seem to be an adventure for an entreprise, with more or less traps depending on their maturity in their data ethics and governance practices. However, with higher and higher expectations from customers and lawmakers in the matter, this field has a primordial importance for entreprises that consider data as a strategical asset.
Entreprises can get help from partners like Wewyse, who carry those data ethics values to dive with passion into the definition of a data ethics
framework.
In summary:
The main risks regarding the usage of data (especially for big data) are an abusive usage of personal data (data leaks, abusive profiling) and a bias in artificial intelligence algorithms (discrimination escalation, low model explicability). A massive data usage also has a huge environmental impact.
Respecting a data ethics policy allows the organisation to limit deviance risks and reputational risks among their customers, partners, funders, and collaborators. It’s even a way to stand out from competitors and create a favorable innovation framework while respecting their own values.
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