Ethics is the expression of values in actual behaviour. So when you want to do data ethics it is about practical issues, and reconsidering entrenched routines. In the past few weeks I successfully challenged some routine steps in a clients’ organisation, resulting in better and more ethical use of data. The provision of subsidies to individuals is arranged by specific regulations. The regulations describe the conditions and limitations for getting a subsidy, and specify a set of requirements when you apply for a subsidy grant. Such subsidy regulations, once agreed have legal status.

With the client we’re experimenting in making it vastly less of an effort for both requester and the client to process a request. As only then does it make sense to provide smaller sized subsidies to individual citizens. Currently there is a rather high lower limit for subsidies. Otherwise the costs of processing a request would be higher than the sum involved, and the administrative demands for the requester would be too big in comparison to the benefits received. Such a situation typically leads to low uptake of the available funding, and ineffective spending, which both make the intended impact lower (in this case reducing energy usage and CO2 emissions).

In a regular situation the drafting of regulation and then the later creation of an application form would be fully separate steps, and the form would probably blindly do what the regulations implies or demands and also introduce some overshoot out of caution.

Our approach was different. I took the regulation and lifted out all criteria that would require some sort of test, or demands that need a piece of information or data. Next, for each of those criteria and demands I marked what data would satisfy them, the different ways that data could be collected, and what role it played in the process. The final step is listing the fields needed in the form and/or those suggested by the form designers, and determining how filling those fields can be made easier for an applicant, (E.g. having pick up lists)

A representation of the steps taken / overview drawn

What this drawing of connections allows is to ask questions about the need and desirability of collecting a specific piece of data. It also allows to see what it means to change a field in a form, for how well the form complies with the regulation, or which fields and what data flows need to change when you change the regulation.

Allowing these questions to be asked, led to the realisation that several hard demands for information in the draft regulation actually play no role in determining eligibility for the subsidy involved (it was simply a holdover from another regulation that was used as template, and something that the drafters thought was ’nice to have’). As we were involved early, we could still influence the draft regulation and those original unneeded hard demands were removed just before the regulation came up for an approval vote. Now that we are designing the form it also allows us to ask whether a field is really needed, where the organisation is being overcautious about an unlikely scenario of abuse, or where it does not match an actual requirement in the regulation.

Questioning the need for specific data, showing how it would complicate the clients’ work because collecting it comes with added responsibilities, and being able to ask those questions before regulation was set in stone, allowed us to end up with a more responsible approach that simultaneously reduced the administrative hoops for both applicant and client to jump through. The more ethical approach now is also the more efficient and effective one. But only because we were there at the start. Had we asked those questions after the regulation was set, it would have increased the costs of doing the ethically better thing.

The tangible steps taken are small, but with real impact, even if that impact would likely only become manifest if we hadn’t taken those steps. Things that have less friction get noticed less. Baby steps for data ethics, therefore, but I call it a win.

7 reactions on “Data Ethics Baby Steps

  1. Ton, see also twitter @StevenvtVeld

    My remark on this text is you are describing availability and use of data as a basis to introduce data ethics. What I am missing is the data itself, even more if data is in fact information. You’ll see the notion of ethics becomes much stronger if you would create a conceptual basis to define the data itself, and you will get to a much stronger basis to get to ethics.

    • Wat bedoel je met ‘je vergeet de data / info zelf’? Ik heb het voorbeeld misschien te veel uitgekleed en geabstraheerd, maar ik wilde vooral het punt maken dat je informatiekundig naar ’n Regeling in wording moet kijken. Als je pas naar je informatiekundig ontwerp gaat kijken nadat een Regeling van kracht is geworden, ben je te laat en móet je die tekst als uitgangspunt nemen. Neemt niet weg dat we ook kijken naar wat er uiteindelijk verzameld wordt, hoe en waarom, of dat allemaal niet anders kan, en welke aspecten rond bewaren, automatische afwegingen, en bijvoorbeeld minimalisatie van wat je een aanvrager wilt laten invullen. Maar als in een Regeling harde eisen staan voor het aanleveren van documenten die geen rol spelen in de besluitvorming op een aanvraag in het kader van die Regeling, dan ben je al te laat. Het gaat me dus om het pleidooi dat je het schrijven van een Regeling hand in hand moet laten gaan met het testen van en reflecteren op hoe zich dat in dataverzameling en gebruik vertaalt. Vooral omdat de praktijk bij het opstellen van een regeling is een vorige regeling als sjabloon te hanteren, zonder reflectie op nut en noodzaak van geformuleerde eisen. En dito aan de kant van de aanvraagprocedure waar het ‘natuurlijk nodig is’ sommige dingen te bevragen, zonder daar bij elke toepassing opnieuw expliciete onderbouwing bij te vereisen.

Reposts

  • R.A. Posthumus
  • Willy Tadema

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.