Towards more inclusive research practise
As Inge Keizer from Service Design Campus pointed out:
Research is fundamental to support strategic design decisions and the development of products, services, interventions and systems. It builds understanding and empathy and generates reliable data, insights and new knowledge.
For this to happen in the best way, we need to mind some aspects of our research process. There are many things to consider, but I’ll point two things, how we do recruitment and awareness of our own bias while doing research.
Recruitment
As we work with our population samples, we need to make sure that our samples represent our population accurately. I often see (and I did it myself in the past) that researchers disregard some essential criteria when screening for participants. Those criteria are gender, race and demographics. Sadly, it’s not hard to find examples where we see some prejudice based on these types of criteria:
- Black Americans face racial bias in the healthcare system. Both from doctors and decision-making algorithms.
- In the publishing world, we see authors from less developed countries or low credited institutions getting their papers rejected because there is a prejudice that works from these authors are of less quality.
- In the scientific world (and I bet in many more areas), the pandemics affected men and women differently.
COVID-19 has not affected all scientists equally. A survey of principal investigators indicates that female scientists, those in the ‘bench sciences’ and, especially, scientists with young children experienced a substantial decline in time devoted to research. (Source)
As we can see, gender, race, and demographics affect the way people experience something. We need to take these criteria into account if we are to be truly inclusive in building our products and services.
My advice is, either you are recruiting your sample or turning to a third party to do the recruitment for you, be rigorous about including diverse people. Don’t make that optional.
Bias while doing research
Another aspect we need to be mindful of is our own biases when doing research. There are a lot of biases that affect the way we do research, but I’m just going to highlight two that I think are most relevant.
Implicit Bias
Implicit bias is the unconscious attribution of particular qualities, attitudes, and behaviours to a social group member. We often call this bias is stereotyping.
In the context of user research, this can lead us to behave in specific ways that might not be correct, as we may have preconceived notions and generalisations about the social group to which the person we are talking belongs.
Before talking to this person, a good practice might be to list all preconceived notions you have about the social group to which the person belongs. This way, you are aware of them, and you can act accordingly.
Fundamental Attribution Error
In social psychology, the fundamental attribution error describes the tendency to over-value personality-based explanations for someone’s behaviours while under-valuing situational reasons for those behaviours. In other words, when explaining someone else’s behaviour, we assume they acted a certain way because of the type of person they are, not the circumstances they were in. Reality is, most behaviour is circumstantial, but most of the time, in design, we end up categorising people based on personality attributes (“She is a social shopper” or “He is pragmatic”) rather than the context or situation they’re in, which varies along their journey.
The Fundamental Attribution Error and the Implicit bias can blind us and lead us to interpret our research results poorly.
To avoid this, instead of asking “Who is this person” try asking, “Where is this person in her journey and what is she trying to accomplish (that’s why I like Need-based personas from Koos).
Conclusions
As we hopefully move to a more inclusive world, our work practices must adapt. We need to challenge the status quo, knowing that sometimes that means challenging ourselves to reinvent how we do things and think about them.
This article was originally published on the Service Design College network.
