Inclusion by design: exploring gender responsive designs in digital welfare is the second of a two-report series. The first report
demonstrated how Western welfare systems
have long reflected the gendered disadvantages
present in society and shone a light on examples of discriminatory automated decision-making systems (ADMS)
managing digital welfare systems in several Western Countries. It concluded by highlighting gender equality principles
for the digital welfare state
. This report builds on those principles. There is still time to address and rectify the gendered harms welfare systems can inflict.
The implementation of automation
has been mostly a two-sided conversation between policymakers and technologists, an approach that does not take into consideration the implications of digitising old ways of working and inherited social structures. We cannot assume that technology is a neutral actor when it is history that has built it. Instead, it is systems designed to acknowledge the historic biases
that preceded them and understand the complex lives of those who seek their services that lead to a more equitable future
To design digital welfare systems
in this way requires an understanding of the interconnected nature of the social categorisations that the system users will belong to. Relating to gender this could mean many things, including the increased probability of a women being unemployed while also more likely to be engaged in in unpaid labour positions such as caring for children or other dependent family members. If public sectors are going to automate the decision-making processes that manage access to welfare systems, these ADMS must include different frameworks to address the intersectionality of women users.
In this regard, this report maps a way forward
in which design can play a fundamental role in envisioning digital welfare services contributing to a more gender-equitable future.
Gender responsive design means compiling and using gender-relevant datasets and statistics, incorporating gender analysis and gender impact assessments, and recognising that co-design and human oversight are fundamental to avoiding the automation of errors and inequalities.