There is a long-standing expectation for feminine sentimentality in Western culture. Women have been the family historians and curators, saving objects and images to later be passed down as the family archive. This expectation extends into cultural practices surrounding mourning and death. Often in times of mourning women are the primary archivists and creators of memorial and sentimental objects for the family after the death of a loved one. In this paper I try to reconcile the traditional role of mourning ritual - language and iconography with generative computing art making in the time of Covid-19.
The text on each card in generated using a predictive algorithm that uses a dataset of Hallmark Cards and Political Speeches about Covid-19 relief packages. The images are derived using a machine learning process called a GAN (Generative Adversarial Network) trained on a dataset of mourning sewing samplers from the 1700’s and 1800’s.
Generating condolences is an expression of communal grief during a global crisis. It is my intention to reexamine traditions surrounding a women’s role in the grief and mourning processes while using this work as a public intervention that also questions the often hallow words of condolence we receive from political figures during a time of crisis. As I develop this work into a public installation it is my hope for participants to generate and mail condolence cards to government representatives who are endangering communities by refusing to pass common sense mask and vaccine requirements or just to tell their own pandemic story.
