T4R - Learning journey

Learning with Microlearning Units

Biases: Gender Data Gap + Lack of Data

FRAMEWORK:
ETHICS, INCLUSION, DEMOCRATIZATION

MODULE: 
Trust your city’s twin

EQF 5

EID-104

Urban planning often suffers from significant data biases, particularly towards social roles like gender. These biases lead to designs that neglect the needs of various demographic groups. There is a pressing need to address the invisible impact of gender data gaps, which results in discriminatory practices and hostile designs in public spaces, impacting accessibility and safety. To tackle gender-biased data gaps in urban planning, this unit proposes creating a checklist to identify and rectify these issues from data collection through analysis. By focusing on understanding who benefits from urban designs and who is excluded, the methodology aims to improve inclusivity and democratization in urban environments. This MLU assists in identifying data gaps, raises awareness of data gaps in an LDT project, and provides a checklist for identifying biases. Resources such as the IDEO ethics cards support critical examination of data sets, emphasizing inclusivity in urban planning and beyond.

EID-100

second loop

Biases: Gender Data Gap + Lack of Data

Learner is sensitized to hidden biases in data collection and their potential consequences when using data for automated decision-support tools. Learner can give examples of biases based on gender data gaps in technology and their effects. Learner can build a checklist for their own data-driven project to avoid gender data gaps.

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