XPRIZE Community members advised on the design of a data challenge for gender data gaps in mental health, backed by the Gender Gap Fund.
About the Prize Design
Sponsored by The XPRIZE Guardian Circle, this ambitious initiative strives to exponentially improve gender equity by incentivizing and accelerating innovations that close the gender data gap.
By Gender Data Gap, we are referring to the reality that the vast majority of data collected perpetually excludes information about the perspective and experience of women. This type of biased data is used to inform design across all facets of the world in which we engage.
To prevent a cycle of algorithmic bias and enable an equitable future for humanity, XPRIZE is designing a series of challenges to incentivize the crowd to create, analyze, use robust data sets that will then be fed into AI and machine learning technologies which will produce unbiased insights that tell the story of all humanity —not just a subset of it.
We are calling on gender, data and technology experts to join us in this Prize Design, which will provide the outline of what the winning team must accomplish to be awarded the prize.
The Missing Data Problem
Data is the basic building block of the modern world. It informs our institutions, shapes our cities, determines how our products are made, and guides policymakers and political systems. For centuries, men have designed the world in their own image: using their worldview, physiology, habits, and priorities as the default. These biases are now embedded in society and the effects that this ‘unthinking’ has on 50 percent of our population is shocking. The world as we know it has been shaped by men, using an average 5’9”, 155 pound male as a substitute for representation for the entire adult human population.
The implications of this assumption range from small inconveniences to matters of life and death. From Google voice recognition software being 70 percent less likely to recognize female voices to 17 percent of women being more at risk of death and 47 percent more likely to be seriously injured in a car crash, it’s clear that designing a world tailored for the average man has had extreme consequences.
Though these design flaws and their consequences were unintended, correcting them is essential for the creation of a more equitable world. As artificial intelligence (AI) and machine learning replace manual design and human oversight, society gains efficiency. However, the inputs used to determine these machine-made choices rely on flawed data that lacks critical information about female preferences, behaviors, and needs. Incomplete or skewed training datasets, bias in labels used for training, and bias introduced in the features and modeling techniques themselves contribute to inaccurate gender data. AI is learning gender bias from humans. Biased data leads to biased insights, biased algorithms, biased solutions and policies, and ultimately a biased world that is designed only to meet the needs of the few.
The XPRIZE Gender Data Gap Prize design seeks to expose biases in data and design and to incentivize the collection of complete and comprehensive data sets reflective of all genders, disrupting the destructive gender bias status-quo and building a future in which the needs and preferences of all humanity are met.
We know your time is precious, and we greatly appreciate your participation and input. In addition to contributing to transformative breakthroughs, community participation also allows you to do the following:
Network with diverse stakeholders
Brainstorm with top experts
Promote your work
Earn [url=[https://community.xprize.org/discussion/406/rewards-for-members%5Drewards%5B/url](https://community.xprize.org/discussion/406/rewards-for-members]rewards[/url)], such as online gift cards
- Be considered for blogs and podcasts
If you have questions or need help with the community, leave a comment here or contact the community manager, Shashi Rai at mailto:firstname.lastname@example.org.