Diversity, Equity, & Inclusion Trainer

Request for Proposals

About DataKind

DataKind is a global nonprofit dedicated to harnessing the power of data science and artificial intelligence (AI) in the service of humanity. Named one of Fast Company's 2017 top 10 innovative nonprofits, DataKind teams talented pro bono experts from academia and industry with visionary changemakers to collaboratively design innovative solutions to tough social challenges. We help social organizations apply their data to predictive analytics, machine learning algorithms, and AI needs in a way that both increases impact and is sensitive to the ethical considerations they have.

  • We are 20,000 strong: DataKind volunteers hail from almost every country across the world, representing a community of technologists and social changemakers who believe in using data science and AI for a stronger planet and a more just and prosperous world.
  • We have served 300+ projects around the world: From using satellite imagery to measure crop yields to automating the fight against hate speech online, our volunteer community has shown up to support a range of humanitarian needs. 
  • People are at the center of our process: The most advanced machine learning algorithms are useless if they’re not designed for real people’s problems. DataKind celebrates human centered design principles that focus on the “why,” the “for whom,” and the “should we” long before we ever get going on the “what.”
  • “AI for Good” will only succeed if it’s “AI for All”: We will continue our work until all people and all communities can use digital technology for the outcomes they want to see. We support not just the tech communities of today, but anyone in any community who wants to lead in how data technologies serve their needs fairly.

The Next Phase

DataKind has been honored to work with social change organizations around the world to do over 300 projects these past eight years. Those projects have resulted in more effective NGOs, more funding for social change organizations, and more awareness of the power (and pitfalls) of data science and AI in the social sector. However, we have always known that we will not be able to combat all of the world’s looming challenges on the backs of individual, uncoordinated, short-term projects alone. Thanks to generous long-term support from The Rockefeller Foundation and the Mastercard Center for Inclusive Growth, we are now focusing the DataKind network on issue areas, such as improving health outcomes through Community Health Workers or increasing economic resilience. Over a period of five years, we have been granted $20M to make this vision a reality, and we are looking for people to join us in this journey. You can read more about the new strategy here.

About the Opportunity

Since our founding in 2012, diversity has been one of our six core values. We've worked to live up to that value by: 

  • Ensuring that our hiring processes are fair and consistent, with an emphasis on recruiting individuals from communities that are historically underrepresented in technology. For example, three of our four Executive Team members are women of color.
  • Putting people at the center of our process. We believe that the most advanced machine learning algorithms are useless if they’re not designed for real people’s problems. We celebrate human-centered design principles that focus on the “why,” the “for whom,” and the “should we” long before they ever get going on the “what.” We also design solutions with, not for, our project partners.
  • Advocating that “AI for Good” will only succeed if it’s “AI for All.” As a leader in the Data for Good movement, we've pledged to continue our work until all people and all communities can use digital technology for the outcomes they want to see. We support not just the tech communities of today, but anyone in any community who wants to lead in how data technologies serve their needs fairly. 

However, we’re now finding that this value doesn’t give us specific enough language or focus to guide how we define our support for/actions around racial justice and other social justice issues. Per our blog post on June 9, 2020, “diversity isn’t enough.” We seek now to define and realize the inclusion and equity we want to see in our organization and the world around us. 

In order to operationalize our new commitments, we're looking for external facilitation to guide us through: 

  • Level setting of key concepts and terms around identity and inequity, so our team has a shared language and baseline understanding
  • Skill building around giving and receiving critical feedback, so that we have the ability to engage in critical conversations, laying the foundation to identify opportunities to improve our practices and behaviors in terms of racial justice and beyond
  • Developing a shared understanding of how these concepts align with our mission, vision, and values, writing an equity rationale or similar definition of organization-wide perspective, and refining the current value of diversity. Moving forward, we’d use this process as a lens or framework that teams can apply to examining their day-to-day work.

How to Submit a Proposal

We're imagining the above goals would be best realized through a series of virtual trainings and discussions where a facilitator is alternating between presenting new terms and information and engaging the group in discussion and co-creation of a vision or lens that will inform future action, internally and externally. However, we're open to hearing whatever a facilitator proposes. We recognize the value of trainers who are skilled in both adult learning around DEI and shaping interactive discussions. For more information about the opportunity, please review the request for proposalsAll proposals should be submitted by 12 PM ET on Friday, June 26, 2020 to gwen@datakind.org.

 

DataKind is an Equal Opportunity Employer
Naturally, we’re an equal opportunity employer and strongly encourage candidates from underrepresented groups in tech to apply. DataKind does not discriminate on the basis of race, color, gender, disability, religion, national origin, age, sexual orientation, genetic information, pregnancy, or any other protected category.          
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