Deadline: 15-Aug-23
data.org, with support from Microsoft, is launching the Generative AI Skills Challenge, a global grant for organizations to help train and upskill teams on generative AI to drive social impact.
This global grant will support organizations driving skilling and economic growth, especially those focusing on fair and community-led implementations of generative AI skills programs, with historically marginalized populations around the world.
As part of the company’s new AI Skills Initiative, Microsoft is providing funding for the Generative AI Skills Grant Challenge, with awards expected for five organizations. In addition to financial support, the awardees will receive access to cloud computing resources, technical guidance from Microsoft AI experts, and data training. data.org and Microsoft will share with the broader community the rubrics and best practices used to judge the applications and select the eventual awardees.
Design Philosophy
- A foundational objective of the Generative AI Skills Challenge is to ensure that AI responsibly serves the public good by providing opportunities and solutions that will enable organizations to train and upskill the workforce in generative AI to keep worker skills relevant in the ever-changing digital economy.
- With that, it is critically important that they develop a design philosophy that accommodates applicants from communities and contexts with systemic inequities and a digital divide. Consequently, the following key considerations will be used to guide the application design and selection judging processes of the Challenge:
- Ensure that generative AI serves the public good to transform society for the better, uplift people’s lives, and advance economic growth for individuals in underserved communities – and does not further widen the digital divide in these communities.
- Avoid/mitigate the ills or negative aspects of this technology by enabling projects and local communities to determine the trustworthiness of its outputs and advance the Principles of Responsible Generative AI.
- One size does not fit all: Underscore inclusion, diversity, equity, and access (IDEA) by observing that there are a diverse range of communities that can bring their expertise to bear on these issues but who are frequently left out of the generative AI conversation.
- Design for Human Systems – Ensure that training and upskilling are part of a holistic process i.e., award money, access to infrastructure including technical resources and assistance, and membership within an enabling ecosystem or community.
- Balance technology with Sociotech: Acknowledge the digital divide and gender inequality, and understand infrastructural challenges and existing policies across regions. Even if organizations lack access to large datasets, quality data, necessary tools, or data science expertise and resources, they may have great ideas for new approaches to solving local problems or offer suggestions for applying existing technologies to local contexts.
Funding Information
- In-kind support for Awardees may include, but is not limited to, data science talent, staff training, technical support and consulting, media production, marketing and promotional outreach, and software and infrastructure licenses.
- The Challenge will award up to five final winners with a combination of grant funding and in-kind support with a combined total value of $250,000 USD.
- Each final Award will be issued pursuant to the terms of a grant agreement between New Venture Fund and the relevant Awardee.
Geographic Focus
- A total of 5 awardees will be selected, one from each of the following geographic regions:
- Asia
- North America
- Latin America
- Africa
- Europe
Eligibility Criteria
- Eligible applicants include nonprofits, social enterprises, and academic/research institutions from across the globe.
- Submissions are welcome from organizations with extensive technical experience, as well those with an emerging and locally unique idea for advancing the workforce and closing the digital divide through the use of generative AI.
For more information, visit data.org.
