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Engaging with AI thoughtfully is part of what makes it better for the sector, and while there exist major factors around ethics, disclosure, and responsible use, AI presents the nonprofit sector with an opportunity to leverage powerful digital tools in service of enhancing the capacity to do good in the world.
Escher, Relativity Stairs Imagine a large - no, bigger, much bigger - nonprofit hospital, university, housing developer, or after school program. Right now, there are 13 universities in the U.S.A. with more than $10 billion endowments (one of which is a "public" university), with the largest topping $50 billion. There is one.
We both have worked across a variety of disciplines, including teaching, ethics, economics, architecture, and design. Bridging the University-to-Workforce Gender Gap Many academically accomplished women struggle to surpass barriers and achieve top positions and competitive salaries after they graduate from college.
Delivering on and scaling AI’s potential for impact on the SDGs is a collaborative endeavor that requires work across companies, universities, nonprofits, governments, and individuals to have real-world impact, according to the authors. More than 65% of these were open source, compared to 44% in 2022 and 33% in 2021.
Most obviously, funders working in specific issue areas—climate, health, education, or in my case, democracy—can work to support efforts downstream to prepare government and civilsociety in their respective sectors to take advantage of the opportunities and mitigate the risks of AI on their specific areas of concern.
Instead of hoarding access to AI and focusing solely on risk mitigation, universities, national laboratories, and industries from around the world need to work together to advance the technology’s benefits.
In trying to ensure that the rapid growth of technology is something that will benefit workers and societies as much as entrepreneurs and executives, there’s a role for all of us: employers and workers, academics and governments, as well as investors committed to seeing the technology they fund be used to increase the common good.
Over that time, I have witnessed an increased emphasis on naming opportunities for buildings and a decreased emphasis on ethical practice in capital fundraising where naming gifts often serve as marketing or reputation enhancing vehicles for donors that overshadow sincere charitable intent. This idea may not be as exaggerated as it sounds.
At the same time, 10 to 25 percent of the $7 trillion spent on healthcare globally every year is lost because of corruption, an amount that exceeds the investments needed to achieve universal healthcare by 2030. School systems are similarly underperforming due to poor governance and weak state capacity.
Original post Since we started the Digital CivilSociety Lab I’ve been invited to countless conferences, workshops, and philanthropic or corporate launches of “some kind of tech” for “some kind of good.” There is no universal definition of good. 5) The lack of universality in terms of what “good” means applies to ethics, also.
Solidarity economies are most often associated with ethical, cooperative economic practices, like local currencies, community land trusts, community gardens, fair trade, and cooperatives. In some locations, solidarity economy is institutionalized and recognized by the state but in others involves civilsociety and informal practices.
SSIR ’s 2023 Data on Purpose conference, Making Tech Work for Workers , will happen online May 2-3 and feature many of the worker organizations leading the movement to build a more just and equitable economy in conversation with some of the sharpest minds in academia, civilsociety, and the public and private sectors.
It’s time to work shoulder-to-shoulder with civilsociety and government to do the big, urgent work that no sector can accomplish alone, to adopt entirely new systems of operating that enable all people to thrive and reach their full potential and protect our natural environment.
However, these breakthroughs often assume a level of access, infrastructure, and digital literacy that is far from universal. This can only be remedied by gathering more inclusive data and implementing ethical AI practices prioritizing diversity and equity. Meanwhile, the consequence of the current global healthcare divide is huge.
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