AI · Philanthropy · Policy
Holding
"AI for Good" Accountable
The current “AI for Good” movement (i.e., the push to fund or deploy LLMs as social impact solutions) should be treated as a danger to society. These same tools power automated weapons and surveillance tech, formed via an environment-destroying training process over non-consensually collected data, and most notably, lack any quality evidence that they are even wanted, let alone helpful.
The Kaleidoscope Project was established to provide a counterbalance. Our work is grounded in the belief that “AI for Good” requires high levels of community authority, robust measurement of both benefits and harms, and a reorientation towards AI tools that aren’t LLMs or otherwise generative.
OUR FIVE GUIDING PRINCIPLES
01
Evidence & Transparency
02
Big Tech Independence
03
Agency & Ownership
04
Surface Collective Input
05
Invest in Foundations
01
Evidence & Transparency
Net Effect
Transparent (policies, data retention)
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02
Big Tech Independence
Biggest harm is conflation. Not only good marketing/PR but making communities dependent on tech that has ethical concerns + financial concerns - Predatory
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03
Community Agency & Ownership
Communities need a say of how to interact.'
Data soveriegnty, Access
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04
Surface Collective Input
Lived experience is not a replacement. Understand the unique contexts someone is in to build effective solutions. Methodology
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05
Invest in Foundations
AI can exacerbate harms, especially if capital is prioritized their. Close foundational gaps like literacy, connectivity
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How we work
Diligence
Evidence-based assessment of AI investments for philanthropies, using the Net Effect framework. Gains and harms measured where tools are actually deployed — before more capital follows. Real funding decisions, not demos.
Policy & Education
Evidence-based assessment of AI investments for philanthropies, using the Net Effect framework. Gains and harms measured where tools are actually deployed — before more capital follows. Real funding decisions, not demos.
Micro-Grants
Evidence-based assessment of AI investments for philanthropies, using the Net Effect framework. Gains and harms measured where tools are actually deployed — before more capital follows. Real funding decisions, not demos.
Evaluations
Evidence-based assessment of AI investments for philanthropies, using the Net Effect framework. Gains and harms measured where tools are actually deployed — before more capital follows. Real funding decisions, not demos.
Our Impact
>$10M
Capital de-risked