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4 Ways Nonprofits Can Start Using AI in 2024

Nonprofit Tech for Good

Along with access to the latest version, ChatGPT 4 Turbo, which is the most intelligent model available at the time of writing, it also provides access to an array of additional tools. 2) Master the Art of Prompting Prompting is the language we use to communicate with Large Language Models (LLMs) like ChatGPT.

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Preparing Your Association for AI

Association Analytics

Types of AI Tools To start, it’s important to know about some of the models already available to the public. The most popular model today is called a Large Language Model (LLM) , which is trained on massive text datasets. LLMs are meant to produce conversational human language responses.

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If Racial Equity is Our North Star, How Can We Navigate Racial Bias in AI/LLMs?

John Kenyon

For nonprofits and grantmaking organizations committed to racial equity, using artificial intelligence (AI) and large language models (LLMs) raises important concerns. The chatbot might respond to a Black visitor’s query with more curt or stereotypical language versus a white visitor’s query. Invest in de-biasing.

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Doing good with AI tools: Navigating ethical considerations for the social sector 

Candid

Similarly, we saw evidence that the model was associating “People of Latin American descent” with “Incarcerated people.” When we use AI to help draft a grant proposal—in a tool currently under development—we must consider the potential that AI-generated language could be harmful and offensive.

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RAG-Enhanced Conversational AI: A Comprehensive Guide

Forum One

The introduction of Retrieval-Augmented Generation, or RAG, now allows AI applications to enhance the capabilities of machine learning models by integrating them with a retrieval component. Avoid Vendor and Model Lock-in: The AI space is still evolving rapidly.

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Top Ten Data Challenges (And Solutions) for Associations

Association Analytics

Older models tended to be AMS-centric, leading to siloed data, static reports, and that trapped feeling. Solution : Solve this challenge by creating a data capture policy. It can be a challenge to get everyone on board with one language when things have been done differently in the past. Unsure where to even begin?

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Connecting the dots: Fighting for equity through a data partnership 

Candid

They sought diverse perspectives in focus groups and made structural changes to address outdated language, power dynamics, and privacy concerns. Intersectional demographic data, vital to feminist philanthropy WFN is a deeply intersectional movement of funders fighting for policies and standards across lines of race, class, and gender.

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