Related/relevant projects/orgs

Note 7 Mar 2023: I just started this page, it is far from complete

Organizations and 'do' initiatives

Other marketing/implementation resources: Including (new) EA-aligned marketing groups

Which links THIS spreadsheet

Much of which is embedded into THIS Airtable view as well (which will have some further comments on the relevance, as well as organizations that are not-so-EA related, with discussion)

Non or semi-EA initiatives

EA or 'effective giving' orgs working with foundations and wealthy donors

Research and information-gathering initiatives - "The IiF wiki collects and presents evidence on the most successful approaches to motivating effective and impactful charitable giving, and promotes innovative research and its application." This precedes and is partially integrated into the current resource

We are an academic collective and research non-profit, dedicated to providing public communication campaigns with cutting-edge research and rigorous tools for message development.

"Crowdsourcing" ... Recent research suggests that regular people can often be far more effective than experts at predicting which messages will best resonate with others in their community.

On Adaptive design/sampling, reinforcement learning...

The challenge is that the “space” of messages for campaigns to decide between is enormous — there are very many things a campaign could say and many different ways to say them. Unfortunately, research shows that relying on theory and expert guidance about “what works” when designing campaign messages is unlikely to be effective by itself, because “what works” is difficult to predict and can change dramatically across contexts (e.g., see [1], [2], [3], [4]).


  • Efficient message search. We design research pipelines that allow campaigns to explore the large space of potential messages more efficiently, and to quickly zero-in on the most impactful messaging strategies. Our methodology is based on a combination of large-scale adaptive online survey RCTs, Bayesian machine learning and surrogate metrics.

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