Lessons on Community Listening: High-quality listening means sharing power and being prepared to act

“What does it take to be ready to listen to communities?” That was the ambitious question we set out to discuss with guest speakers Ayawa Fiagbedzi (The Rockefeller Foundation), Megan Campbell (Feedback Labs), and Katherine Haugh (Convive Collective) earlier this month. 

For the past year, The MERL Tech Initiative has been working with The Rockefeller Foundation on a pilot project to uncover how and where technology might help us listen, learn, and adapt better. As part of this pilot, four different vendors are supporting program teams with their listening efforts (we’ll share more from their work in the project in the coming months!). Implementation has surfaced tons of reflections on the ways that organizational readiness influences and informs how organizations respond to insights generated through listening efforts. During our conversation with Ayawa, Megan, and Katherine, we explored some of those questions.

Challenging the notion that fast is better and considering the conditions for listening

“The pilot started with a very practical question: How and where might technology help us listen better, learn better, and adapt better? And through implementation, we’re asking more, and deeper questions. One question that’s come up is: what does rapid actually mean in community listening? And when is speed helpful versus harmful?”

A key learning that Ayawa shared during the event: “Technology does not automatically create better or faster listening. Listening depends on organizational structure and readiness.” As the pilot projects are being implemented across various programmatic and geographical contexts, the findings have led us to challenge the notion that fast is better. According to Ayawa, community listening should involve “questioning whether pace should be judged by speed alone, or whether enough time is being given for clarity and consent, inclusion, ethical practices, and learning.”

Another important point is around the conditions for meaningful and responsible listening. Before listening, teams need to consider whether they have clarity of purpose (“What is it that we are actually trying to learn, what are we listening for?”), ability to act on what they’ve learned

(“How are these insights going to be used? Are we ready to make decisions about next steps?”), and existing resources needed (“What relationships do we already have with communities, and what relationships do we need to establish?”).

A third learning Ayawa shared is that, while the pilot is testing how and where technology can support community listening, another key aim is to help program teams adopt responsible listening practices as part of their work. That makes program team ownership essential. Conversations about responsible data and technology cannot sit only with outside partners or those directly collecting data. Program teams need to engage across the data lifecycle, from shaping questions and weighing trade-offs to addressing consent, privacy, and the risk of extractive data collection. If the goal is to strengthen an organizational culture of listening, these practices need to be embedded in how program teams work.

Ayawa closed with a note on the distinction between the listening product and the listening process: “A listening product can summarize what communities said, and technology can help us produce that summary quickly. But authentic listening is built through the listening process that leads to those insights: defining the listening questions, weighing the trade-offs,  identifying ethical and practical risks, interpreting results, and how those interpretations are shared back with communities. If program teams are only the audience for the final product, listening risks becoming a reporting pipeline rather than a real practice. If we want listening to become an organizational capability, we need to design for the full process, not just for faster outputs.”

Commitment to action and listening to those most affected by systemic inequities

Building on her experience at Feedback Labs – a non-profit field builder that supports nonprofits, foundations, and other social sector organizations to listen to communities at the heart of their work in high-quality, equitable, and inclusive ways – Megan brought us some insights on how funders can listen meaningfully and well, and act on what they hear.

Funders can listen in different ways: They may listen directly to communities, listen to their grantees, or support their grantees to listen to communities. Different types of listening will make more sense at different times in the grant-making cycle, and the ability to listen will depend on organizational capacity. 

With that in mind, Megan echoed Ayawa in highlighting the importance of purpose: “The first thing it takes for funders to listen meaningfully is for them to be clear on why they’re listening, how it fits into their work at that time, and what’s the plan for doing something based on what they hear”. Commitment to acting on what they hear from constituents, Megan noted, is a Core Principle of High-Quality Listening and Feedback.

Importantly, Megan discussed how decision-making power about how to act must be shared with communities. Listening should be a process designed to involve communities in interpreting what’s heard and what happens next. In other words, meaningful listening shouldn’t be about extracting data from community members; it should be about “involving them in deciding what that data means and sharing in the decisions over how to act on it.”

Relatedly, for funders interested in community listening, special effort must be directed towards hearing and acting on the input from people who are historically underrepresented in listening efforts and who are most affected by systemic inequities. “A way to start with that is asking yourselves, your colleagues, your partners, community members, who have we heard from in the past? Who are we not hearing from? And how can we listen to them better?”, offered Megan. (This resource addresses the top questions Feedback Labs has heard from funders about how to listen well in moments of upheaval).

AI and listening: Systemic biases, risk of “neutrality,” and making sure high-quality listening continues to be relational

Feedback Labs has recently completed a large-scale literature review looking at how AI can both support and work against high-quality listening at scale. During our event, Megan discussed how the societal risks of increasing AI usage – impacts on water, energy, environment – largely fall on communities who have the least power to contest them and whose voices are usually least prioritized in decision-making. She also mentioned the risks around data privacy and sovereignty of using commercial AI tools in listening analysis, and the concerns over centralizing sensitive community data. 

When it comes to listening, Megan highlighted how those interested in using AI for their work should keep in mind the issues around bias, inequities, and worldviews that are inherently embedded in these systems. She also raised a point that may be a little less known: “AI analysis tools, synthesis tools in particular, often generate outputs that are biased towards neutrality. These tools, for example, classify sentiments or input as neutral when the data reflect ambiguity. And [their outputs] also tend to overemphasize the dominant viewpoints contained within listening data, and under-represent minority perspectives that are still really important for us to hear and understand.”

“For funders, it’s important to keep in mind that high-quality listening is relational. It’s participatory, it’s transparent, it involves constituents in designing listening efforts, interpreting what’s heard, and it shares decision-making power. It’s not just data collection. It is possible in review to use AI tools to support that kind of listening, but it really requires thoughtful judgment about how to do that, so that we’re using AI to support and bolster human judgment and involvement, but we’re not replacing it, and we’re not reproducing the exclusions or the power imbalances that high-quality listening is ultimately meant to address.”

Turning listening into an organizational capability: Readiness, sense-making, and action

Katherine Haugh brought an organizational learning lens to the conversation, asking what must happen inside a foundation for listening to genuinely influence its decisions and behavior. At Convive Collective, Katherine has spearheaded an initiative called the Learning Philanthropy Project, which provides a shared language and maturity model to help philanthropic organizations assess, strengthen, and embed learning practices—particularly around learning from feedback. 

Katherine emphasized that gathering high-quality feedback does not automatically lead to meaningful listening—or meaningful change. Even when feedback is thoughtfully collected, an organization may not have the structures, culture, time, or decision-making practices needed to absorb and act on what it hears. In those conditions, valuable insights can remain trapped in reports, within individual teams, or among the people responsible for evaluation and learning, rather than informing choices across the organization.

This challenge was one of the reasons Convive Collective created the Learning Philanthropy Project. Through its work with foundations, the team repeatedly saw listening and feedback practices become concentrated within particular roles or departments. 

Seeing this feedback be stuck within foundations, Katherine suggests that organizational readiness requires foundations to ask two critical questions: “Are we actually able to hear the feedback that we’re receiving? And really, what’s beneath that question is, are we ready to act on the feedback that we’re requesting, first and foremost? Secondly, are we able to truly make sense of that feedback together?”

Convive has also observed that organizations sometimes gather data to answer questions they believe they already know the answers to. Often unintentionally, listening becomes an exercise in confirmation: validating an existing strategy, reinforcing a prevailing assumption, or gathering support for a decision already taking shape. Genuine learning demands something more challenging. It requires organizations to approach listening with curiosity, actively seek perspectives and evidence that may unsettle their current thinking, and remain open to the possibility that what they hear could change the question—not only the answer.

Being able to receive feedback is not the same as being ready to hear it. Feedback may challenge an organization’s assumptions, expose tensions between its stated values and its practices, or point toward changes that require resources, authority, or a shift in strategy. Katherine’s first tip for funders is to test their readiness before asking communities for input. One question Convive frequently poses to clients is: Imagine you received the feedback you are seeking—what would you actually do with it? Exploring that question in advance helps organizations determine whether their listening effort is connected to a genuine decision or opportunity for action. It can also surface internal constraints that should be addressed—or communicated honestly—before inviting people to share their perspectives.

Katherine also highlighted collective sense-making as one of the most important—and frequently neglected—parts of listening. To counter this tendency, Convive encourages organizations to plan for approximately three times as much time for collective sense-making as for data gathering. The precise ratio may vary, but the principle is important: more information is not necessarily more valuable if an organization lacks the capacity to engage with it carefully: “In feedback these days, it can feel like we’re swimming in content and information, but then usually organizations have an hour-long workshop or 45 minutes to read about it, talk about it, and then everybody’s moving on to the next thing.” Katherine explained that the quality of the process of analysing and interpreting the data is just as important as the process of listening: “The sense-making step is really important and often missing”. If needed, collecting significantly less information is advisable to ensure organizations can actually take it in together. 

Ultimately, Katherine’s reflections reinforced a central theme of the conversation: high-quality listening is not defined by how much feedback an organization collects or how quickly it can analyze it. It depends on whether the organization has created the conditions to hear what is being shared, make meaning of it collectively, and allow it to shape what happens next.