Hi Denis, thanks for your reply and the thoughtful takes. A few reflections from me below.
You’re right that coverage skews to the arguments and away from the work. Part of that is the nature of news. Part of it is on us. We have historically been better at writing for people who already think this way than for people meeting these ideas for the first time.
I also agree that the nuance gets lost, and that the caring rarely survives the path to coverage. Zach gave a talk on this if you’re interested – we don’t make spreadsheets because we don’t care, we make spreadsheets because we care so much. We’ve gone some way to humanising EA to that end through stories, which try to show the depth and range of the people in this movement. But you’re right that the overall picture hasn’t shifted much. I want to offer some thoughts on why, because I don’t think it’s simply an effort or messaging problem.
From what we can see of how EA gets discussed, three patterns repeat:
Reach asymmetry. Critical content doesn’t just outnumber favourable content, it also travels further per post. On a bad day, a single critical thread has outperformed everything positive published that day.
The negative spikes are often event-driven, but the criticism isn’t always about the events. Attention arrives with whatever story is running that week, and the same handful of frames attach themselves to it regardless. That’s why correcting a factual error, which we regularly do, rarely touches these narratives.
Favourable coverage is real but quiet. It tends to cluster in careers, philanthropy and research contexts, which are the places with lower organic reach. The supportive mentions are there; the amplification isn’t.
All that being said, there have been some encouraging signs in recent coverage, including balanced and positive pieces in major outlets.
We can definitely improve our own output, and we are, but I don’t think it reduces to one problem. Favourable material exists and doesn’t travel. Critical material travels easily and isn’t especially responsive to anything we publish. Those need different answers. That’s something I’d love to compare notes on if it matches what you’ve worked on! You can find me here or on LinkedIn.
I agree you are doing great work in a tough environment! I’ve sent you a message on linkedin.
Where I might have ideas is in how to make the communication strategy more data-based. I cannot judge where you are now. But let me give an example of what I mean:
Let’s say you market Beer Z, a typical lager. You know that your beer looks and tastes much the same as 50 other beers to most beer-drinkers. But somehow many of them consider Beer Z to be, say, weak. What do you do?
Multinationals have developed whole ecosystems to work on trivial problems like this, including omline surveys, focus groups, etc.
You have some ideas: you could talk about your alcohol content, you could get an NFL lineman or rugby player spokesman, you could run promotions among groups who might think weak is good, etc.
Basically, they would test these ideas, optimise down to the level of the exact words to use (“tough” or “strong” or “not like the others” …), generate new ideas, test those, and finally design an intervention based on what would sell the most beer, based on statistically significant data.
The challenges you describe may be amenable to some of this. Who might be a great advocate foe EA? How to create a story line that has potential to go viral but focused on care? Etc.
Hi Denis, thanks for your reply and the thoughtful takes. A few reflections from me below.
You’re right that coverage skews to the arguments and away from the work. Part of that is the nature of news. Part of it is on us. We have historically been better at writing for people who already think this way than for people meeting these ideas for the first time.
I also agree that the nuance gets lost, and that the caring rarely survives the path to coverage. Zach gave a talk on this if you’re interested – we don’t make spreadsheets because we don’t care, we make spreadsheets because we care so much. We’ve gone some way to humanising EA to that end through stories, which try to show the depth and range of the people in this movement. But you’re right that the overall picture hasn’t shifted much. I want to offer some thoughts on why, because I don’t think it’s simply an effort or messaging problem.
From what we can see of how EA gets discussed, three patterns repeat:
Reach asymmetry. Critical content doesn’t just outnumber favourable content, it also travels further per post. On a bad day, a single critical thread has outperformed everything positive published that day.
The negative spikes are often event-driven, but the criticism isn’t always about the events. Attention arrives with whatever story is running that week, and the same handful of frames attach themselves to it regardless. That’s why correcting a factual error, which we regularly do, rarely touches these narratives.
Favourable coverage is real but quiet. It tends to cluster in careers, philanthropy and research contexts, which are the places with lower organic reach. The supportive mentions are there; the amplification isn’t.
All that being said, there have been some encouraging signs in recent coverage, including balanced and positive pieces in major outlets.
We can definitely improve our own output, and we are, but I don’t think it reduces to one problem. Favourable material exists and doesn’t travel. Critical material travels easily and isn’t especially responsive to anything we publish. Those need different answers. That’s something I’d love to compare notes on if it matches what you’ve worked on! You can find me here or on LinkedIn.
Hi Tess,
I agree you are doing great work in a tough environment! I’ve sent you a message on linkedin.
Where I might have ideas is in how to make the communication strategy more data-based. I cannot judge where you are now. But let me give an example of what I mean:
Let’s say you market Beer Z, a typical lager. You know that your beer looks and tastes much the same as 50 other beers to most beer-drinkers. But somehow many of them consider Beer Z to be, say, weak. What do you do?
Multinationals have developed whole ecosystems to work on trivial problems like this, including omline surveys, focus groups, etc.
You have some ideas: you could talk about your alcohol content, you could get an NFL lineman or rugby player spokesman, you could run promotions among groups who might think weak is good, etc.
Basically, they would test these ideas, optimise down to the level of the exact words to use (“tough” or “strong” or “not like the others” …), generate new ideas, test those, and finally design an intervention based on what would sell the most beer, based on statistically significant data.
The challenges you describe may be amenable to some of this. Who might be a great advocate foe EA? How to create a story line that has potential to go viral but focused on care? Etc.