Also relatedly, do you have a guess for what pathway most of your impact flows through? 

E.g. is it stuff like "voters are more informed, which means we get better policies"? Or something more like: "Policymakers can use OWID resources to make informed decisions?" Or not policy-related: "OWID resources inform people who want to start or contribute to impactful projects, improving their prioritization or problems and the quality of their work"?

Thanks for the question!

It depends significantly on how we measure impact, which has always been tricky. As Lizka guessed below, there are multiple ways we can do this, as our impact can consist of influencing the general public (for some of our most viral pieces), "influencers" (journalists, book writers, or anyone with a significant social media presence), teachers, policymakers, etc. These can be very different paths to impact.

Some are pretty easy to measure (the general public can be roughly measured by raw pageviews). In contrast, others are much harder; influence on policymakers can be somewhat measured through mentions in things like government reports, but a lot of it happens behind closed doors (thankfully, we sometimes hear about this too, e.g., someone on our team getting a text message by a friend who works in government, saying our charts were shown in a critical meeting).

If we measure impact purely in terms of media mentions, paper citations, significant re-use, views of our charts, etc., nothing comes even close to our work on COVID-19. Both on our site, but also because it was the underlying data used by many national media on their site, the number of eyeballs on this data was quite crazy, and the rest of our content isn't within the same order of magnitude.

A second way to answer the question would be to examine which of our articles or charts keep popping up in books, learning materials, online conversations, etc. In that regard, I think that Hannah Ritchie's articles "You want to reduce the carbon footprint of your food? Focus on what you eat, not whether your food is local" and "What are the safest and cleanest sources of energy?" are probably the articles that have the highest cumulative impact over time.

If we zoom out, a third way of measuring impact is to ask which of our pieces seem to have shaped other people's worldviews. In that way, Max Roser's broader essays such as "The world is awful. The world is much better. The world can be much better." and "The short history of global living conditions and why it matters that we know it" are strong foundations of our content and a significant fraction of the people who read us have probably come across them.

But overall, it's hard to pinpoint precisely what has had the most impact. We have a long tail of 3,500 charts, so if one was ever shown to a head of state who made a different decision because of it, that could count as some of our highest direct impact ever – but we might not even be aware of that!

Relatedly, how does OWID prioritize what to focus on next in a way that prioritizes impactful research?

Thanks for the question, Kei!

When choosing the topics we would ideally cover on OWID, we aim to be quite broad in our approach. Our tagline is that we publish "research and data to make progress against the world’s largest problems" and voluntarily apply a broad definition of the "world's largest problems". We don't try to follow a specific framework or list of questions (compared to how 80,000 Hours defines the highest-priority problems).

But of course, even though we wish we could cover hundreds of important topics, we only have limited resources and must make choices regarding marginal prioritization. Our principles broadly follow EA's ITN framework, although with a slightly adapted version of each concept.

- Importance: is the topic a big problem for the world? Does it kill people, generate suffering (physical or mental), or cause societal instability? Or, on the positive side, does it unlock potential progress for the world, or preserve something valuable?

- Tractability: is there enough quality data on this topic for us to cover it? Given that OWID's mission consists of relying first and foremost on data to explain important issues, we need reliable, accurate, up-to-date data on a topic if we're going to cover it.

- Neglectedness: is the topic accurately covered by other media, publications, or institutions? Do we often spot confusion or misconceptions about it online? Is there good data on a topic ready to be used somewhere, but it's been ignored or misunderstood for lack of good visualizations and presentation?

In deciding how to prioritize our work, I'd say that importance and tractability are filters that make a topic "OWID material" or not. Neglectedness will typically lead us to prioritize something over the rest of our (very long) wishlist.

Better data publishing practices are probably the number 1 answer. My team spends heaps of time importing data that is hard to access and process, poorly documented, or contains obvious mistakes. This applies to virtually every type of data publisher, whether government, big international organizations, NGOs, companies, research teams…

Better data harmonization between governments would also be tremendously helpful. Across many topics, national agencies tend to record and analyze things differently, making the resulting figures hard to compare. Organizations like the UN, WHO, World Bank, and OECD, work hard to bridge the gap between national methodologies. Still, a world where governments would stop reinventing the wheel whenever they need to measure something would be great!

There are categories of data that are indeed still relatively inaccessible. One example is satellite data, which is "gatekept" by technological difficulty, and the existing commercial data is costly. High-quality open-domain satellite data would be an excellent opportunity to measure trends like land use, economic activity, pollution, etc.

Global energy data has also been in a strange situation for the last few years, with the data locked behind a paywall by the International Energy Agency. We've been campaigning publicly for this to change, and there have been encouraging signs from the IEA, but nothing concrete has happened yet.

Hey James – great question, thanks!

100% of the content we publish is planned, decided, and created by our team, without direct input from funders or donors.

Generally, we work hard to convince funders to give us unrestricted grants. But some grants we receive are restricted, which means they are tied to a list of deliverables. When we've accepted restricted grants:

• They've only ever been tied to general, non-specific outputs such as "expanding our work on COVID-19", "producing a Global Health Explorer", "maintaining the content in our SDG Tracker", or "improving our content on democracy". This means funders never tell us how to produce this content, what the data should show, what insights users should learn, what they should think about an issue after reading it, etc.
• Funders never get to review or influence the deliverables at any point. Grant reports are typically sent once a year, in which we tell funders, "This year, we produced these things as part of the deliverables for this grant", and link to the content live on our site.

The Longview grant was an unrestricted grant allocated to OWID in 2020, which we used for product development across the site (see our 2020 annual report, page 9). Our article on longtermism was published around two years later, and was entirely disconnected from this donation.

(As a slightly pedantic point: in a very vague and indirect way, there's of course a link there: Longview sees OWID as a charity that cares about the long-term flourishing of humanity, and so they gave us money. And because OWID is a charity that cares about the long-term flourishing of humanity, we thought it'd be great to introduce our audience to longtermism. So these things are not entirely disconnected from a sociological point of view. But in terms of money, deliverables, and editorial freedom, we always make sure they're wholly disconnected.)

Hi Lizka – thank you for your thoughtful question!

Our direct engagement with policymakers is somewhat limited, but we do have occasional opportunities to present our work to large international organizations like the UN and WHO. And we know from testimonies and occasional public reports that OWID is also considered very helpful by policymakers at the national level. We know that policymakers, or their aides, value the clarity and conciseness of our work. OWID's approach allows them to comprehend the broader picture quickly, which we believe is mainly due to what we now label as "key insights". This overview provides an immediate understanding of a topic without diving into specifics.

When a more detailed analysis is necessary, our platform allows policymakers to drill down into the data, explore specific time series, and interpret detailed data points. This functionality is beneficial when policymakers want to understand what the data implies, or perhaps bring charts to a meeting, without necessarily jumping to conclusions.

As for bottlenecks in evidence-based policy similar to those in forecasting, we've identified "technical text" as a significant challenge. By technical text, we mean all the information that needs to be presented alongside a chart to make sense, be accurately understood, and be placed into a broader context. This could mean explaining key terms, linking to in-depth articles, discussing the data source, the data's age, and its limitations, etc. We strongly believe that many of our charts could be misunderstood or even misleading without this accompanying text. It's in this space that we feel we bring added value, in contrast to chart-catalog websites like Statista or, to some extent, Wikipedia, which provide the raw data but often lack in-depth explanations.

So, while data is indeed powerful, it's the contextual, nuanced information that often determines the effectiveness of data-based approaches in policymaking.

Thanks for the question, Angelina!

The article on longtermism and our content on AI were published in 2022. They've had great success (6-figure page views in both cases). I was particularly happy that we had no negative reaction to either topic, given that both could have seemed outside of our usual coverage for traditional OWID readers.

On longtermism, the reception was very positive. Max Roser's hourglass chart had a Wait-but-Why vibe that made it particularly popular on social media. My (unsubstantiated) impression is that many people remembered that part of the article more than the broader presentation of longtermism. But if we want existential risks to be taken more seriously, getting more people to adopt a broader perspective of humanity's past and future is probably an essential first step, so I'd say the article was very beneficial overall. Another nice aspect is that it was well-received in longtermist circles; no one seemed to think we had neglected or distorted any angle of the topic.

On AI, the impact has been more immediate. We published a new topic page, 5 articles, and 29 charts late last year. We were delighted that we could give a platform to the excellent data published by Epoch and that it was much more widely seen because of it (both on our site and in re-uses, e.g., in The Economist). Reactions to the 5 articles seemed very positive as well; "Technology over the long run" and "The brief history of artificial intelligence" were the most shared among them.

The most significant limitation is that this was all published just a few weeks before the ChatGPT/GPT-4 craze started. If anything, we're even more convinced now than at the time that AI is one of the world's largest problems, and we're working on an interim update of our content.

Thanks, Lizka!

In an ideal world, we'd be all over these niches ourselves! We're grateful that our articles are well-received, but we know their format (heavy on text and charts) might deter some people.

Videos are a big one. Kurzgesagt and Vox are the ones that come closest in terms of style and quality. (In my dream world, each article we'd publish would have its own Kurzgesagt-style video.) This niche could comfortably accommodate several players if they're ready to meet the high production quality threshold needed.

Regarding books, I'm not so sure about a distinct "niche" as such. I think it comes down to the author's style. Some books (Factfulness is an obvious example, and my colleague Hannah Ritchie's upcoming book will likely fall into this category, too) are essentially doing this already.

For the "tool" niche, I think Tableau, Datawrapper, and the like have it reasonably well covered. There's room for more innovation, but the barrier to entry is higher if you want to offer something genuinely creative and competitive.

The biggest niche I can think of would be "news reporting in the style of OWID". I think there's a great need for this; something that combines OWID's editorial style, high standard of research, and reliance on evidence and data, but applied to current events (like the situation in Ukraine or the migrant crisis).

Vox's reporting style, or what the FT and Economist data teams do, comes somewhat close to this idea. FiveThirtyEight is another comparison, although their focus has primarily been on US politics and sports rather than global issues. (And unfortunately, given recent layoffs there, the future doesn't look too bright for them.) Still, I believe there's a niche for a more prominent, more focused player to emerge in this area.

I think I'm also curious about how you notice that something is a common misconception, or if that's something that you focus on at all. E.g. I think part of the success of this article, "The world is awful. The world is much better. The world can be much better.," is that it hits at a common blindspot/belief (that life for humans today is worse than it was in the past) and then shows evidence against it (same with "Global economic inequality: what matters most for your living conditions is not who you are, but where you are"). (Edited to add: I think a lot of your work on climate also follows this pattern.)