If there are already smarter people around, how can I find good ideas?

Smart people find good ideas and detect bad ones. Effective altruism community is full of smart people. So, the logical conclusion is those good ideas are already found and bad ideas are already detected. One can interpret this as both good and bad news. Good news: we should be in a good position to achieve our goals. Bad news: there is not much more to do (at least not for us).

But of course, there are, at the very least, some more good ideas to be found, and some bad ideas to be detected. That is bad news: we have more work to do to achieve our goals. Also, good news: there is still a role for us. But we're still in a pickle: if there are unexplored good ideas or undetected bad ideas, how come smart people haven't already figured them out? And, more importantly, how can we?

My aim as a (new) blogger (or more formally, an iNdEpEndEnt ResEarcHer) is not to find out and compile the existing knowledge and analysis. This is, of course, also valuable and needed. But there are already good sources of information, and this mission is better served by institutions or the mediums of these institutions. One can perfectly learn about effective altruism and effective animal advocacy in particular, by consuming effective altruism forums, websites, podcasts, and newsletters: such as EA forum, EA websites, 80000 Hours, Our World in Data, Sentience Institute, etc. Since these sources are already very good at introducing and presenting existing ideas to the audience, I do not think this or any other blog can provide a significant service by presenting the same information in a slightly more organized or more fun way. 

My main goal is to discover new ideas and patterns of explanation, as well as to identify ideas that are accepted as true but have flaws. Blogs are much better suited for this role than institutions since blogs (especially anonymous ones) can afford to write more freely, be more contrarian, refuse to defer to community consensus, follow the lead of some minor data even if it does not yet have an established framework, and most importantly, can afford to try and error. 

It's easier said than done. In this post, I will explain two components that I think are necessary to generate new good ideas, detect bad ideas, or, if you prefer, conduct independent research, which is marginally more valuable and instrumental to figuring out how to do good.

Not all details will be useful to generate a new idea, but in order to find it you need all the odds you need.

The first component (the boring part - being a good boy/girl)

This part will be boring because it will state the obvious: accumulate more knowledge (this is like “eat less to lose weight” or “lift more to get bigger” type advice). But I will try to make it a little bit fun, and quickly move on to the second, more interesting component. So please bear with me. 

The first component is about learning all the things that are related to the field in which we are trying to find a new idea. This is expected: one cannot outsmart smart people by being an idiot. One also needs to learn the details, not just the basics.  Details are especially useful to detect incorrect patterns (more on that later). To quickly sum up, immersing yourself in consuming as much information as possible is a good start and in most cases, is a must. So if you are aiming for generating new ideas in effective altruism or in effective animal advocacy, in particular, it is a good sign if you are like this: 

“Cage-free welfare gains are listed on the Welfare Footprint Project’s website. Some argue that cage-free has drawbacks. Free roaming hens pile on each other in some barns, leading to higher mortality rates. Wayne Hsiung from Direct Action Everywhere made this criticism against Open Philanthropy’s cage-free campaign grants, which were overseen by Lewis Bollard (he is a good guy; he voiced support for Wayne when he was on trial for rescuing a pig - which is definitely not effective activism, IMO). Then, Ajeya Cotra made another investigation that still favored cage-free reforms, but made a more modest claim about their impact. Another welfare issue in cage-free systems is knee fractures since hens make small flies and hurt their legs when they can’t land properly:( But don’t worry, another animal charity called Healthier Hens aims to fix this by improving the quality of feeds which will hopefully strengthen hens’ bones. By the way, have you seen Deloitte’s report on alternative meats? Not great news I guess. 

Hey, if you wanna keep in touch, what’s your account in the EA forum? Mine is NathanPyne-Carterfangirl1234.” 

I know. This is cringe. But you need some level of cringe obsession in order to find out new ideas on the edge. 

One final boring point is that being a generalist, rather than a one-trick pony helps a lot. So learning other fields (such as philosophy, sociology, economics, history, politics, natural (real) sciences, etc.), reading prominent writers, listening to quality podcasts, and following important news and events is good for general "bulking." Of course, you can’t go deep as NathanPyne-Carterfangirl1234 does into animal advocacy in every field, but reaching a very reasonable level in many fields is possible, and enjoyable. I assume most effective altruists are already like this. Learning for the sake of learning is fun for nerds. (And yes, most effective altruists are nerds, if you haven’t noticed.). Being informed about many fields creates more possibilities for cross-hybridization (more on that later).  

Second component: figuring out what other smart people don’t normally think of (thank you for coming this far, now it will be more interesting)

After stating the obvious, now let’s talk about how to research things that add to existing knowledge. In order to do that, we need to think about why other smart people (which are abundant in the EA community) did not figure it out already. 

Figuring out what filters are at play 

A good starting point for research is to ask the question “what filters may be in play that might be hindering other smart people to see good ideas and detect bad ones?”. Call this “meta-research”. Researchers and other experts in the field may be unable to see what would normally be seen, due to their fears, biases, obsessions, ideologies, or simply lack of interest.  

If you can figure out other people’s blindspots, you can zoom in on those areas and find things that others don’t see. 

To me, a good starting point was to see that almost all animal advocates in the effective altruism community were vegans, and their history of being a farmed animal advocate started with veganism (just like myself). So an interesting “meta-research” question is: “why is that? and can this impair smart people’s judgments about the effectiveness of different interventions?” 

Good traders are good at noticing underrated and overrated stocks. They understand how other traders panic or get excited, even if they are not extremely knowledgeable about every stock. One can use a similar approach here. 

Finding mismatches 

Check out Animal Advocacy Careers’ bottleneck survey. One of the conclusions of this survey is that most organizations are funding constrained and fundraisers constitute a talent bottleneck for animal organizations. This sounds so normal. 

But if you are like NathanPyne-Carterfangirl1234, you would know that something is not right here. Because Open Philanthropy and other funds usually provide the necessary funding to advocacy organizations that focus on animal welfare campaigns. If you check the subgroups of the survey you would see that organizations which focus on corporate reforms are fine with funding, it is those organizations that aim for individual diet change that push the score of funding need upwards. And “weighting” of the survey does not necessarily fix this, since the organizations are accounted for by their “size” not their approval of EA funders (say their absolute or relative funding by EA funds).  So an alternative conclusion of this survey might be that major EA funders select only a group of charities that focus on certain interventions and not others (due to relatively less cost-effectiveness).

This is just an example. Some things may look perfectly data-driven and sound perfectly reasonable but if you know the details you may detect some alternative interpretations that most people don’t see. 

Seeing the smaller picture, thinking short-term, and providing only a partial (yet working) solution

Most people (even the knowledgeable) are inclined to see the bigger picture. This is understandable and also necessary. It is also sexier. Once you see the bigger picture, you can talk about the bigger picture which is more interesting than some details which can impress nobody. 

But this is not an ideal mindset for finding actionable solutions to existing problems. Precisely because some problems are (so) big, they don’t have big solutions. I mean, one can of course claim that there are big solutions: “let’s go vegan everybody!”. But unfortunately, these don’t work. If these were so easy, the problems wouldn’t get so big in the first place. 

For these reasons, zooming into details and finding a solution that is smaller yet does achieve results in the short run is underrated. This approach also has the potential of getting bigger and having much longer impacts. 

Take the example of cage-free campus cafeteria campaigns. These were very small (just some cafeterias of some universities) compared to “the bigger picture” (factory farming). But I am sure that campaigners were amazed by their new idea. Not because it was so large, but because it was working and was producing results RIGHT AWAY. 

Flash forward 10 years, and this intervention is used all over the world. First-time campaigners probably didn’t know how important their finding was, but they knew they were onto something. 

Most advocates are focused on “fighting against” factory farming. We are attached to what we usually value. But sometimes simpler solutions can be very impactful. Take Fish Welfare Initiative. This organization “works with” the fish farmers to improve the welfare of farmed fish. They achieve this by convincing fish farmers that higher standards are also in their interest, they can “harvest” more fish if they provide better conditions for their fish.

Partial yet working solutions are not sexy, but they are better. So rather than answering the questions like “how can we end factory farming” or “how can we create a vegan world” (types of questions that calls for naive answers), we should be asking questions like this:

“How can we limit the consumption of chicken and fish in Asia and Africa?”

My rather counterintuitive answer to this question was to increase dairy supply in these regions where the dairy industry is very inefficient. I hope to explain it in more detail in the future.

“If you had 10 million dollars and you weren’t allowed to donate to existing charities, how would you spend that money to help animals?”

My answer to this question was to spend it on stunning equipment for fishing boats that catch lots of small fish. I hope to explain this in more detail too. 

Questions and answers like these are much better at adding to the existing knowledge. 

Talking to people like a human being

Most researchers, and good researchers, mostly read and write. A good complementary is to see things in action with your own eyes and talking to people. Normally, formal scientific research instruments will provide data. But most surveys or statistics are dry. Talking to people on the other hand is less scientific, but can reveal more things to tinker with. Of course, some conversations don’t prove anything. But asking follow up questions, having long chats can help understanding “whys” and “deepdown whys”. Having long conversations with founders, campaigners, protesters, volunteers, donors would almost surely bring about some interesting patterns. 

Applying good ideas which have been explored in other fields 

Aztecs knew about wheels, they had toys with wheels. But they didn’t apply the idea for vehicles. Europeans knew about wheels and vehicles but they “invented” suitcases with wheels by 1970s. The “tech” was right before their eyes, but it took them some time to apply it to another field. 

There are lots of good ideas around. But most ideas are known and used in small circles. An easy way to generate more ideas and solutions is just to apply them to other fields. A good way of doing this is to ask the question “what would X (another smart thinker who is not necessarily related to effective animal advocacy) say about animal advocacy?”.  In a previous post, for example I asked at some point what Nassim Taleb would answer the question “why being vegan is such a focal point in animal advocacy?”.

Another interesting way to generate hybrid ideas is to apply theories to different fields. For example, I am planning to analyse The Power Elite theory of Wright Mills (a sociologist who has nothing to do with animal rights), and look for things that would serve us to better understand and find solutions for factory farming.

One final interesting way to generate hybrid ideas is to look for successful practical suggestions that work in other fields. For those who are familiar with Y combinator, you might have already noticed that I used similar themes in their courses “how to start a startup”. Some of their suggestions about finding new startup ideas are used in this blog post. Why not use more ideas like this to answer questions like “how to better manage animal charities?” or “how to increase our instagram followers” or “how to detect beforehand the failure of certain interventions or forecast the success of good interventions?” etc.

So, these were my modest ways to conduct “independent research”. If you have more ideas, comment below. Thanks in advance!