In short, Singer argues that we are morally obligated to help others if we can do so without significant sacrifice on our own part. He illustrates this through his “drowning child” thought experiment, which asks: would you wade into a shallow pond of water to save a drowning child if doing so would ruin your clothes? The vast majority of us say yes, which leads to another question: why aren’t we as willing to sacrifice our resources to save lives that aren’t in front of us?
Singer stresses that it doesn’t matter if the child is in front of us — if we can save lives for comparatively little cost (the value of the clothes we are wearing, for example), why don’t we? Why are we motivated to be altruistic for the drowning child in front of us, but not the ones we don’t see?
“If it is in our power to prevent something bad from happening, without thereby sacrificing anything of comparable moral importance, we ought, morally, to do it.” — Peter Singer
The simplicity, effectiveness, and elegance of the core argument made complete sense to me. Contrary to my previous belief that I was only a small fish in a big ocean, it turns out I can positively impact others’ lives, oftentimes quite substantially. There are drowning children out there (metaphorically, in this case), and I have an obligation to help them. Better yet, I’m in a good position to help a lot of drowning children over the course of my life if I follow the evidence and use careful reasoning. That’s both exciting and nerve-wracking.
The drowning child thought experiment was powerful enough to make me buy into the effective altruism project. Actually, I didn’t just buy in — I felt infused with a resounding sense of motivation that I can make a difference.
But that motivation soon turned into anxiety as I began grappling with the sorts of tricky philosophical and empirical questions that come with putting these feelings of obligation and fuzzy ideas into practice.
“Now, what can I do to help as many people as possible?”, I would think to myself. Anything less would mean that someone might not live a happy life. This sort of practical introspection quickly morphed into something like, “Holy s**t, what should I be doing to help?”
Any action I thought about taking was quickly picked apart by a feeling of uncertainty that bordered on neuroticism. “What if this action isn’t going to maximise the amount of good I do?”, I would ask.
These kinds of questions wouldn’t be followed by answers; they’d instead be followed by even more questions. Yikes.
What is the most good? How much should I donate? What if donating elsewhere would increase my impact? Can I really justify buying this sandwich if I could spend it on a mosquito net instead? Have I really earned any of the things I own?
What began as a force for motivation started turning into a pipeline of negativity — one that would take a healthy degree of uncertainty as an input, and spit out an ever-encroaching feeling that I was failing the project of effective altruism as an output.
That was the wrong mindset, and I’ve since come to terms with the fact that I’m a human who is trying to do the best I can, not some sort of omniscient maximiser from an economics model. This realisation has made me much happier and significantly more motivated to continue doing good in the world.
I’m writing this piece because I don’t want you to feel the anxiety I felt. I want to help you to feel comfortable with uncertainty, especially if you’re new to effective altruism.
Here’s why it’s perfectly okay to be an imperfect effective altruist.
Effective altruism is, almost by definition, complicated. If it wasn’t, we’d skip the complex analysis because we’d already know exactly what to do. But in practice, it can be really hard to find the best ways to use our resources to help others the most.
We really don’t have this effective altruism thing entirely figured out, contrary to the impression that newcomers might have. There are a lot of unanswered questions, incomplete analyses, tough considerations, and noisiness involved with many of the things effective altruists care about. It’s important to remember that effective altruism is carried out by humans, not robots — and we are flawed reasoners who must navigate incomplete information, social norms, personal desires, cognitive biases, and finite resources.
But that’s okay. If you feel uncomfortable with this uncertainty, I encourage you to introduce simplicity wherever you can. I’ll describe a few practical rules of thumb below to help you get started. These can help with the complex considerations that effective altruism often demands, and can make you feel better about the actions you’re taking to satisfy them. This can often be especially true if you’ve only recently discovered effective altruism.
Consider the importance, tractability, and neglectedness (ITN) framework, which helps us figure out the kinds of problems we should work on. Effective altruism has changed in the last few years, but a few things have stayed relatively constant. The ITN framework is a key example. Like most other models, the ITN framework is flawed and oversimplified. Yet despite this, it has stayed relevant over the past decade as ideas within the effective altruism community have ebbed and flowed. Why? My best guess is that even though the ITN framework is imperfect, it still broadly points us in the right direction in many circumstances. The framework’s ability to direct the user at a quick-yet-still-useful answer allows us to forgive its shortcomings, hence why it is still one of the primary tools in the effective altruism toolkit.
So yes, maybe there is another tool out there that would enable you to do a little bit more good. But maybe it would require days of thinking, 10 spreadsheets, and 20 cups of coffee to work through, and even then you might still have a lingering sense of uncertainty. Crucially, if these kinds of barriers would stand in the way of you actually taking action, the ITN framework would be the clear winner.
You can adopt other rules of thumb that, much like the ITN framework, can increase your impact, make your life easier, and help you deal with the anxiety that you aren’t making the absolute perfect choice.
If you’re new to effective giving — or even if you’re not, but you value keeping your life as simple as can be — a good simplifying rule would be to stick closely to the recommendations of charity evaluators like GiveWell or Animal Charity Evaluators. These organisations hire smart people to spend thousands of hours working through the inner complexities of evaluating charity effectiveness, something that an individual would have difficulty doing alone. You can take advantage of that work (at no cost to yourself) by following their recommendations.
Alternatively, you could donate to funds that hire expert grantmakers to disperse donations. Think of this like hiring your own personal impact advisor, except for free.
And also note that you can always change where you donate later, especially as your knowledge, key considerations, and beliefs change. These options are good places to start in the meantime.
If you’re not sure about how much you should donate, start by picking a simple rule and sticking with it.
If the “simple” approach helps you get started with some positive action in the first place, then you should strongly consider acting on it. You can build from there and progressively refine your decision making in the long run.
Here are some other rules of thumb you might find helpful (but by all means, feel free to create your own):
Remember, you are guaranteed to have zero impact if you donate nothing out of fear of failing to choose the absolute best option. But choosing a possibly-imperfect-yet-entirely-reasonable starting point (e.g., donating 5% of your income to GiveWell’s recommended charities) is an excellent way to do good in the world. We can’t ever be entirely sure whatever we’re doing is maximising some abstract goal, so we should at least start somewhere.
Speaking of which, we often can’t maximise our goals — but that’s okay!
Effective altruists often use maximising language like “the most good you can do” or “maximising the amount of good you can do.” But this can be difficult to practically implement when we’re uncertain about different options. If effective altruism is about trying to do as much good as possible, are we ‘failing’ if we fall short of this goal?
I don’t think so. We will pretty much never be able to calculate which actions will maximise the amount of good we do, but aiming in a promising direction seems like a good rule of thumb. As someone who cares about effectiveness, it can be hard to feel as if you’re leaving impact on the table. But think of effective altruism as a long game — one that you should do sustainably and in a way that can inspire others.
The world is messy and confusing, so embrace uncertainty and do your best. You’ll have zero impact if you do nothing, so start by doing something that will get you on the path to maximising your impact (e.g., donate 1% of your income to our recommended charities) and then adjust as time goes on. I wager that you’ll feel pretty good about how much you’re helping others if you start at as little as 1%. Then, as you increase that number to 5%, and then 10%, you’ll see why effective giving can feel so rewarding and meaningful.
Giving is a long-term endeavour, not one that you have to maximise and optimise for over the course of a year. It shouldn’t be stressful or anxiety-inducing, and it should be something you can see yourself doing over the course of your life. Most importantly, you should aim to set an example for people who are on the fence by demonstrating that giving significantly and effectively is not just compatible with living a happy and fulfilling life, but is integral to it. If giving is making you stressed out or anxious, others might not want to follow your lead, so remember to take care of yourself.
At the end of the day, we’re imperfect beings who would like to live in a perfect world. That's fine — we can still make a substantial amount of progress by noticing the uncertainty and complexity around us, and acting anyway.