When considering “helping out”, also consider the costs of your helping out and what alternatives there are.

Folding@home (FAH for short) boasts of being the largest/most powerful distributed computing project in the world with >5 petaflops of capacity, focused on the NP-hard problem of protein folding. It is powered by volunteers running its client on their computers, or more specifically, their GPUs and PS3s. (Their architectures are more specialized than normal CPUs and, if a problem happens to match their architecture, can run an order of magnitude or two faster & more power-efficiently than a CPU would.)

The researchers solve their problems, the volunteers know their idle computing capacity is going to good use—everyone wins. Right?

But where is this free lunch coming from? Why are the researchers relying on volunteers? What does it cost the volunteers to run the clients? Their time in setting this all up, of course, but more importantly: electricity. Lots and lots of electricity.

Wikipedians have already done the legwork on how much electricity consumption FAH causes. Each petaflop costs ~3 megawatts, so at >5 petaflops (6 as of November 2011), it uses >15 megawatts. To put it another way, every hour FAH uses up 15 megawatt-hours .

Sins of commission Electricity doesn’t come from nowhere. If we are to do even the most simplistic cost-benefit analysis, we can’t simply assume the cost is 15 megawatts conjured out of nowhere or that the electricity would have been consumed anyway. What a silly defense that would be—what are the power companies doing, generating a fixed amount of electricity and if the FAHers shut down, the plants dump their electricity into the air? Of course the marginal demand from FAH causes the generation of megawatt-hours that would not otherwise have been generated. (Oh, but FAH users are so altruistic that they engage in conservation to offset their increased electricity consumption! Yeah, right.) And it doesn’t matter what other wastes of electricity may be going on—those wastes stand condemned as well (“two wrongs don’t make a right”). No more distractions or excuses: what are the costs of that cost? The most obvious cost is air pollution. It is major enough that we don’t even need to consider any other costs, because air pollution kills. The editors of Next Big Future have listed a number of interesting statistics from the WHO and other studies of electricity generation and the deadliness of air pollution (see also Markandya & Wilkinson 2007). For example, half the world’s electricity production is done by that filthiest and most fatal of sources, coal. (In comparison, nuclear power is a stroll in the park, which means that French users can run FAH with a 75% cleaner conscience than the rest of us, while Germany’s reaction to Fukushima demonstrates how fatal knee-jerk reactions can be, in the saddest and most utterly predictable way possible .) We will—generously—pretend that everyone contributing to FAH is located in the US, with its relatively clean coal plants. Nevertheless, each terawatt-hour of coal kills 15 people. How often does FAH burn through a terawatt? Well, 1000 megawatt-hours is one gigawatt-hour, and 1000 gigawatt-hours is one terawatt-hour, and 1000⋅1000=1,000,000, so how fast does FAH burn through 1 million megawatt-hours? Each year, FAH uses 15⋅24⋅365.25=131,490 megawatt-hours, or 131.5 gigawatt-hours, or 13.15% of a terawatt-hour. Each terawatt-hour means, remember, 15 dead people; in our grim calculus, what is 13.15% of 15 dead people? 1.8 dead people. So if the power is entirely derived from coal, FAH kills 2 people a year. What if the power is from an oil plant? That’s worse! The listed deaths per terawatt-hour for oil is 36 dead people, for an annual death toll of 4.4 people. Hey, it could be much worse: if FAH had been invented and popularized in China, with a terawatt-hour death toll of 278, that’d be 34 deaths every year. With coal and oil out of the way, we can look at the minority fuels which make up a small slice of the US power supply. Biofuel is pretty bad with a death toll of 12/TWh; hydro isn’t too bad at 1.4/TWh; solar, wind, and nuclear power have <1/TWh death tolls. But of course, we don’t live in an environmental fantasy where all our power is generated by those cleaner sources, and even if we did, that wouldn’t help the people in the past who have already been killed by FAH’s pollution. The actual power mix of the USA in 2009 was 45% coal, 24% natural gas, 20% nuclear, and 7% hydro, so balancing our numbers that gives us 1.01 annual deaths for a USA power mix. Phew! Only one dead person. Doesn’t that make you feel better?

Sins of omission We already saw how much electricity FAH consumes: 15 megawatt-hours. But how much does each megawatt-hour cost? The EIA says the average US rate for 1 kilowatt-hour in November 2010 was $0.0962. A megawatt-hour is 1000 kilowatt-hours, so 1 megawatt-hour is 1000⋅0.0962, or $96.2, so 15⋅96.2 = $1443/hr. And its annual bill is 1443⋅24⋅365.25, or ~12,650,000 dollars per year . $12.65 million is a lot of money. Money is both fungible and limited; by spending that money on FAH power bills, that was not spent on other things, although these points seem lost on a lot of people. What could one have done with that? Meta-charity Givewell estimates that <$1000 could save one life; another source says “Cost-effectiveness estimates per death-averted are $64–294 for a range of countries” . (One modest proposal is to use this $1000 figure as the base unit of a new coinage: the DC or ‘dead child’; it has the merit over the dollar of possibly ingraining an understanding of opportunity costs.) And these interventions are the kind of things that can absorb a lot of money. (There are a lot of people out there who could use some help.) If <$1000 will buy 1 life, then $12.65m would buy ~12,650 lives. Quite a few, that. One wonders whether FAH was the best form of charity the 300k or so volunteers could have chosen to engage in. (FAH is lucky to be an academic project; otherwise we would see deeply ironic outcomes like Seti@home shutting down & begging for funding—while its volunteers burn 0.5 petaflops annually. Perhaps if all those petaflops—spent on checking and rechecking for signals—had ever done anything useful in those decades, they would not have to. It would be interesting to hear from Seti@home at what point they would consider it was time to throw in the towel and finally admit the obvious: that there is not a scrap of astronomical evidence of any kind indicating intelligent alien life and so there just probably aren’t aliens out there.) Maybe they would have done better to donate a few dollars to a regular charity, and not run up their electricity bill. One might wonder, though, about the case where one isn’t paying for one’s electricity. So, either you are paying for all of your electrical bill or you’re not: If you are paying for all of it, then yes, you can donate your electrical costs! Just don’t run Folding@Home and send Oxfam a Paypal donation at the end of the year.

If you are not paying for all of it, if someone is sharing the bill or footing the bill entirely, then donating directly may harm your pocketbook, yes. But in such a situation, does it really still make sense to force the other to pay for all the electricity you are using? The overall economics are bad per the original note, it’s an inefficient way to turn someone else’s money into charity. What right do you have to burn the electricity like there’s no tomorrow, for that matter? If you weren’t going to use a year’s worth of electricity, then whomever is paying for your electricity is poorer by that $10 as surely as if you had pick-pocketed him of $10; few would agree that you are Robin Hood who may steal from the rich and give to the charitable. He accepted that risk when he gave you access to his electricity and deserves however you can contrive to screw him over? What an attitude! Other points can be dealt with similarly: perhaps one worries that overhead on a small donation of $10 will eliminate the value. But the overhead on financial transactions is usually only a few percent, and the difference between FAH and the best charities is a difference of far more than a few percent. A dollar is a dollar, no matter where it comes from. If you and 99 other people each donate $100 to 100 charities, then it’s the same as if each person donated $10,000 to just 1 charity. The only difference is whatever overhead there might be; and even if we say that our Folding@Home contributors lose 50% to overhead and the charities wind up getting only $6 million in their bank accounts to use, that’s still thousands more lives saved than by running Folding@Home and wasting the same amount of money!

and the best charities is a difference of far more than a few percent. A dollar is a dollar, no matter where it comes from. If you and 99 other people each donate $100 to 100 charities, then it’s the same as if each person donated $10,000 to just 1 charity. The only difference is whatever overhead there might be; and even if we say that our Folding@Home contributors lose 50% to overhead and the charities wind up getting only $6 million in their bank accounts to use, that’s still thousands more lives saved than by running Folding@Home and wasting the same amount of money! perhaps one worries that it’s easier to run a FAH client than to donate regularly; leaving aside the basic fact that a one-time donation through Paypal is a lot easier than installing FAH , checking that it works, and perpetually sysadminning one’s computer for it, there are many ways to make donating easier. One could set up a recurring donation. One could annually flip a coin to decide whether to donate twice the usual amount. (Or one could roll a 1d10 dice every year, agreeing to donate 10× one’s annual donation.) One could ask for others to donate in lieu of a birthday or Christmas present; one could take advantage of employer matching plans. And so on. (If ease of contributing is one’s true reason, then good news—it is very easily dealt with!)

Benefits But hey, perhaps it’s done good research that will save even more lives. Biology, hell yeah! Wikipedia has a partial list of 75 papers published drawing in some way on FAH. That is an average of 7.5 papers per year. The skeptic will notice that not a few (especially early papers, naturally) seem more concerned with FAH per se than with actual new results generated by it, and that project lead Vijay Pande seems to be author or co-author on almost all of the papers, which doesn’t indicate a large research community around the large investment of FAH. None of them seem important, and the number of publications seems to have peaked back in 2005–2006. The few actual compounds seem stalled in their test tubes. And a reminder, the wasted money amounts to many thousands of lives; for these sort of stakes, one would hope that one had good evidence, not mere possibility. But let’s lower standards and ask for ordinary evidence. What reason do we have to think Folding@Home has potential to save millions of lives? It has been operating for nearly 11 years. 11! And nothing that has yet saved a single life. (Readers are invited to provide a counter-example.) At what point do we stop talking about its potential to save millions of lives and about the possibility of teapots in orbit around Mercury? ‘Basic research’ is great and all, but at some point enough is enough. Wouldn’t it be better to redirect efforts to, say, Foldit—which besides not being polluting, is a fun puzzle game that can solve long-standing problems? As I am not a biologist nor omniscient, I can’t say for sure that the FAH work wasn’t useful, and I certainly couldn’t say it looks pretty worthless. But I feel much more comfortable asserting that the $12.65m could have been better spent on saving those 12,000 people (and the 12,000 people the year before, and the 12,000 the year before that, and…). Updating on evidence The hope function No one has yet shown me anything valuable done by FAH; but, they argue, it may yet produce something next year or perhaps the year after that. This is a statistical argument. There is an interesting perspective on this suggestion, known as the hope function. The idea is that you are looking at each time period (each year) for some sort of singular event (a discovery justifying FAH’s air-pollution and fatalities), but you also have a certain probability for the event never happening, for example because it is impossible. As each time period passes without the event, unsurprisingly, one’s probability that the event will happen the next period increases—as does the belief the event is impossible! (This isn’t contradictory.) Example: AI Interestingly, depending on one’s belief as to the probability distribution, the increases can be very small. One example I’ve run concerns the creation of Artificial Intelligence; AI enthusiasts have suggested AI could be invented anywhere in a very broad time span (Alan Turing, for example, putting it at post-1990). Many of those dates (like 1990) have already passed, and AI has clearly not happened. This has lead to a skepticism and belief that AI enthusiasts are irrational dreamers who refuse to update on the evidence; but what does the hope function say? I and others ran some estimates and found that for reasonable values, the failure of AI to happen only minimally supports the belief that AI is impossible! For example, suppose one thought AI if possible would show up in the 100 years between 2000 and 2100 (a superset of many expert forecasts), that its possibility was 90% (0.9), but it was an essentially random breakthrough which could as easily happen in 2000 as 2099 (a uniform distribution). In x years, what is our new belief about its possibility? The equation goes: numberOfPeriods−xnumberOfPeriodspossibility−x We substitute in our 100 years and 90% belief: 100−x1000.9−x We plug the year of interest into the hope function and find that in 2050, or in 50 years (100−501000.9−50=0.81), our original 90% belief AI is possible has fallen only 9%, to 81%! (Intuitively , one might think that a half-century of failure would count for more, but it doesn’t.) Even in 2090, after 90 years of failure (100−901000.9−90=0.474), our view that AI is impossible has fallen only to 47%. If we adopt a more realistic distribution like a bell curve centered in 2050, we get similar results—very small decreases each year until 2050, followed by a sudden plummet (as most of the chances get used up each year at or near the peak of the bell curve), and then a gradual curve downwards to 0% as 2100 draws near. Waiting for Foldot Setting up a hope function equation for FAH is conceptually clear: what is the full lifetime of FAH, how many years has it run without finding such a thing, what is the probability it will ever find anything useful, and what is the distribution of said probability? Internet distributed-computing projects are young enough that there’s no clear lifecycle. Seti@home looks like it will never shut down (hope for E.T. springs eternal), other projects shut down after a year or two or finished their goals, like a number of the cryptographic brute-forcing projects set up to resolve the DES Challenges to definitively prove DES insecure and force the world to move onto more secure algorithms. (distributed.net has completed 9 such challenges but continues 2 long-term tasks, whose value I am dubious about.) Let’s guess and say FAH has another decade to go, for a total n = 20 FAH began in 2000 or so, so we can put x at 11 This is the contentious one. Let’s see what 90% does—that is surely a favorable probability We could choose either the uniform or bell curve distribution; both are attractive as models ( FAH as serendipity machine! FAH as project gearing up in the early years for its maturity and eventual decline!) But as it happens, we already put n = 20 and x = 11, so we’d be in the middle of the bell curve and that’s almost the same as the uniform distribution. So we’ll use the simpler uniform distribution. We substitute in: 10−11200.9−11=0.8 or a fall of 10% in our belief that FAH will ever produce anything, which is a little sobering. Switching to the bell curve distribution will only make matters worse; recall that after the midpoint, the bell curve plummeted. With a bell curve centered on 2010 or 2011 and an end date of 2020, the hope function drops the 90% belief down to the <30% range by 2012 or 2013. (Further examples would not be enlightening; the reader can calculate out the variations himself.) I leave some questions for the FAH enthusiast to ponder: Are these unreasonable assumptions? (Aren’t they favorable?) Do you have any real reason to believe that FAH’s discoveries ought to be heavily back-loaded, that one would expect it to take, say, 15 years (consuming ~2 terawatt-hours)? Would you have argued for this back-loading before reading about the hope function? If you do not dispute the assumptions, have you actually dropped your faith in FAH by ~10%? Or at all? What sort of evidence would convince you FAH is harmful?