The nature of the curve, with virtually no chance of death until about 65, with a strong dropoff after, should give rise to a fair bit of reflection.
I'm the same as the author, a 34 year old male. For me, chances are pretty concentrated on me living a good few decades more. Which is ok, I can plan for that. I'll need a house to live in for the next 30 years, changing careers could be done, etc. I'm pretty unlikely to die in the next couple of decades, so hopefully I'll see my kids go to college. Chances of dying earlier are so low I can basically ignore them.
It also makes me sad about my high school classmate who passed away at 29. Set the marker to 18 and you have to wait quite a while before one of the simulations ends at 29 or earlier.
For someone older, there's an interesting issue. Say I put in my father's age, 71. There's a 1/3 chance of not making it to 81. But then there's also a 20% chance of making it past 91. What do you do about that? You can't spend all your money now. But you can't not spend it, either. Should you wait until next year to see your old friends? The likelihood is flattened out, which makes it quite hard to decide things.
> There's a 1/3 chance of not making it to 81. But then there's also a 20% chance of making it past 91. What do you do about that? You can't spend all your money now. But you can't not spend it, either.
Pensions and annuities, unlike private retirement savings in stocks and bonds, spread this risk out among many people. Your father could get about $650 per month guaranteed for life for every $100,000 he puts in an annuity today.
That insures you against the long tail of living too long, yes. But if you knew you had exactly 5 years with 99% probability, you wouldn't do that, right?
Also plenty of things are not purely financial. How will you know if this is the last opportunity to see an old friend? As a 34 year old there are plenty of friends I put off catching up with because it will happen someday. As a 71 year old?
On the monetary side, that is fixed in part by social security here in the US. It pays out monthly as long as you are old enough and alive. A kind of "old age" insurance.
A bit OT, but when I was programming actuarial software, with access to the mortality tables, I was interested to learn that most people need to get to the age of 105 or so before the chance of them making their next birthday is less than 50/50.
I am in my 40s, so I'll give the current life expectancy stats about a 50% chance of being valid by the time I reach the age to die.
But somebody who is 10 today, will likely have a life expectancy much longer than the 80 yeas. The entire curve will be pushed out. So for that person, I'd guess the probability of this being correct is closer to 10%.
An industry that will be destroyed or bailed out when there is a large upward discontinuity in life expectancy trends thanks to advances in medicine. There is a very big change going on in medical research at the moment, shifting from not trying to treat aging as a medical condition to actually treating aging and its causes. The difference in outcomes will be night and day; some relevant technologies are transferring out of the lab and into startups even now. E.g. Gensight in France, Pentraxin Therapeutics Ltd in the UK, Oison Biotech and Human Rejuvenation Technologies in the US.
Anyway, pensions and life insurance will most likely be bailed out when the crash comes, and the expectation of this socialization of losses might explain some of what is observed there in the sense that they are not responding aggressively to the actuarial community's ever more strident warnings on the uncertainty of their projections. Also people are not particularly rational in their expectations about aging - see this for example, a survey of the actuaries who are the same time as warning that life expectancy predictions are increasingly uncertain due to medical advances in the works, still base their future expectations on what happened to their grandparents:
I don't think that will destroy the life insurance industry. In fact, I think it will help them.
If I buy a life insurance policy for a 15 year old today, I pay them $X in order to receive $Y when the insured dies. If the insured lives for 70 years, the insurance company has 70 years to invest $X, in order to have $Y available when the insured dies.
But if the insured lives 80 years, then the insurance company has 10 more years to invest $X. They gain from that situation, rather than lose.
The main problem if I understand correctly is with pensions. They have 10 more years to invest your money, but they also have to pay you for 10 more years... so the longer you live, the less they profit. Live long enough, and they will lose money. And if enough people live longer than expected, the insurance company could go bankrupt.
The issue with pensions is already being dealt with. Either by their absence from many employers (US, not sure about the rest of the developed world), or by delaying the age at which you can receive it or reducing the rate at which you earn into it.
Social Security is an example of this, http://www.ssa.gov/planners/retire/agereduction.html. This, of course, requires an act of Congress to change. But businesses aren't so limited, new employees can be brought in on a new pension system while grandfathering in the old ones, with few (if any) legal holdups.
Pensions (especially) and life insurers are going to need/want bailouts regardless of medical changes. The combination of global ZIRP and absurdly optimistic assumptions about investment returns have led to extreme underfunding for nearly every pension fund in the developed world. This problem is especially acute in the United States but is not unique to it.
The extra uncertainty in actuarial assumptions will only leverage that problem further. Your assessment of expectations is actually pretty reasonable: pension fund managers aren't taking it seriously because they expect to be bailed out regardless, so they may as well enjoy their moral hazard dividends in advance. But I think that has more to do with the fact that financial repression and systemic underfunding have rendered everything else irrelevant anyway.
Yes, but what is the implied life expectancy? I'd guess pretty low.
Also note that policies like this require ongoing maintenance payments, otherwise you forfeit past payments and benefits.
The problem with claiming that the life insurance market is a predictor for death statistics is that firms tend to keep the most important data and calculations used to derive their pricing schemes secret. The firm is only concerned with keeping to projections as far out as they can model.
The consumer has no real input into the model (except as a selector of alternatives) and therefore cannot obtain much knowledge about actual death statistics (except perhaps a near meaningless lower-bound).
But they're probably wrong, too. Insurers have a lot of money riding on the actuarial tables, but they're still just a wisdom-of-crowds best guess. No one will know what the true life expectancy was of everyone born this year until the last of them dies; similarly, no one will know the true remaining life expectancy of everyone who is currently 50 years old until the last of them dies. I agree that actuaries are taking into consideration a lot more data and experience than any HN armchair futurist, but that doesn't mean they're going to be right. Until the 1970s, most of the increase in life expectancy at birth was due to reductions in child mortality, which from an actuarial standpoint is not very interesting because it's rare for infants to have life insurance policies. The life expectancy of a 40-year-old didn't change much from 1850 until then (source: http://www.infoplease.com/ipa/A0005140.html). In essence, nearly everyone now makes it to 40, and what's changed greatly since is what happens after that. The widespread concern is that it's not well understood whether that trend will continue, accelerate rapidly (and if so, whether the mean will increase, skew will increase, or both), or even reverse. Actuaries are professionals paid to make good guesses; they do it well, but they are not oracles.
Are you saying the assumption that the curve will change significantly is questionable or that the effects of the assumed change in the curve change are immaterial?
IE, if we accept an assumption that the curve will shift such that average life expectancy at birth is 110 50 years from today, how is this immaterial for a 30 year old today? My common sense understanding is that their chance of kicking it in the 30-35 age bracket is locked in, but once they get to 65, the curve will have shifted enough that their chance of kicking it between 65-70 (a more substantial risk) have meaningfully decreased.
Take this extreme scenario.. say we accept Aubrey De Grey's most optimistic (and probably misquoted) prediction that "the first person to live to 1,000 will be born in the next two decades," then that seems to obviously affect people alive today materially, especially if they are young.
> Are you saying the assumption that the curve will change significantly is questionable or that the effects of the assumed change in the curve change are immaterial?
Sorry, that's not quite what I am saying.
My point was that "given the purpose of this analysis, mortality factors are immaterial."
If the purpose of this analysis was to give some quantitative answers that were going to be used as the basis for decisions - then it's highly likely that you would want to build in mortality improvement.
However, in this case the analysis is just a simple illustration to convey a simple idea (actual lifespan vs life expectancy), and I would say that building in mortality improvement would muddy the waters and make it just that little bit harder for the audience to understand.
Not actually valid analysis, but it is a commonly held belief. I had an interesting conversation with a person who had just passed 50 and they where coming to grips with the realization that science was not going to defeat aging before they needed it to save them. That moment of mortality when you stop thinking about all the things you want to do, and start prioritizing them to the things you have enough time left to finish. There have been a couple of articles discussing this disconnect.
It's very generous to give the current life expectancy stats about a 50% chance of being valid by the time you reach the age to die. If the historical growth rate in life expectancy continues -- or at minimum doesn't go to zero -- there's a 0% chance. Moreover as we witness regularly on HN there are many reasons to believe that the growth rate in longevity will accelerate.
The top chart looks correctly formed, but you may be right about the bottom chart on that page: "Probabilities For Years Left to Live".
If I'm reading correctly, it seems they tried to deduce the bottom chart from the top chart, which is not appropriate for the reason you wrote.
The top chart only considers ONE year into the future from TODAY, based on someone's age TODAY. More specifically -- It's a chart for survival analysis (predict rate of failure, based on a certain fixed time period and a certain starting date) not life expectancy (predict the time period over which a certain fixed rate of failure occurs, based on any future date.)
The bottom chart though, should be far more influenced by the predicted increase in life expectancy -- since it would have to account for decades of predicted average life expectancy improvement, instead of just increase in average predicted life expectancy over one year, which probably has a negligible effect on the top chart.
I think more important than this is the fact that there are WIDE variations in the stats based on just a few important factors like smoking status, race and income - these can actually have a bigger impact than sex. If you are a non-smoking Asian programmer in Silicon Valley your curve is going to be significantly shifted to the right compared to the average presented here.
Overall, great visualization, though. Really like how it highlights the concept of chance and the range of outcomes beyond a single average number.
Last autumn I was involved in working on a similar web app [1] for WorldBank which consumed its data sources.
I think it should be more accurate as they at WorldBank collect the data from multiple sources and process it in a scientifically precise manner. You can enter country you live in, which can make a dramatic difference.
What's really depressing about this is setting the calculator to fast and to the age of my youngest kid and watching the rare odd ball fall at ages younger than me. It is rare, but it does fall. Probability, you heartless bitch.
I remember reading somewhere on the internet about a person who had a decorative bowl in their house. This bowl was full of marbles. Once a week, they would take a marble out of the bowl and throw it away. Each marble was a week of their life. When they started this practice, they calculated their life expectancy and bought enough marbles for each week they were statistically expected to live. The idea is to give you the constant reminder that our time is limited, always running out, and shouldn't be wasted. The older you get, the less time you have, and the fewer marbles that are left in that bowl. If you are a typical HN reader, you likely have less than 3,000 marbles left.
I believe that we will see significant advances in lifespan-increasing research over the next hundred years, barring any major disasters affecting humanity. Old models and expectations for calculating death can no longer be relied upon.
Most of the people alive today will probably (unfortunately or fortunately, depending on your world view) be among the last generations to die from what we currently consider natural causes.
That may be true, but I'm skeptical. Most of the advances we make are in causes of death that would lead you to die before you're at an advanced age - extending someone's life from 45 to 90 is a matter of stopping them dying from a disease or a cancer. Extending life from 90 to 100 is a matter of mitigating ageing processes where your body literally can't support itself any more. The two things (curing disease versus curing aging) are two very different realms of medicine. We've made a lot more progress in the former than the latter.
I don't doubt that it will happen, but I do doubt the timescales involved. Possibly children alive today will benefit from these advances, but 'most people alive today' seems unlikely.
I believe you misunderstood the last sentence of my post, since we seem to be in agreement. I also say that most people alive today will probably not benefit from the advances.
This notion seems to be as old as humanity. It's built on some inner hope that mortality can be outsmarted and escaped.
Back in the real world, we can't even agree as a society what level of healthcare should be afforded to all members vs. what level you have to earn.
The greatest advancements in life extension in recent years have only added more years of horribly low quality life. I don't want to die, but I am going to. Why should I invest my resources to spend years suffering?
Generally speaking, we are actually reducing the amount of time people spend suffering, while at the same time extending peoples lives. From the 2013 NBER working paper "Evidence for Significant Compression of Morbidity In the Elderly U.S. Population":
"For a typical person aged 65, life expectancy increased by 0.7 years between 1992 and 2005. Disability-free life expectancy increased by 1.6 years; disabled life expectancy fell by 0.9 years.
"The reduction in disabled life expectancy and increase in disability-free life expectancy is true for both genders and for non-whites as well as whites. Hence, morbidity is being compressed into the period just before death."
And, given that part of the low quality of life at end of life comes from two thirds of people not thinking through and documenting their wishes for care, one can improve one's personal odds by creating and advanced health care directive. And of course, many of the things that we dislike about old age result from chronic conditions that can be addressed through good nutrition and exercise.
So, good news, end of life isn't as bad as you fear!
They have added years of lower quality of life because they have focused on the wrong thing. I doubt, no matter how much research we do, that we will get a higher than 100-120 life expectancy unless we focus on actually reversing aging, instead of spending money on curing all the diseases that come with aging. It's not very smart. Aubrey de grey has some very good talks about it.
I like this way of visualizing probability as a series of random variates of the distribution in a timed sequence. After watching for a while, your mind can get an intuitive notion of the probability without having to parse numbers and functions.
It's actually a nice example of places where technology plays a real role, especially as we accumulate a lot of these little tools. This would be a handy little widget to have in a high school textbook.
The thing about this tool is it answers the following question: given your gender and your age (and no other data about you), based on CDC data of mortality in the US, how many more years do you have left to live?
In reality, you'd likely better be able to predict your remaining years if you have more details about yourself (you should, unless you're Benjamin Kyle). Are you a long-term heavy smoker, overweight like most Americans, or do you work in a dangerous job like construction? You're more likely to live less. On the other hand, do you have a safe job, stay physically fit, and avoid alcohol and drugs? You're more likely to live more.
Why? What exactly is it that you think "life insurance" does? If there were a product that would reduce the variance in remaining life length, that might be interesting, but that's not what "life insurance" is. All it does is pay someone else some amount of money when you die, after you pay them some (usually increasing) amount each year while you're alive (with countless weird financial variants for those who really like being taken to the cleaners). The ev of every such policy is negative, as it is for all types of insurance. You are almost certainly better off taking the money you would have spent on premiums and investing it conservatively; that's all the insurer is going to do with it anyway, and that way you don't have to give them a cut or worry about them going out of business before you die.
As always, the primary exception to this rule is adverse selection: if you know something about yourself that makes you much more likely to die soon, isn't reflected in actuarial tables, and won't be found by a medical exam (if required), then it may be to your designated beneficiary's advantage to buy insurance. But a healthy 34-year-old is so unlikely to die any time soon that they'll almost always be better off if you just stick money into some tax-deferred account and designate a beneficiary. Which is probably what you ought to be doing anyway, just in case you do happen to live a long time.
The EV of all insurance policy is negative when measured in absolute dollars. But the EV can be positive if the value of dollars to you doesn’t scale linearly.
For example, if you have to spend $10,000 on medical bills, that might be 1 unit of disutility. But if you have to spend $100,000 on medical bills, that might be 30 units of disutility, not 10, because you just don’t have that kind of money and you will go bankrupt and your quality of life will go way down. With this reasoning, health insurance might have a positive EV for utility, even though it has a premium that gives you a negative EV for money.
This reasoning is less likely to apply to life insurance, because people are less likely to care about what happens after they die. But for people whose beneficiaries would suffer a lot from losing their income – perhaps they would be evicted – life insurance can be worth it.
If I've understood this correctly, the one main flaw this has is that the probability to live to your next birthday is dependent not just on your current age, but also the current year. In other words, if you're 30 right now, the probability you'd need to look up is "the probability to live to my next birthday at age 30 during year 2015". When you're 40, you'll want to look up "the probability to live to my next birthday at age 40 during the year 2025", which could very well be different from "the probability to live to my next birthday at age 40 during the year 2015".
Obviously, though, we don't know how this value will change in future years, so this isn't really a fault of the chart so much as it is an unavoidable limitation. Some sort of model could be introduced for predicting healthcare advances, but I doubt anyone can do so reliably enough to produce a net increase in accuracy here.
During the early 1940s, if you were a young Russian male adult, the chance of living until 1946 was 2 in 3. Pretty strange time period. Each time you walked down the street, you could say "live, live, die, live, die, live, die, live, live" and be statistically correct.
Did you set age to 49? If you've made it this far (well done, BTW) you're chances of still ticking for log enough to worry about your 60s are pretty god, >90%.
Still, the possibility of not making it another 10 years is quite a bit higher than I am personally comfortable with, at pretty much any age. If someone has an idea for an immortality startup, I would definitely be willing to pay the $29 subscription. I would even seriously consider the $79 pro tier.
Sign up with Alcor with payment via life insuance. Or donate to the SENS Research Foundation, which is spinning off and seed funding relevant biotech startups these days.
I'm 36, and there's a spike at 37, which immediately drops down to the expected tail-end of a bell curve at 38. There seems to be something in the algorithm that disproportionately weights "next year."
I think about my own death daily, as a reminder to not take for granted this incredible opportunity of being alive in the universe. But I am still unnerved by this graph! I'm 33, and I'm old enough to know that time passes very very quickly. If I want to die well it is better to start preparing myself now; it may take a long time to get square with the truth that absolutely everything dies. 10 years from now or 1000 years from now, what difference does it make if I can't accept that I will cease to be in this form at some point?
Any hearsay over some technology that might exist to expand our lifetimes completely misses the point. There will never be an absolute end to death. Even the Sun will eventually explode, and even beyond that the universe itself will probably die in heat death. Where will we be then? At what point do we think that we will have "lived enough"? Why do we assume that if we only live longer that we'll somehow be more cool with being dead some day? Is there anything in our experience that suggests we're more OK with death the older you get?
If I have no known health problems, how does that change the distribution? Are there richer datasets that include that type of breakdown?
From a different angle, if 15% of males my age will die in the next 30 years, how many of those are foreseeable due to current circumstances vs accidents that could happen to anyone?
I was investigating this topic for some time and it turns out that the mortality curve is interesting: grows exponentially in time. In some sense, we start "aging" at the age of 6-8 y.o. (the safest age in Western countries). Plus, there is a bump of mortality in around 20, much more pronounced for males (accidents).
Running the simulation on fast, it's like those little marbles run out of gas after a certain limit and fall off. In my case the limit is somewhere in the 80s. After they hit that invisible barrier, very few continue to fly.
By comparison, there's a continuous trickle of marbles falling off randomly early.
So what I take from the simulation is that there are two main components: the random stuff that can take you out at any time, and then there's a more-or-less fixed amount of "gas" you have - when that one is gone, it's gone.
Could someone explain to me the necessity of the animation? A graph showing the probability distribution for each year would have been much better IMHO.
I think it is to reinforce the feeling of individual lives. You watch the ball scoot along to 38 years old and suddenly drop, and you recognize that sometimes it just gets cut short. When presented with just the probability distribution, it's easy to ignore the wings and focus on the mode.
I'm 24, and I recently bought $2 million of life insurance for $80 a month that's good for the next 10 years. I figure that's a pretty good deal. If I die young, I want my wife to not have to worry about money.
I don't think that's a good fit for a person in your situation. It's so unlikely that you'll die in that period. I don't know about if you have kids, a house, or your work situations, but I would consider lowering the the payout and investing the rest in a retirement account. If you dropped it down to $500,000, your wife would still be fine for years after you died. If that freed up $40 that you could invest every month, it would result in over $50,000 that you would have at retirement.
Yea, but a freak accident is unlikely to occur before 34. It is likely the decade after would be more concerning where she might have to support kids, etc. in addition to herself.
Note that life expectancy is a statistical construct, an expected outcome if you lived through the period of technological development from a lifetime ago to now.
But you won't. You will be living through the period of technological development from now until an undefined future date, and we are in the early years of a great and sweeping revolution in the capabilities of biotechnology and medicine.
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The cautious majority believes that human life span will continue to increase, but only incrementally, much as it has done for the past few decades - both life expectancy at birth and life expectancy after 60, due to the continued introduction of new medical technologies. (Which proceeds far more slowly than it could, thanks to the heavy hand of the state). One faction of epidemiologists even argues for the possibility of a dip in overall life expectancy as present trends in obesity take their toll - to their eyes the consequences of being overweight look set to outweigh modest gains due to advances in medicine.
To my mind, arguing for incrementalism in any trend relating to medicine at the present time is choosing to go against the tide. The biotechnologies that underpin advances in medicine are going through a period of massive, revolutionary change. While it is true that organizations such as the FDA do pretty much everything short of shooting scientists to slow down and increase the cost of turning research into therapies, the rapid pace of progress in the life sciences will win through.
Allow me to put forward a historical analogy: standing in 2012 and arguing a case for gentle future changes in life expectancy over the next few decades, based on the past few decades, is something like standing in 1885 or so and arguing that speed and convenience of passenger travel will steadily and gently increase in the decades ahead. The gentleman prognosticator of the mid-1880s could look back at steady progress in the operating speed of railways and similar improvement in steamships throughout the 19th century. He would be aware of the prototyping of various forms of engine that promised to allow carriages to reliably proceed at the pace of trains, and the first frail airships that could manage a fair pace in flight - though by no means the equal of speed by rail.
Like our present era, however, the end of the 19th century was a time of very rapid progress and invention in comparison to the past. In such ages trends are broken and exceeded. Thus within twenty years of the first crudely powered and fragile airships, heavier than air flight launched in earnest: a revolutionary change in travel brought on by the blossoming of a completely new branch of applied technology. By the late 1920s, the aircraft of the first airlines consistently flew four to five times as fast as the operating speed of trains in 1880, and new lines of travel could be set up for a fraction of the cost of a railway. Little in the way of incrementalism there: instead a great and sweeping improvement accomplished across a few decades and through the introduction of a completely new approach to the problem.
This is one of many historical examples of discontinuities in gentle trends brought about by fundamentally new technologies. Returning to the medicine of the present day, there are any number of lines of work we could point to as analogous to the embryonic component technologies of an aircraft in 1885. They are still in the lab, or only being trialed, or still under development - but they exist in great numbers. There are the SENS technologies; a range of advanced applications of immunotherapy; targeting methodologies to safely destroy specific cell types; organ engineering; and others. Just because we can't see the exact shape of the emerging technologies that will be constructed atop these foundations doesn't make them any less likely to be created: great changes are coming down the line in medicine. The future is not one of steady and incremental progress.
I'm the same as the author, a 34 year old male. For me, chances are pretty concentrated on me living a good few decades more. Which is ok, I can plan for that. I'll need a house to live in for the next 30 years, changing careers could be done, etc. I'm pretty unlikely to die in the next couple of decades, so hopefully I'll see my kids go to college. Chances of dying earlier are so low I can basically ignore them.
It also makes me sad about my high school classmate who passed away at 29. Set the marker to 18 and you have to wait quite a while before one of the simulations ends at 29 or earlier.
For someone older, there's an interesting issue. Say I put in my father's age, 71. There's a 1/3 chance of not making it to 81. But then there's also a 20% chance of making it past 91. What do you do about that? You can't spend all your money now. But you can't not spend it, either. Should you wait until next year to see your old friends? The likelihood is flattened out, which makes it quite hard to decide things.