Monthly Archives: March 2020

Virtual reality helmet for video calling

Current virtual reality headsets can display video calls, but the person wearing the VR goggles is filmed from outside these. A face with its top half covered by VR goggles is not very expressive, which somewhat defeats the purpose of a video call. The solution is a sphere around the head with the webcam inside it and the video of the other caller projected on the inside. An astronaut’s helmet is an analogy.

To prevent suffocation, the sphere should not be airtight – small CPU fans can be installed at the top or back to circulate air in and out. This also prevents humidity buildup. For headphones as well, I would prefer some ventilation of the area covered.

Multiple webcams pointed at the face allow for 3D imaging, so the video call could take full advantage of the 3D display of virtual reality headsets. However, 3D display relies on projecting a different image to each eye. If the video call is simply projected on the inside of the sphere, then it is a single image and the 3D effect is lost. One solution is to point a small data projector at each eye to display different images. Then the sphere is not needed, just cameras and projectors attached to a stick attached to a headband. A Dilbert comic had this idea, but I cannot find the link on the web.

Oxygenating blood directly

Engineering and biological constraints may make the following idea infeasible, but theoretically, one way to keep people with lung damage alive is to pump their blood through a machine that oxygenates it. Dialysis is an analogous treatment for kidney failure.

Blood would be taken out via a cannula, pumped through a system with a large surface area covered with an oxygen-permeable membrane. On the other side of the membrane is gaseous oxygen. After passing through, blood is pumped back into the body via another cannula.

The large surface area could be just two flat plates with a narrow gap between them. The oxygen-permeable plate probably needs to be thin, which makes it weak. Positioning the plates horizontally allows the pressure of the blood between the plates to support the top plate. The pressure of the oxygen above it could be regulated so the plate does not bulge outward. With careful pressure management, the plate does not have to be rigid, could be just a thin film.

The potential complications are in the details: ideally the blood would be taken from the arteries leading from the heart to the lungs and inserted into the veins going from the lungs to the heart, but puncturing these vessels is dangerous. Taking the blood from an arm or leg vein is straightforward, but there may be biological problems if oxygenated blood is pumped back into a vein instead of an artery.

Sudden lung failure does not leave enough time for such a system to be set up, because death occurs quickly without oxygen. However, if the lung failure is predicted with high probability in advance (such as when a disease is disabling the lungs), then the person can be connected to the oxygenation system and kept alive. This buys time for either the disease to be cured, in which case the lungs may become functional again, or for lung transplantation if feasible.

On the optimality of self-quarantine

Is self-quarantine early in an epidemic optimal, either individually or for society?

Individual incentives are easier to analyse, so let’s start with these. Conditional on catching a disease, other things equal, later is better. The reasons are discounting and the advances in treatment. A delay of many years may increase the severity conditional on infection (old age weakens immunity), but such long time intervals are typically not relevant in an epidemic.

Conditional on falling ill within the next year (during which discounting and advances in treatment are negligible), it is better to catch the disease when few others are infected, so hospitals have spare capacity. This suggests either significantly before or long after the peak of the epidemic. Self-quarantine, if tight enough, may postpone one’s infection past the peak.

Another individually optimal choice is to get infected early (also called vaccination with live unattenuated virus), although not if immunity increases very little or even decreases. The latter means that one infection raises the probability of another with the same disease, like for malaria, HIV and herpes, which hide out in the organism and recur. Cancer displays similar comebacks. For viral respiratory diseases, as far as I know, immunity increases after infection, but not to 100%. The optimality of self-quarantine vs trying to be infected early then depends on the degree of immunity generated, the quality of the quarantine, whether the disease will be eradicated soon after the epidemic, and other details of the situation.

Individual optimality also depends on what the rest of the population is doing. If their self-quarantine is close to perfect, then an individual’s risk of catching the disease is very low, so no reason to suffer the disutility of isolation. If others quarantine themselves moderately, so the disease will be eradicated soon, but currently is quite infectious, then self-isolation is individually optimal. If others do almost nothing, and the disease spreads easily and does not generate much immunity, then an individual will either have to self-quarantine indefinitely or will catch it. Seasonal flu and the common cold (various rhinoviruses and adenoviruses) are reasonable examples. For these, self-quarantine is individually suboptimal.

Social welfare considerations seem to weigh in favour of self-quarantine, because a sick person infects others, which speeds up the epidemic. One exception to the optimality of self-quarantine comes from economies of scale in treatment when prevalence is not so high as to overwhelm the health system. If the epidemic is fading, but the disease increases immunity and is likely to become endemic, with low prevalence, then it may be better from a social standpoint to catch the disease when treatment is widely available, medical personnel have just had plenty of experience with this illness, and not many other people remain susceptible. This is rare.

Herd immunity is another reason why self-quarantine is socially suboptimal for some diseases. The logic is the same as for vaccination. If catching chickenpox as a child is a mild problem and prevents contracting and spreading it at an older age when it is more severe, then sending children to a school with a chickenpox epidemic is a smart idea.

Reducing the duration of quarantine for vulnerable populations is another reason why being infected sooner rather than later may be socially optimal. Suppose a disease is dangerous for some groups, but mild or even undetectable for most of the population, spreads widely and makes people resistant enough that herd immunity leads to eradication. During the epidemic, the vulnerable have to be isolated, which is unpleasant for them. The faster the non-vulnerable people get their herd immunity and eradicate the infection, the shorter the quarantine required for the vulnerable.

For most epidemics, but not all, self-quarantine is probably socially optimal.

If top people have families and hobbies, then success is not about productivity


1 Productivity is continuous and weakly increasing in talent and effort.

2 The sum of efforts allocated to all activities is bounded, and this bound is similar across people.

3 Families and hobbies take some effort, thus less is left for work. (For this assumption to hold, it may be necessary to focus on families with children in which the partner is working in a different field. Otherwise, a stay-at-home partner may take care of the cooking and cleaning, freeing up time for the working spouse to allocate to work. A partner in the same field of work may provide a collaboration synergy. In both cases, the productivity of the top person in question may increase.)

4 The talent distribution is similar for people with and without families or hobbies. This assumption would be violated if for example talented people are much better at finding a partner and starting a family.

Under these assumptions, reasonably rational people would be more productive without families or hobbies. If success is mostly determined by productivity, then people without families should be more successful on average. In other words, most top people in any endeavour would not have families or hobbies that take time away from work.

In short, if responsibilities and distractions cause lower productivity, and productivity causes success, then success is negatively correlated with such distractions. Therefore, if successful people have families with a similar or greater frequency as the general population, then success is not driven by productivity.

One counterargument is that people first become successful and then start families. In order for this to explain the similar fractions of singles among top and bottom achievers, the rate of family formation after success must be much greater than among the unsuccessful, because catching up from a late start requires a higher rate of increase.

Another explanation is irrationality of a specific form – one which reduces the productivity of high effort significantly below that of medium effort. Then single people with lots of time for work would produce less through their high effort than those with families and hobbies via their medium effort. Productivity per hour naturally falls with increasing hours, but the issue here is total output (the hours times the per-hour productivity). An extra work hour has to contribute negatively to success to explain the lack of family-success correlation. One mechanism for a negative effect of hours on output is burnout of workaholics. For this explanation, people have to be irrational enough to keep working even when their total output falls as a result.

If the above explanations seem unlikely but the assumptions reasonable in a given field of human endeavour, then reaching the top and staying there is mostly not about productivity (talent and effort) in this field. For example, in academic research.

A related empirical test of whether success in a given field is caused by productivity is to check whether people from countries or groups that score highly on corruption indices disproportionately succeed in this field. Either conditional on entering the field or unconditionally. In academia, in fields where convincing others is more important than the objective correctness of one’s results, people from more nepotist cultures should have an advantage. The same applies to journals – the general interest ones care relatively more about a good story, the field journals more about correctness. Do people from more corrupt countries publish relatively more in general interest journals, given their total publications? Of course, conditional on their observable characteristics like the current country of employment.

Another related test for meritocracy in academia or the R&D industry is whether coauthored publications and patents are divided by the number of coauthors in their influence on salaries and promotions. If there is an established ranking of institutions or job titles, then do those at higher ranks have more quality-weighted coauthor-divided articles and patents? The quality-weighting is the difficult part, because usually there is no independent measure of quality (unaffected by the dependent variable, be it promotions, salary, publication venue).

Learning and evolution switch the sign of autocorrelations

Animals are more successful if they learn or evolve to predict locations of food, mates and predators. Prediction of anything relies on correlations over time in the environment. These correlations may be positive or negative. Learning is more difficult if the sign of the correlation switches over time, which occurs in nature due to resource depletion, learning and evolution.

If a herbivore eats a tasty patch of plants or a predator a nest full of eggs, then the next day that food is not there (negative correlation), but the next year at the same time it is probably there again (positive correlation) because the plants regrow from roots or seeds, and if the prey found the nesting spot attractive one year, then other members of the prey species will likely prefer it the next year as well. However, over many generations, if the plants in that location get eaten before dispersing seeds or the young in that nest before breeding, then the prey will either learn or evolve to avoid that location, or go extinct. This makes the autocorrelation negative again on sufficiently long timescales.

Positive correlation is the easiest to learn – just keep doing the same thing and achieve the same successful outcome. Negative correlation is harder, because the absence of success at one time predicts success from the same action at another time, and vice versa. Learning a changing correlation requires a multi-parameter mental model of the superimposed different-frequency oscillations of resource abundance.

There is a tradeoff between exploiting known short-period correlations and experimenting to learn longer-period correlations. There may always be a longer pattern to discover, but finite lifetimes make learning very low-frequency events not worthwhile.