I just returned from a week of amazing talks at the IEEE conference on computational intelligence in Paris (yay!). I won’t bore you with a full review but I thought I’d do a post on an interesting debate I had based on a paper presented at the conference. The debate was about how much a human life is worth, it’s a crucial variable if you are writing an algorithm for managing a rapid response to a state of emergency. It is still generally too much of a taboo to put a real number on the value, let alone seriously consider giving different lives different values. That said we know if we had one fire engine to send to a burning school or a burning office we would not make a random decision. At the moment it takes up to 16 minutes for emergency vehicles to be dispatched in a state of emergency, if the dispatch was fully automated decisions would be made in seconds (Mohammadi & Sadeghian, 2011).
It’s a relevant question for me because my interest is in brain computer interfacing (BCI), a technology that provides means of communication for the severely paralysed by linking the human brain directly to a computer. BCI isn’t widely used clinically yet largely because the medical grade EEG equipment required costs tens of thousands of dollars. What isn’t discussed is the question of whether health authorities are interested in extending lives using artificial means, it certainly doesn’t do health budgets any favours and for some people the prospect leaves a bitter taste in the mouth.
One reason I’m fully behind the (BCI) developments is that history shows clearly that the costs of these systems are destined to fall rapidly and if we invest in them their performance is likely to increase exponentially. If you were to plot a graph of the increase in computing power or the reduction in computing cost over time using a regular linear graph it would be a relatively straight line disappearing almost vertically in to the sky.
The graph below is a semi-logarithmic plot which means each level on the y-axis represents a number one hundred times the level below it.
During some slightly off-topic research on this somewhat rhetorical question I stumbled across this rather morbid paper which presents some intriguing stats from a meta-analysis of peer reviewed journals. Below are just a few of the relative costs of treatments or state interventions that are in practice. They are presented in terms of the cost of the intervention for every “life-year” saved.
I’ll be first to admit that some of the figures are more than a little bit odd (probably due to the infinite number of confounding factors in a comparative study like this) and I haven’t reviewed the sources of the paper but I recommend taking a glance at the original (PDF). It’s morbidly intriguing, if nothing else.
Tengs, T., Adams, M., Pliskin, J., Safran, D., Siegel, J., Weinstein, M., & Graham, J. (1995). Five-Hundred Life-Saving Interventions and Their Cost-Effectiveness Risk Analysis, 15 (3), 369-390 DOI: 10.1111/j.1539-6924.1995.tb00330.x
Mohammadi, & Sadeghian (2011). iFAST: An Intelligent Fire-Threat Assessment and Size-up Technology for First Responders Proceedings of IEEE Symposium Series in Computational Intelligence
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