What is amazing is that computers have not already reduced the workforce to run bureaucracies.
In my upcoming book I analyze the Australian Tax Office in 1955 (when Parkinson wrote is great paper) and 2008. At both times it took about 1.5% of GDP to do essentially the same function. (Normalizing for GDP takes into account inflation and population size.)
Back in 1955 tax returns were largely processed by hand, by rows of clerks with fountain pens. Just one ancient mainframe could do the work of thousands of people. Today few returns are even touched by a human hand.
The steam tractor and the combine harvester have reduced the agricultural work force from 80% of the population to less than 20%, depending how you count. But the huge increase in the power of bureaucratic tools has produced no reduction in the proportion of the population that work in bureaucracies, quite the opposite.
People complain about increased regulation nowadays - are these bureaucrats managing more things than before?
I haven't given much thought to the concept of automation and computer induced unemployment. Others at the FHI have been looking into it in more details - see Carl Frey's "The Future of Employment", which did estimates for 70 chosen professions as to their degree of automatability, and extended the results of this using O∗NET, an online service developed for the US Department of Labor, which gave the key features of an occupation as a standardised and measurable set of variables.
The reasons that I haven't been looking at it too much is that AI-unemployment has considerably less impact that AI-superintelligence, and thus is a less important use of time. However, if automation does cause mass unemployment, then advocating for AI safety will happen in a very different context to currently. Much will depend on how that mass unemployment problem is dealt with, what lessons are learnt, and the views of whoever is the most powerful in society. Just off the top of my head, I could think of four scenarios on whether risk goes up or down, depending on whether the unemployment problem was satisfactorily "solved" or not:
with AI problems, people and
organisations are willing and
able to address the big issues.
misery that unrestricted AI
research can cause, and very
wary of future disruptions. Those
at the top want to hang on to
their gains, and they are the one
with the most control over AIs
and automation research.
automation problems in a
particular way (eg taxation),
people underestimate the risk
and expect the same
solutions to work.
conflict between those benefiting
from automation and those
losing out, and superintelligence
is seen through the same prism.
Those who profited from
automation are the most
powerful, and decide to push
ahead.
But of course the situation is far more complicated, with many different possible permutations, and no guarantee that the same approach will be used across the planet. And let the division into four boxes not fool us into thinking that any is of comparable probability to the others - more research is (really) needed.