for whom the bell tolls.
I originally wrote this post in April 2016 but given the WSJ discussion on “World’s Largest Hedge Fund Is Building an Algorithmic Model From its Employees’ Brains” then I thought it was worth repeating but with the snark dial turned all the way up to 11. Remember the old adage of “go away or I’ll replace you with a small Perl script” … well, maybe we might just get to enact our threat on the “robots”.
On machine intelligence
I frequently read articles about how machine intelligence and robotics will replace basic roles in society, they will become the new drivers, the new waiters, the new hospital porters and nurses of this world. But is this likely? And if they are going to replace jobs then whose job are they most suited to?
With questions like this I tend to look through three lenses — ability, cost and acceptability. Does it have the ability to do a better job at a reasonable cost and would we accept it? For example, let us take the idea of a waiter. Certainly there’s some mileage in terms of a marketing gimmick to begin with but humans are surprisingly good at taking orders, delivering food and cleaning up tables. Humans are also relatively cheap compared to the current cost of machine intelligence and robotics to replace them and in general though we might be able to trust a robot to deliver our food, would the banter be the same and would it be as socially acceptable to customers? Beyond the gimmick, I doubt this change will happen for quite a long time.
However, there are other groups where ability, cost and acceptability are far more positive for replacement. One possible candidate is that of the CEO. The CEO? Of a company? Surely not? Well, I think so. Lets go through the reasons.
Ability
From my experience, most CEOs tend to demonstrate poor situational awareness and an inability to decipher doctrine from context specific play. My own work in 2012, which examined situational awareness versus action for 160+ Silicon Valley companies showed that those with high levels of situational awareness performed better. But this was Silicon Valley, it was supposed to be at the cutting edge and even here there were large companies operating with poor situational awareness of their environment and suffering for it.
Going beyond Silicon Valley and boardrooms started to feel more akin to alchemy, gut feel and whatever is popular in the HBR than to chess playing masters. Situational awareness appeared to be the exception and not the rule. So rather than being a Darwinian competition of survival of the fittest where all conquering CEOs battle each other in a game of wits, there’s another less charitable way of looking at this — survival of the least hazardous. It’s governed by the same rules but rather than a positive chess like game of survival, it’s more random with the occasional hero characters. A bit like the brawl of new players in fantasy role playing games like world of warcraft where most run around shouting “I’m lost” and one player saves the team. An awful lot boils down to luck. Surely, this can’t be the case? Alas various studies have questioned the impacts of CEOs e.g. Markus Fitza’s study demonstrated that the measurable CEO effect on firm performance varies little from chance.
Given that situational awareness can be improved, that doctrine and context specific play can be learned and we’ve seen first hand the experience of companies failing to understand basic lessons and being disrupted by highly predictable change (e.g. cloud) then we have to ask whether this is just inertia, blindness or caused by some other motivation? CEOs are not daft people but then neither are fund managers and the vast majority were outperformed by simple trackers of financial indices. From my experience, this is an area where machine intelligence might vastly improve on the performance of the incumbent executives along with the industry of management consultants that often “supports” them.
Cost
The other upside of replacing the CEO with machine intelligence is cost. Unlike your average waiter, CEOs aren’t cheap — they tend to be very expensive. Now, whilst Marissa Mayer’s performance at CEO of Yahoo has not been bad (despite what many think, the company has at least maintained its revenue), the question becomes whether this has been worth the speculated $365 million for 5 years of work. It doesn’t actually matter how much the figure is, we simply know it’ll be a lot more than a waiter expects. In general, there’s a lot more money on the table replacing the CEO than there is your average worker.
Acceptability.
But CEOs lead us! You wouldn’t trust a robot! Well, that’s probably the idea in the hallowed walls of executive thinking and business schools. But on the shop-floor we’re already becoming used to machines taking life and death decisions for us in areas such as driving cars. Most people tend to be motivated by their own autonomy, the ability to gain mastery, purpose (as in direction) and financial rewards. Using cell based structures, maps, fitness functions and other tools (e.g. the pioneer, settler and town planner structure which AirBnB discussed) then it should be possible for most companies to create such an environment. I’d argue a machine intelligence could manage this just as easily as a human.
A machine could direct a cell of human pioneers to go do what they are good at by exploring an uncertain area to see what is found. Equally, at the other extreme a machine is just as capable of telling a cell of human town planners to look at industrialising something and it is even more likely to take rational decisions without inertia and sentimental motivation or concerns over political capital due to past investments. Also, a machine is perfectly capable of learning the basic economic patterns that apply to an environment. The failures of past technology giants in cloud computing were executive failures and human error against highly predictable changes. It wasn’t lack of skilled engineers on the shop-floor.
Back in 2008, at Canonical (Ubuntu) we exploited the predictable changes of cloud computing in order to take the company from a small fraction of the market to 70% of all cloud in around 18 months. Ubuntu has maintained that position ever since. Had we been up against machines rather than human executives then I’m not sure we could have got away with it and we certainly couldn’t have used inertia against others. I somehow doubt people will have a problem with a machine intelligence being the CEO if it leads to more stability and more security along with enhancements to their own autonomy and mastery. Given these conditions I suspect many on the shop-floor would happily cheer for our robot overlords — “hey, are you’re still running with that old Cyberdyne systems CEO? We’ve just installed the new HAL 9000, it comes with better stock performance and added EQ with moral imperative subroutines. Everyone is really happy.”
Except of course, there’s one group that might not cheer — those desiring to be CEO and those who are the CEO. Actually, there’s another group which are the management consultants that thrive off them. Executives tend to be very busy people trying to deal with complex and complicated environments. They are always looking for quick answers and there’s an entire industry ready to sell the latest magic solution. Just look at the stuff that pervades our industry from Myers Briggs Personality Tests to how earlobes can signify leadership potential (as reported in the HBR). Could we not do better? Would a machine care about earlobes? Unfortunately, such groups voting for robotic CEOs would be like turkeys voting for Christmas. If such a change was to happen then it would have to be through testing first in startups and then activist investors. Which, by the way, is why that WSJ article is so fascinating.
Given all the roles that could be replaced then on a basis of ability, cost and acceptability then the average CEO seems as good if not a far better bet than your average waiter. There are always exceptions to rules but it’s certainly worth thinking about. In my view it’s not the blue collar workers that need to be immediately worried about robots / machine intelligence but instead the white collar workers who think they’re not the target.
Originally published at blog.gardeviance.org on December 22, 2016.