Will my boss ever be a robot?

I received that question via quora (Spanish version) a couple of days ago, and I’ve thought that it is a good matter of debate. In few words, yes, I think it’s feasible, but not in the way many people think of a robot: anthropomorphic, individual, like those we’ve seen in sci fi films like Ex Machina, Eva or Westworld; at the end, those are general AI examples that we won’t see realized before many decades, (if ever).

I see it more likely that an operating system like the one in the movie Her is developed to analyze millions of data, plan and distribute tasks among all employees of a company -no matter how numerous they are- and always find the optimal path to achieve business goals (in the fastest-less expensive way, and with better final results compared to a human manager). In that sense, that “robot boss” would play a hybrid role between a tradicional project managers and current scrum masters.

A good reference to go deeper into this subject is this excellent McKinsey report on AI impact on labour throughout all sectors and jobs. It makes a comparative analysis to assing the probability of being automated for a given role within a sector, taking into consideration 5 factors: 1) technical feasibility; 2) costs to automate; 3) the relative scarcity, skill level, and cost of workers who might otherwise do the activity; 4) benefits (eg., superior performance of automation beyond labor-cost substitution); and 5) regulatory and social-acceptance considerations.

Their conclusion is that management tasks will be among the lasts to be automated… what doesn’t mean that the wave of automation will not reach them at the end. From my point of view the main barrier for that is the need to digitize every interaction in the work environment, in order to reach traceability and develop models based on enough and reliable data*.

A couple of examples show how an operating system as described above can become technically feasible perhaps not so far away in the near future:

  1. Think that you already interact with a supercomputer when you make your tax declaration, that system successfully detects fraud using machine learning algorithms and multiple data sources to find anomalies among millions of tax return forms.

In any case, I see these systems as a support to the management and execution of specific predefined objectives, but to devise those business aims after an analysis of the strategic environment and opportunities, I believe that human creativity will continue to be essential for a long time.

Let’s think of the most relevant pros and cons of this possibility:

( — )Monitor workers’ behaviour and performance is a very invasive approach to gain efficiency, and it is seen as unacceptable by most western citizens, that would feel it like a throwback to the times of industrial taylorism. The fact is that, if it is feasible and profitable, at the end it will be developed in any other part of the world with less concerns on privacy and more pressure to gain efficiency (yes, I am reading your mind: it starts with Chi and ends with na).

(+)In that scenario cool objectivity would guide promotions and salary improvements decisions, based on objective metrics about performance, and not by personal sympathies or affinities.

*To close the reflection let’s highlight the importance of ensuring a minimum level of reliability through one of my favourite quotes on AI:

“People worry that computers will get too smart and take over the world, but the real problem is that they’re too stupid and they’ve already taken over the world.”

Pedro Domingos at The Master Algorithm



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Juan Murillo Arias

MSc Civil Engineer by UPM, Executive MBA by EOI. Experience as urban planner and project manager in technological innovation and smart cities initiatives.