Creative and Social Intelligence are Computational Bottlenecks

Our model predicts that the second wave of computerisation will mainly depend on overcoming the engineering bottlenecks related to creative and social intelligence. As reported in Table III, the “fine arts”, “originality”, “negotiation”, “persuasion”, “social perceptiveness”, and “assisting and caring for others”, variables, all exhibit relatively high values in the low risk category. By contrast, we note that the “manual dexterity”, “finger dexterity” and “cramped work space” variables take relatively low values. Hence, in short, generalist occupations requiring knowledge of human heuristics, and specialist occupations involving the development of novel ideas and artifacts, are the least susceptible to computerisation. As a prototypical example of generalist work requiring a high degree of social intelligence, consider the O∗NET tasks reported for chief executives, involving “conferring with board members, organization offi- cials, or staff members to discuss issues, coordinate activities, or resolve problems”, and “negotiating or approving contracts or agreements.” Our predictions are thus intuitive in that most management, business, and finance occupations, which are intensive in generalist tasks requiring social intelligence, are largely confined to the low risk category. The same is true of most occupations in education, healthcare, as well as arts and media jobs. The O∗NET tasks of actors, for example, involve “performing humorous and serious interpretations of emotions, actions, and situations, using body movements, facial expressions, and gestures”, and “learning about characters in scripts and their relationships to each other in order to develop role interpretations.” While these tasks are very different from those of a chief executive, they equally require profound knowledge of human heuristics, implying that a wide range of tasks, involving social intelligence, are unlikely to become subject to computerisation in the near future

The low susceptibility of engineering and science occupations to computerisation, on the other hand, is largely due to the high degree of creative intelligence they require. The O∗NET tasks of mathematicians, for example, involve “developing new principles and new relationships between existing mathematical principles to advance mathematical science” and “conducting research to extend mathematical knowledge in traditional areas, such as algebra, geometry, probability, and logic.” Hence, while it is evident that computers are entering the domains of science and engineering, our predictions implicitly suggest strong complementarities between computers and labour in creative science and engineering occupations; although it is possible that computers will fully substitute for workers in these occupations over the long-run. We note that the predictions of our model are strikingly in line with the technological trends we observe in the automation of knowledge work, even within occupational categories. For example, we find that paralegals and legal assistants – for which computers already substitute – in the high risk category. At the same time, lawyers, which rely on labour input from legal assistants, are in the low risk category. Thus, for the work of lawyers to be fully automated, engineering bottlenecks to creative and social intelligence will need to be overcome, implying that the computerisation of legal research will complement the work of lawyers in the medium term.


Generalist skills, like management, are hard to automate. Could everyone therefore become a manager of an automatized field?

Folksonomies: futurism employment automation

/sports/hockey/field hockey (0.574272)
/education (0.304805)
/society/welfare/healthcare (0.268511)

social intelligence (0.915425 (negative:-0.652688)), low risk category (0.853591 (negative:-0.456400)), O∗NET tasks (0.664983 (neutral:0.000000)), Computational Bottlenecks Generalist (0.633588 (neutral:0.000000)), human heuristics (0.580851 (neutral:0.000000)), engineering bottlenecks (0.580271 (negative:-0.652688)), generalist occupations (0.574796 (neutral:0.000000)), cramped work space (0.566811 (negative:-0.615978)), relatively low values (0.564514 (negative:-0.467362)), high degree (0.561307 (negative:-0.310816)), computerisation (0.553250 (negative:-0.573379)), high risk category (0.547693 (neutral:0.000000)), specialist occupations (0.547450 (neutral:0.000000)), finance occupations (0.543905 (neutral:0.000000)), legal assistants (0.538248 (neutral:0.000000)), science occupations (0.537010 (negative:-0.495003)), generalist tasks (0.536256 (neutral:0.000000)), engineering occupations (0.534825 (neutral:0.000000)), generalist work (0.516739 (neutral:0.000000)), manual dexterity (0.499883 (neutral:0.000000)), finger dexterity (0.498412 (neutral:0.000000)), prototypical example (0.498011 (neutral:0.000000)), social perceptiveness (0.497501 (neutral:0.000000)), fine arts (0.489840 (positive:0.524319)), creative intelligence (0.489600 (negative:-0.310816)), novel ideas (0.488961 (neutral:0.000000)), low susceptibility (0.486565 (negative:-0.495003)), board members (0.485831 (positive:0.397044)), staff members (0.485698 (neutral:0.000000)), media jobs (0.485662 (positive:0.385644))

chief executive:JobTitle (0.788375 (neutral:0.000000))

Mathematics (0.985860): dbpedia | freebase | opencyc
Science (0.593491): dbpedia | freebase | opencyc
Scientific method (0.587395): dbpedia | freebase
Hand (0.548702): dbpedia | freebase | opencyc
Computer science (0.504935): opencyc | freebase | dbpedia
Engineering (0.461407): freebase | dbpedia
Category theory (0.440258): dbpedia | freebase | opencyc
Fine motor skill (0.428305): dbpedia | freebase | opencyc | yago
Chief executive officer (0.427427): dbpedia | freebase | opencyc
The Work (0.427266): dbpedia | freebase | yago
Law (0.387832): dbpedia | freebase | opencyc

 The Future of Employment: How Susceptible are Jobs to Computerization
Periodicals>Journal Article:  Frey, Carl Benedikt and Osborne, Michael A. (September 17, 2013), The Future of Employment: How Susceptible are Jobs to Computerization, Retrieved on 2017-03-10
  • Source Material []
  • Folksonomies: automation