There's some game theoryish ideas such as the Peter Principle which might explain why meritocratic promotion may not work out in the long run for organizations. See: https://arxiv.org/abs/0907.0455 which won the parody Ig Nobel prize, but I don't really understand why, as I thought it was at least as interesting as Robert Axelrod's simulation of successful strategies in the iterated prisoner's dilemma. In fact, I think it would be even warranted to do an extension of this model, considering possible assumptions such as Dilbert principle, negative selection, and alignment of agents with different goals and basic strategies. I am not understanding why such a model would be considered silly instead of insightful.
The Peter Principle Revisited: A Computational Study
Alessandro Pluchino, Andrea Rapisarda, Cesare Garofalo
2009 · arXiv
- HN score
- 0
- Mentions
- 5
- Readers
- 5
- Months
- 5
From the abstract
In the late sixties the Canadian psychologist Laurence J. Peter advanced an apparently paradoxical principle, named since then after him, which can be summarized as follows: {\it 'Every new member in a hierarchical organization climbs the hierarchy until he/she reaches his/her level of maximum incompetence'}. Despite its apparent unreasonableness, such a principle would realistically act in any organization where the mechanism of promotion rewards the best members and where the mechanism at their new level in the hierarchical structure does not depend on the competence they had at the previous level, usually because the tasks of the levels are very different to each other. Here we show, by means of agent based simulations, that if the latter two features actually hold in a given model of an organization with a hierarchical structure, then not only is the Peter principle unavoidable, but also it yields in turn a significant reduction of the global efficiency of the organization. Within a game theory-like approach, we explore different promotion strategies and we find, counterintuitively, that in order to avoid such an effect the best ways for improving the efficiency of a given organization are either to promote each time an agent at random or to promote randomly the best and the worst members in terms of competence.
Metadata: arXiv. Abstracts retain their original authors’ rights.
In the conversation
Original HN comments, with labels from simple text rules. A label describes the whole comment and may miss context or irony. Read the discussion to make up your own mind. About the labels
5 selected excerpts · 5 total mentions
Also worth noting that a promotion is not just a raise, it is also a change of job. See Peter Principle. There is even a igNobel winning publication suggesting that it might be more efficient to promote people at random... https://arxiv.org/abs/0907.0455
This fits nicely with the study which shows that organizations are more efficient if people are promoted at random ;-) http://arxiv.org/abs/0907.0455
This also reminds me of a paper I had submitted in the past. Randomly promoting people is more effective than using merit: http://arxiv.org/abs/0907.0455
Yes, I read the paper. (Not, I confess, every word, but enough to be pretty sure I'm not misrepresenting it.) It's linked right at the end of the article. http://arxiv.org/abs/0907.0455
Keep following the thread.
More in PsychologyMore from the same topics.
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan +11
Artificial intelligence (AI) researchers have been developing and refining large language models (LLMs) that exhibit remarkable capabilities across a variety of domains and tasks, challenging our understanding of learning and cognition.
Talent vs Luck: the role of randomness in success and failure
A. Pluchino. A. E. Biondo, A. Rapisarda
The largely dominant meritocratic paradigm of highly competitive Western cultures is rooted on the belief that success is due mainly, if not exclusively, to personal qualities such as talent, intelligence, skills, efforts or risk taking.
Categorizing Variants of Goodhart's Law
David Manheim, Scott Garrabrant
There are several distinct failure modes for overoptimization of systems on the basis of metrics.
Generative Agents: Interactive Simulacra of Human Behavior
Joon Sung Park, Joseph C. O'Brien, Carrie J. Cai +3
Believable proxies of human behavior can empower interactive applications ranging from immersive environments to rehearsal spaces for interpersonal communication to prototyping tools.