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Talent Versus Luck: The Role Of Randomness In Success And Failure

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  • ALESSANDRO PLUCHINO

    (Department of Physics and Astronomy, University of Catania, Via S.Sofia 64, Catania 95123, Italy2INFN-CT, Via S. Sofia 64, Catania 95123, Italy)

  • ALESSIO EMANUELE BIONDO

    (Department of Economics and Business, University of Catania, Corso Italia 55, Catania 95129, Italy)

  • ANDREA RAPISARDA

    (Department of Physics and Astronomy, University of Catania, Via S.Sofia 64, Catania 95123, Italy2INFN-CT, Via S. Sofia 64, Catania 95123, Italy4Complexity Science Hub Vienna, Austria)

Abstract

The largely dominant meritocratic paradigm of highly competitive Western cultures is rooted on the belief that success is mainly due, if not exclusively, to personal qualities such as talent, intelligence, skills, smartness, efforts, willfulness, hard work or risk taking. Sometimes, we are willing to admit that a certain degree of luck could also play a role in achieving significant success. But, as a matter of fact, it is rather common to underestimate the importance of external forces in individual successful stories. It is very well known that intelligence (or, more in general, talent and personal qualities) exhibits a Gaussian distribution among the population, whereas the distribution of wealth — often considered as a proxy of success — follows typically a power law (Pareto law), with a large majority of poor people and a very small number of billionaires. Such a discrepancy between a Normal distribution of inputs, with a typical scale (the average talent or intelligence), and the scale-invariant distribution of outputs, suggests that some hidden ingredient is at work behind the scenes. In this paper, we suggest that such an ingredient is just randomness. In particular, our simple agent-based model shows that, if it is true that some degree of talent is necessary to be successful in life, almost never the most talented people reach the highest peaks of success, being overtaken by averagely talented but sensibly luckier individuals. As far as we know, this counterintuitive result — although implicitly suggested between the lines in a vast literature — is quantified here for the first time. It sheds new light on the effectiveness of assessing merit on the basis of the reached level of success and underlines the risks of distributing excessive honors or resources to people who, at the end of the day, could have been simply luckier than others. We also compare several policy hypotheses to show the most efficient strategies for public funding of research, aiming to improve meritocracy, diversity of ideas and innovation.

Suggested Citation

  • Alessandro Pluchino & Alessio Emanuele Biondo & Andrea Rapisarda, 2018. "Talent Versus Luck: The Role Of Randomness In Success And Failure," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(03n04), pages 1-31, May.
  • Handle: RePEc:wsi:acsxxx:v:21:y:2018:i:03n04:n:s0219525918500145
    DOI: 10.1142/S0219525918500145
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    References listed on IDEAS

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    Cited by:

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    2. Siudem, Grzegorz & Nowak, Przemysław & Gagolewski, Marek, 2022. "Power laws, the Price model, and the Pareto type-2 distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    3. Didier Sornette & Spencer Wheatley & Peter Cauwels, 2019. "The fair reward problem: the illusion of success and how to solve it," Papers 1902.04940, arXiv.org, revised Apr 2019.
    4. Savi, Alexander O. & Marsman, Maarten & van der Maas, Han L.J., 2021. "Evolving networks of human intelligence," Intelligence, Elsevier, vol. 88(C).
    5. Filip Gesiarz & Jan-Emmanuel De Neve & Tali Sharot, 2020. "The motivational cost of inequality: Opportunity gaps reduce the willingness to work," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-18, September.
    6. A. E. Biondo & G. Burgio & A. Pluchino & D. Puglisi, 2022. "Taxation and evasion: a dynamic model," Journal of Evolutionary Economics, Springer, vol. 32(3), pages 797-826, July.
    7. Sobkowicz, Pawel & Frank, Robert H. & Biondo, Alessio E. & Pluchino, Alessandro & Rapisarda, Andrea, 2020. "Inequalities, chance and success in sport competitions: Simulations vs empirical data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    8. Mrowinski, Maciej J. & Gagolewski, Marek & Siudem, Grzegorz, 2022. "Accidentality in journal citation patterns," Journal of Informetrics, Elsevier, vol. 16(4).
    9. Zappalà, Chiara & Biondo, Alessio Emanuele & Pluchino, Alessandro & Rapisarda, Andrea, 2023. "The paradox of talent: How chance affects success in tennis tournaments," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    10. Tian, Songtao & Liu, Zhirong, 2020. "Emergence of income inequality: Origin, distribution and possible policies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    11. Didier Sornette & Spencer Wheatley & Peter Cauwels, 2019. "The Fair Reward Problem: The Illusion Of Success And How To Solve It," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(03), pages 1-52, May.

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