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New technologies, potential unemployment and ‘nescience economy’ during and after the 2020 economic crisis

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  • Stepan Zemtsov

Abstract

The coronavirus pandemic and the economic crisis in 2020 are accelerating digital transformation. During and after the crisis, there are opportunities and needs for remote work facilities, online services, delivery drones, etc. We discuss how unmanned technologies can cause a long‐term employment decrease, and why compensation mechanisms may not work. Using the internationally comparable Frey–Osborne methodology, we estimated that less than a third of employees in Russia work in professions with a high automation probability. Some of these professions can suffer the most during quarantine measures; employment in traditional services can be significantly reduced. By 2030, about half of the jobs in the world and a little less in Russia will need to adapt during the fourth industrial revolution because they are engaged in routine, potentially automated activities. In the regions, specializing in manufacturing, this value is higher; the lowest risk is in the largest agglomerations with a high share of digital economy, greater and diverse labour markets. Accelerating technological change can lead to a long‐term mismatch between the exponential increase in automation rate and compensating effects of retraining, new jobs creation and other labour market adaptation mechanisms. Some people will not be ready for a life‐long learning and competition with robots, and accordingly there is a possibility of their technological exclusion. The term “nescience economy” and corresponding assessment method were proposed. Using an econometric model, we identified factors that reduce these risks: human capital concentration, favourable business climate, high quality of life and ICT development. Based on these factors, some recommendations for authorities were proposed in the conclusion. La pandemia de coronavirus y la crisis económica de 2020 están acelerando la transformación digital. Durante y después de la crisis, hay oportunidades y necesidades de instalaciones de teletrabajo, servicios en línea, drones de entrega, etc. Se discute cómo las tecnologías no tripuladas pueden causar una disminución del empleo a largo plazo y por qué es posible que los mecanismos de compensación no funcionen. Utilizando la metodología comparable internacionalmente de Frey‐Osborne, se estimó que menos de un tercio de los empleados en Rusia trabajan en profesiones con una alta probabilidad de automatización. Algunas de estas profesiones pueden ser las que más sufran durante las medidas de confinamiento y el empleo en los servicios tradicionales puede reducirse considerablemente. Para 2030, cerca de la mitad de los puestos de trabajo en el mundo y algo menos en Rusia tendrán que adaptarse durante la cuarta revolución industrial porque realizan actividades rutinarias y potencialmente automatizables. En las regiones especializadas en manufacturas, este valor es más alto; el riesgo más bajo se da en las mayores aglomeraciones con una alta participación en la economía digital, y mercados de trabajo mayores y más diversos. La aceleración del cambio tecnológico puede conducir a un desajuste a largo plazo entre el aumento exponencial de la tasa de automatización y los efectos compensatorios del reciclaje laboral, la creación de nuevos empleos y otros mecanismos de adaptación del mercado laboral. Algunas personas no estarán preparadas para un aprendizaje de por vida y a competir con robots, y por lo tanto existe la posibilidad de una exclusión tecnológica. Se propone el término “economía de la nesciencia” y el correspondiente método de evaluación. Mediante un modelo econométrico, se identificaron los factores que reducen esos riesgos: la concentración de capital humano, un clima empresarial favorable, una alta calidad de vida y el desarrollo de las TIC. Tomando como base estos factores, en las conclusiones se propusieron algunas recomendaciones para las autoridades.

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  • Stepan Zemtsov, 2020. "New technologies, potential unemployment and ‘nescience economy’ during and after the 2020 economic crisis," Regional Science Policy & Practice, Wiley Blackwell, vol. 12(4), pages 723-743, August.
  • Handle: RePEc:bla:rgscpp:v:12:y:2020:i:4:p:723-743
    DOI: 10.1111/rsp3.12286
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    5. M. E. Baskakova & V. N. Baskakov & E. A. Yanenko, 2022. "Medium-Term Forecast of Government Spending on the Unemployment Social Protection System in Russia in the Conditions of Economic Recession," Studies on Russian Economic Development, Springer, vol. 33(1), pages 45-54, February.
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