Artificial intelligence competitiveness and employment
- Autores: José Miguel Zaldo Santamaría
- Directores de la Tesis: Carlos Gregorio Hernández Díaz Ambrona (dir. tes.)
- Lectura: En la Universidad de Deusto ( España ) en 2020
- Idioma: inglés
- Tribunal Calificador de la Tesis: Pedro Díaz Simal (presid.), Leire Alcañiz (secret.), Carlos Mataix Aldeanueva (voc.)
- Programa de doctorado: Programa de Doctorado en Competitividad Empresarial y Territorial, Innovación y Sostenibilidad por la Universidad de Deusto y la Universidad Pontificia Comillas
- Materias:
- Enlaces
- Tesis en acceso abierto en: TESEO
- Resumen
Summary This Thesis titled “Artificial Intelligence, Competitiveness and Employment” was born because of our concern about future employment in Spain and in Europe and specifically our concern about the effects that the last new technologies will have on employment -in quantity and quality-.
There are so many specialists -around 50%- which believe that this time it will be different than in the past and therefore we will not be able -at least in economically advanced societies as EE.UU and Europe- to create as many jobs as the ones displaced by the new technologies, that we decided to carry out this research in order to fully understand the phenomenon so as to contribute to give solutions to the potential unemployment problem that the application of new technologies could create. A few months after starting this research we decided to concentrate on AI -Artificial Intelligence- systems and the technologies around AI, as the most disrupted ones changing jobs and displacing tasks on next ten or twenty years at least. Our next step was to understand the most pessimists positions about the displacement of jobs -the displaced are really tasks and therefore less jobs are needed for the same work- by AI applications, coming to the conclusion that the most pessimistic specialists are probably right about the quantity of tasks that will likely be displaced by AI systems and other technologies around it. It was also essential to study and understand the tasks less likely to be displaced by AI and we did it.
The next step of this research was about the possibilities of job’s creation with AI applications, and finally we researched the solutions proposed in the Academy to solve the potential unemployment problem. From the literature review we got many ideas about jobs creation when new technologies are applied but not a systematic proposition to improve the employment -in quantity and quality- and to avoid the time gap -affecting to employment and wages between displacement and creation of jobs, accepting that AI applications will displace many tasks and therefore many jobs.
As the displacement is happening not depending on our will, because the AI application is globally unstoppable and whoever tries to stop it will become non-competitive and will destroy more jobs than those destroyed by the displacement, we propose that the best solution is to apply AI systems as soon as possible doing whatever might be necessary to foster the jobs’ creation to avoid unemployment and to do it very fast to avoid the time gap -affecting employment and wages- between displacement and creation of jobs. Using System Dynamics (SD) we build the Causal Loop Diagrams (CLDs) to understand the relation among all the variables that intervene on the phenomenon between AI applications and employment and we introduced the variable Competitiveness because we want to propose the creation of competitive new jobs which are the only ones that guarantee a sustainable future with enough and good employment. We also use Stock and Flows Diagrams (SFDs) to quantify the relations among AI, Competitiveness and Employment.
And finally, we propose new models based on SFDs to help the decision makers -private and public- to get better employment on any reality where they apply AI systems, or any technology based on AI; also avoiding the wage and unemployment time gap. If we get better employment on any reality where we apply AI it is obvious that we will contribute to the improvement of global employment in our society.
The models are easy to adapt to any reality that the applier controls, as long as he accepts to create only competitive jobs. We hope that for any decision maker it is clear that to create non-competitive jobs is an easier solution for unemployment but it is not sustainable and sooner or later this will destroy jobs, weakening the society and affecting -as usual- to the most needy people.
José Miguel Zaldo, May 2020
