Blog #13


Authors: Álvaro López López
Cátedra de Industria Conectada, ICAI – COMILLAS ICAI

Artificial Intelligence (AI) is called upon to qualitatively change the economy, and society in general, during the 21st century. The appropriate adoption of AI technologies will result in advanced automation processes, in this case in combination with the different types of robotics (industrial, collaborative, logical, mobile, etc.), which will allow us humans to focus on the tasks of more value and more aligned with our nature. In addition, it is expected that AI will allow, from a certain point, to master the complexity of many of the problems we face, opening the door to an economy “of abundance” derived from the development of exponential technologies. The reader can inquire about “singularity” if interested in the projections that are made today on this scene.

To this day, and despite the fact that the development dynamics of these technologies may tend to be exponential, everything indicates that we are still far from singularity. However, we are in a stage of important changes in which advanced automation will transform (or make disappear) a high percentage of the tasks performed by the human workforce. While the exact number is uncertain, there are studies such as the 2018 OECD’s one on automation, skills and training that estimate that 46% of jobs today present a risk of being automated greater than 50%, with 14 % (about 66 million jobs in the 32 countries of the study) at high risk (greater than 70%). In addition, it is important to note that the jobs most exposed to automation are those that correspond to low and medium levels of training.
Of course, the transformative and productivity-boosting effect associated with automation will create new jobs, but these will emerge in different sectors and places than the ones destroyed. We are therefore faced with two opposing effects, one destroying and the other creating employment, and it is important to design the transition to the new economy so that the second predominates. As of 2018, a study on robotization in Europe argues that the adoption of 1 robot for every 1000 workers in the European manufacturing sector would produce a contraction in the total number of employees at the aggregate level of between 0.16 and 2%, therefore It seems that, for the moment, the effect of job destruction dominates.
If we focus on the rate at which it is expected that the tasks will be automated, it must be considered that investments in robotics and AI will be strongly influenced by their economic feasibility. In this sense, the threshold to undertake investments will shift both due to cheaper technology and higher wages, thus leaving jobs developed by people with an average educational level, better paid but still automatable, exposed to greater pressure of automation if we look at countries with developed economies like the EU members. It would be convenient to reflect on the consequences of the disappearance of this type of employment, since it could lead to a strong polarization of the workforce, accentuating inequality in society. In the international scenario, it is expected that emerging or developing countries, with low wage costs, will show a somewhat slower rate of adoption of these technologies. These dynamics may have a stabilizing demographic and social effect at the global level in the transitional period of automation of the economy. However, in a scenario of rapid adoption of AI in emerging countries, there could be situations of great migratory pressure on advanced economies.
With what has been exposed so far, it seems clear that in the medium or long term, the industry and the economy will be very different from the current ones. There will probably be a greater labor supply, with jobs yet to be defined in which people will develop their creativity, their capacity for abstract thinking and problem solving and, ultimately, those skills that make them human. In order for these positions to be adequately filled, a profound restructuring of education systems around the world is necessary. It is of great importance that the aforementioned skills are worked on, and that the systems prepare future workers to undertake several far-reaching changes in their professional careers. It may also be convenient to implement a modular and flexible design of educational systems that allows students to combine different disciplines to optimize their access to the labor market, as well as to choose the moment when they start their career, to change their itinerary quickly if perceive that they need to reorient their training (for example, with agile and effective gateways from Vocational Training to the University), and, of course, continue accessing training throughout their career (lifelong learning) in a model of bidirectional knowledge transactions. Along these lines, the reflections and suggestions of Stanford University collected in its Open Loop University initiative are worth to mention.
The education and training system will also have to face the transitional period until the future “stable” scenario. In the process of adopting advanced automation technologies, it is expected that large numbers of workers will lose their jobs and do not have the capacity and flexibility to find another on their own. To prevent these situations from becoming a structural problem, it is urgent that the states define proactive and predictive transition plans, instead of the current reactive approach of the public employment systems. These plans should include the personalization of employment advice which, by the way, is one of the great possibilities offered by the new information economy.
In this VUCA (volatile, uncertain, complex and ambiguous) scenario, where fast-paced changes in industry are challenging the education system dynamics and shape, shifting a fraction of education to companies, the works and reflections performed in the frame of the EDDIE project, where the digital-skill gaps in the Energy sector are dealt with in a pan-European approach, may well assist policy makers in defining the right politics to attain the objective aforementioned. It is important to note that, far from being sector specific, the main insights obtained for the Energy sector may be extrapolated to the rest of the economy.
We end by emphasizing the importance of designing specific and ambitious plans for the optimized adoption and promotion of AI technologies. In this sense, if we analyze the AI strategies of different relevant players on the world scene, we first see that the US and China lead the scene with huge investments. The US, in its strategy for AI announced in 2018, focused on preventing excessive regulation from putting a brake on the development of AI that would make them lose world leadership. China has set itself the goal of being a world leader in AI by 2030, for which it has assigned its most cutting-edge technology companies (Baidu, Alibaba, Tencent, iFlytek and SenseTime) the leadership of 5 strategic lines for the development of AI: autonomous conduction, Smart City, Health, voice recognition and artificial vision, respectively.
In the EU, we find that state members start to define strategies to specialize in specific fields within AI. For instance, France has placed the emphasis on promoting care for the environment with AI, Germany on applying it to industry, while the United Kingdom (in its late stages within the EU) has opted for the development of an ethical framework that guarantees a safe and harmonious adoption of AI. Estonia has designed a plan with which it intends to be a leader in digital governance of the public sector. However, we find that the EU as a whole lacks a harmonized plan for AI adoption that allows leveraging the advantages of the critical mass that would result from the aggregation of the economies of all its members. In our opinion, the EU should not lose the opportunity of emerging as a reference in the moment of development of the technologies that will drive the evolution of Humanity during this 21st century. In this line, putting AI at the service of the flagship values of the Union in order to promote a more fair, safer and more sustainable world could be a good way of making the future AI have the genuine European stamp.


This article is a extended version of another article of the author: https://www.monedaunica.net/2020/03/automatizacion-avanzada-empleo-y-educacion/

OECD, 2018. Automation, skills use and training.

Bruegel, 2018. The impact of industrial robots on EU employment and wages: A local labour market approach. FRANCESCO CHIACCHIO, GEORGIOS PETROPOULOS, DAVID PICHLER

European Political Strategy Center, 2019. The Future of Work? Work of the Future!