It is becoming increasingly clear that we are moving towards a digital economy. It is called ‘Industry 4.0’, where data and data analytics are becoming the central elements of the economy. We are talking about the digitisation of products and services offered, digital business models, consumer interaction and profiling. We have vertical and horizontal digitisation and integration of the value chain.
What do we use? Mobile devices, sensors, 3D and 4D printing, augmented reality, location sensing technologies, Internet of Things platforms for real-time monitoring, Cloud, Big Data analytics and advanced algorithms including Artificial Intelligence, machine learning, but also process automation.
All these processes have been accelerated by the pandemic we are going through and the direction is clear. A study by IMF economists shows that previous pandemics, regardless of the period, have had the same effect – increased automation. Obviously, with the technologies and impact of that time. In the 1920s, after the Spanish flu in the US, telephone operators were heavily impacted by the automation implemented, as it was the most popular job among American women. Ebola and SARS “accelerated the adoption of robots, especially when healthcare was heavily impacted, being associated with a major economic downturn”.
In other words, it’s a normal trend. It is essential to identify the areas where jobs will be eliminated but also the areas where new jobs will be created. New jobs also mean new skills, and these are not formed overnight.
A McKinsey analysis highlights where algorithms and automation will replace humans. The main criteria used are: predictability/lack thereof, physical work, data collection and processing, interaction and coordination of teams, but also the application of expertise – decision making, planning and creative tasks.
* McKinsey_Where machine can replace humans and where they can’t_2016
What is obvious? In construction, agriculture, real estate and administration, where we have unpredictable physical labour, we will continue to need people to take on these roles. By contrast, in finance and insurance, where data collection and processing have a strong impact, automated systems and algorithms are taking over routine jobs. What’s still needed is that banking consultant who does the business analysis – different for each individual client – that banking consultant who contributes to the financial education of his or her clients.
Areas that will require people’s expertise, determined by skills, knowledge but also by the experience gained, are not replaced by AI or machine learning. Healthcare, professional-technical services, information, management and educational services add value precisely because of the people in these positions. Where roles are primarily about managing and developing people, the percentage of automation is at 9%. If you work in health, education and management services, your roles will change, but they will not be automated.
What do we see? Automation takes over roles that require basic physical, manual and cognitive skills.
Where roles require high cognitive skills and knowledge, where we need interpersonal and emotional skills, but also technological skills (research and development, advanced programming), HUMANS are irreplaceable.
What does this mean?
EDUCATION 4.0 – OUR NEW JOB IS TO LEARN!
- Adapting our skills development system – formal training in schools and universities, but also within companies – to the new jobs and roles demanded by the labour market. We are already seeing a redesign of jobs due to the remote work variable, but we have started to include automation as well. Jobs are starting to look different. Skills development needs to keep pace.
- Implementing the concept of life long learning. Education only up to the age of 25 is an outdated concept. In such a dynamic economic environment where even WE, as customers, change our needs and desires so suddenly and drastically, we impose a maximum speed of change. We need to keep pace.
- Putting ethics at the heart of AI and machine learning. Let’s not wait for critical situations to raise the question of ethics, especially when it comes to AI and machine learning. Yuval Noah Harari said in an interview “just as you can’t become a doctor if you don’t take ethics courses, so it must be for a programmer”. Why? Because artificial intelligence and machine learning are predictions based on data analysis, which are never objective enough and are influenced by the designer and programmer of the whole process and how they see things. It is the designer or the programmer who defines and implements the rules that AI will apply. Ethics must always underpin such decisions.
What does the future of jobs look like?
The Word Economic Forum highlights the trend of change in its October 2020 Future of Jobs report. 85 million jobs will disappear worldwide by 2025, but another 97 million jobs will be created. As the graph below shows, the direction is to replace those areas where routine, algorithm and predictability meet.
What conclusion can we draw from all this?
Let’s stay connected with the dynamic movement in the market. We may not feel it now, but it’s happening. We need to learn constantly – and there are multiple and valuable sources (if only we know what to choose).
And for things to happen, we need the discipline of work and effort, keeping in mind what we want to do and where we want to go.