Does technology need us to go back to school?
Gerald Muna
Strategic IT Professional Optimizing IT Infrastructure, Enhancing Cybersecurity, & Streamlining Cloud Environments to Drive Performance & Security Excellence.
Artificial intelligence (AI) will have a fundamental impact on the global labour market in the next few years. Therefore, the authors discuss legal, economic and business issues, such as changes in the future labour market and in company structures, impact on working time, remuneration and on the working environment, new forms of employment and the impact on lab our relations.
When we transfer the experience of the past to the future, disturbing questions arise: what will the future world of work look like and how long will it take to get there? Will the future world of work be a world where humans spend less time earning their livelihood? Alternatively, are mass unemployment, mass poverty and social distortions also a possible scenario for the new world, a world where robots, intelligent systems and algorithms play an increasingly central role?1 What is the future role of a legal framework that is mainly based on a 20th century industry setting? What is already clear and certain is that new technical developments will have a fundamental impact on the global labour market within the next few years, not just on industrial jobs but on the core of human tasks in the service sector that are considered ‘untouchable’. Economic structures, working relationships
- ^As private get stronger more than government entity? What industry as the government will create more job to the people? Since the 19th century, production robots have been replacing employees because of the advancement in technology. They work more precisely than humans and cost less. Creative solutions like 3D printers and the self- learning ability of these production robots will replace human workers
multi roles will be affected soon
major advances in prediction
may facilitate the automation
of entire tasks. This will re-
quire machines that can both
generate reliable predictions
and rely on those predictions
to determine what to do next.
For example, for many
business-related language
translation tasks, the role of
human judgment will become
limited as prediction-driven
translation improves (though
judgment might still be im-
portant when translations are
part of complex negotiations).
However, in other contexts,
cheaper and more readily
available predictions could
lead to increased value for
human-led judgment tasks.