In preparation for the panel discussion at the VIP night event in September, we got interviewed by media partner Der Brutkasten.
There is this famous quote from Bill Gates, in which he says: "We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next.". With 5 years we are pretty much in the middle. I think until then normalization will have started and AI will be considered a natural part of the job. In the white-collar area, full integration of AI into office programs will enable new ways for data analytics, which nowadays still require coding skills. Furthermore, recommender systems will meet us at every turn such as giving us suggestions for data visualisation or even identify the topic for your next article.
On the blue-collar side AI will continue its triumphant advance, which started with predictive maintenance a few years ago. Above all, we will see trickle-down effects from early adopting industries - such as the automotive or aircraft industry - to other industries. In general, it can be stated that repetitive tasks such as the evaluation of X-ray images, etc., can be solved by AI and thus lead to an adaptation of the job description. A radiologist, for example, will no longer be concerned with the interpretation of tumors on X-ray images, but with the diagnosis, therapy and examination of the patient.
As with the introduction of each new technology, the demands on the work of each individual are slowly but surely increasing.
Let's take research as an example: 20 years ago, when we still had to go to the library to conduct research, it was often an excuse that you only could carry out a limited search in selected sources due to time and/or resource constraints. With Google, there was a rapid increase in opportunities, which is reflected in an increasing number of research results. The same can also be observed for classic management tasks, where each new version of Microsoft Office or Salesforce, thanks to automation, leads to ever-longer analysis and presentations.
Unfortunately, we humans are very bad at using new technologies correctly. This starts with children playing until they fall asleep, to adults who experience self-stress with notifications on their smartphone.
We will get used to trust AI based evaluations and consider them as given. It's just a matter of time until the technology lives up to this expectation. Society probably will not perceive the impact as dramatically as we think. Perhaps the general public is not interested in who recommends the hotel room, but only how well it fits their expectations.
Each technology shift changes to dynamic of he labor market. The question is whether society, politics and economics accept this as god-given, or actively take steps to mitigate the consequences. However, the impact will be very different depending on the region. For example retail in Austria: According to statistics approximately 360.000 persons work in retail, many of them women. Considering where we stand with Amazon Go today already, it's not far fetched to predict a large wave of automation until 2030 in this area.
The counter-example are classic male professions such as truck drivers in emerging markets. Due to the lack of qualified truck drivers, European truck manufacturers are keen to produce autonomously moving trucks as soon as possible. This has a positive impact on Western Europe. However, it has a fatal impact on emerging markets, where there is still a very high number of long-distance drivers.
I expect laws like in Germany, where employees are no longer expected to be reachable after work, in a big way also in Europe. Otherwise we might end up in a 24/7 working world. Unfortunately, we humans are very bad at using new technologies correctly. This starts with children playing until they fall asleep, to adults who experience self-stress with notifications on their smartphone.
Full article at Der Brutkasten (in German): Link
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