Web-Talks on the transformation of the economy
In the coming years, Artificial Intelligence (AI) will fundamentally change both entrepreneurial business models and many jobs - in large corporations as well as in medium-sized companies. This is because the intelligent linking of corporate data will enable new products and services to be developed and processes to be optimised. Learning assistance systems can support employees individually in their work. Where we stand on the way to an AI-supported economy and what challenges this poses for entrepreneurs and employees was discussed by experts from Plattform Lernende Systeme in two web-talks with virtual guests on 6 July.
The data-driven economy is changing business models, but small and medium-sized enterprises (SMEs) in particular still rarely have the necessary data and technologies to implement innovative solutions. In addition, there is often a lack of awareness that data sharing and collaboration across company boundaries will be essential for business success in the future. In a recent publication(in German), Plattform Lernende Systeme highlights the hurdles and potential of data-based value-added networks by means of concrete practical examples.
The platform presented results and selected examples from these in a web talk on the topic of "Learning from pioneers of the platform economy: How to turn data into successful business models". Karl-Heinz Streibich, chairman of Plattform Lernende Systeme and acatech President, and Frank Riemensperger, CEO of Accenture Germany and steering committee member of Plattform Lernende Systeme, discussed under the moderation of platform member Svenja Falk (Accenture Germany) where German companies are competing in digital ecosystems and how data-based value-added networks can be created. Josef Brunner, managing director of relayr, and Olga Mordinova, founder of incontext.technology and platform member, illustrated how concrete added value can be created from shared data and which stumbling blocks companies should be aware of, using the AI-based business models they have implemented.
Emphasizing strengths of employees and assistance systems
Is AI developing into a competition for employees - or rather a helpful support? This question was the focus of the web-talk "How will man and machine work together in the future", which Plattform Lernende Systeme also organized on July 6th in cooperation with the Stiftung Bayerisches Amerikahaus and the Zentrum Digitalisierung Bayern (ZD.B). Nadine Bender, senior analyst social impacts of robotics at KUKA Group Research, and Norbert Huchler, member of the executive board at ISF Munich, provided impulses on the psychosocial consequences of human-robot collaboration and on criteria for successful cooperation from the employees' perspective.
The two platform members then discussed questions from the virtual audience under the moderation of Philip Ramin, founder and managing director of the Innovation Center for Industry 4.0. It became clear: At present, robots usually work alongside humans instead of with them, and are often not used in a way that is appropriate to their tasks - especially in SMEs. Used strategically, intelligent systems will be able to relieve workers in the future according to their individual abilities and stress levels, according to Nadine Bender. Instead of playing off people and technology against each other, the respective strengths should be brought to the fore - such as the machine recognition of correlations and human intuition, says Norbert Huchler. A current whitepaper(in German) of Plattform Lernende Systeme, which he co-authored, sets out criteria for designing the interface between man and machine in the interests of employees.
The recording of the two web-talks on 6 July 2020 can be accessed via YouTube:
Further information:
Linda Treugut / Birgit Obermeier
Press and Public Relations
Lernende Systeme – Germany's Platform for Artificial Intelligence
Managing Office | c/o acatech
Karolinenplatz 4 | 80333 Munich
T.: +49 89/52 03 09-54 /-51
M.: +49 172/144 58-47 /-39
presse@plattform-lernende-systeme.de