Dr. Bernhard Kronfellner’s Post

📢 New German Blogpost: C-Level Executives from the Microtechnology-industry see competitive advantages through AI - but companies lack technical and legal know-how! 📈🧠The hype around #ChatGPT continues to surge, and for good reason! Scientific studies reveal remarkable efficiency gains and fresh creative possibilities across various domains. At the end of last year, IVAM Microtechnology Network and Hochschule Hamm-Lippstadt conducted a survey titled "Generative #KünstlicheIntelligenz in der Unternehmenspraxis: Chancen und Risiken aus der Perspektive mittelständischer Unternehmen aus der #Mikrosystemtechnik." The findings confirm the significance of the topic and highlight the existing knowledge gap. Uwe Kleinkes comments on the results in his new guest article "KMU sehen Wettbewerbsvorteile durch KI – Noch fehlt fachliches und rechtliches Know-how!" https://lnkd.in/gSvvSqR7 The detailed results of the survey are also available in English at https://lnkd.in/g_VdjhfH #IVAM #Microtechnology #Network #ExecutiveClub #AI #KnowledgeGap #BusinessInsights #IVAMResearch

💡 Position paper on the danger of deskilling through AI When discussing AI and skills, the focus is often on upskilling or retraining. A topic that is not so often the focus in the discourse around AI education is deskilling. Deskilling is the phenomenon that with AI systems, certain skills are no longer used as often and atrophy. A typical example is text translation, which is now so good with AI systems that humans only need to check the translated text for typos or stylistic problems. Or in ChatGPT, idea generation is often taken over by the system and humans have much less incentive to come up with original ideas themselves. To draw attention to this problem, Professor Gabi Reinmann from the University of Hamburg has written a position paper about the possible disadvantages of using AI. If you want to get a deeper insight into deskilling, I recommend the article by Advaid Bhat and colleagues, which explains how Large Language Models influence the writing process. In my opinion, there is a fine line between AI deskilling and complementing existing skills. Skills are often represented as a tree structure, with complex skills at the top. Take writing a book as an example: this high-level skill is unlikely to be replaced any time soon and is not at risk of deskilling, but any other subskill, such as coming up with an idea for a chapter, could be at risk of de-skilling. Nevertheless, I would argue that de-skilling is often accompanied by a newly learned skill that supports the high-level skill, e.g. getting good ideas from large language models by prompting them. 🔗 https://lnkd.in/gkRvRD5C 🔗 Advaid Bhat and colleagues: https://lnkd.in/gGeiEs4e #aieducation appliedAI Institute for Europe gGmbH

Read this BigData-Insider article by EPAM Systems’ own Alexei Zhukov to find out the industries that are in the #AI disruption spotlight. https://epamsys.co/3szEQ2T #ArtificialIntelligence #GenerativeAI #GenAI