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Peter GentschPeter Gentsch
Peter GentschPeter Gentsch
  • Home
  • Speaker & Coach
    • about Peter
    • Awards & Honors
    • Achievements
    • Mergers &Acquisitions
    • Key Topics
  • Impressions
  • Publications
    • Books
    • Professional Articles / Press
    • Whitepapers
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  • Generative AI
    • The New Kid on the Block – Short Introduction into Foundation Models
    • The Shooting Star: ChatGPT
    • ChatGPT & Co. as Stochastic Parrots: Is Everything Just Stolen?
    • Foundation-Models: Without the “Human in the Loop”?
    • Use und Business Cases for Foundation Models
    • There is no free (AI) lunch
    • Right Here – Right Now: How to Get Started
    • Conversational AI as a Game Changer for Search Engines?
    • ChatGPT & Co.: Job Killer or Job Booster?
    • Foundation-Models – the Market
    • Outlook: The Future of Foundation Models
  • Knowledge
    • Artificial Intelligence – How to get it done! 
    • Artificial intelligence as a business booster 
    • Artificial Intelligence: Framework and Use Cases
    • Process model with roadmap / maturity model
    • AI for marketing and communication
    • AI – the new creative!
    • Conversational Business / Conversational AI
    • Messenger intelligence
    • (Chat)Bots: types, functioning and best practice  
    • AI and Data-Driven Sales in SMEs
  • Events
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ChatGPT & Co.: Job Killer or Job Booster?

ChatGPT will take over many of today’s routine tasks: Answering customer concerns in customer service, creating documents such as legal department confidentiality statements, search engine optimisation (SEO) in digital marketing or creating product descriptions in e-commerce – to name just a few examples.

This means that roles and tasks are increasingly shifting towards higher-value, creative and strategic activities. The exciting question is how companies and our society will approach and implement the “up-skilling” necessary for this. In addition, completely new job profiles are emerging, such as the already well-paid profession of prompt engineer, who tries to get the most out of AI by asking the right questions. Experts are sought here who feed the language models to generate the desired output as intelligently as possible. The various dimensions of the changes will be illustrated using the example of the programming environment:

  1. ChatGPT can also help generate software code and thus automate the programming process. Regarding the ability to generate code automatically with GPT-3 – the former CEO of GitHub once said that the solution produces 70% junk – i.e. generates non-functioning code. How can we turn this problem into a product? They have developed the product “Copilot” and designed it to be a technology that helps the developer to program faster and better, but does not replace him. This shifts the job description from coder to debugger. In this way, ChatGPT can help increase the efficiency and productivity of developers and reduce the time needed to develop new products.
  2. ChatGPT can serve as a troubleshooting and problem-solving tool for programmers. If the developer encounters a particular problem, he can consult ChatGPT to get possible solutions. ChatGPT can also help explain complex programming concepts.
  3. ChatGPT can also help train and support developers, especially when it comes to learning new programming languages and tools. ChatGPT can provide relevant learning materials and resources to help developers deepen their understanding of programming concepts and practices.

Overall, it can be said that no employee will be replaced by an AI. But possibly by employees who work successfully with AI tools like ChatGPT.

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