The tech industry is experiencing a significant transformation due to the presence of artificial intelligence (AI) tools like ChatGPT chatbot. As a result of this development, Google's monopoly in internet searches is being challenged for the first time by the new AI software. However, the impact of this technological disruption is not limited to Silicon Valley alone.
AI will also radically change the everyday work of many people outside of California's tech hubs. This is the result of two studies that deal with the consequences of the AI revolution on the world of work.
The first study comes from the creators of ChatGPT themselves: Researchers from the start-up company OpenAI teamed up with scientists from the University of Pennsylvania to find out which jobs are most affected by ChatGPT.
According to the study, accountants are among the professional groups most affected by the possibilities of generative artificial intelligence. At least half of accounting tasks could be done much faster with this technology.
According to the study, mathematicians, programmers, translators, writers, and journalists should also be prepared because AI could take over at least some of their previous tasks.
Because although AI systems are currently still "hallucinating" incorrect facts in their answers, they are already delivering remarkable results in tasks such as translation, classification, creative writing, and generating code.
The researchers from OpenAI and the University of Pennsylvania assume that AI language models will change most workplaces in some way.
Around 80% of workers in the U.S. are in jobs where at least one task can be completed more quickly by generative AI. But there are also professions in which AI will only play a minor role: These include cooks, car mechanics, and jobs in oil and gas production, but also in forestry and agriculture.
In a study, a research department at the investment bank Goldman Sachs calculated what this development could mean for the labor market in concrete terms. If generative AI delivers on its promised capabilities, this could lead to "significant disruptions in the job market." "Generative AI" is understood to mean computer programs that can create new ideas, content, or solutions instead of just working through predefined rules or instructions.
Goldman Sachs estimates that about two-thirds of current jobs will be exposed to some level of AI automation. Generative AI could replace up to a quarter of current work. "If you project our estimates around the world, generative AI could expose the equivalent of 300 million full-time jobs to automation."
Hinrich Schütze, Director of the Centre for Information and Language Processing at the Ludwig Maximilian University of Munich, sees the development of generative AI as a revolution that is technologically comparable to the internet or smartphones. However, AI systems are still a long way from a real understanding of the content of topics: "The basic technology for language patterns is simply to always predict the next word, very mindlessly, always predicting the next word."
Nevertheless, the consequences are already vast: "There will be major changes in how we write, how we program." This also has major consequences for day-to-day work. "A lot of jobs that involve collecting and condensing knowledge and writing summaries will disappear."
However, Schütze warns against giving artificial intelligence too much scope when it comes to making decisions, for example in the judiciary, medicine, tax advice, or asset management. AI makes many statements that seem convincing, even if the facts are often incorrect. "People think it must be true if the model is so sure. But in reality, the language model is not able to assess its own certainty. That's one of the biggest problems we have."
Computer science professor Christoph Meinel sees another obstacle to the widespread breakthrough of AI in the world of work because the systems require enormous computing capacities and thus also involve huge amounts of power.
"Many of the expectations placed on AI seem excessive to me and also unrealistic in terms of their energy consumption," says the director of the Hasso Plattner Institute in Germany. Successful AI applications are based on so-called deep learning, i.e. training with huge amounts of data.
"And they consume a lot of energy." Introducing AI on a mass scale would therefore be a catastrophe for the climate and in achieving climate targets. "We first need to develop significantly more energy-efficient AI systems."
Meinel sees a challenge not only in AI's high carbon footprint but also in data protection. "If you're trying out the latest AI applications online, you should be careful about disclosing sensitive data," advises Meinel.
Everyone should know their inquiries and data to help train the AI models and make them smarter – for free. For example, anyone who uploads confidential financial data to certain platforms to create a presentation must know that this may also result in business secrets being disclosed.
