by Jochen Werne
published on May 8, 2024 the below article in the original German version. Find the link HERE. Pictures used here are from private sources and Pixabay. Translation made by DeepL.com.
Throughout human history, transformative technological innovations have repeatedly led to impressive leaps in development that have reshaped our societies, economies, politics and daily lives in previously unimaginable ways.
The printing press developed by Johannes Gutenberg in the 15th century is a particular example of the far-reaching power of technological innovation. It was not only a tool for the mass production of books, but also ushered in the age of universal literacy. It has changed the world of work by making typists redundant and creating new professions in publishing and literature. Artificial intelligence (AI) is said to have a similarly revolutionary potential, and not just since large language models (LLM) such as OpenAI’s ChatGPT were established for the public to see. The extensive and immediately usable possibilities – such as the simplification of text generation or summarisation, coding – are inspiring. AI is about to fundamentally change the way we work today. But how do we deal with it?
The revolution through large language models: decoding their magic
At the forefront of this AI transformation are LLMs such as GPT-4. To truly understand their complex structure, one must dive deep into the underlying technologies, unravel the multitude of practical applications they enable and critically evaluate the challenges they pose. The range of applications of LLMs has already left an indelible mark on a wide variety of sectors. For example, LLMs are already creating new clarity in the confusing world of research through optimised summaries and presentations of key findings. LLMs are also leading to a paradigm shift in our understanding of work dynamics. The research report “Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality” describes this change and shows that the use of AI in a real-world work environment can lead to a significant increase in productivity: In this case, to 12.2 per cent more completed tasks and a 25.1 per cent reduction in processing time. These are impressive figures that illustrate the transformative power of AI even at today’s stage of development.
Utilisation of LLMs: Best practice approach
As a data insights company, Experian recognised the transformative essence of information early on. With the help of machine learning (ML), we gain important insights from data that companies can use to make informed decisions. In a recent video interview, Alex Lintner, CEO of Experian Software Solutions, explains the evolving role of AI in the financial sector and highlights the unprecedented opportunities that exist, particularly with carefully constructed large-scale language models.
Alex Lintner, CEO of Experian Software Solutions
Lintner explains the scalability of such technologies and the potential of using machine learning in monitoring market trends and anticipating credit risk. Technological advances are enabling machines to independently ask questions of decision makers, automate routine model monitoring processes and even predict which variables should be included in models in the future, allowing humans to focus their resources elsewhere.
In addition, Lintner highlights the enormous potential of AI for financial services, in particular agile risk detection and the associated ad hoc response management. As always, with great opportunity comes great responsibility: strict compliance, governance and transparency measures are urgently needed to ensure the ethical and sustainable use of AI. It is important to understand that the use of LLM’s is not just about improving back-end processes, but more importantly about equipping the workforce for the future. It is therefore mandatory for all Experian employees worldwide to complete the internal GenAI training programme. We see this – as well as all the other activities of our own Experian GenAI Academy – as important measures to keep our corporate culture in line with the wave of digital transformation rolling across industries.
Harmonisation of AI, business and society
Large-scale language models are now at the forefront of the AI revolution and have the ability to understand, generate and augment text, sound, images and video on a previously unimaginable scale. This has particular implications for all companies operating in data-centric industries, whose job it is to extract actionable insights from big data. Companies that utilise these opportunities for new data usage most effectively will gain market share in the future. For us, the integration of machine learning and large-scale language models in particular is not just a technological upgrade, but a comprehensive transformative strategy to reshape the future of our industry.
Innovation has always changed societies and had a lasting impact on the course of human progress. AI today represents the latest frontier where the complex interaction between humans and technology can be explored and refined. We therefore need to understand that our future most likely lies in the balance of harmonising AI and humans – a harmonisation that goes beyond mere coexistence: it involves collaboration and synergies that can merge human intuition and computing power into a powerful force that can drive profound change in all aspects of our lives.
To achieve this harmonisation, several key principles must be followed. Ethics come first. The development and use of AI must be based on a solid ethical foundation that ensures fairness, transparency and accountability. Prejudice and discrimination must be carefully avoided and it must be ensured that AI benefits all of humanity and excludes no one.
Second is education and skills. With the increasing integration of AI into our daily lives, it is important that individuals have access to the knowledge and skills they need to use this new technology. Education is key to realising the potential of AI while mitigating the associated risks. After all, collaboration is the key to success. Governments, businesses, researchers and citizens must work together across borders and sectors to realise its full potential. Interdisciplinary collaboration can pave the way for breakthroughs that benefit society as a whole.
With a strong focus on ethics, education and collaboration, we are able to create a future where AI and humans work in harmony and reach a new level of progress. This is a technological challenge, but also a societal one.