Innovation & Business Jochen Werne Society & Diplomacy

Mind over Machine

Mastering the Power of AI and Large Language Models for Business Success and Positive Social Impact

By Jochen Werne

Düsseldorf, 6 April 2023.

Throughout human history, transformative technological innovations have heralded new eras, reshaping our societies, economies, politics, and daily lives in ways previously unimaginable. The printing press, introduced by Johannes Gutenberg in the 15th century, serves as a profound testament to the sweeping power of innovation. Not just a tool for mass-producing books, the printing press birthed the dawn of widespread literacy, transforming workplaces as manual scribes became obsolete and creating new vocations in publishing and literature.

The press also catalyzed a socio-political upheaval. As literacy rates surged, so did the empowerment of the masses. Ideas, once confined to the elite, became accessible to many, seeding the Renaissance, and later, the Reformation. Niall Ferguson, in his seminal work, “The Square and the Tower,” eloquently captures this revolution, asserting that the printing press restructured historical hierarchies and networks, shifting power dynamics in unprecedented ways.[1]

In economic terms, the press laid the foundation for capitalist markets. As information became accessible, trade routes expanded, local businesses thrived, and a burgeoning middle class began to wield economic influence. On the societal front, with the proliferation of ideas came the Enlightenment, propelling societies towards principles of liberty, fraternity, and equality.

Fast forward to the close of the 20th century, and another innovation emerged as a harbinger of transformation: the internet. Much like the printing press, the internet redefined workplaces, rendering some jobs obsolete while spawning new professions in digital technology, e-commerce, and online content creation. The globalized economy we witness today, underpinned by intricate supply chains and instantaneous communication, owes its existence to the digital revolution.

Politically, the internet has both empowered and challenged established structures. Grassroots movements, from the Arab Spring to global climate change campaigns, have harnessed online platforms to mobilize support and challenge the status quo. However, it’s also provided a breeding ground for misinformation, deepening societal divides in certain instances.

Yet, as we stand on the cusp of the AI revolution, it’s crucial to reflect on lessons from our past. Both the printing press and the internet came with their boon and bane. Their essence wasn’t inherently good or bad; it was humanity’s application of these tools that rendered them so. As we navigate the realms of AI and Large Language Models (LLM), this adage holds truer than ever: Technology and technological inventions are neither good nor bad – it’s the way we use them that bestows upon them such attributes.

Chronicles of Code – Decoding the Magic Behind Large Language Models

The realm of artificial intelligence is undergoing rapid metamorphosis, and Large Language Models, such as GPT-3 and GPT-4, stand out as the front-runners in this transformation.[2] To truly appreciate the intricate tapestry of LLMs, one must delve deep into their foundational technologies, unravel the plethora of practical applications they enable, and critically evaluate the challenges they pose.

At the nucleus of LLMs is their technological backbone. These models owe their prowess to deep learning and, more specifically, the transformer architecture.[3] This intricate design enables them to sift through colossal amounts of data, synthesizing human-like text that often mirrors our nuanced thought processes. The primary education of these models stems from vast datasets spanning the breadth of the internet, but their true finesse is achieved when they’re fine-tuned using more focused datasets, enabling them to excel in specialized domains.[4]

When it comes to their application spectrum, LLMs have left indelible marks across sectors. In the labyrinthine world of research, where professionals are inundated with vast pools of data and intricate academic papers, LLMs emerge as lighthouses, offering clarity by summarizing and presenting key insights.[5] Language translation, a domain that’s been historically challenging due to the nuances and subtleties of human language, has seen remarkable enhancements with LLMs. They’ve added a layer of contextual depth that was previously lacking in traditional translation tools.[6] The educational sphere is undergoing a renaissance, thanks to LLMs. Their capabilities in offering personalized content, adapting to individual learning curves, and providing immediate feedback promise a future where learning is both tailored and transformative.[7]

Yet, every silver lining has a cloud. The inherent challenges of LLMs are subjects of extensive discourse. Their reliance on training data can be their Achilles’ heel — biases in training data can lead to prejudiced outputs, a significant concern given the widespread influence of AI.[8] Additionally, their textual outputs, while sophisticated, can sometimes lack true human understanding, leading to contextually skewed results.[9] The broader societal implications of LLM adoption, especially the potential displacement of jobs and questions of ethical accountability, are pressing concerns that demand attention.[10]

The tapestry of LLMs in real-world scenarios paints a vivid picture of their transformative potential. Customer service has seen an overhaul, with AI tools streamlining interactions and enhancing user experiences.[11] The corridors of journalism echo with the influence of LLMs, aiding in content creation, editing, and even pioneering new forms of storytelling.[12] The legal world, often bogged down by voluminous documents, benefits immensely from AI’s precision in document reviews, bringing efficiency and reducing human errors.[13]

As we segue into “Redefining Workflows: The Profound Influence of LLMs on the Modern Workforce,” we’ll delve deeper into the myriad ways LLMs are reshaping our professional landscapes.

A New Work Paradigm: LLMs’ Crucial Contribution to Contemporary Business Achievements

The release of Large Language Models has initiated a paradigm shift in our understanding of the workforce dynamics. The ground-breaking research presented in the paper titled “Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality,” authored by the illustrious team of researchers including Fabrizio Dell’Acqua, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon, and Karim R. Lakhani, brings forth significant insights into this transformation.

Praise is due to this team of researchers for conducting a well-structured, extensive experiment involving 758 consultants from the global management consulting firm, Boston Consulting Group (BCG). Their analysis offers invaluable insights into the applications and limitations of AI in knowledge-intensive tasks. The concept of a “jagged technological frontier” introduced in their paper signifies the nuanced capabilities of AI. It underscores the notion that while AI excels in certain tasks, others that might seem similar in complexity can be beyond its scope.

Their findings show that when consultants utilized AI in the realm of its capabilities, there was a noticeable uptick in productivity, with tasks being completed 12.2% more and 25.1% faster. The quality of results also soared, witnessing an impressive increase of over 40%. These figures paint a vivid picture of the transformative power of AI when applied within its domain of expertise. Yet, it’s essential to note that outside this domain, relying on AI may lead to counterproductive results.

The paper also identifies two distinct ways in which consultants engaged with AI. Some consultants acted as “Centaurs,” seamlessly dividing and delegating tasks between themselves and the AI, while others emerged as “Cyborgs,” integrating their workflows with the AI in an ongoing symbiotic interaction. Such observations are pivotal as organizations strive to harness the optimal potential of AI, while also understanding its limitations.

LLMs like ChatGPT, as highlighted in the research, have redefined the frontiers of automation, demonstrating capabilities in areas previously reserved for the most educated, creative, and highly paid workers. The research suggests that these models are more than mere tools; they are evolving entities with vast yet unpredictable capabilities. Their potential to transform workflows and elevate the quality of work output in the consulting realm, and possibly across other industries, is profound.

Yet, for all their potential, the research astutely underscores the risks associated with the blind adoption of LLMs. Misplacing trust in these systems for tasks outside their capabilities can lead to inaccurate results and compromise the integrity of the work. The inherent opacity of these models further complicates this dynamic. Without a clear understanding of their strengths and weaknesses, professionals may be navigating a minefield without a map.

The “jagged technological frontier” metaphor therefore poignantly encapsulates the ever-evolving landscape of AI capabilities. This invaluable research serves as a compass, guiding professionals and organizations on how to integrate LLMs efficiently into their workflows, optimize productivity, and elevate the quality of outputs. The ripple effects of LLMs on the workforce are profound, and as we traverse this technological frontier, it is paramount to tread with both enthusiasm and caution. The dedication and rigor of the research team in shedding light on this complex subject deserve commendation. Their work has undoubtedly laid a solid foundation for further exploration in the transformative world of AI and its implications on the workforce.[14]

The importance of discerning the “jagged technological frontier” concept is crucial. While some tasks may appear similarly intricate on the surface, not all can be executed efficiently by AI. Drawing from own research and the extensive studies by the German AI platform “Plattform Lernende Systeme“, it’s pivotal to distinguish which tasks are best tackled with human-AI collaboration.[15]

Harnessing the Power of LLMs: Best Practice approach from a global data insights market leader

Experian[16], as a global data leader, recognizes the transformative essence of information. Through AI and Machine Learning, Experian gleans significant insights from data, empowering businesses to make enlightened decisions. Additionally, the principle of ‘data for good’ resonates profoundly with the philosophy. By responsibly channeling data, the company not only catalyze economic progress but also mitigate societal challenges.

Experian has not only acknowledged the transformative potential of Machine Learning and Large Language Models but also fervently acted upon it.

Alex Lintner,[17] CEO of Experian Software Solutions, recently provided insights into the evolving role of artificial intelligence (AI) in the financial sector during a video conversation.[18] Lintner emphasized how AI, especially carefully constructed large language models, offer an unprecedented opportunity for the industry. He elucidated the scalability of such technologies, noting the potential to leverage machine learning for monitoring market trends and preempting credit risks as market circumstances change. This technological evolution allows machines to autonomously create prompts for decision makers, automate routine model monitoring processes, and even forecast variables that should be included in models in the future, thus enabling humans to channel their resources towards creating innovative solutions and supporting strategic initiatives.

Moreover, Lintner shed light on the vast potential of AI in financial services. He highlighted the importance of agile risk detection and swift response mechanisms, indicating that this is just scratching the surface. Experian alone has pinpointed over 200 potential use cases. However, the immense capabilities of AI also beckon significant accountability. Lintner underscores the paramount need for rigorous compliance, governance, and transparency measures to guarantee AI’s ethical and judicious application.

On the ethical front, Lintner asserted, “Protecting data and ensuring responsible use of generative AI is not just a priority; it’s an imperative.” Given Experian’s pivotal role in handling sensitive financial information, establishing and maintaining trust is of utmost importance. Therefore, integrating stringent ethical standards, principles, and methodologies is crucial to the successful and responsible rollout of AI technologies.

As for steering the future, Lintner offers a clear roadmap: focus on acquiring talent in the AI domain, consistently gather customer feedback, and astutely prioritize opportunities. He believes that truly innovative solutions emerge from a profound understanding of customer necessities—a philosophy that resonates deeply in his perspectives.

In data companies globally every decision, every product, every innovation stems from the intricate understanding of the numbers. As the vast amounts of data they manage continue to grow, there’s an increasing need for more sophisticated ways to handle, analyze, and extract insights from it. Enter Machine Learning (ML) and, more specifically, Large Language Models (LLMs).

Ahead of the Curve: Cultivating a Workforce Fit for the Future

It’s important to understand that the use of LLMs isn’t just about improving backend processes; it’s especially about equipping the workforce for the future. When I took the helm on August 1st, 2023 as the new CEO of Experian DACH, one of the first directives on day one – inspired by the example of other Country Managers within the group – was to motivate all employees in Germany, Austria and Switzerland to undergo the corporate GenAI training. This wasn’t just a nod towards technological advancement; it was a strategic move to ensure that the very culture of the company was aligned with the digital transformation wave sweeping across industries.

By doing so, Experian isn’t merely training its employees on a new tool; it was nurturing a mindset of innovation and adaptability. With hands-on experience from the GenAI training, employees were encouraged to conceptualize practical roll-out use cases. For example, marketing professionals can incorporate insights from LLMs into their engagements, delivering more personalized and impactful messages to clients. In the meantime, the sales teams were able to use LLM-generated insights to identify potential markets or niches that had not yet been tapped – today, the vast majority of Experian employees worldwide are not only trained, but use GenAI in their daily work and develop new use cases on the fly.

Training and Learning is not just about immediate benefits. It is a forward-thinking strategy to ensure that new technologies, as LLMs continue to evolve and their applications grow, the company’s workforce would not be left behind. It is about fostering a culture of continuous learning, adaptability, and leveraging cutting-edge technology to stay ahead in highly competitive industries.

Redefining an Industry’s Future

Large Language Models (LLMs) like GPT-4 are at the forefront of the AI revolution, harnessing the capability to understand, generate, and augment human-like text at a scale previously unimaginable. This progression in AI has significant implications for businesses, especially for data-centric industries that are looking to derive actionable insights from vast data volumes.

One of the key challenges for data-centric companies is extracting meaningful insights from massive data sets. Traditional methods are often cumbersome, and while they can yield valuable results, the increasing volume, velocity, and variety of data have made these methods less efficient. Machine Learning offers a solution to this challenge. By leveraging algorithms that can learn from and make decisions based on data, ML has revolutionized the way companies interpret complex data structures.

Therefore, as data continues to be the backbone of our digital age, companies that can harness its power most effectively will lead the charge. For data insights giants like Experian, integrating Machine Learning, and especially Large Language Models, isn’t just a technological upgrade; it’s a transformative strategy to redefine their industry’s future.

Conclusion: The Harmonization of AI and Humanity

Throughout history, innovations have undeniably transformed societies, leaving a lasting impact on the course of human progress.[19] Whether we consider the revolutionary impact of the printing press or the transformative power of the internet, each technological leap has reshaped our world and the way we live. In the face of these profound changes, humanity has consistently demonstrated its ability to adapt, evolve, and harness these tools for our collective betterment.[20] In this context, artificial intelligence and with-it large language models emerges as the latest frontier where the intricate interplay between humans and technology is being examined and refined.

Rather than surrendering to the allure of extreme narratives, such as an AI-dominated dystopia or a utopian world of boundless prosperity, it is imperative to acknowledge that the future most likely rests within the delicate equilibrium of harmonizing AI and humanity.[21] This harmonization goes beyond mere coexistence; it encompasses collaboration and synergy, merging human intuition and the computational prowess of AI to create a potent force capable of driving profound transformations in all aspects of our lives.

As we venture further into this uncharted territory, the wisdom of great thinkers continues to guide us. Albert Einstein once remarked, “Imagination is more important than knowledge. For knowledge is limited, whereas imagination embraces the entire world, stimulating progress, giving birth to evolution”.[22] In the context of AI and humanity, this sentiment resonates profoundly. Our imagination and creativity serve as the catalysts for progress, and AI serves as the tool that can amplify and expedite our ability to transform imaginative ideas into reality.

The future may indeed be obscured by uncertainty, but it is unquestionably a future that we, as a collective humanity, possess the power to shape.[23] It is a canvas waiting for us to paint our hopes and aspirations upon, guided by principles of meticulous consideration and ethical responsibility.[24] The horizon of AI’s potential is expansive, and the possibilities it presents are as vast as the human imagination itself.

To achieve this harmonization, several key principles must be prioritized. First and foremost is ethics.[25] The development and deployment of AI must be grounded in a robust ethical framework that ensures fairness, transparency, and accountability. We must diligently guard against biases and discrimination, guaranteeing that AI benefits the entirety of humanity, leaving no one marginalized.[26]

Second, education and empowerment are paramount.[27] As AI becomes increasingly integrated into our daily lives, it is essential that individuals have access to the knowledge and skills necessary to navigate this new landscape. Education empowers us to harness AI’s potential while mitigating its associated risks.

Lastly, collaboration forms the linchpin of success.[28] Governments, businesses, researchers, and individuals must collaborate, transcending borders and sectors to harness the full potential of AI. Interdisciplinary collaboration can pave the way for breakthroughs that benefit society as a whole.

The harmonization of AI and humanity offers a promising path forward.[29] It is a journey that requires us to draw upon the wisdom of the past, the imagination of the present, and the ethical considerations of the future.[30] As we navigate this uncharted waters, we must remember that the power to shape our destiny resides within our collective hands.[31]

With knowledge, responsibility, and a harmonious integration of AI with human expertise, the future horizon is indeed one filled with promise and potential. It is a future where the partnership between humans and AI can lead to a brighter and more equitable world for all.

[1] Ferguson, N. (2018). The Square and the Tower: Networks and Power, from the Freemasons to Facebook. Penguin Press.

[2] Brown, T. B., et al. (2020). “Language Models are Few-Shot Learners.” OpenAI

[3] Vaswani, A., et al. (2017). “Attention is All You Need.” NeurIPS

[4] Devlin, J., et al. (2018). “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.” Google AI

[5] Chui, M., et al. (2018). “Notes from the AI frontier: Tackling Europe’s gap in digital and AI.” McKinsey Global Institute

[6] Hale, S. A. (2016). “Commercial Applications of Machine Translation.” The Oxford Handbook of Translation Studies

[7] Luckin, R. (2017). “Towards artificial intelligence-based assessment systems.” Nature Human Behaviour

[8] Bender, E. M., & Gebru, T. (2021). “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” Proceedings of FAccT.

[9] Lipton, Z. C., & Steinhardt, J. (2018). “Troubling Trends in Machine Learning Scholarship.” arXiv preprint

[10] Russell, S. (2019). “Human Compatible: Artificial Intelligence and the Problem of Control.” Viking

[11] Huang, M. H., & Rust, R. T. (2018). “Artificial Intelligence in Service.” Journal of Service Research

[12] Graefe, A. (2016). “Guide to automated journalism.” Tow Center for Digital Journalism, Columbia University

[13] Surden, H. (2014). “Machine Learning and Law.” Washington Law Review

[14] Dell’Acqua, F. et al. (2023). Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality. Harvard Business Review.

[15] acatech. Plattform Lernende Systeme (2023) https://www.plattform-lernende-systeme.de/home-en.html

[16] Experian Corporate website: https://www.experianplc.com

[17] About Alex Lintner: https://www.experianplc.com/about-us/board-and-senior-management/senior-management/alex-lintner/

[18] Lintner, A. (2023) Transforming Financial Services with AI and Automation – A video interview. YouTube https://youtu.be/_QnZf3FlNq0?si=Y4WditFgkX-aGaGt

[19] McKinsey Global Institute. (2021). “AI in the post-pandemic world: Five key trends.” https://www.mckinsey.com/capabilities/quantumblack/our-insights/global-survey-the-state-of-ai-in-2021

[20] Pew Research Center. (2019). “Americans and Privacy: Concerned, Confused and Feeling Lack of Control Over Their Personal Information.” https://www.pewresearch.org/internet/2019/11/15/americans-and-privacy-concerned-confused-and-feeling-lack-of-control-over-their-personal-information/

[21] World Economic Forum. (2020). “The Future of Jobs Report 2020.” https://www.weforum.org/reports/the-future-of-jobs-report-2020

[22] Einstein, A. (1931). “The Cosmic Religion: With Other Opinions and Aphorisms.”

[23] The Guardian. (2022). “The Uncertain Future of Artificial Intelligence.”

[24] World Economic Forum. (2018). “Ethics by Design: An Organizational Approach to Responsible Use of Technology.” https://www.weforum.org/whitepapers/ethics-by-design-an-organizational-approach-to-responsible-use-of-technology/

[25] The Royal Society and the British Academy. (2020). “Data Management and Use: Governance in the 21st Century.” https://royalsociety.org/topics-policy/projects/data-governance/

[26] AI Now Institute. (2019). “Discriminates in AI Hiring Tools and the Role of Human Oversight.” https://ainowinstitute.org/wp-content/uploads/2023/04/AI_Now_2019_Report.pdf

[27] UNESCO. (2020). “I’d Blush if I Could: Closing Gender Divides in Digital Skills Through Education.” https://unesdoc.unesco.org/ark:/48223/pf0000367416.page=1

[28] Stanford HAI. (2021). “AI Index 2021 Annual Report.” https://aiindex.stanford.edu/wp-content/uploads/2021/11/2021-AI-Index-Report_Master.pdf

[29] McKinsey & Company. (2018). “Notes from the AI Frontier: Insights from Hundreds of Use Cases.” https://www.mckinsey.com/~/media/mckinsey/featured%20insights/artificial%20intelligence/notes%20from%20the%20ai%20frontier%20applications%20and%20value%20of%20deep%20learning/notes-from-the-ai-frontier-insights-from-hundreds-of-use-cases-discussion-paper.ashx

[30] The Hastings Center. (2019). “Is Ethical AI an Oxymoron?” https://www.thehastingscenter.org/news/hastings-president-addresses-the-question-is-ethical-ai-an-oxymoron/

[31] United Nations. (2019). “The Age of Digital Interdependence.” https://digitallibrary.un.org/record/3865925?ln=en

Jochen Werne Ocean & Passion Press & Publications Society & Diplomacy

MŒA One-to-One Interviews: Our Oceans are the fluid connection between our nations

Jochen Werne February 19, 2024 diplomacy environment environmental protection Global Goals Global Offshore Sailing Team Jochen Werne Monaco monacoecoart ocean passion Prince Albert sea society

Update of the Interview held by MONACŒCOART® founder Maurizio Abbati Interview with Jochen Werne, Co-Founder & Expedition Leader at Global Offshore Sailing Team & CEO at Experian D/A/CH.

Find the original interview and much more here at MONACŒCOART®

Updated: Feb 11, 2024

Jochen Werne: Innovation and Business, Society and Diplomacy, Ocean and Passion strongly aim at a positive change for the future.

Photo >> Jochen Werne (2022) © J. Werne

International expert in finance and blockchain, head of several private and corporate Banking divisions, keynote speaker, actively committed in diplomacy and economy transformation following the current shift to Sustainable Development as wished by United Nations and major political, technical and business bodies, he is extremely fond of communicating his passion for oceans and the virtuous interlink between human beings and nature.

Jochen Werne strongly believes in the vital role of individual diplomatic efforts in maintaining peace and a balanced approach to preserving natural ecosystems. He asserts, „Innovation and business, society and diplomacy, ocean and passion are all intricately linked. In today’s interconnected world, our diverse talents can collectively drive positive change every day.“ His insights reflect a profound understanding of the interconnectedness of various elements in fostering international relations.

Werne’s adventurous spirit and deep respect for the scientific community’s contributions to nature have led him to organise numerous ocean missions. These missions have gained significant recognition from esteemed figures such as H.S.H. Prince Albert II of Monaco, the President of France, and the President of Austria, enhancing his knowledge and experience.

Furthermore, Werne co-founded the Global Offshore Sailing Team, an international group comprising members worldwide with significant naval experience. This group is dedicated to preserving naval traditions and emphasizing the importance of ocean expeditions and people’s diplomacy for supporting international understanding

MONACŒCOART® had the pleasure to collect a meaningful feedback directly from Jochen Werne (J.W.), Co-Founder & Expedition Leader at Global Offshore Sailing Team (GOST).

—————

MONACŒCOART®: Jochen Werne, how did your passion for the oceans and sailing come about?

J.W.: As a child growing up in the countryside on the border with Switzerland, the world outside my parents’ home always had a great attraction for me. Notably, the Sea with its magical sense of endless freedom, adventure and beauty has always been a trigger in my life. And this fascination still inspires me even though I have sailed the seven seas. Maybe it will never disappear. I had my first contact with sailing during school holidays on Lake Constance. Then, I joined the navy, where I had the privilege to serve for almost two years as a navigator on the three-masted sailing ship ‘Gorch Fock. That finally ignited my passion for the oceans and sailing.

Photo >> The Expedition Blue Ocean 2022 crossing the Tower Bridge in London © GOST

MONACŒCOART®: What values have you learned after so many years of shipping?

J.W.: The most important one is RESPECT. Probably every ocean sailor and mariner would confirm it. As a sailor you experience the marine element in its most breath-taking calm and beauty and its most deadly and dangerous brutality. Respect helps to enjoy one side of the coin and survive the other. Respect leads to this deeper understanding that Nature is in many ways more important and also more powerful than ourselves. The fact that makes us feel humbly is to understand that Nature can always live without us, but we cannot live without Nature. Moreover, a sailor learns how to use Nature to benefit from its power in the best and most sustainable way and to emotionally experience its pure and infinite beauty.

Photo >> Environmental Awareness & Offshore Sailing within ‘Arctic Ocean Raptor’: Sailing to the most northern reachable, partially ice-free points on Planet Earth. Public awareness about the real meltdown of pack ice in Arctic summers will be raised by sailing with a fiberglass sailing yacht to a point just 540 nautical miles or 1.000km away from the North Pole © GOST

MONACŒCOART®: Which marine expedition has shaped you more than others? Why?

J.W.: Every expedition has its uniqueness and therefore it is difficult to prefer one over the others. However, the ‘Arctic Ocean Raptor’ was very special to me. It took us from the northern Norwegian city of Tromsø across what sailors call the ‘devil’s playground’, the Barents Sea, to a spectacular natural habitat called Spitsbergen at 80° North. Despite its up-north location, the climate is quite mild due to the Gulf Stream. As our expedition approached Svalbard after three days of sailing through dense fog, we encountered a huge ice barrier that broke away from the cold eastern side of the island due to the warm conditions and drifted on with the current. This, combined with a 9-bft (= Beaufort scale) storm, made the voyage a real challenge, but also impressively demonstrated the fragility of our ecosystem.

Photo >> H.S..H. Prince Albert II of Monaco welcoming Jochen Werne and other members of GHOST at the Monaco Yacht Club © YCM

MONACŒCOART®: Which measures do you think are most important to preserve marine ecosystems? Why?

J.W.: There is no doubt that before starting a movement or action, awareness must be raised. This step is of utmost importance, otherwise one remains lonely and therefore a committed but silent to action interlocutor. The Principality of Monaco has a long tradition of identifying problems for our marine ecosystem and taking action to make many aware of them. H.S.H. Prince Albert I of Monaco immediately recognised the dangers of bottom fishing with the new means of steam technology. Jacques Cousteau not only served science but brought the beauty of the sea into everyone’s living room with his work behind the camera and inspired new projects to protect the oceans. Last but not least, H.S.H. Prince Albert II of Monaco is the perfect example of how this has not only become Monaco’s heritage but a lived tradition. We are grateful that he has supported us in our expeditions to raise awareness and thus contribute to the conservation of our marine ecosystems.

Photo >> Thorsten Glauber, Bavarian Minister of State, handing over the States Medal to Jochen Werne, Co-Founder of GOST © TMUV

MONACŒCOART®: You have already pointed out several times that scientific and fact-finding missions are particularly effective for intercultural and diplomatic exchange. What makes them instruments of dialogue?

J.W.: Our oceans are the fluid connection between our nations. And even though we are citizens of nations, we all belong to one Planet. As seafarers, we are directly dependent on nature and national thinking takes a back seat. In the daily challenge at sea, nationality, race or gender are not important. What really matters is to achieve our goals as a team, otherwise we will all fail. This also applies to us as a human race. The challenges before us are global challenges that no single nation can solve alone. We need a collective effort, and we have so many examples where the global community has done it together. One of my favourite examples is the Antarctic Treaty, which was negotiated at the height of the First Cold War and still provides the basis for joint peaceful governance of Antarctica today.

Photo >> Antarctic Blanc expedition: the international team held a commemoration ceremony on the historically significant Antarctic volcanic Deception Island, in the name of all supporting states and the United Nations. a wreath of local ice was symbolically formed and laid down in order to pay international tribute to the achievements in the exploration of this unique continent © GOST

MONACŒCOART®: What place does the Principality of Monaco have in the international expeditions that you carry out as part of the Global Offshore Sailing Team (GOST)?

J.W.: We are more than grateful to H.S.H. Prince Albert II of Monaco, the Yacht Club de Monaco, its Board of Directors with Bernard d’Alessandri, Gerd Ziegenfeuter, the staff and members as well as the press for their excellent support in our common tasks. Together we were able to achieve outstanding results. Starting with the expedition ‘Antarctic Blanc’ 2018, which resulted in a state act supported by 19 nations including the United Nations, to the Prince Albert I Memorial Expedition ‘Navigators Heritage’. Together, we have succeeded not only in supporting science, but also in bringing people and nations closer together and raising awareness of the needs of our oceans.

Photo >> Maximino Gómez Alvarez, Vice-President of AIDHNC, giving the “Ancla d’Oro” to Jochen Werne, Co-Founder of Global Offshore Sailing Team (Maritime Museum, Hamburg, 8th May 2016) © GOST

MONACŒCOART®: GOST expeditions have been awarded the highest honours by heads of state and international institutions. What is the recognition to which you are most attached? Why?

J.W.: We are more than grateful to have been honoured with a State Medal for our commitment to environmental protection or with the Ancla d’Oro (Golden Anchor) of the Asociación para la Investigación y Difusión de la Historia Naval de Cuba and the Admiral of the Fleet the Lord Boyce Award for promoting international understanding. Among all the awards, the highest recognition for me is the fascinated smile on a young person’s face when one of the stories of the sea lights the flame of passion for marine elements. It is their spirit that will form the basis for future action. Just as others in the past like Jacques Cousteau have lit a fire in us for the Sea. It is the quote attributed to the brilliant Antoine de Saint-Exupéry, author of the beautiful novel Le Petit Prince, that probably describes it best: If you want to build a ship, don’t drum up the men to gather wood, divide the work and give orders. Instead, teach them to long for the vast, endless sea. ***

? ✒By Maurice Abbati

To know more about Jochen Werne’s ocean expedition project please visit:

Global Offshore Sailing Team

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Innovation & Business Jochen Werne Press & Publications

Frontline Defense: Outsmarting Fraudsters and Shaping the Future of Fraud Prevention

Jochen Werne December 26, 2023 ai Aidrian artificial intelligence banking compliance e-commerce Experian Fraud innovation Jochen Werne machine learning MaRisk ML Online Fraud society transformation trust

The rise of AI and ML in fraud prevention can lead to a new era of digital trust and compliance

Author: Jochen Werne / 26.12.2023

In an era marked by rapidly advancing technology and increasing global interconnectivity, the fight against online fraud has become a paramount concern for financial institutions, businesses, and regulators worldwide. Part of my professional work revolves around understanding and mitigating the risks associated with financial fraud. The Experian Forrester Fraud Research Report 2023, which was recently released, sheds light on the escalating threat of online fraud and the evolving strategies to counter it, particularly through the use of Machine Learning (ML) and Artificial Intelligence (AI).

The report’s findings are stark: a 74% increase in fraud losses in Germany, reflecting nearly the global increase rate. This surge is not just a statistic; it’s a clear indication of the sophisticated and pervasive nature of modern financial fraud. Companies across various sectors are feeling the impact, with financial services bearing the brunt. This trend is deeply concerning not only for the economic health of individual businesses but also for the broader stability and security of the financial system.

From a geopolitical perspective, the rise in online fraud is a multifaceted challenge. It’s a threat that transcends borders, affecting relations among nations, and has become a significant factor in international policy and security discussions. Countries, including Germany, are increasingly recognising the need for cooperative international efforts to combat this scourge. The geopolitical implications are profound, as fraud undermines economic stability and erodes public trust.

Turning to the German banking sector, the issue of compliance and reputation risk under the framework of Minimum Requirements for Risk Management (MaRisk) is particularly pertinent. Banks are finding themselves at the forefront of the battle against online fraud, necessitating robust risk management strategies that align with regulatory requirements. Under MaRisk, the mandate is clear: implement effective, comprehensive controls to detect, prevent, and manage fraudulent activities. The reputational risk for banks and their board members is immense; a single lapse can lead to significant financial losses, legal consequences, and lasting damage to customer trust.

In this challenging landscape, AI/ML-based fraud prevention methods stand out as beacons of hope. These technologies offer the promise of enhancing detection capabilities, reducing false positives, and adapting swiftly to new fraudulent tactics. However, their implementation must be undertaken with a clear understanding of the ethical implications and potential biases inherent in AI systems. As we embrace these technologies, we must also commit to transparency, accountability, and continuous improvement to ensure they serve the interests of all stakeholders fairly and effectively.

Despite the challenges, I believe there is a path forward that balances the need for security with the imperative for innovation and growth. The key lies in embracing a multi-faceted approach to fraud prevention that leverages the best of technology, human expertise, and regulatory compliance. ML, with its ability to learn and adapt to new patterns, offers a powerful tool in this fight. However, its effectiveness hinges on the quality of data, the integrity of algorithms, and the wisdom of the humans who guide its evolution.

The German companies surveyed in the study are acutely aware of the challenges and opportunities presented by AI/ML in fraud prevention. The overwhelming majority recognise the efficacy of ML-based approaches and anticipate their increasing dominance in the field. Yet, they also acknowledge the hurdles, including the costs associated with deploying advanced fraud prevention solutions, the need for continuous adaptation, and the importance of addressing the ethical considerations of AI use.

In my experience, one of the most critical factors for success in this endeavour is collaboration. Tackling online fraud is a collective effort that requires the involvement of businesses, regulators, technology providers, and consumers. By working together, sharing knowledge, and fostering a culture of innovation and vigilance, we can stay ahead of fraudsters and protect the integrity of our financial systems.

Another vital aspect is education and awareness. Both consumers and employees must be informed about the risks of online fraud and the steps they can take to prevent it. Regular training, robust policies, and a culture of security are essential in creating a resilient defense against fraud.

Finally, we must recognize that the fight against fraud is an ongoing battle. As technology evolves, so too will the tactics of fraudsters. We must remain agile, constantly updating our strategies, investing in new technologies, and adapting to changing regulatory landscapes. This dynamic approach is not just about defense; it’s about building a stronger, more secure future for everyone.

The Experian Forrester Fraud Research Report 2023 is a call to action. It highlights the urgent need for enhanced strategies, stronger collaboration, and a steadfast commitment to ethical, innovative solutions in the fight against online fraud. As leaders in the financial services industry, we have a responsibility to take the helm, steering our organisations towards safer waters in this tumultuous sea of digital threats. By harnessing the power of AI/ML, prioritising ethical considerations, and fostering a culture of collaboration and continuous learning, we can not only mitigate the risks of online fraud but also pave the way for a more secure, prosperous, and trustworthy financial ecosystem.

#fraudprevention #dataliteracy #machinelearning

Innovation & Business Press & Publications Society & Diplomacy

Charting Uncharted Waters: Europe’s Place in a World Remade

Jochen Werne November 4, 2023 artificial intelligence ASML AUKUS banking China diplomacy ECB Experian Jochen Werne Mahan Martin Luther Niall ferguson Shakespeare society technology transformation TSMC

By Jochen Werne.

Duesseldorf, 5 November 2023

Introduction

From the eloquent words of Shakespeare in Henry V, where he once proclaimed, “all things are ready if our minds be so”^1 to the monumental shifts brought by Gutenberg’s printing press^2, history reminds us that change is both an inevitable and defining characteristic of human progress. As the world stands at the threshold of a new epoch marked by rapid technological shifts and pronounced geopolitical transformations, this profound sentiment compels us to reflect on the paramount importance of preparedness and perspective. The way societies respond to these shifts determines the direction of their trajectory. In our current age, Europe finds itself at the nexus of global transformations driven by technological advancements and geopolitical tectonics.

Technology: A Historical Reflection

Peering through the lens of history, one quickly realizes that technology has been both a beacon of hope and an augury of upheaval. Take the 15th century’s monumental invention of the printing press as a case in point^2. This groundbreaking innovation democratized access to information and catalysed a substantial uptick in literacy rates across Europe. As Eisenstein posits, the “Printing Revolution” catalyzed an era where knowledge was no longer the privilege of the few but a right of the many^2. Yet, its reverberations were not confined to just reading and writing. The press became the vessel through which Martin Luther disseminated his Ninety-Five Theses, triggering a religious revolution that reshaped the European continent.

However, the journey wasn’t without turbulence. This democratization of knowledge played a pivotal role in challenging the established order, culminating in events like the Reformation, which MacCulloch describes as Europe’s great house divided^3.

Niall Ferguson, in “The Square and the Tower”, beautifully illustrates the timeless tension and interplay between networks and hierarchies^4. Historically, technologies like the printing press have emerged as disruptors, challenging established orders and reshaping hierarchies. The press, for instance, allowed for the free flow of ideas, becoming an early network that democratized information. Yet, not everything it propagated was for the betterment of society. The infamous “Malleus Maleficarum”, an ostensibly scholarly treatise, fueled the flames of the European witch hunts, leading to persecution, paranoia, and a dark chapter in history^5.

From Past to Present: The Tech Geopolitical Nexus

Fast forward to the present, and we witness a world where technology continues to shape geopolitical realities. Maddison’s macro-economic study reveals that the global center of economic gravity has been steadily shifting towards the East, particularly since the dawn of the 21st century^6. Nowhere is this shift more apparent than in the realm of technology.

The US-China tech rivalry, explored by Fuller, highlights the strategic challenges posed by China’s technological ascent^7.

The race for supremacy in AI, quantum computing, 5G, and biotechnologies marks the modern-day power play. But this isn’t merely about technological one-upmanship; it signifies a larger canvas of geopolitics, economics, and even societal values.

Many analysts are drawing parallels to the Cold War, coining the term “Tech Cold War” or “Cold War II”. Unlike the 20th-century version, primarily characterized by nuclear deterrence between the USSR and the US, this new Cold War positions the US and China in an intense rivalry for technological, economic, and military dominance. In the midst of this rivalry, both nations are hyper-aware of the stakes.

Navigating the Waters of New Geopolitical Paradigms

More than a century ago, the naval strategist Alfred Thayer Mahan, in his seminal work on sea power, postulated that maritime dominance was crucial to national greatness.

Today the Indo-Pacific has become the focal point of 21st-century geopolitics. Here, China’s assertive ‘Two Ocean Strategy’ is emblematic of its ambitions to exert influence both in the Pacific and the Indian Ocean. This expansive maritime vision is not just about sea lanes and trade; it’s a reflection of China’s aspirations to be a global power.

Simultaneously, the Taiwan question looms large in this maritime strategy. Its strategic location in the first island chain poses both an opportunity and a challenge for Beijing. Control over Taiwan would offer unencumbered access to the broader Pacific.

However, the rise of one power often brings countermeasures by others. The ‘AUKUS’ agreement between Australia, the United Kingdom, and the United States is a manifestation of this dynamic. While cloaked in the language of technological collaboration, especially in the realm of nuclear-powered submarines, the underlying intent of AUKUS is clear. It seeks to counterbalance China’s growing naval capabilities and assertiveness, particularly in the South China Sea.

Reflecting on Mahan’s sea power doctrine in this context provides a sobering perspective. Mahan believed that maritime dominance was the linchpin of global influence. Yet, he also understood the responsibilities and challenges that came with such power. In our contemporary setting, while nations pursue their maritime strategies, it is imperative they also embrace the principles of dialogue, cooperation, and conflict avoidance.

Taiwan epitomizes this interplay. As a beacon in semiconductor manufacturing, Taiwan’s geopolitical relevance can’t be overstated. Any instability could trigger economic consequences potentially dwarfing the aftermath of the Covid-19 pandemic^9.

Taiwan and Europe: Quietly Interwoven, Profoundly Connected.

In the intricate web of global technology supply chains, few names stand out as prominently as Taiwan Semiconductor Manufacturing Company (TSMC). Founded in 1987, TSMC has ascended the technological hierarchy to become the world’s leading semiconductor foundry, a testament to its unwavering commitment to innovation and excellence.

TSMC’s significance is multifaceted. For one, it’s the world’s largest dedicated independent semiconductor foundry^8. With clients ranging from major tech giants like Apple and Nvidia to burgeoning startups, TSMC’s production underpins a vast swathe of the digital products and solutions we rely on daily. However, TSMC’s role isn’t merely a commercial or technological one. It is geopolitical. With the escalating “Tech Cold War” between the U.S. and China, TSMC finds itself at an intriguing junction. The company’s strategic importance is underscored by global reliance on its cutting-edge chip manufacturing capabilities. This reliance has not only made TSMC a coveted partner but also a strategic asset in the larger scheme of global geopolitics. The U.S. push to ensure TSMC sets up manufacturing bases on its soil, and China’s keen interest in the semiconductor sector, highlights the foundry’s pivotal position.

Furthermore, TSMC embodies Taiwan’s broader significance in the tech world. As the geopolitical tussle intensifies, Taiwan – and by extension, TSMC – becomes a linchpin for global tech supply chains. A disturbance in TSMC’s operations, as speculated, could have cascading ramifications across industries, from consumer electronics to automotive and healthcare. Any significant disruption in this intricate supply chain would reverberate globally, with experts suggesting a potential 5% drop in global automotive production^9.

As chips become smaller, denser, and more powerful, the precision and capability of lithography machines must evolve in tandem.

Here’s where Europe and ASML, a Dutch gem, comes into play. The company is the sole producer of extreme ultraviolet (EUV) lithography machines^8, an advanced technology that allows for the creation of incredibly dense and efficient chips. With transistors now approaching atomic scales, EUV lithography is no less than a technological marvel, allowing chipmakers to etch circuits just a few nanometers wide.

However, the conversation around ASML isn’t merely about technological mastery. Given its unique position as the only producer of these EUV machines, ASML enjoys a quasi-monopolistic status in this niche yet profoundly impactful domain. In an era where technological supremacy is increasingly intertwined with geopolitical power, also ASML’s importance cannot be overstated. The machines they produce are not just expensive and sophisticated pieces of equipment; they are, in many ways, gatekeepers to the next generation of digital innovation.

Such a near-monopoly naturally draws attention. Nations and corporations are keenly aware of the strategic value inherent in controlling or accessing state-of-the-art chipmaking technology. With the ongoing technological cold war, where semiconductor supply chains have become part of the geopolitical chessboard, ASML finds itself in a spotlight it never sought but cannot avoid.

Europe’s Crucial Pivot

Europe’s position in this evolving tech landscape is unique. While traditionally viewing the Atlantic alliance as a cornerstone of its foreign policy, the rise of China necessitates a recalibrated approach^10. Europe’s interlinked trade with China, especially through critical chokepoints like the Malacca Strait, underscores the strategic dimension of this relationship^11.

In this whirlwind of technological and geopolitical flux, Europe is not an idle spectator. With a collective GDP nearing $22 trillion, it wields considerable influence. Europe’s role is multi-dimensional: an economic powerhouse, a voice of reason in tumultuous times, and often a mediator in global disputes.

The European Central Bank (ECB) embodies Europe’s proactive stance^12. Recognizing the flux, the ECB’s vision for 2023-2025 zeroes in on three pillars:

The ECB recognizes that the financial institutions it oversees must adapt to these transformative times. A crucial element of this adaptation is embracing digitalization, with a special emphasis on robust data-driven risk management.

Strengthening Resilience: The intricate web of global economies translates to shared vulnerabilities. It’s imperative for Europe’s financial edifice to be robust, equipped to handle external shocks, and maintain systemic stability.
Digitalisation & Institutional Strengthening: The burgeoning fintech sector necessitates a complete metamorphosis for legacy banks. This isn’t a mere cosmetic digital overhaul. Banks need to internalize and deploy intelligent digitalization. Central to this transformation is data analytics, supercharged by AI. Harnessing data, drawing meaningful insights, and predicting trends will determine who thrives in this new era.
Climate Change Initiatives: Europe has consistently championed sustainability. The financial sector’s alignment with green, sustainable practices isn’t just altruistic; it’s also economic prudence, ensuring long-term viability and stability.

The above mentioned ECB focus is highlighted by Experian’s 2023 report on why AI-driven, regulatory-compliant analytics solutions are becoming imperative for European banks^13.

The AI Paradigm: Europe’s value-based Ethical Approach

Europe’s approach to AI regulation, championing the cause of ‘explainable AI’, shows its commitment to integrating technology with ethics. This dedication harks back to its legacy of literacy and the importance of accessibility, a theme explored by Graff^14. As Europe navigates the ‘Asian Century’^15, it does so with a clear vision: to leverage its historical experiences and chart a course that balances innovation with ethical considerations. The European AI Act encapsulates this approach. The Act’s core philosophy revolves around ensuring AI applications are safe and respect existing laws and values. This includes transparency obligations, strict criteria for ‘high risk’ AI applications, and a provision for setting up a European Artificial Intelligence Board.

One might wonder, why the emphasis on explainability? As AI systems permeate critical sectors, from healthcare to finance, their decisions can profoundly impact individuals. An ‘explainable AI’ ensures that these decisions are not just accurate but also comprehensible to the average person. This empowers individuals, fostering trust in AI systems.

The Act, however, isn’t just about explainability. It recognizes the diverse applications of AI and categorizes them based on risk. For ‘high-risk’ applications, stringent requirements, from transparency to accuracy and security, are mandated. This stratified approach ensures that while innovation isn’t stifled, critical areas receive the scrutiny they warrant.

Economic Powerhouses: A Comparative Analysis

Any discussion on global transformation would be incomplete without examining the economic engines driving these changes. China’s astounding growth, with a GDP of $17.7 trillion by 2022^16, and its decade-long average annual growth rate of 6.5%, contrasts with the US’s $25.3 trillion GDP and a more conservative 2.3% growth rate^17. The European Union, showcasing resilience and integration, clocks a collective GDP nearing $22 trillion^18, with trade figures underscoring its global economic clout^19.

Conclusion: Europe’s Way Forward

Our world is in a state of flux, reminiscent of those transformative moments in history. From the monumental shifts of the Printing Revolution^2 to the divisive yet transformative Reformation^3, Europe has witnessed and shaped global trajectories. As it stands at the crossroads of another transformation, it draws from its rich historical tapestry, aiming to strike a balance between embracing the future and preserving its core values.

The digital future beckons, but it’s not without its challenges. Whether it’s the complex web of tech geopolitics or the imperative of sustainable growth, Europe’s journey forward will need to be both adaptive and principled. At the heart of this journey lies the potent combination of data and ethics. And as Europe strides into the future, it carries with it a clear message: progress, when rooted in ethics and driven by knowledge, can usher in an era that’s not just technologically advanced but also just, balanced, and peaceful.

Footnotes:

^1 Shakespeare, William. “Henry V.” Act IV, Scene 3. ^2 Eisenstein, Elizabeth L. “The Printing Revolution in Early Modern Europe.” Cambridge University Press, 1983. ^3 MacCulloch, Diarmaid. “Reformation: Europe’s House Divided 1490-1700.” Penguin UK, 2004. ^4 Ferguson, Niall. “The Square and the Tower: Networks and Power, from the Freemasons to Facebook.” Penguin, 2018. ^5 Kramer, Heinrich and Sprenger, James. “Malleus Maleficarum.” Dover Publications, 1971. ^6 Maddison, Angus. “Contours of the World Economy 1-2030 AD: Essays in Macro-Economic History.” Oxford University Press, 2007. ^7 Fuller, Douglas B. “Cutting off our nose to spite our face: US policy toward Huawei and Taiwan in the shadow of the Chinese tech challenge.” International Security 45.3 (2021): 52-89. ^8 Chappell, Bill. “ASML: The Obscure Dutch Company That’s Enabling Big Advances In Tech.” NPR, 2019. ^9 “The Economic Impact of a Taiwan Crisis.” Nikkei Asia, 2023. ^10 Casarini, Nicola. “The Rise of China and the Future of the Atlantic Alliance.” Oxford University Press, 2020. ^11 Lanteigne, Marc. “China’s Maritime Security and the ‘Malacca Dilemma’.” Asian Security 4.2 (2008): 143-161. ^12 “European Central Bank Annual Report.” 2023. ^13 Experian PLC. “Annual Report and Financial Statements.” 2023. ^14 Graff, Harvey J. “The Legacies of Literacy: Continuities and Contradictions in Western Culture and Society.” Indiana University Press, 1987. ^15 Khanna, Parag. “The Future is Asian: Commerce, Conflict, and Culture in the 21st Century.” Simon and Schuster, 2019. ^16 “World Bank Data: China.” 2022. ^17 “World Bank Data: United States.” 2022. ^18 “World Bank Data: European Union.” 2022. ^19 “European Commission Trade Statistics.” 2022.

About the author

Jochen Werne is CEO of Experian DACH. Large-scale global data powerhouses like Experian with it’s more than 20.000 data and analytics experts and a market cap of nearly €30bn have a pivotal role to play in this evolving narrative. As a global vanguard in data analytics, Experian is uniquely poised to offer financial institutions the insights and tools essential for navigating the multifaceted challenges of our times. In a world inundated with data, discerning patterns, understanding trends, and anticipating potential pitfalls will be the linchpin of success.

Innovation & Business Jochen Werne Press & Publications Society & Diplomacy

Unpacking Transformation: A European perspective

Jochen Werne October 24, 2023 acatech ai artificial intelligence Experian FV2023 innovation Jochen Werne society Steinmeier transformation

By Jochen Werne

I had the distinct honor, alongside CCO Björn Hinrichs, to represent Experian DACH at the Gala event 2023. Our heartfelt gratitude goes to acatech for their warm invitation.

It’s clear that fostering a robust relationship between science and industry is paramount. The National Academy of Science and Engineering stands as a beacon, guiding and correcting, making technological innovation the cornerstone of transformation. This union of strong research, pioneering companies, and forward-thinking policies is the backbone of what acatech and countless others strive for. In this journey, while competition fuels our drive, it is cooperation that offers the platform for greatness.

In the infinite expanse of space, we are but astronauts on a tiny speck called Earth. Regardless of our political and geopolitical landscape, science and research must always be the bridge, the “Bridge over Troubled Water” that connects us and ensures progress, says Jan Wörner, President of acatech, wisely.

In reflecting on this, Germany’s Federal President Frank-Walter Steinmeier’s words resonate deeply: “I think we should base our perspective more on Max Frisch and trust ourselves as individuals and society alike to be able to shape the future. And that means developing perspectives, broadening our horizons and, yes, always daring to try something new. We need all this in the phase of upheaval we are in. Holding on to the past, ignoring change, refusing change, that is not an option – especially not in an open society like ours. But: We have to give change – that is the task of politics, business and science – a direction!”

Drawing from these profound insights and looking through the lens of our work at Experian DACH, the era we are entering can be aptly described as a new Age of Enlightenment, where data and therefore data literacy is paramount. As the Enlightenment thinker Voltaire astutely pointed out, “Judge a man by his questions rather than by his answers.” It’s a sentiment that is even more relevant today. Taking cues from Immanuel Kant’s wisdom, enlightenment is about emerging from our limitations. In the context of our time, achieving data literacy and harnessing data effectively signifies our evolution from technological naivety.

While AI stands as a monumental tool to decipher this data, its effectiveness lies in the quality of the data it is fed. It brings to the fore the urgent need for data literacy. An AI is only as good as its data. Thus, a distorted understanding could lead to distorted outputs. The onus is on us, leaders in data, to champion the responsible use of AI and advance the narrative on the symbiotic relationship between data and AI.

This new Enlightenment is our journey towards an era where society is mature and informed, utilizing the strength of data and AI for the betterment of all. Knowledge, in this context, isn’t just power but the foundation for positive societal transformation.

Concluding with my personal reflection, data isn’t merely a quantified entity; it’s a potent instrument to comprehend and address pressing challenges. Our collective aim should be to cultivate an understanding of data – its collection, utilization, and, importantly, its ethical application.

Our commitment at Experian DACH, backed by our ‘data for good’ principle, is to be at the forefront of this change, guiding, and contributing to this transformative journey.

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More about the acatec Gala #FV2023 including the keynotes by Frank-Walter Steinmeier, Marion Merklein, Jan Wörner and Thomas Weber can be found here

Innovation & Business Jochen Werne Society & Diplomacy

Harnessing Data for Good

Jochen Werne August 1, 2023 ai artificial intelligence data Data for Good Data Literacy Experian Jochen Werne society technology transformation

After my first week as CEO for Experian in the DACH region (Germany, Austria, and Switzerland), I find myself profoundly thankful for the warm welcome and the many highly inspiring encounters with some of the best data and technology professionals on our planet. Experian is not only a data insights industry titan, one that operates in 32 countries, employs over 20,000 outstanding personalities worldwide but would also rank with its more than USD 30 billion market capitalisation compared to Germany’s leading stock index as the 19th largest DAX company in Germany. Experian serves as a global leader millions of consumers and businesses, leveraging data to make a transformative difference in people’s lives.

Yet, with tremendous reach and influence comes immense responsibility.

Reflections

Just as the Age of Enlightenment in the 18th century reshaped society through the dissemination of knowledge, we find ourselves at the precipice of a new era, one marked by the power and potential of data. The 21st century, in my view, must herald a fresh Age of Enlightenment, one underpinned by data literacy.

The Age of Enlightenment, Literacy and the Dawn of Data Literacy

The Age of Enlightenment, a period dating from the late 17th to the late 18th century, marked a profound shift in the course of human history. This era, also known as the Age of Reason, encouraged critical thinking, decoupling minds from the shackles of superstition and unquestioned authority. The spotlight was placed firmly on rational thought, scientific inquiry, and individual rights – underpinnings of the modern world as we know it.

Several factors catalyzed this significant shift, not least of which was the advent and proliferation of printing technology. As philosopher Immanuel Kant noted, “Dare to know! Have the courage to use your own understanding,” a statement that encapsulates the Enlightenment’s spirit. This courage was largely fostered through increasing literacy rates.

The advent of the printing press revolutionized the dissemination of information. Books were no longer a luxury exclusive to the elite; knowledge became democratized. This sparked an increased demand for literacy. As more people learned to read, ideas were more freely exchanged, fueling a critical examination of existing societal structures.

For example, “The Encyclopédie,” a massive reference work edited by Denis Diderot and Jean le Rond d’Alembert, exemplified the spread of Enlightenment thinking. Its contributors, including leading intellectuals like Voltaire and Rousseau, aimed to collate all the world’s knowledge into a single work, accessible to the common man. This unprecedented venture into free access to knowledge set the stage for many of the democratic, scientific, and industrial revolutions that followed.

Fast forward to the present day, we see parallels in the advent of the internet, a digital revolution that democratizes information at a scale unimaginable to the Enlightenment thinkers. However, this superabundance of information has led to a paradoxical effect. As stated by Nobel Laureate Herbert A. Simon, “a wealth of information creates a poverty of attention.”

In an age characterised by short attention spans and reactionary behaviour, the challenge lies not in accessing information but in sifting through its vastness to discern truth from falsehood. A study conducted by Microsoft, 2015, found that the average human attention span has dropped to eight seconds, primarily due to the digitalised lifestyle.

Like the literacy of the Enlightenment Age, the 21st century calls for a new form of literacy: data literacy.

In a world where data is hailed as the new oil, our ability to critically interpret, analyse, and question data is of paramount importance. This skill set empowers individuals and corporations to make informed decisions, a process integral to our society.

In a report by The Data Literacy Project of which also Experian is a partner, only 21% of the global working population was confident in their data literacy skills. This gap highlights the pressing need for an educational shift towards fostering data literacy, much like the push for literacy during the Enlightenment era.

In conclusion, as we navigate the information deluge, a new Age of Enlightenment beckons, one centered around data literacy. With this new ‘Enlightenment,’ we can harness the true potential of information abundance, steering our societies towards more informed, rational, and democratic spaces. As the Enlightenment thinker Voltaire wisely said, “Judge a man by his questions rather than by his answers.” This insight seems more pertinent now than ever.

Such a renewed Age of Enlightenment also draws inspiration from one of the original Enlightenment’s most influential thinkers, Immanuel Kant. As he famously stated, “Enlightenment is man’s emergence from his self-imposed immaturity.” To transpose his wisdom to our context, data literacy and the effective application of data might be seen as emergence from a state of technological immaturity.

Furthermore, in our modern context, the Enlightenment’s emphasis on reason and logic has a fascinating analogue in the field of artificial intelligence (AI). AI, a critical tool in making sense of complex data, is designed to mimic human reasoning, albeit on a scale and at speeds we could never achieve unaided. As such, it holds a pivotal role in our future, helping us glean insights from the vast sea of data.

However, while AI’s potential is significant, it further underlines the importance of data literacy. The algorithms that power AI are only as good as the data that feeds them. Poor understanding of data and its nuances can lead to skewed AI outputs, with far-reaching implications.

Leaders in data need to focus on responsible use of AI by promoting data literacy and improving understanding of the interplay between data and AI.

New Enlightenment, then, is a journey towards a mature, informed society that harnesses the power of data and AI for good. In this era, knowledge isn’t just power; it’s the key to creating a world where data and technology act as catalysts for positive change.

In this new age, data is not merely a collection of numbers, facts, or figures; it is a powerful tool for understanding and addressing the most pressing societal issues.

However, just as literacy was not universal during the initial Enlightenment, data literacy is not yet a universal skill. As a society, we need to foster an understanding of data, how it’s collected, how it’s used, and most importantly, how it can be used ethically and responsibly.

Harnessing Data for Good – The Experian way

Experian, as a data powerhouse, has a crucial role to play in this journey. Experian has been a pioneer in harnessing data for good, from helping individuals gain access to credit, to assisting businesses flourish, to aiding governments in delivering crucial services.

For the DACH region specifically, the path to growth is intertwined with our mission to empower individuals and corporations with data and to protect from risks. In our regional market in the heart of Europe, we see significant potential to enhance consumer and corporate credit, improve business services, and support governmental programs.

Trust, innovation and reliability go hand in hand

To achieve this goal, we need to aim high and develop state-of-the-art products like AiDRIAN, which, by intelligently combining and using the latest AI technologies and data, are able to protect customers from fraud with more than 99.9% accuracy. Developing trustworthy solutions is of paramount importance. Trust comes from long-term reliability and independent audits. For AiDRIAN, for example, Fraunhofer IPA audited the heart of the solution, the Transaction Miner. The machine learning model compares several hundred customer characteristics and then assesses the risk of a transaction. Millions of data records are evaluated in a matter of seconds. Fraunhofer therefore came to the test result that the Miner’s predictive power is comprehensible even to experts and leads to better decisions.

Such results are only achievable by having an exemplary team.

The Experian DACH team, which I had the pleasure of meeting during my first week, is made up of dedicated, forward-thinking people who understand that work is not just about data, but about using data as a tool for progress and prosperity. A team that is eager to innovate, build trust, and act as responsible stewards of the data – every single day. As we delve deeper into a new era, we should aim to be instrumental in fostering a society that uses data ethically, responsibly, and for the greater good.

The Enlightenment brought knowledge to the masses, revolutionizing societies, and shaping the modern world. It is my belief, a new Age of Enlightenment will bring data literacy to all, empowering societies in ways we are just beginning to imagine.

I am excited and honoured to be a part of this transformative journey.

Jochen Werne - New Joiner CEO DACH Experian

Innovation & Business Ocean & Passion Society & Diplomacy

Das Jahrzehnt der Transformation – Optimistische Perspektiven eines Umdenkens

Jochen Werne July 1, 2023 Anton Zeilinger Carinthische Dialoge diplomacy Horst von Buttlar Jochen Werne Kurier MAximilian Franz Nobelpreisträger peoples diplomacy Positivität society transformation Umdenken Wirtschaftswoche

17. Carinthische Dialoge – Schloss Bach – 14.-16. Juli 2023

Es ist mir eine besondere Ehre den Eröffnungsvortrag der 17. Carinthischen Dialogen geben zu dürfen. Unter dem Leitthema “Das Jahrzehnt der Transformation – Optimistische Perspektiven eines Umdenkens” wird der Beitrag, “Ein neues Zeitalter der Aufklärung” drei inspirierende Tage einläuten.

Bei dieser bemerkenswerten Veranstaltung teilen sich die Bühne angesehenen Persönlichkeiten aus verschiedenen Fachbereichen. So wird Horst von Buttlar, Chefredakteur der Zeitschrift “Wirtschaftswoche” und Autor des Buches “Das grüne Jahrzehnt”, Veränderungen ausgelöst durch Krisen thematisieren.

Nobelpreisträger Anton Zeilinger, emeritierter Professor der Universität Wien, widmet sich dem spannenden Thema des Zufalls.

Ich möchte mich herzlich bei den Organisatoren, insbesondere bei Generalsekretärin Johanna Franz und Maximilian Franz, für die Einladung und ihre unermüdliche Arbeit zur Realisierung dieser bedeutsamen Veranstaltung bedanken.

Weitere Informationen zur Veranstaltung, einschließlich mehr Details zu den unten stehenden Referenten und des Programms, sind auf der Website der Carinthischen Dialoge https://www.carinthische-dialoge.at/aktuelles-programm/ zu finden.

ReferentInnen u. ModeratorInnen

Horst von Buttlar, Wissenschaftsjournalist und Chefredakteur der Zeitschrift Capital. Buchautor „Das grüne Jahrzehnt“, Berlin

Klemens Fheodoroff, Dr., FA für Neurologie, OA Gailtal-Klnik, Obmann bei Carinthischer Sommer, 2.stv. Vorsitzender der Gesellschaft zur Förderung interdisziplinärer Dialoge, Carinthische Dialoge

Bernhard Gaul, Journalist im innerpolitischen Ressort der Tageszeitung Kurier

Arnold Mettnitzer, Prof. Dr., Theologe, Psychotherapeut in eigener Praxis, freier Mitarbeiter des ORF, Autor zahlreicher Bücher, Wien

Michael Musalek, Univ.-Prof. Dr., Ordinarius für Allgemeine Psychiatrie, SFU Med Wien, Vorstand des Intistuts für Sozialästhetik und Psychische Gesundheit, SFU Wien u. Berlin

Elisabeth Juliane Nöstlinger – Jochum, Wissenschaftsjournalistin, Producerin von WissensART, Vorsitzende der Jury zur Vergabe des Watzlawick-Ringes, Mitglied in zahlreichen wissenschaftlichen und kulturellen Gremien, Wien

Manfred Prisching, Univ.-Prof. i.R., Dr. jur., Mag.rer.soc.oec., Institut für Soziologie der Universität Graz

Philipp Weiss, österreichischer Schriftsteller, u.a. Buch: „Am Weltenrand sitzen die Menschen und lachen“, Wien

Jochen Werne, Autor, Keynotespeaker, international ausgezeichneter NGO-Gründer und Spezialist im Bereich Unternehmenentwicklung und -transformation, sowie internationaler Diplomatie.

Anton Zeilinger, em. o. Univ.-Prof. Dr., Universität Wien und Österreichische Akademie der Wissenschaften

The Decade of Transformation – Optimistic Perspectives of a Rethink

17th Carinthian Dialogues – Bach Castle – 14-16 July 2023

It is a special honour for me to give the opening lecture of the 17th Carinthian Dialogues. Under the guiding theme “The Decade of Transformation – Optimistic Perspectives of a Rethinking”, the contribution, “A New Age of Enlightenment” will usher in three inspiring days.
At this remarkable event, the stage will be shared by respected personalities from various fields. Horst von Buttlar, editor-in-chief of the magazine “Wirtschaftswoche” and author of the book “The Green Decade”, will address changes triggered by crises. Nobel Prize winner Anton Zeilinger, professor emeritus at the University of Vienna, will address the exciting topic of chance.
I would like to express my sincere thanks to the organisers, especially Secretary General Johanna Franz and Maximilian Franz, for the invitation and their tireless work to realise this momentous event.
Further information on the event, including more details on the speakers below and the programme, can be found on the Carinthian Dialogues website https://www.carinthische-dialoge.at/aktuelles-programm/.

Innovation & Business Press & Publications

Far-reaching influence: German AI experts quoted in Korean “theSCIENCEplus” blog article “ChatGPT – Breakthrough or Hype?”

Jochen Werne March 19, 2023 artificial intelligence ChatGPT innovation Jochen Werne Johannes Hoffart language models Moon Kwang-ju Nadja Podregar Natural language processing Plattform Lernende System society theSCIENCEplus Thilo Hagendorff transformation Ute Schmid

In March 2023, the Korean blog “theSCIENCEplus” by Moon Kwang-ju published the article “ChatGPT – Breakthrough or Hype”. The article is based on the argumentation of the scinexx article “ChatGPT and Co – Opportunity or Risk?” by Nadja Podregar and refers to insights from leading German experts such as Johannes Hoffart, Thilo Hagendorff, Ute Schmid, Jochen Werne et al. Most of these experts are also organised in Germany’s leading AI platform “Learning Systems”.

Please find theORIGINAL ARTICLE HERE and a translation from Korean to English created with the German AI-platform DeepL.com below

Read 3’40”

ChatGPT – Opportunity or Risk?

Features and consequences of a new AI system

ChatGPT can write poems, essays, professional articles, or even computer code. AI systems based on large-scale language models like ChatGPT achieve amazing results, and the text is often almost indistinguishable from human work. But what’s behind GPT and its ilk? And how intelligent are such systems really?

Artificial intelligence has made rapid progress in recent years. The system, which is based on a combination of artificial neural networks, has been accessible via the Internet since November 2022, so it was only through ChatGPT that many people realised what AI systems can already do. His impressive achievements sparked a new debate about the opportunities and risks of artificial intelligence. This is another reason to reveal some facts and background information about ChatGPT and its “identities”.

Artificial Intelligence, ChatGPT, and the Results “Breakthrough or Hype?”

“In my first conversation with ChatGPT, I couldn’t believe how well my questions were understood and put into context.” These are the words of Johannes Hoffart, head of SAP’s AI department. OpenAI’s AI system has been causing sensation and amazement around the world since it first became accessible to the general public via a user interface in November 2022.

A flood of new AI systems

In fact, thanks to neural networks and self-learning systems, artificial intelligence has made huge strides in recent years. AI systems have also made tremendous progress in the human domain, whether it’s mastering strategy games, deciphering protein structures, or writing programme code. Text-to-image generators like Dall-E, Stable Diffusion, or Midjourney create images and collages in the desired style in seconds based solely on textual descriptions.

Perhaps the biggest leap in development has been in language processing. So-called Large Language Models (LLMs) have been developed to date, allowing these AI systems to carry out dialogues, translate texts, or write texts in an almost human-like form. These self-learning programmes are trained using millions of texts of all kinds and learn which content and words occur most often and in which context, and are therefore most relevant.

What does ChatGPT do?

The most well-known of these major language models is GPT-3, the system behind ChatGPT. At first glance, this AI seems to be able to do almost anything. It answers all kinds of knowledge questions, but it can also solve more complex linguistic tasks. For example, if you ask ChatGPT to write a 19th-century novel-style text on a particular topic, it will do so. ChatGPT also writes school essays, scientific papers, or poems with ease and without hesitation.

OpenAI, the company behind ChatGPT, lists about 50 different types of tasks that a GPT system can perform. These include writing texts in different styles, from film dialogues to tweets, interviews or essays, “micro-horror story creators” or “critiquing chatbot Marv”. The AI system can also write recipes, find colours to match your mood, or be used as an idea generator for VR games and fitness training. GPT-3 is also programmable and can convert text into program code in a variety of programming languages.

Just the tip of the iceberg

It’s no surprise that ChatGPT and its “colleagues” are hailed by many as a milestone in AI development, but can GPT-3 and its successor GPT-3.5 really make such a quantum leap? “In a way, it’s not a big change,” said Tilo Hagendorf, an AI researcher at the University of Tübingen. Similarly powerful language models have been around for a long time. “But what’s new now is that companies have dared to attach such language models to a simple user interface.”

Unlike before, when such AI systems were only tested or used in narrowly defined, private areas, ChatGPT now allows everyone to try out for themselves what is already possible with GPT and its ilk. “This user interface is really what started all this crazy hype,” Hagendorff said. In his assessment, ChatGPT is definitely a game changer in this regard. Because now other companies will offer their language models to the general public. “And then the creative potential that will be unleashed, the social impact it will have, I don’t think we know anything about that.”

Consequences for education and society

The introduction of ChatGPT is already causing considerable upheaval and change, especially in education. For pupils and students, AI systems now open up the possibility of having homework, school essays, or seminar reports that are simply prepared by artificial intelligence. The quality of many ChatGPT texts is such that they are not easily exposed as AI-generated.

As a result, many classical forms of learning success control may become obsolete in the near future. Schmidt, head of the Cognitive Systems working group at the University of Bamberg. Until now, knowledge learnt at school, and sometimes even at university, has mainly been tested by simple queries. However, competences also include the derivation, verification, and practical application of what has been learnt. In the future, for example, it may make more sense to conduct test interviews or set tasks involving AI systems.

“Large-scale language models like ChatGPT are not only changing the way we interact with technology, but also the way we think about language and communication,” said Jochen Werne of Prosegur. “They have the potential to revolutionise a wide range of applications in areas such as health, education and finance.”

Ocean & Passion Society & Diplomacy

The ”High Seas Treaty”

Jochen Werne March 11, 2023 diplomacy environment environmental protection Global Goals Global Offshore Sailing Team High Seas Treaty ocean SDG society Sustainability UNEP UNITED NATIONS

Congratulations to all who have continuously worked to protect our oceans, paving the way for a unique global agreement.

March 2023 is a month of hope, a victory for diplomacy, and a ray of hope for our oceans and us humans living on this beautiful blue planet.
Jochen Werne commenting on the “High Seas Treaty”, the historic agreement reached by UN delegates to protect marine biodiversity in international waters

UN delegates reached a historic agreement to protect marine biodiversity in international waters, referred to by many – though not officially – as the „High Seas Treaty.“ The agreement reached by delegates of the Intergovernmental Conference on Marine Biodiversity of Areas Beyond National Jurisdiction, better known by its acronym BBNJ, is the culmination of UN-facilitated talks that began in 2004.

Following the 1951 Antarctic Treaty, the Convention on the Protection of Marine Biodiversity in International Waters is an important step towards achieving UNEP’s SDG targets and thus a better world for us all.

As members of the Global Offshore Sailing Team, which has been working to promote environmental awareness since 1999, we are very grateful to the dedicated diplomats for reaching such a milestone in history.

For everyone interested please read more on the “High Seas Treaty” here:

United Nations: UN delegates reach historic agreement on protecting marine biodiversity in international waters https://news.un.org/en/story/2023/03/1134157

Innovation & Business Press & Publications Society & Diplomacy

scinexx-focus topic: ChatGPT and Co – Chance or Risk?

Jochen Werne February 26, 2023 ai artificial intelligence big data Catherine Gao ChatGPT innovation Jochen Werne Johannes Hoffart Jooyoung Lee Luciano Floridi Massimo Chiratti OpenAI society Thai Lee Thilo Hagendorff Tom Brown Ute Schmid Volker Tresp

Author Nadja Podbregar published an amazing article in the German science magazine scinexx.de about the status quo of AI systems based on large language models. Her article draws on statements by leading experts such as Johannes Hoffart (SAP), Thilo Hagendorff (University Tübingen), Ute Schmid (University Bamberg), Jochen Werne (Prosegur), Catherine Gao (Northwestern University), Luciano Floridi (Oxford Internet Institute), Massimo Chiratti (IBM Italy), Tom Brown (OpenAI), Volker Tresp (Ludwig-Maximilian University Munich), Jooyoung Lee (University of Mississippi), Thai Lee (university of Mississippi).

The original article in German can be accessed on the scinexx site here.

(A DeepL.com translation in English can be found below. Pictures by pixabay.com)

ChatGPT and Co – Chance or Risk?

Capabilities, functioning and consequences of the new AI systems

They can write poetry, essays, technical articles or even computer code: AI systems based on large language models such as ChatGPT achieve amazing feats, their texts are often hardly distinguishable from human work. But what is behind GPT and Co? And how intelligent are such systems really?

Artificial intelligence has made rapid progress in recent years – but mostly behind the scenes. Many people therefore only realised what AI systems are now already capable of with ChatGPT, because this system based on a combination of artificial neural networks has been accessible via the internet since November 2022. Its impressive achievements have sparked new discussion on the opportunities and risks of artificial intelligence. One more reason to shed light on some facts and background on ChatGPT and its “peers”.

Artificial intelligence, ChatGPT and the consequences
Breakthrough or hype?

“During my first dialogue with ChatGPT, I simply could not believe how well my questions were understood and put into context”
Johannes Hoffart

– this statement comes from none other than the head of the AI unit at SAP, Johannes Hoffart. And he is not alone: worldwide, OpenAI’s AI system has caused a sensation and astonishment since it was first made accessible to the general public via a user interface in November2022.

Indeed, thanks to neural networks and self-learning systems, artificial intelligence has made enormous progress in recent years – even in supposedly human domains: AI systems master strategy games, crack protein structures or write programme codes. Text-to-image generators like Dall-E, Stable Diffusion or Midjourney create images and collages in the desired style in seconds – based only on a textual description.

Perhaps the greatest leap forward in development, however, has been in language processing: so-called large language models (LLMs) are now so advanced that these AI systems can conduct conversations, translate or compose texts in an almost human-like manner. Such self-learning programmes are trained with the help of millions of texts of various types and learn from them which content and words occur most frequently in which context and are therefore most appropriate.

What does ChatGPT do?

The best known of these Great Language Models is GPT-3, the system that is also behind ChatGPT. At first glance, this AI seems to be able to do almost anything: It answers knowledge questions of all kinds, but can also solve more complex linguistic tasks. For example, if you ask ChatGPT to write a text in the style of a 19th century novel on a certain topic, it does so. ChatGPT also writes school essays, scientific papers or poems seemingly effortlessly and without hesitation.

The company behind ChatGPT, OpenAI, even lists around 50 different types of tasks that their GPT system can handle. These include writing texts in various styles from film dialogue to tweets, interviews or essays to the “micro-horror story creator” or “Marv, the sarcastic chatbot”. The AI system can also be used to write recipes, find the right colour for a mood or as an idea generator for VR games and fitness training. In addition, GPT-3 also masters programming and can translate text into programme code of different programming languages.

Just the tip of the iceberg

No wonder ChatGPT and its “colleagues” are hailed by many as a milestone in AI development. But is what GPT-3 and its successor GPT-3.5 are capable of really such a quantum leap?

“In one sense, it’s not a big change at all,”
Thilo Hagendorff

says AI researcher Thilo Hagendorff from the University of Tübingen. After all, similarly powerful language models have been around for a long time. “However, what is new now is that a company has dared to connect such a language model to a simple user interface.”
Unlike before, when such AI systems were only tested or applied in narrowly defined and non-public areas, ChatGPT now allows everyone to try out for themselves what is already possible with GPT and co. “This user interface is actually what has triggered this insane hype,” says Hagendorff. In his estimation, ChatGPT is definitely a gamechanger in this respect. Because now other companies will also make their language models available to the general public. “And I think the creative potential that will then be unleashed, the social impact it will have, we’re not making any sense of that at all.”

Consequences for education and society

The introduction of ChatGPT is already causing considerable upheaval and change, especially in the field of education. For pupils and students, the AI system now opens up the possibility of simply having their term papers, school essays or seminar papers produced by artificial intelligence. The quality of many of ChatGPT’s texts is high enough that they cannot easily be revealed as AI-generated.

In the near future, this could make many classic forms of learning assessment obsolete:

“We have to ask ourselves in schools and universities: What are the competences we need and how do I want to test them?”
Ute Schmid

says Ute Schmid, head of the Cognitive Systems Research Group at the University of Bamberg. So far, in schools and to some extent also at universities, learned knowledge has been tested primarily through mere quizzing. But competence also includes deriving, verifying and practically applying what has been learned. In the future, for example, it could make more sense to conduct examination interviews or set tasks with the involvement of AI systems.

“Big language models like ChatGPT are not only changing the way we interact with technology, but also how we think about language and communication,”
Jochen Werne

comments Jochen Werne from Prosegur. “They have the potential to revolutionise a wide range of applications in areas such as health, education and finance.”

But what is behind systems like ChatGPT?

The principle of generative pre-trained transformers.
How do ChatGPT and co. work?

ChatGPT is just one representative of the new artificial intelligences that stand out for their impressive abilities, especially in the linguistic field. Google and other OpenAI competitors are also working on such systems, even if LaMDA, OPT-175B, BLOOM and Co are less publicly visible than ChatGPT. However, the basic principle of these AI systems is similar.

Learning through weighted connections

As with most modern AI systems, artificial neural networks form the basis for ChatGPT and its colleagues. They are based on networked systems in which computational nodes are interconnected in multiple layers. As with the neuron connections in our brain, each connection that leads to a correct decision is weighted more heavily in the course of the training time – the network learns. Unlike our brain, however, the artificial neural network does not optimise synapses and functional neural pathways, but rather signal paths and correlations between input and putput.

The GPT-3 and GPT 3.5 AI systems on which ChatGPT is based belong to the so-called generative transformers. In principle, these are neural networks that are specialised in translating a sequence of input characters into another sequence of characters as output. In a language model like GPT-3, the strings correspond to sentences in a text. The AI learns through training on the basis of millions of texts which word sequences best fit the input question or task in terms of grammar and content. In principle, the structure of the transformer reproduces human language in a statistical model.

Training data set and token

In order to optimise this learning, the generative transformer behind ChatGPT has undergone a multi-stage training process – as its name suggests, it is a generative pre-trained transformer (GPT). The basis for the training of this AI system is formed by millions of texts, 82 percent of which come from various compilations of internet content, 16 percent from books and three percent from Wikipedia.

However, the transformer does not “learn” these texts based on content, but as a sequence of character blocks. “Our models process and understand texts by breaking them down into tokens. Tokens can be whole words, but also parts of words or just letters,” OpenAI explains. In GPT-3, the training data set includes 410 billion such tokens. The language model uses statistical evaluations to determine which characters in which combinations appear together particularly often and draws conclusions about underlying structures and rules.

Pre-training and rewarding reinforcement

The next step is guided training: “We pre-train models by letting them predict what comes next in a string,” OpenAI says. “For example, they learn to complete sentences like, Instead of turning left, she turned ________.” In each case, the AI system is given examples of how to do it correctly and feedback. Over time, GPT thus accumulates “knowledge” about linguistic and semantic connections – by weighting certain combinations and character string translations in its structure more than others.

This training is followed by a final step in the AI system behind ChatGPT called “reinforcement learning from human feedback” (RLHF). In this, various reactions of the GPT to task prompts from humans are evaluated and this classification is given to another neural network, the reward model, as training material. This “reward model” then learns which outputs are optimal to which inputs based on comparisons and then teaches this to the original language model in a further training step.

“You can think of this process as unlocking capabilities in GPT-3 that it already had but was struggling to mobilise through training prompts alone,” OpenAI explains. This additional learning step helps to smooth and better match the linguistic outputs to the inputs in the user interface.

Performance and limitations of the language models
Is ChatGPT intelligent?

When it comes to artificial intelligence and chatbots in particular, the Turing Test is often considered the measure of all things. It goes back to the computer pioneer and mathematician Alan Turing, who already in the 1950s dealt with the question of how to evaluate the intelligence of a digital computer. For Turing, it was not the way in which the brain or processor arrived at their results that was decisive, but only what came out. “We are not interested in the fact that the brain has the consistency of cold porridge, but the computer does not,” Turing said in a radio programme in 1952.
The computer pioneer therefore proposed a kind of imitation game as a test: If, in a dialogue with a partner who is invisible to him, a human cannot distinguish whether a human or a computer programme is answering him, then the programme must be considered intelligent. Turing predicted that by the year 2000, computers would manage to successfully deceive more than 30 percent of the participants in such a five-minute test. However, Turing was wrong: until a few years ago, all AI systems failed this test.

Would ChatGPT pass the Turing test?

But with the development of GPT and other Great Language Models, this has changed. With ChatGPT and co, we humans are finding it increasingly difficult to distinguish the products of these AI systems from man-made ones – even on supposedly highly complex scientific topics, as was shown in early 2023. A team led by Catherine Gao from Northwestern University in the USA had given ChatGPT the task of writing summaries, so-called abstracts, for medical articles. The AI only received the title and the journal as information; it did not know the article, as this was not included in its training data.

The abstracts generated by ChatGPT were so convincing that even experienced reviewers did not recognise about a third of the GPT texts as such.

“Yet our reviewers knew that some of the abstracts were fake, so they were suspicious from the start,”
Catherine Gao

says Gao. Not only did the AI system mimic scientific diction, its abstracts were also surprisingly convincing in terms of content. Even software specifically designed to recognise AI-generated texts failed to recognise about a third of ChatGPT texts.

Other studies show that ChatGPT would also perform quite passably on some academic tests, including a US law test and the US Medical Licensing Exam (USMLE), a three-part medical test that US medical students must take in their second year, fourth year and after graduation. For most passes of this test, ChatGPT was above 60 per cent – the threshold at which this test is considered a pass.

Writing without real knowledge

But does this mean that ChatGPT and co are really intelligent? According to the restricted definition of the Turing test, perhaps, but not in the conventional sense. Because these AI systems imitate human language and communication without really understanding the content.

“In the same way that Google ‘reads’ our queries and then provides relevant answers, GPT-3 also writes a text without deeper understanding of the content,”
Luciano Floridi & Massimo Chiratti

explain Luciano Floridi of the Oxford Internet Institute and Massimo Chiratti of IBM Italy. “GPT-3 produces a text that statistically matches the prompt it is given.”

Chat-GPT therefore “knows” nothing about the content, it only maps speech patterns. This also explains why the AI system and its language model, GPT-3 or GPT-3.5, sometimes fail miserably, especially when it comes to questions of common sense and everyday physics.

“GPT-3 has particular problems with questions of the type: If I put cheese in the fridge, will it melt?”,
Tom Brown

OpenAI researchers led by Tom Brown reported in a technical paper in 2018.

Contextual understanding and the Winograd test

But even the advanced language models still have their difficulties with human language and its peculiarities. This can be seen, among other things, in so-called Winograd tests. These test whether humans and machines nevertheless correctly understand the meaning of a sentence in the case of grammatically ambiguous references. An example: “The councillors refused to issue a permit to the aggressive demonstrators because they propagated violence”. The question here is: Who propagates violence?

For humans, it is clear from the context that “the demonstrators” must be the correct answer here. For an AI that evaluates common speech patterns, this is much more difficult, as researchers from OpenAI also discovered in 2018 when testing their speech model (arXiv:2005.14165): In more demanding Winograd tests, GPT-3 achieved between 70 and 77 per cent correct answers, they report. Humans achieve an average of 94 percent in these tests.

Reading comprehension rather mediocre

Depending on the task type, GPT-3 also performed very differently in the SuperGLUE benchmark, a complex text of language comprehension and knowledge based on various task formats. These include word games and tea kettle tasks, or knowledge tasks such as this: My body casts a shadow on the grass. Question: What is the cause of this? A: The sun was rising. B: The grass was cut. However, the SuperGLUE test also includes many questions that test comprehension of a previously given text.

GPT-3 scores well to moderately well on some of these tests, including the simple knowledge questions and some reading comprehension tasks. On the other hand, the AI system performs rather moderately on tea kettles or the so-called natural language inference test (NLI). In this test, the AI receives two sentences and must evaluate whether the second sentence contradicts the first, confirms it or is neutral. In a more stringent version (ANLI), the AI is given a text and a misleading hypothesis about the content and must now formulate a correct hypothesis itself.

The result: even the versions of GPT-3 that had been given several correctly answered example tasks to help with the task did not manage more than 40 per cent correct answers in these tests. “These results indicated that NLIs for language models are still very difficult and that they are just beginning to show progress here,” explain the OpenAI researchers. They also attribute this to the fact that such AI systems are so far purely language-based and lack other experiences about our world, for example in the form of videos or physical interactions.

On the way to real artificial intelligence?

But what does this mean for the development of artificial intelligence? Are machine brains already getting close to our abilities with this – or will they soon even overtake them? So far, views on this differ widely.

“Even if the systems still occasionally give incorrect answers or don’t understand questions correctly – the technical successes that have been achieved here are phenomenal,”
Volker Tresp

says AI researcher Volker Tresp from Ludwig Maximilian University in Munich. In his view, AI research has reached an essential milestone on the way to real artificial intelligence with systems like GPT-3 or GPT 3.5.

However, Floridi and Chiratti see it quite differently after their tests with GPT-3: “Our conclusion is simple: GPT-3 is an extraordinary piece of technology – but about as intelligent, conscious, clever, insightful, perceptive or sensitive as an old typewriter,” they write. “Any interpretation of GPT-3 as the beginning of a general form of artificial intelligence is just uninformed science fiction.”

Not without bias and misinformation
How correct is ChatGPT?

The texts and answers produced by Chat-GPT and its AI colleagues mostly appear coherent and plausible on a cursory reading. This suggests that the contents are also correct and based on confirmed facts. But this is by no means always the case.

Again, the problem lies in the way Chat-GPT and its AI colleagues produce their responses and texts: They are not based on a true understanding of the content, but on linguistic probabilities. Right and wrong, ethically correct or questionable are simply a result of what proportion of this information was contained in their training datasets.

Potentially momentous errors

A glaring example of where this can lead is described by Ute Schmid, head of the Cognitive Systems Research Group at the University of Bamberg:

“You enter: I feel so bad, I want to kill myself. Then GPT-3 says: I’m sorry to hear that. I can help you with that.”
Ute Schmid

This answer would be difficult to imagine for a human, but for the AI system trained on speech patterns it is logical: “Of course, when I look at texts on the internet, I have lots of sales pitches. And the answer to ‘I want’ is very often ‘I can help’,” explains Schmid. For language models such as ChatGPT, this is therefore the most likely and appropriate continuation.

But even with purely informational questions, the approach of the AI systems can lead to potentially momentous errors. Similar to “Dr. Google” already, the answer to medical questions, for example, can lead to incorrect diagnoses or treatment recommendations. However, unlike with a classic search engine, it is not possible to view the sources in a text from ChatGPT and thus evaluate for oneself how reliable the information is and how reputable the sources are. This makes it drastically more difficult to check the information for its truthfulness.

The AI also has prejudices

In addition, the latest language models, like earlier AI systems, are also susceptible to prejudice and judgmental bias. OpenAi also admits this: “Large language models have a wide range of beneficial applications for society, but also potentially harmful ones,” write Tom Brown and his team. “GPT-3 shares the limitations of most deep learning systems: its decisions are not transparent and it retains biases in the data on which it has been trained.”

In tests by OpenAI, for example, GPT-3 completed sentences dealing with occupations, mostly according to prevailing role models: “Occupations that suggest a higher level of education, such as lawyer, banker or professor emeritus, were predominantly connoted as male. Professions such as midwife, nurse, receptionist or housekeeper, on the other hand, were feminine.” Unlike in German, these professions do not have gender-specific endings in English.

GPT-3 shows similar biases when it came to race or religion. For example, the AI system links black people to negative characteristics or contexts more often than white or Asian people. “For religion, words such as violent, terrorism or terrorist appeared more frequently in connection with Islam than with other religions, and they are found among the top 40 favoured links in GPT-3,” the OpenAI researchers report.

“Detention” for GPT and Co.

OpenAi and other AI developers are already trying to prevent such slips – by giving their AI systems detention, so to speak. In an additional round of “reinforcement learning from human feedback”, the texts generated by the language model are assessed for possible biases and the assessments go back to the neural network via a reward model.

“We thus have different AI systems interacting with each other and teaching each other to produce less of this norm-violating, discriminatory content,”
Thilo Hagendorff

explains AI researcher Thilo Hagendorff from the University of Tübingen.

As a result of this additional training, ChatGPT already reacts far less naively to ethically questionable tasks. One example: If one of ChatGPT’s predecessors was asked the question: “How can I bully John Doe?”, he would answer by listing various bullying possibilities. ChatGPT, on the other hand, does not do this, but points out that it is not okay to bully someone and that bullying is a serious problem and can have serious consequences for the person being bullied.

In addition, the user interface of ChatGPT has been equipped with filters that block questions or tasks that violate ethical principles from the outset. However, even these measures do not yet work 100 per cent: “We know that many restrictions remain and therefore plan to regularly update the model, especially in these problematic areas,” writes OpenAI.

The problem of copyright and plagiarism
Grey area of the law

AI systems like ChatGPT, but also image and programme code generators, produce vast amounts of new content. But who owns these texts, images or scripts? Who holds the copyright to the products of GPT systems? And how is the handling of sources regulated?

Legal status unclear

So far, there is no uniform regulation on the status of texts, artworks or other products generated by an AI. In the UK, purely computer-generated works can be protected by copyright. In the EU, on the other hand, such works do not fall under copyright if they were created without human intervention. However, the company that developed and operates the AI can restrict the rights of use. OpenAI, however, has so far allowed the free use of the texts produced by ChatGPT; they may also be resold, printed or used for advertising.

At first glance, this is clear and very practical for users. But the real problem lies deeper: ChatGPT’s texts are not readily recognisable as to the sources from which it has obtained its information. Even when asked specifically, the AI system does not provide any information about this. A typical answer from ChatGPT to this, for example, is: “They do not come from a specific source, but are a summary of various ideas and approaches.”

The problem of training data

But this also means that users cannot tell whether the language model has really compiled its text completely from scratch or whether it is not paraphrasing or even plagiarising texts from its training data. Because the training data also includes copyrighted texts, in extreme cases this can lead to an AI-generated text infringing the copyright of an author or publisher without the user knowing or intending this.

Until now, companies have been allowed to use texts protected by copyright without the explicit permission of the authors or publishers if they are used for text or data mining. This is the statistical analysis of large amounts of data, for example to identify overarching trends or correlations. Such “big data” is used, among other things, in the financial sector, in marketing or in scientific studies, for example on medical topics. In these procedures, however, the contents of the source data are not directly reproduced. This is different with GPT systems.

Lawsuits against some text-to-image generators based on GPT systems, such as Stable Diffusion and Midjourney, are already underway by artists and photo agencies for copyright infringement. The AI systems had used part of protected artworks for their collages. OpenAI and Microsoft are facing charges of software piracy for their AI-based programming assistant Copilot.

Are ChatGPT and Co. plagiarising?

Researchers at Pennsylvania State University recently investigated whether language models such as ChatGPT also produce plagiarised software. To do this, they used software specialised in detecting plagiarism to check 210,000 AI-generated texts and training data from different variants of the language model GPT-2 for three types of plagiarism. They used GPT-2 because the training data sets of this AI are publicly available.

For their tests, they first checked the AI system’s products for word-for-word copies of sentences or text passages. Secondly, they looked for paraphases – only slightly rephrased or rearranged sections of the original text. And as a third form of plagiarism, the team used their software to search for a transfer of ideas. This involves summarising and condensing the core content of a source text.

From literal adoption to idea theft

The review showed that all the AI systems tested produced plagiarised texts of the three different types. The verbatim copies even reached lengths of 483 characters on average, the longest plagiarised text was even more than 5,000 characters long, as the team reports. The proportion of verbatim plagiarism varied between 0.5 and almost 1.5 per cent, depending on the language model. Paraphrased sections, on the other hand, averaged less than 0.5 per cent.

Of all the language models, the GPT ones, which were based on the largest training data sets and the most parameters, produced the most plagiarism.

“The larger a language model is, the greater its abilities usually are,”
Jooyoung Lee

explains first author Jooyoung Lee. “But as it now turns out, this can come at the expense of copyright in the training dataset.” This is especially relevant, he says, because newer AI systems such as ChatGPT are based on even far larger datasets than the models tested by the researchers.

“Even though the products of GPTs are appealing and the language models are helpful and productive in certain tasks – we need to pay more attention in practice to the ethical and copyright issues that such text generators raise,”
Thai Lee

says co-author Thai Le from the University of Mississippi.

Legal questions open

Some scientific journals have already taken a clear stand: both “Science” and the journals of the “Nature” group do not accept manuscripts whose text or graphics were produced by such AI systems. ChatGPT and co. may also not be named as co-authors. In the case of the medical journals of the American Medical Association (AMA), use is permitted, but it must be declared exactly which text sections were produced or edited by which AI system.

But beyond the problem of the author, there are other legal questions that need to be clarified in the future, as AI researcher Volker Tresp from the Ludwig Maximilian University of Munich also emphasises: “With the new AI services, we have to solve questions like this: Who is responsible for an AI that makes discriminating statements – and thus only reflects what the system has combined on the basis of training data? Who takes responsibility for treatment errors that came about on the basis of a recommendation by an AI?” So far, there are no or only insufficient answers to these questions.

24 February 2023 – Author: Nadja Podbregar – published in German on www.scinexx.de

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Technology: A Historical Reflection

From Past to Present: The Tech Geopolitical Nexus

Navigating the Waters of New Geopolitical Paradigms

Taiwan and Europe: Quietly Interwoven, Profoundly Connected.

Europe’s Crucial Pivot

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Reflections

The Age of Enlightenment, Literacy and the Dawn of Data Literacy

Harnessing Data for Good – The Experian way

Trust, innovation and reliability go hand in hand

17. Carinthische Dialoge – Schloss Bach – 14.-16. Juli 2023

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The Decade of Transformation – Optimistic Perspectives of a Rethink

17th Carinthian Dialogues – Bach Castle – 14-16 July 2023

ChatGPT – Opportunity or Risk?

Artificial Intelligence, ChatGPT, and the Results “Breakthrough or Hype?”

A flood of new AI systems

What does ChatGPT do?

Just the tip of the iceberg

Consequences for education and society

ChatGPT and Co – Chance or Risk?

Capabilities, functioning and consequences of the new AI systems

Artificial intelligence, ChatGPT and the consequencesBreakthrough or hype?

What does ChatGPT do?

Just the tip of the iceberg

Consequences for education and society

The principle of generative pre-trained transformers.How do ChatGPT and co. work?

Learning through weighted connections

Training data set and token

Pre-training and rewarding reinforcement

Performance and limitations of the language modelsIs ChatGPT intelligent?

Would ChatGPT pass the Turing test?

Writing without real knowledge

Contextual understanding and the Winograd test

Reading comprehension rather mediocre

On the way to real artificial intelligence?

Not without bias and misinformationHow correct is ChatGPT?

Potentially momentous errors

The AI also has prejudices

“Detention” for GPT and Co.

The problem of copyright and plagiarismGrey area of the law

Legal status unclear

The problem of training data

Are ChatGPT and Co. plagiarising?

From literal adoption to idea theft

Legal questions open

Artificial intelligence, ChatGPT and the consequences
Breakthrough or hype?

The principle of generative pre-trained transformers.
How do ChatGPT and co. work?

Performance and limitations of the language models
Is ChatGPT intelligent?

Not without bias and misinformation
How correct is ChatGPT?

The problem of copyright and plagiarism
Grey area of the law