AI & Society: AI’s impact on society discussed in Decisively Digital: From Creating a Culture to Designing Strategy. John Wiley & Sons. (photo by Gerhard Müller)
Three years ago, while drafting my book Decisively Digital (Amazon), I believed that the peak popularity of artificial intelligence (AI) was nearing its zenith. Little did I realize then how profoundly and rapidly the landscape of AI would transform, much like the unexpected and remarkable discovery of the Higgs boson in particle physics. The current surge in AI interest, fueled by innovations like ChatGPT and Copilot, has catapulted AI into a realm of unprecedented growth and societal impact.
AI’s Journey: From Concept to Ubiquity
The journey of AI from a niche concept in the labs of computer scientists to a ubiquitous force in society mirrors the trajectory of many revolutionary technologies. In its infancy, AI was a subject of academic curiosity, often confined to theoretical discussions and small-scale applications.
However, as technology advanced, we witnessed the birth of practical AI applications. From rudimentary chatbots to sophisticated machine learning algorithms, AI began to find its footing in the real world. These applications, although impressive, were just the tip of the iceberg.
Today, AI is not just a tool but a companion in our digital journey. Platforms like ChatGPT have democratized AI, making it accessible to everyone. They’ve turned AI from a mere concept into a daily utility, reshaping how we interact with technology and each other.
AI’s Impact on Society
AI is redefining job roles and industries. It’s automating mundane tasks, enhancing productivity, and even creating new career paths. While there are concerns about AI displacing jobs, it’s also undeniable that AI is creating opportunities for more creative and strategic roles.
As AI becomes more ingrained in our lives, ethical and societal considerations come to the forefront. Issues like privacy, bias in AI algorithms, and the digital divide need urgent attention to ensure that AI benefits society as a whole.
From personalized recommendations on streaming services to AI-assisted medical diagnostics, AI’s presence in our daily lives is growing. It’s not just a corporate or academic tool; it’s becoming a personal assistant, a healthcare advisor, and much more.
The Future of AI and Society
The future of AI is not just about technological advancements but also about how we, as a society, adapt to these changes. It’s about ensuring that AI grows in a way that is ethical, equitable, and beneficial to all.
As AI continues to evolve, it’s essential for individuals and organizations to stay informed and adapt to these changes. Embracing AI doesn’t mean blind adoption; it means understanding its capabilities and limitations and using it to enhance our lives and work.
AI is a catalyst for innovation, driving advancements in various fields. Its potential to solve complex problems and create new opportunities is immense. We are just scratching the surface of what AI can achieve.
Conclusion
The growth of AI, much like the discovery of the Higgs boson, is a breakthrough moment in our history. It’s a testament to human ingenuity and a reminder of the rapid pace of technological change. As we stand at this crossroads, it’s crucial to ponder how AI will shape our society and how we, in turn, will shape AI. The journey of AI is not just about technological development; it’s about the evolution of our society as a whole.
Explore more about the interplay of AI and society in my book Decisively Digital.
Künstliche Intelligenz im Controlling Beispiele: KI-generierte Zwillingstürme in Frankfurt am Main.
Die rasante Entwicklung der Künstlichen Intelligenz (KI) verändert viele Unternehmsbereiche, darunter auch das Controlling. Diese Entwicklung hin zu intelligenteren Systemen und Prozessen verändert die Art und Weise, wie Unternehmen ihre Daten analysieren und nutzen. KI wird damit zu einem unverzichtbaren Werkzeug für eine fortschrittliche und effiziente Unternehmenssteuerung.
In diesem Blogbeitrag widmen wir uns der tiefgreifenden Bedeutung von KI im Controlling. Wir beleuchten, wie Künstliche Intelligenz nicht nur die Effizienz steigert, sondern auch präzisere und fundiertere Entscheidungen ermöglicht. Anhand von Praxisbeispielen und Use Cases zeigen wir, wie KI-Technologien Controller in ihrer täglichen Arbeit maßgeblich unterstützen und so einen echten Mehrwert schaffen.
Relevanz von KI im Controlling
Die Integration von KI in das Controlling ist heute wichtiger denn je. KI-Technologien bieten wertvolle Unterstützung bei Datenanalyse, Reporting und Entscheidungsfindung. Sie ermöglichen nicht nur die schnelle und effiziente Auswertung riesiger Datenmengen, sondern auch die Automatisierung von Reportingprozessen und die Erstellung präziser Prognosen durch den Einsatz von Predictive Analytics. Damit können Controller ihre Arbeitsprozesse optimieren, Risiken genauer einschätzen und fundierte strategische Entscheidungen treffen.
Anwendungsfälle und Beispiele
Die Anwendungsmöglichkeiten von KI im Controlling sind breit gefächert und vielseitig. Im Folgenden stellen wir diverse Praxisbeispiele und konkrete Anwendungsfälle vor, die das enorme Potenzial von KI-Technologien in diesem Bereich verdeutlichen:
Datenanalyse im Controlling: Künstliche Intelligenz als Schlüsselwerkzeug
Die Datenanalyse spielt im Controlling eine zentrale Rolle, um tiefe Einblicke in Geschäftsprozesse zu gewinnen und zukunftsweisende Entscheidungen zu treffen. Durch die Integration von Künstlicher Intelligenz (KI) eröffnen sich neue Dimensionen in der Analyse komplexer Datensätze. Ein prägnantes Beispiel hierfür ist die Unterstützung bei der Auswertung von Zinsstrukturkurven, wodurch wesentliche Erkenntnisse und Trends sichtbar gemacht werden können.
Für eine umfassende Analyse verwenden wir in diesem Beispiel ChatGPT mit dem erweiterten GPT-4-Modell und der spezialisierten Funktion „Advanced Data Analysis„. Diese Kombination ermöglicht eine tiefgehende und präzise Analyse der Finanzdaten.
Analysiere den Datensatz zur Zinsstrukturkurve und nenne mir die wesentlichen Erkenntnisse und Trends.
ChatGPTs hochentwickelte Algorithmen durchsuchen den Datensatz, identifizieren Muster und liefern präzise Erkenntnisse:
Ergebnis der ChatGPT-Analyse der Zinsstrukturkurve der Europäischen Zentralbank. Die dargestellten Erkenntnisse und Trends bieten Controllern wertvolle Ansatzpunkte für strategische Entscheidungen und Risikobewertungen.
Dokumentenanalyse im Controlling: Effizienzsteigerung durch Künstliche Intelligenz
Die fortschreitende Digitalisierung ermöglicht im Controlling den Einsatz von Künstlicher Intelligenz (KI), um Dokumente schneller und präziser zu analysieren. Insbesondere bei umfangreichen Geschäftsberichten kann KI helfen, die wesentlichen Informationen herauszufiltern und so dem Controller wertvolle Zeit zu sparen.
In diesem Abschnitt stellen wir eine praktische Anwendung von ChatGPT mit dem erweiterten GPT-4-Modell vor, das mit der spezialisierten Option „Advanced Data Analysis“ ausgestattet ist. Diese Kombination ermöglicht es uns, komplexe Dokumente wie Jahresberichte effektiv zu analysieren und zusammenzufassen.
Als Beispiel dient uns der Jahresbericht von UNICEF Deutschland für das Jahr 2022. Zu Demonstrationszwecken laden wir eine PDF-Datei des Berichts in eine neue ChatGPT-Session. Der Bericht ist unter folgendem Link zu finden: UNICEF Deutschland Geschäftsbericht 2022.
Mit folgendem Prompt leiten Sie die Analyse durch ChatGPT ein:
Fasse diesen Geschäftsbericht zusammen.
Die KI durchforstet den Bericht, extrahiert die wesentlichen Informationen und erstellt eine prägnante Zusammenfassung:
Frankfurter Buchmesse Podcast Folge: „Lesen wir noch? Ein Bericht von der Frankfurter Buchmesse“ – Literatur trifft Technologie in einer spannenden Diskussion, die ihr nicht verpassen solltet!
In unserer neuesten Folge von Die Digitalisierung und Wir sprechen wir über die spannende Schnittstelle zwischen Literatur und Technologie, direkt von der Frankfurter Buchmesse. Wir tauchen in die komplexen Fragen des Urheberrechts bei mit KI erstellten Texten ein, diskutieren den Einfluss von KI in der Bildung und hinterfragen, warum die Perspektive der Tech-Branche auf solchen Events oft zu kurz kommt. Bereit für eine Reise durch Bücher und Bytes? Dann hört unbedingt rein!
KI und Urheberrecht: Wer schreibt, der bleibt?
Jedes Jahr zieht die Frankfurter Buchmesse Literaturfans und Brancheninsider in ihren Bann. Eines der heißesten Themen auf der Buchmesse war die Frage nach dem Urheberrecht von Texten, die mit KI erstellt wurden. Erinnert ihr euch an unsere Serie über KI und Ethik? Genau da knüpfen wir an. Ist der Algorithmus der Autor oder der Mensch dahinter? In einer hitzigen Debatte wurde schnell klar: Es gibt mehr Fragen als Antworten.
ChatGPT in der Bildung: Revolution oder Hype?
Weiter ging es mit dem Einfluss von KI im Bildungsbereich. Dr. Peter Schell warnte davor, dass Tools wie ChatGPT zwar Informationen wiedergeben, aber nicht das Lernen ersetzen können. Prof.in Dr. Kirsten Schindler hingegen sieht großes Potenzial, vor allem bei Facharbeiten.
Die Tech-Lücke: Wo bleibt die digitale Perspektive?
Uns beiden ist aufgefallen, dass die Tech-Seite etwas zu kurz gekommen ist. KI wurde oft als Black Box dargestellt. Wir denken, dass Autoren, Verlage und Tech-Leute gemeinsam diskutieren sollten. Mit unserem Podcast wollen wir genau diese Lücke schließen. Wer unser Gespräch über die Rolle der KI in der Kunst verpasst hat, sollte unbedingt reinhören!
Das Digitale Manifest: Gestalte deine digitale Zukunft
Bei dieser Gelegenheit habe ich auch mein Digitales Manifest vorgestellt. Es ist ein Aufruf, unsere digitale Zukunft bewusst zu gestalten. Lest das Digitale Manifest hier und lasst uns die Diskussion über die Frankfurter Buchmesse hinaus weiterführen!
Buchempfehlungen: Das Echtzeitalter und Verity
Neben all der Technik dürfen wir die Literatur nicht vergessen. Echtzeitalter von Tonio Schachinger, Gewinner des Deutschen Buchpreises 2023, haben wir auch kurz im Podcast vorgestellt. Ein Must-Read!
Buchempfehlung Verity
Außerdem ist das Buch Verity von Colleen Hoover eine absolute Empfehlung für alle, die nach einer psychologisch komplexen und fesselnden Lektüre suchen. Hoover verlässt ihre gewohnten Pfade und präsentiert eine Story voller überraschender Wendungen, in der nichts ist, wie es scheint. Die einzigartige Mischung aus Spannung, Charaktertiefe und geschickt eingeflochtenen Plot-Twists macht dieses Buch zu einem unvergesslichen Erlebnis, das man nicht so leicht aus der Hand legen kann. Lest hier das komplette Review zu Verity auf Amazon.
Transparenzhinweis: Buch gratis auf der Frankfurter Buchmesse erhalten.
Das war’s von unserer Seite aus dem Literaturmekka Frankfurter Buchmesse. Interessiert? Dann hört unbedingt in die neue Episode rein und abonniert Die Digitalisierung und Wir. Wir freuen uns auf eure Gedanken und Fragen!
Jetzt seid ihr dran: Was denkt ihr über die Themen, die wir besprochen haben? Teilt eure Gedanken gerne auf Twitter und LinkedIn! 🎧👇
DALL-E 3 integrates with ChatGPT so you don’t have to write cryptic txt2img prompts anymore! (source: OpenAI)
Ever struggled with cryptic text prompts while trying to generate an image with AI? The latest iteration of OpenAI’s image generation model, DALL-E 3, is now natively integrated with ChatGPT for a more seamless and intuitive user experience. In this blog post, we will take a deep dive into the capabilities of DALL-E 3, its integration with ChatGPT, and why this is a game changer for anyone looking to translate text into highly accurate images.
What Sets DALL-E 3 Apart?
DALL-E 3 is not just another upgrade; it’s a leap forward in AI image generation. It understands far more nuance and detail than previous models. This means that the images generated are more closely aligned with the text prompt you provide. No more struggling with prompt engineering or settling for images that only vaguely resemble what you had in mind.
DALL-E 3 integrates with ChatGPT so you don’t have to write cryptic txt2img prompts anymore!
Multi-Modal Models: The Tech Behind the Magic
The secret sauce behind DALL-E 3’s advanced capabilities lies in its foundation as a multi-modal model. These models are trained to understand and generate both text and images, making them incredibly versatile. Multi-modal models like DALL-E 3 and ChatGPT are at the forefront of AI research, pushing the boundaries of what’s possible in natural language understanding and computer vision. For a deeper dive into the world of multi-modal models, check out my previous blog post The Rise of Generative AI.
DALL-E 3 Built Natively on ChatGPT
Built natively on ChatGPT, DALL-E 3 allows you to use ChatGPT as a brainstorming partner. Not sure what kind of image you want to create? Just ask ChatGPT and it will automatically generate customized, detailed prompts for DALL-E 3 that can bring your vague ideas to life. You can also ask ChatGPT to tweak an image with just a few words if it’s not quite what you were looking for.
Following the talk, I was inspired by a conversation to leverage the power of GPT-4 and create an automatically generated summary of the Microsoft Teams transcript. This approach not only streamlines information sharing but also showcases the practical applications of advanced AI technology.
Below, I will share the key insights generated by GPT-4 and also include some captivating images from the event:
Decisively Digital: AI’s Impact on Society
In my talk, I drew inspiration from my book Decisively Digital, which discusses the impact of AI on society. I shared about the innovative projects underway at Microsoft’s AI for Good Lab. In light of GPT-4’s recent launch, I also highlighted our mission to leverage technology to benefit humanity.
AI’s impact on society is discussed in Decisively Digital: From Creating a Culture to Designing Strategy. John Wiley & Sons. (photo by Gerhard Müller)
By harnessing Generative AI, we can stimulate the creation of innovative ideas and accelerate the pace of advancement. This cutting-edge technology is already transforming industries by streamlining drug development, expediting material design, and inspiring novel hypotheses. AI’s ability to identify patterns in vast datasets empowers humans to uncover insights that might have gone unnoticed.
Generative AI can Augment our Thinking
For instance, researchers have employed machine learning to predict chemical combinations with the potential to improve car batteries, ultimately identifying promising candidates for real-world testing. AI can efficiently sift through and analyze extensive information from diverse sources, filtering, grouping, and prioritizing relevant data. It can also generate knowledge graphs that reveal associations between seemingly unrelated data points, which can be invaluable for drug research, discovering novel therapies, and minimizing side effects.
„Now is the time to explore how Generative AI can augment our thinking and facilitate more meaningful interactions with others.“
Alexander Loth
At the AI for Good Lab, we are currently employing satellite imagery and generative AI models for damage assessment in Ukraine, with similar initiatives taking place in Turkey and Syria for earthquake relief. In the United States, our focus is on healthcare, specifically addressing discrepancies and imbalances through AI-driven analysis.
Our commitment to diversity and inclusion centers on fostering digital equality by expanding broadband access, facilitating high-speed internet availability, and promoting digital skills development. Additionally, we are dedicated to reducing carbon footprints and preserving biodiversity. For example, we collaborate with the NOAH organization to identify whales using AI technology and have developed an election propaganda index to expose the influence of fake news. Promising initial experiments using GPT-4 showcase its potential for fake news detection.
„We live in a rapidly changing world, facing big challenges.“ (photo by Gerhard Müller)
ChatGPT will be Empowered to Perform Real-time Website Crawling
While ChatGPT currently cannot crawl websites directly, it is built upon a training set of crawled data up to September 2021. In the near future, the integration of plugins will empower ChatGPT to perform real-time website crawling, enhancing its ability to deliver relevant, up-to-date information, and sophisticated mathematics. This same training set serves as the foundation for the GPT-4 model.
GPT-4 demonstrates remarkable reasoning capabilities, while Bing Chat offers valuable references for verifying news stories. AI encompasses various machine learning algorithms, including computer vision, statistical classifications, and even software that can generate source code. A notable example is the Codex model, a derivative of GPT-3, which excels at efficiently generating source code.
Microsoft has a long-standing interest in AI and is dedicated to making it accessible to a wider audience. The company’s partnership with OpenAI primarily focuses on the democratization of AI models, such as GPT and DALL-E. We have already integrated GPT-3 into Power BI and are actively developing integrations for Copilot across various products, such as Outlook, PowerPoint, Excel, Word, and Teams. Microsoft Graph is a versatile tool for accessing XML-based objects in documents and generating results using GPT algorithms.
Hardware, particularly GPUs, has played a pivotal role in the development of GPT-3. For those interested in experimenting with Generative AI on a very technical level, I recommend Stable Diffusion, which is developed by LMU Munich. GPT-3’s emergence created a buzz, quickly amassing a vast user base and surpassing the growth of services like Uber and TikTok. Sustainability remains a crucial concern, and Microsoft is striving to achieve a CO2-positive status.
Generative AI Models have garnered Criticism due to their Dual-use Nature
Despite its potential, Generative AI models such as GPT-3 have also garnered criticism due to their dual-use nature and potential negative societal repercussions. Some concerns include the possibility of automated hacking, photo manipulation and the spread of fake news (➡️ deepfake disussion on LinkedIn). To ensure responsible AI development, numerous efforts are being undertaken to minimize reported biases in the GPT models. By actively working on refining algorithms and incorporating feedback from users and experts, developers can mitigate potential risks and promote a more ethical and inclusive AI ecosystem.
Moving forward, it is essential to maintain open dialogue and collaboration between AI developers, researchers, policymakers, and users. This collaborative approach will enable us to strike a balance between harnessing the immense potential of AI technologies like GPT and ensuring the protection of society from unintended negative consequences.
Microsoft‘s responsible AI principles: fairness, reliability & safety, privacy & security, and inclusiveness, underpinned by transparency and accountability. (photo by Gerhard Müller)
GPT-3.5 closely mimics human cognition. However, GPT-4 transcends its forerunner with its remarkable reasoning capabilities and contextual understanding. GPT models leverage tokens to establish and maintain the context of the text, ensuring coherent and relevant output. The GPT-4-32K model boasts an impressive capacity to handle 32,000 tokens, allowing it to process extensive amounts of text efficiently. To preserve the context and ensure the continuity of the generated text, GPT-4 employs various strategies that adapt to different tasks and content types.
GPT-4 Features a Robust Foundation in Common Sense Reasoning
One of GPT-4’s defining features is its robust foundation in common sense reasoning. This attribute significantly contributes to its heightened intelligence, enabling the AI model to generate output that is not only coherent but also demonstrates a deep understanding of the subject matter. As GPT-4 continues to evolve and refine its capabilities, it promises to revolutionize the field of artificial intelligence, expanding the horizons of what AI models can achieve and paving the way for future breakthroughs in the realm of generative AI.
Results of the live Twitter survey: 47.8% predict the emergence of AGI is possible within the next 5 years (photo by Bernd Vellguth)
In the near future, advanced tools like ChatGPT will elucidate intricate relationships without requiring us to sift through countless websites and articles, further amplifying the transformative impact of Generative AI.
I appreciate the opportunity to share my insights at the German Chapter of the ACM.
Did you enjoy this GPT-generated Summary of my Talk?
Leveraging GPT-4 to generate a summary of my talk was an exciting experiment, and I have to admit, the results are impressive. GPT was able to provide a brief overview of the key takeaways from my talk.
Now, I would love to hear about your experiences with GPT. What are your experiences with GPT so far? Feel free to share your thoughts in the comments section of this Twitter thread or this LinkedIn post:
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