Stepping Higher - Reflections on the Knowledge Age

In knowledge management (KM), explicit knowledge – what’s written in documents and stored in files or other forms of media – has often had a bad reputation, and for good reason. Over years, KM has wrongly focused on documents and was busy building databases and repositories, when – as David Snowden put it – it shouldhave been focusing on connecting people instead . This preference is understandable. After all, explicit knowledge is just the tip of the iconic knowledge iceberg. Below the surface lies implicit knowledge, thoughts in people’s heads, rich with context and application insights, and accessible only through relationships and trust. However, I believe what we have been experiencing in 2023 with Generative AI marks a significant shift that could see explicit knowledge get its long-awaited moment in the sun. The Limitations of Content-focused KM and the Rise of AI Traditionally, KM never succeeded to fully leverage the knowledge that’s supposedly „stored“ in all the document

Bias is a problem in the use of AI. What most people don't know, however, is that you can use ChatGPT specifically to expose bias in AI outputs (as well as in our human-written texts). In this article, I'll show you how! All people have biases. AI is trained on human-generated texts from the web. This means AI also inherits the biases of an internet dominated by content from Western, white, and English-speaking people. Just as we have to deal with the unquestioned assumptions and prejudices of our fellow humans (and ourselves!), we must also do so with AI. Even more so, because AI, by default (i.e., without specifically asking for possible biases), actually amplifies existing biases in the training data .  So, what can we as users do? We need to question every text, and every assumption, no matter who wrote it or who made it. And this is where AI can help us again. Because just as it amplifies existing advantages in training data without special instructions, AI can also be cal

Contrary to dystopian narratives, artificial intelligence (AI) isn't here to take our jobs. Rather, it is turning us all into managers. And your success in the AI age depends on whether you are willing to step into that new role. The current AI discourse paints a bleak picture of mass unemployment and identity crises, as AI surpasses our abilities as humans. I disagree. Historically, technological transformations have always yielded a net gain in jobs, albeit amidst disruptive periods and the extinction of certain professions. I don’t see a reason why AI should deviate from this trend, even when accounting for its unprecedented pace of change. Far from making you less useful or worthy, AI is not replacing you or diminishing the value you bring to the table. On the contrary, AI, like any other technology before, gives you powers you didn't have before. It enhances your existing skills and allows you to do the things you already do – but faster, with higher quality and with bigge

      (Illustrative Image generated with Midjourney) On May 3, 2023, I had the pleasure to talk to the World Bank Group's Community of Practice on Knowledge Management about the opportunities that ChatGPT and similar tools present to the KM space. The group was exceptionally astute and came up with a number of very important questions that I believe are critical to reflect on. In the following, I am showcasing a few of them, along with my own thoughts that I articulated in the exchange: Question 1: I am interested to know if systems like ChatGPT can generate valuable new knowledge, i.e. combine lessons from a few past projects and suggest how should we approach the upcoming project? Generative models like GPT-4 will always build on existing bodies of knowledge, and therefore are (at the moment at least) better suited for a look into the past than as a tool for foresight or predictive analysis. However, as you suggest, we can ask it to combine information, theories, frameworks and m