What are your chatbot’s pronouns?

We don't have pronouns by which we can address inanimate objects because we haven't had any occasions to have actual conversations with them.

Are you data-driven or knowledge-driven?

We no longer need to blindly accept the output of even the most sophisticated AI/ML platforms. In fact, we should not consider any artifact, whether produced by humans or machines, as valid knowledge unless it contains not only supporting data and analyses, including provenance, but also an explanation of the underlying plausibility.

Get your game on: KM skills needed for reliable use of LLMs

There is no questioning that generative AI is here to stay, but its use in mission-critical work has some way to go before it can be trusted and let loose.

The ChatGPT ways of knowledge

These two types of knowing—understanding the world and understanding knowledge—are, in some important ways, at odds in AI-based chatbots.

Extraordinary times demand extraordinary leadership

The emergence of hybrid work environments post-COVID has resulted in the accelerated introduction of technologies and methods that increasingly enable the adaptive, democratic enterprise.

The evolution of the KM technology stack

Historically, KM managers have tried to centralize knowledge assets into a single KM platform and curate within it. But outside of a few niche use cases, this has not been feasible for many years. Combining few KM human resources and an increasing data deluge makes it impractical. That is not to say we don't have the tools and resources to manage knowledge assets effectively; rather, we need to recognize corporate realities, be open to innovation, and embrace radical change.

Tags, AI, and dimensions

Tags have become so common that they've faded from consciousness since 2007, although sometimes a clever hashtag pops up.

Look to the skies for KM opportunities

Then there's the inevitable demand for more automation, from the flight planning and clearance process to the operation of the air vehicles themselves. No human or group of humans could possibly keep track of so many constantly changing variables

AI technologies upending traditional KM

If we are not careful and proactive about it, the concept and importance of knowledge itself may soon become blurred or lost.

AI’s new type of knowledge

This way of knowing works pragmatically for some very complex systems of the sort we find in the real world. But, oddly, itseems not to work so well in some artificially simple systems.

Return on … Infrastructure???

As our physical and IT infrastructure continues to grow in size, complexity, and vulnerability, people and the knowledge they possess will play an ever-increasing role.

The effect of ChatGPT on KM

At this peak of ChatGPT hype, we have to ask what value it may bring.

Introducing work intelligence systems

Technological advances are significant and can bring huge benefits, but only as long as you understand that they can advise, augment, and support, but not replace, you.

Knowledge as I remember it

The web transformed the role of knowledge by making it instantly available but not inherently reliable.

Three trends in ’23

The combined human and computing clouds will drive our core KM processes of search, collaboration, and discovery to new heights.

Getting more confused about regulating social media

Out of the mix of commercial greed, politics, and genuine desires to make the world better, we'll try many ways to "fix" social media. But I think it may take a couple of generations, affected by what we do, for us to begin to agree about what's right and wrong.

The undiscovered country

Capturing and sharing what you already know is good; and with today's data and text analytics tools, it has become much easier than when we'd first begun this journey.

The human capability to under-or overestimate

Yet maybe the most glaring example of underestimating humans we encounter in our work is in the world of AI. It's partly the term "intelligence" in AI that misleads so many, as AI is not intelligent in the same way that humans are intelligent. Though powerful, AI ultimately matches patterns it has learned, and even the smartest of AI systems is limited in how many patterns it can match and make sense of.

What ‘sentient’ AI teaches us

As Gary Marcus says, a large language model is just a "spreadsheet for words" that lets it act as a massive autocompletion system that knows how words go together but has not the foggiest idea how those words connect to the world.

The final frontier

Given the rapid expansion of satellite communication webs in support of IoT, the volume of data will continue to explode.