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.

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.

The effect of ChatGPT on KM

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

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.

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.

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.

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.

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.

AI’s ways of being immoral

The most powerful ML can require the resources of wealthy organizations. Such organizations usually have at best mixed motivations, to be charitable about it.

Dispatches from the edge

Edge-of-chaos decisioning means being continually informed on the critical elements needed to make better, faster decisions.

Finding the weakest link

Though traditional and often reluctant to change, the supply chain sector is now reassessing its lack of embrace of technology and, significantly, rethinking long-established processes.

The Law and AI

AI is very good, and light years ahead of where it was just a decade ago, but it is far from "intelligent." Indeed, it is only as good as the data it is provided and needs close human supervision.

Getting to the future of KM

AI can and does do a good job of assisting and even augmenting knowledge work, but our "to be" state should not take the human element—however flawed—from the work.

From robots to digital workers

As more firms use the term "digital workers" in place of bots, a spotlight is being shone on the role, importance, and increasing controversy surrounding enterprise automation.

The way of the scenario

The Delphi technique has become less effective in recent years, especially in crisis situations in which conditions, assumptions, and other variables are changing faster than the group is able to respond.