Agentic AI—So hot right now!

We are in the earliest stages of Agentic AI, and, much like the early days of RPA and GenAI, there's a lot of excitement but also a lot of uncertainty. While the potential benefits are enormous— streamlined operations, lower costs, fewer human errors—there are equally important concerns about job displacement, bias in AI decision making, and a lack of transparency in how these systems operate.

Trees, chains, and brains

Today's AI has many different flavors and architectures, along with massive amounts of memory and processing capacity. We could probably make better use of this computational power by looking at how we can improve the quality of our queries and, as a result, make better quality decisions.

Links conquer the universe

We can talk about these relationships as links. They're not expressed in blue underlined text, and you can't click on them. But they are the relationships among words that matter in any particular circumstance. They are the relationships that give words meaning. And as in life, those meanings are multiple and contextual. Without those relationships, there is no language.

On Chat AI and BS

So, I'm sticking with hallucinations for all of chat AI's statements, true or false. But that leaves us with a question: Why isn't there a word that perfectly expresses this situation? The answer is easy: LLMs are doing something genuinely new in our history. Our lack of a perfectly apt verb proves it.

Inefficient at the speed of light

While process mining started years ago as a mainly data-driven exercise, its stated goal is to be knowledge-driven. Given KM's multidisciplinary scope, we can play a major role in achieving that goal. Any process, no matter how simple, has the potential to reach across an entire business ecosystem, including all stakeholders. This seems like a perfect match for collaborative workflow, AI/ML, knowledge graphs, human sensemaking, and many of the other arrows in our KM quiver.

The rise and potential fall of the citizen developer

The citizen developer movement was heralded as a revolution. Like most revolutions, things have sometimes gone differently than planned. The logic is sound, empowering those who know the business best to build the tools and systems needed to do their job. Ah, if only things were that simple …

The end of tech glory days

The tech industry's glory days may be fading a little, but this is not a time for despair. It's an opportunity for renewal. By shifting to a needs-driven approach, the industry can ensure its relevance in a rapidly changing landscape.

What is Bharat and why should you care?

Knowledge should always be considered as accretive, not something that's "here today, gone tomorrow."

When AI’s eyes are smiling

As of now, GenAI doesn't learn from the knowledge it creates any more than a paint-mixing machine learns more about colors every time it's used.

Will AGI be intelligent?

AGI's holistic approach not only could enhance the accuracy and reliability of its decisions, but it would also mirror the interconnectedness of the real world.

Pushing the boundaries of knowledge curation

Knowledge democratization occurs in two directions, seemingly engaged in an endless tug of war: acquisition and dissemination.

The third place of knowledge management

The third place I alluded to goes far beyond mechanistic KM or curated knowledge and takes us into the actual world of tacit knowledge. Here, knowledge comes from and often remains as personal experience, impressions, and intuition; it's undocumented and often hidden and elusive.

Should we go back to paper-based KM?

The sheer volume of largely useless data we have accumulated across the years severely limits the ability of AI to work well, and it comes at a heavy environmental and financial cost.

The flip side of generative AI: Extractive AI

Extractive AI takes a more comprehensive and transparent approach to machine intelligence.

Was the web good for knowledge management?

So, yes, the web enables everyone with an internet connection and the freedom to use it to contribute to our new, global, contentious, and contradictory knowledge space. But I did not foresee the dark side because of an optimism born of privilege.

The five ages of data

Perhaps this latest phase in the history of data will bring us to accept inexplicable complexity as a property of the world. We could view this as pure chaos, but thanks to having lived through the past four ages in rapid succession, we might instead recognize that chaos as being rich with endless mysteries we will never uncover completely.

8 billion and counting

The message is clear: No single person or committee or group can weave the best paths through the infinite maze of possible event chains. Only humans and machines working together, side by side, can produce a better result than would ever be possible from either one alone.

The trust problem with GenAI

2023 has been the year of ultra-hyping GenAI, and who is paying for this deluge of marketing? Technology vendors that want us to buy it. Again, it's impressive stuff, but when we shift from selling to buying and ultimately using it, many tough questions need to be asked.

When is good enough enough?

Our goal should be to improve the quality of knowledge assets and their accuracy and relevance in use. Much of this will come from human expertise and effort, increasingly combined with the power of AI.

The fun side of future tech

Everything about the future doesn't have to be so frightening or serious. Instead, let's take a break from all of that and look at the fun side of what lies ahead.