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The Knowledge Aware process can match people to the learning opportunity. It’s a similar machine AI process that the learning opportunity is identified. When you have units of knowledge published, knowledge is being reused, and context is being captured, this allows learning opportunities to identified through machine learning. It identifies issues and who were involved, to locate candidates on who should be involved.
To learn more about this, watch the “Creating a Learning Organization through AI” webinar at https://www.youtube.com/watch?v=AhijsXQfujs&feature=youtu.be
When we refer to “a unit of knowledge,” we are talking about a Knowledge Packet. Knowledge Packets are a way to capture knowledge in a durable format that produces active, uniformed, granular, and structured in a way that allows knowledge to be provisioned. A Knowledge Packet is like the turn instruction in your navigation app, it gives you that next bit of information you need to get the job done. The unit of knowledge is the way the Knowledge Aware process allows knowledge to be provisioned.
To learn more about this, watch the “Creating a Learning Organization through AI” webinar at https://www.youtube.com/watch?v=AhijsXQfujs&feature=youtu.be
Closed-Loop Learning is not a thing of a future. It’s happening today, however, it’s not yet mundane. There are use cases in production that have proven the value. Of course, opportunities are still at hand for improvement.
To learn more about this, watch the “Creating a Learning Organization through AI” webinar at https://www.youtube.com/watch?v=AhijsXQfujs&feature=youtu.beWe started out with the top-down approach but then quickly found out that the bottom-up organic approach was more effective, especially when you focus on the technical area. We built them organically and then make them formal. We work on knowledge and people as being two important pieces. In both cases, we want to mature and grow both people and knowledge because they’re interdependent of each other.
A Knowledge Community is often referred to as a Community of Practice, which tends to be individuals that are passionate about how you do work. An example would be that I am challenged on a technical community where we can evaluate the knowledge in a feedback cycle. The difference is when we get a red and green state that is very high, we want to filter those to the top, but we need a body of people that can evaluate that knowledge and then be able to assess whether or not action needs to be taken. We want to make sure that the knowledge is healthy so when it gets back in the stream in the next iteration it can be reused for the next consumers.
Traditionally, I would ask how would do you do that today? Within our organization we have design reviews, where a group of people come in together to assess what they think of, from a knowledge perspective, of the red and green states of what they expect and vs what they don’t expect. I would say even informally this probably happens in the small teams before they get to the design review. The issue on both cases is that they’re not available to everyone when decisions are made. The Knowledge Aware technique we’ll be able to quickly address how the knowledge is addressed or how it would address the problem state. It allows everyone to be visible.
The virtuous cycle of Knowledge Knowledge Aware doesn’t really have one starting point. Think of it of having a critical mass. So, there are elements of the cycle… when you have success, you will contribute, then your contribution is available for others and others make use of it and find success. There isn’t one spot where it should start, but to get the cycle going, there needs to be some effort applied to get it started. Then there becomes a point where you can take the foot off the gas and it continues to cycle on its own.
The cost of the Model-Centric approach is changing, so it’s a moving target. Modeling as science becomes cheaper and it’s becoming more available, but there are still many failure modes. The Knowledge Aware approach abstracts the knowledge, readies it for reuse and provision it into the model in real time. It’s hard to say where it makes sense for an energy standpoint, but the target is dropping.
