KM-AI: Managing business risks
1 August 2021
Dr. Moria Levy
Aug 3rd. Session 19 of our KMGN Knowledge-Management-Artificial-Intelligence course. Art Murray speaks about implementing and maintaining AI and human knowledge. Governance is crucial.
I want to focus on the post on the topic of RISKS in the context of knowledge management and Artificial Intelligence projects.
There are several ways that we, knowledge managers, can assist in mitigating the AI risks.
We can simplify the existing business rules network in the organization, thus simplifying processes, data, decision-making, and of course, business risks. Knowledge engineering will also benefit, and the chance for better knowledge learned by the AI machine will increase.
We can add, in the training stage of the AI project, additional subject matter experts. At first glance, this may seem like over investment and maybe more confusion, but the contrary is true. Adding SMEs will help the machine training processes, as our biases may turn us sometimes blind. Diversion of thoughts and understandings of experts is a good way to mitigate the risk.
But my best takeaway here is that help is mutual. KM can help AI, but AI can also help KM. Applying data and text analytics (AI), based on internal and external sources, can help us be aware of week signals and monitor the potential risks.
So who said life isn't fun sometimes?
picture credit- Tobias Tullius
This post was initially published in LinkedIn