AI Use Cases
As discussed in an earlier blog, a digital twin may be a virtual replica of a particular patient that reflects the unique genetic makeup of the patient or a simulated three-dimensional model that exhibits the characteristics of a patient’s heart. Digital twins may be utilized to accelerate clinical trials and reduce costs in the life sciences industry. The YDC team implemented an overview of the Digital Twins for Clinical Trials AI Use Case in Atlan.

AI Risk Assessments
We conducted an AI Risk Assessment for the use case with Atlan. Digital twins have the potential to introduce bias risks based on the algorithms and the underlying data sets. We documented the bias risk assessment and a mapping to the associated regulations in Atlan.



AI Risk Assessment Workflows
We configured an AI Risk Assessment workflow in Atlan to route the AI Risk Assessment to the appropriate parties for approval.


Shadow AI Governance to Ingest Metadata from ServiceNow CMDB and YDC_AIGOV Agents on Hugging Face to Highlight COTS Apps with Embedded AI
In an earlier blog, I discussed Shadow AI Governance and the YDC_AIGOV agents. As part of the current exercise, we ingested metadata around the Commercial-off-the-Shelf (COTS) apps into Atlan. This information includes metadata such as Application Name, Privacy Policy URL, Data Specifically Excluded from AI Training, Embedded AI and Opt-Out Option.
The screenshot below shows Atlan before running the integration with the YDC_AIGOV agents. The catalog only contains one AI Use Case (Digital Twins for Clinical trials) and one application (Google Product Services).

Conditional Logic with Atlan API to Auto-Create AI Use Case and AI Risk Assessment Objects
We implemented conditional logic in the Atlan API to auto-create AI use cases only for applications with embedded AI. In this case, we created an AI use case object in Atlan for Actimize Xceed because Embedded AI = “Yes.”

