This visitor submit is by Sunil Soares, founder and CEO of YDC – AI Governance. Beforehand, he based and led Info Asset, an information administration agency. Sunil brings a deeply-researched perspective to AI governance—authoring 13 books which have formed how enterprises strategy knowledge and AI at scale.
The YDC group developed an AI Governance prototype in Atlan. We reused the prevailing working mannequin with belongings and added customized attributes and relations.
AI Use Circumstances
As mentioned in an earlier weblog, a digital twin could also be a digital reproduction of a selected affected person that displays the distinctive genetic make-up of the affected person or a simulated three-dimensional mannequin that displays the traits of a affected person’s coronary heart. Digital twins could also be utilized to speed up scientific trials and cut back prices within the life sciences business. The YDC group applied an summary of the Digital Twins for Scientific Trials AI Use Case in Atlan.
AI Threat Assessments
We carried out an AI Threat Evaluation for the use case with Atlan. Digital twins have the potential to introduce bias dangers primarily based on the algorithms and the underlying knowledge units. We documented the bias danger evaluation and a mapping to the related rules in Atlan.
We additionally documented the privateness dangers in Atlan.
We documented different dimensions of AI danger together with Reliability, Accountability, Explainability and Safety in Atlan. For the sake of brevity, I’ve not included these screenshots right here.
This use case would seemingly be categorised as Excessive Threat primarily based on the Medical Machine class of Article 6 of the EU AI Act.
AI Threat Evaluation Workflows
We configured an AI Threat Evaluation workflow in Atlan to route the AI Threat Evaluation to the suitable events for approval.
The screenshot under exhibits the AI Threat Evaluation in Authorised standing primarily based on approvals from the Operational Threat Administration Committee (ORMC) and the AI Governance Council.
Shadow AI Governance to Ingest Metadata from ServiceNow CMDB and YDC_AIGOV Brokers on Hugging Face to Spotlight COTS Apps with Embedded AI
In an earlier weblog, I mentioned Shadow AI Governance and the YDC_AIGOV brokers. As half of the present train, we ingested metadata across the Industrial-off-the-Shelf (COTS) apps into Atlan. This info consists of metadata equivalent to Software Identify, Privateness Coverage URL, Information Particularly Excluded from AI Coaching, Embedded AI and Decide-Out Possibility.
The screenshot under exhibits Atlan earlier than working the mixing with the YDC_AIGOV brokers. The catalog solely accommodates one AI Use Case (Digital Twins for Scientific trials) and one software (Google Product Companies).
After working the mixing with Atlan API, Atlan accommodates a broader checklist of purposes together with Actimize Xceed together with metadata in the fitting panel.
Conditional Logic with Atlan API to Auto-Create AI Use Case and AI Threat Evaluation Objects
We applied conditional logic within the Atlan API to auto-create AI use circumstances just for purposes with embedded AI. On this case, we created an AI use case object in Atlan for Actimize Xceed as a result of Embedded AI = “Sure.”
We additionally applied conditional logic within the Atlan API to auto-create AI Threat Evaluation objects the place Information Particularly Excluded for AI Coaching = “No.” Clearly, this logic is configurable.
It is a fundamental AI Governance configuration in Atlan with extra to come back!
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