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 information and AI at scale.
The YDC group developed an AI Governance prototype in Atlan. We reused the present working mannequin with belongings and added customized attributes and relations.
AI Use Instances
As mentioned in an earlier weblog, a digital twin could also be a digital reproduction of a specific affected person that displays the distinctive genetic make-up of the affected person or a simulated three-dimensional mannequin that reveals the traits of a affected person’s coronary heart. Digital twins could also be utilized to speed up medical trials and cut back prices within the life sciences business. The YDC group carried out an outline of the Digital Twins for Scientific Trials AI Use Case in Atlan.
AI Threat Assessments
We performed 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 information 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 doubtless be categorized 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 beneath exhibits the AI Threat Evaluation in Accepted 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 data contains metadata resembling Software Title, Privateness Coverage URL, Knowledge Particularly Excluded from AI Coaching, Embedded AI and Choose-Out Choice.
The screenshot beneath exhibits Atlan earlier than operating the combination with the YDC_AIGOV brokers. The catalog solely comprises one AI Use Case (Digital Twins for Scientific trials) and one software (Google Product Companies).
After operating the combination with Atlan API, Atlan comprises a broader record of functions together with Actimize Xceed together with metadata in the best panel.
Conditional Logic with Atlan API to Auto-Create AI Use Case and AI Threat Evaluation Objects
We carried out conditional logic within the Atlan API to auto-create AI use circumstances just for functions 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 carried out conditional logic within the Atlan API to auto-create AI Threat Evaluation objects the place Knowledge Particularly Excluded for AI Coaching = “No.” Clearly, this logic is configurable.
This can be a fundamental AI Governance configuration in Atlan with extra to come back!
This submit was initially printed on Your Knowledge Join. Learn the unique article right here.
