This visitor put up is by Sunil Soares, founder and CEO of YDC – AI Governance. Beforehand, he based and led Info Asset, a knowledge administration agency. Sunil brings a deeply-researched perspective to AI governance—authoring 13 books which have formed how enterprises method knowledge and AI at scale.
The YDC staff 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 duplicate 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 trade. The YDC staff applied an summary of the Digital Twins for Medical 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 based mostly on the algorithms and the underlying knowledge units. We documented the bias danger evaluation and a mapping to the related laws 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 labeled as Excessive Threat based mostly on the Medical Gadget 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 based mostly 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 consists of metadata akin to Software Title, Privateness Coverage URL, Knowledge Particularly Excluded from AI Coaching, Embedded AI and Decide-Out Choice.
The screenshot under exhibits Atlan earlier than operating the combination with the YDC_AIGOV brokers. The catalog solely accommodates one AI Use Case (Digital Twins for Medical trials) and one utility (Google Product Companies).
After operating the combination with Atlan API, Atlan accommodates a broader checklist of purposes together with Actimize Xceed together with metadata in the proper 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 instances 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 Knowledge Particularly Excluded for AI Coaching = “No.” Clearly, this logic is configurable.
This can be a primary AI Governance configuration in Atlan with extra to return!
This put up was initially printed on Your Knowledge Join. Learn the unique article right here.