Comprehensive AI governance
The widespread enterprise adoption of conventional AI and GenAI require risk mitigation and governance, to ensure safe, ethical and responsible AI (RAI) at scale. Only through comprehensive AI governance can enterprises maintain control and visibility over AI, enforce responsible policies, comply with external regulations, and address the many threats and gaps to delivering responsible AI by default.
Mitigating risks to responsible AI
The stakes have never been higher. Regulators in the European Union have already created the EU AI Act, Canada’s released the E-23 framework, and many other regulations are planned, imposing significant fines for non-compliance. AI misuse — whether intentional or accidental — can impact a company’s finances, reputation, and jeopardize its future.
Risks that impeded responsible AI, include:
Transparency
It may be impossible for humans to understand how models generate results.
Privacy and security
Private data may leak through careless use in model training. Lax security may lead to breaches, data poisoning, and diminishing a model's value.
Turn governance into a swift and dependable process — and make AI responsible by default
Domino Governance helps enterprises apply all internal and external policies across all AI — today and tomorrow — to mitigate risks instantly so they can deliver more value from AI.
Domino lets you embed and enforce your AI policies to mitigate risks, ensure compliance and drive more value. Domino makes any abstract policy actionable through smart automation, so enterprises can comply with current and future regulations, adopt best practices, enforce standards, and innovate faster.
As a head of data science and AI, you've got to have a governance process that works across the business, because there are different types of AI. We’re incentivizing projects not to shy away from governance — and designing some of the platform work in Domino, where it’s within the development process by design.
One of the big concerns, at least for us, again, FINRA being in a financial services space and being a regulator in a financial services space, privacy and data security are paramount. That's like the absolute one thing we can never mess up that has got to be perfect at all times.
We can now go back to any project at any point in time and see what decision was made, and recreate that model if needed, which is huge in explaining to both management and regulators how we built a particular model — including what data went into it and what variables it identified.
Chief Data Scientist
Allstate
