Responsible AI

Scaling With Speed and Safety

Responsible AI is a framework that aligns AI with an organization’s values by proactively checking for and mitigating issues related to bias, fairness, transparency, explainability, and accountability.

Without a clear strategy around Responsible AI, companies face several risks including reduced consumer trust or employee confidence, fines, increased audits and scrutiny, and unclear accountability which can lead to AI disfunction.

Responsible Data Preparation

Safely Procure and Process Data to Mitigate Biases Upfront

Responsible AI best practices begin before machine learning (ML) models are even created. The first step in reducing the risk of biased ML models is ensuring the right data preparation methods are put in place.

Dataiku offers key features to support these best practices, including advanced statistical analyses, augmented data exploration, customizable metrics and checks, and data privacy in accordance with major regulations.

Training Fair and Robust Models

Experiment and Build Models While Controlling for Quality

Ensuring models are fair can be time consuming and challenging to do at scale, but Dataiku offers several features to bring greater accuracy to your process.

Automatically check that predictions for subpopulations meet certain conditions. Get warnings if new versions of your model don’t behave as expected.

Identify imbalances in your datasets and differences in variable importance.

Select key customizable metrics upon which you want to measure bias in your model and get comprehensive reporting to quickly identify problems.

Easily understand how predictions change at global, regional, and local levels.

Clear, Comprehensive Reporting

Build Easy-to-Understand Documentation and Visualizations

To bring greater accountability and transparency to your ML process, Dataiku offers explainable AI features to help your team quickly understand where your models stand.

Get row-level explanations for why a model is producing a given prediction and easily export via API.

Check different input scenarios and publish the what-if analysis for business users for better visibility across all roles.

Calculate key model metrics and receive automatic notifications for specific model errors.

Quickly and automatically generate model documentation including what the model does as well as how the model was built, tuned, and performed.

Enforce Responsible AI Best Practices

Create Clear Steps and Gates With Dataiku Govern

When models are pushed to production without the appropriate risk assessments, they may run afoul of Responsible AI best practices. With Dataiku Govern, you can build out the right checks and balances without slowing down your data science teams.

Create standard project plans and leverage workflow blueprints with clear steps and gates to explore, build, test, and deploy AI projects.

A centralized way to see all models (whether developed in Dataiku or externally) in one place, versioned and with performance metrics and project summaries for leaders and project managers.

Request and collect sign-offs on models prior to deployments in order to ensure audit-readiness on deployment decisions.

Dataiku: Your Partner in Responsible AI

Support and Guidance Following Industry Best Practices

Beyond tooling, Dataiku experts will work with you to identify key areas of opportunity based on your company’s unique needs.

Risk/value mapping workshops to prioritize initiatives and translating intentions to actionable checklists.

Education on high-level and practical applications of Responsible AI with Dataiku so that your teams can put best practices into action.

Responsible AI reviews of high-risk projects and support for custom bias detection and mitigation techniques.

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