Overview
We deliver trustworthy AI solutions
Many enterprises are hindered in making full use of AI, usually due to a lack of trust in the solutions. Our IBM Expert Labs team works across all stages of the AI lifecycle, from plan to build, deploy to operate, to help deliver trustworthy AI solutions at scale and speed.
Aspects of trustworthy AI
Evaluating your AI solutions
Fair
Ensure models and outcomes are impartial and avoid bias. Fairness avoids privileged groups having a systemic advantage over others.
Private
Follow high-integrity data and business compliance guidelines. Privacy assures owners that they retain control of data and insights.
Explainable
Provide explanations to understand outcomes and decisions. Users should be able to understand why AI arrived at a conclusion and at which point it would have been different.
Transparent
Inspire with trust and transparency for inspection. Transparent results mean that users can increase their understanding of why and how AI was created.
Robust
Handle exceptional conditions effectively and with ease. Robust AI should be able to evaluate and defend itself against a variety of threats.
Benefits
Innovate with confidence
Quickly move to market
Deploy trustworthy operational AI
Increase ROI with validated AI
Maximize opportunity with confidence
AI risks: three real world examples
Explainability

Explainability
A customer is rejected for a loan, while his neighbor is accepted for the exact same loan, and with excellent terms. Can the business provide an explanation to the customer?
Drift

Drift
What was fraudulent activity last month, may less likely be fraudulent activity this month. How do we know the ML/DL models are still accurate and don’t provide bad business decisions?
Solutions
Solution planning for AI
Create an AI action plan
In planning AI solutions, it is critical to translate business needs into specific, actionable requirements to ensure trust in the solution itself, as well as its monitoring and maintenance. Solution planning for AI uses a structured method to establish AI business needs and translate them into precise technical specifications.
AI build
Create trustworthy AI solutions with an agile approach
At the core of any business’s use of AI is a specific AI solution that must be trusted, usually a machine learning model. An experienced team of data scientists and AI practitioners produces an initial solution with the characteristics needed for trust in just six weeks using agile methodologies.
MLOps validate and deploy
Efficient and reliable AI deployment
Even the best AI model brings no value to the business until it can be confidently deployed and used. The key to promoting models from development to test in production is validation-- not only of the accuracy, but also of trustworthy characteristics and configuration management, which must be maintained in order to trust what is promoted. MLOps Validate and Deploy establishes pipelines for the full process, regardless of what tools were used to build models.
MLOps monitor and manage
Operating with trust and transparency
Even with the best processes for planning and building a trustworthy solution, we need special monitoring and processes for machine learning models to be able to use them confidently. MLOps monitor and manage uses IBM Cloud Pak® for Data and OpenScale™ to establish operational monitoring for key elements of trustworthy AI.
Speak with an expert
Have questions? Schedule a free 30-minute consultation.