IBM has announced new capabilities for IBM Watson designed to help businesses build trustworthy artificial intelligence (AI). These capabilities further expand Watson tools designed to help businesses govern and explain AI-led decisions, increase insight accuracy, mitigate risks and meet their privacy and compliance requirements.
An IBM-commissioned survey found that trust, transparency and explainability are top-of-mind concerns for businesses, with 84% of AI professionals surveyed agreeing that consumers are more likely to choose services from a company that offers transparency and an ethical framework on how its data and AI models are built, managed and used. However, the barriers to developing trustworthy AI and mitigating risk remain pervasive, with 82% of AI professionals surveyed saying their organization has been negatively impacted by problems, like bias, with data or AI models.
To help businesses overcome these challenges, IBM is continually bringing new capabilities to its Watson products that are designed to build trust throughout key stages of the AI lifecycle and to help businesses achieve greater confidence in AI-powered outcomes. The new capabilities announced today include:
• New data privacy management capabilities: IBM OpenPages with Watson now includes a new Data Privacy Management module designed to help businesses meet evolving data privacy challenges. By integrating with Watson Knowledge Catalog, IBM OpenPages can now provide businesses with a holistic, near real-time view of how private data is being used throughout the organization, from applications to AI models. As new privacy regulations are enacted around the world, businesses need to be able to account for how they use personal data. This new capability is designed to help automate the reporting of personally identifiable information (PII) in order to improve accuracy and reduce audit times.
• Enhanced explainability for planning forecasts: IBM Planning Analytics with Watson will include a new statistical details page designed to provide more transparent and easy-to-understand facts about how a forecasting prediction was generated. As more businesses turn to predictive forecasting capabilities to strengthen their financial, sales and supply chain planning, they require transparency in the models and data used to generate the forecast. This new feature is planned for generally availability in 2021 Q2 to provide users with more granular information as well as increased explainability and accountability in their forecasts.
• New Federated Learning capabilities: IBM Watson Studio now includes new federated learning capabilities as a tech preview to help businesses apply machine learning techniques to situations where data cannot or should not be moved due to reasons such as data privacy, secrecy, regulatory compliance, or simply the size of data involved. With IBM Watson Studio, businesses will be able to train AI models on previously siloed data sources.
• New Time Series capabilities: IBM Watson Studio now includes Time Series capabilities in beta designed to tackle the challenges of automating, analyzing, and forecasting time series data commonly seen in many industries like finance, manufacturing, and retail. The new capabilities are designed to help businesses develop models that predict future values of a time series based on past data or features. Time Series on IBM Watson Studio is designed to achieve accuracy across a variety of univariate datasets — including data such as phone call data logs, weather data, travel times, retail sales, production volume, to driving increase insight accuracy.
“AI is only as useful as your trust in it. Especially in business and when the stakes are high,” said Daniel Hernandez, General Manager, Data and AI, IBM. “IBM Watson continues to deliver critical new capabilities to help enterprises build trust into every step of the AI lifecycle so business leaders can confidently operationalize AI across the hybrid cloud.”