How can IBM Watson OpenScale help you scale AI and how does it compare to its competition

The IBM Think Conference in February had three broad themes: digital and AI strategy, hybrid and multi-cloud architecture, and trust in AI and corporate stewardship. The third of these themes is where IBM is leveraging its existing ecosystem of AI and machine learning products to offer capabilities that help organizations ensure model performance, explainability, and detection and mitigation of bias in models in production. The IBM Watson OpenScale platform, which became generally available in late 2018, was specifically highlighted at the conference for its ability to achieve these objectives.

Worldwide, transparency and explainability are becoming table stakes for AI and machine learning, driven by increasing regulatory pressure and consumer rights, as well as the business need to simply understand how and why certain outcomes were reached. Visibility into models and their performance is needed not only for defensibility but for scalability as well.