Posted December 5, 2022

Building Trusted and Transparent AI/ML Solutions on Amazon SageMaker

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Building Trusted and Transparent AI/ML Solutions on Amazon SageMaker Data is the backbone of modern business, and this is why companies have put their trust in data-driven decision-making with the help of AI. But in the landscape of AI-supported enterprise decision-making, accuracy and consistency issues threaten this trust. The need for transparency and trust in AI A behavioral science study found that improving perceived transparency in AI decision-making increased effectiveness, which in turn encouraged trust. In the meantime, lack of openness increased discomfort, which in turn prevented trust. If ignored, users’ lack of trust in the algorithm might easily develop into a serious issue. The accuracy of the automated analysis will be contested by stakeholders. Companies must concentrate more than ever on creating AI Trust and ensuring that AI is reliable. This can be done by making the AI transparent so that interested parties can comprehend how the system operates. Building trusted and transparent AI solutions using Amazon SageMaker Amazon SageMaker is a fully managed machine learning service that allows data scientists and developers to quickly and easily build and train machine learning models, then directly deploy them into a production-ready hosted environment. It enables them to build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. SageMaker enables more people to innovate with ML through a choice of tools — such as IDEs for data scientists and no-code interface for business analysts. With SageMaker, data scientists and developers can: access, label, and process large amounts of structured data (tabular data) and unstructured data (photo, video, geospatial, and audio) for ML; reduce training time from hours to minutes with optimized infrastructure; boost team productivity up to 10 times with purpose-built tools; and automate and standardize MLOps practices and governance across your organization to support transparency and auditability. Konfer ( has recently published our latest e-book designed to help organizations experience the full benefits of AI by ensuring transparency, trust, and truth in the AI/ML solutions they build. The e-book covers:
  • Amazon SageMaker prerequisites and features
  • A step-by-step guide to creating, setting up, and configuring a Notebook instance
  • How to configure SageMaker Clarify to get bias reports and transparency
  • How to browse through metric namespaces to find and view metrics in SageMaker CloudWatch
  • How to use SageMaker CloudTrail to enable operational and risk auditing, governance, and compliance of your AWS account
  • A step-by-step guide to setting up a SageMaker Domain for SageMaker Studio users, creating a Studio Project, using SageMaker templates, and creating your own Organization templates.
  • Walk-through of Model development using SageMaker Studio Projects
The e-book is a comprehensive guide to using SageMaker to build not just AI/ML solutions — but trusted and transparent AI/ML solutions. To download a copy of the e-book, simply go to this download link. Increase AI Trust with Konfer Konfer prioritizes transparency in all AI/ML development stages by automatically mapping, measuring, and managing your AI framework. Our flagship solution, Konfer Confidence Cloud, helps businesses improve collaboration to achieve maximum productivity and efficiency. This helps businesses improve AI traceability and understanding, thereby empowering business leaders to trust AI-powered decision-making and maintain a competitive advantage. Contact us today to find out how your business can help you achieve AI Transparency, Trust, and Confidence in your AI development and production.

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