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Data & Analytics Blog

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How Trustworthy AI Solves Data Science Challenges

Posted by LPA, A Converge Company on May 12, 2022 10:37:57 AM

IMARC Group research shows the global AI market reached a value of $56.5 billion in 2021 and is forecast to grow at a compound annual growth rate (CAGR) of 31.9% between now and 2027. With so many organizations embracing AI in virtually every industry, artificial intelligence is playing a pivotal role in business strategy.

Nearly three-quarters of AI users say that data access is a challenge, according to 451 Research. Yet, the strength of AI models depends on being to aggregate accurate data from multiple sources, including internal and external sources across public and private clouds.

For data science teams, this often means difficulty in moving AI models into production. According to Gartner, 53% of AI/ML projects are stuck in the pre-production phases due to a lack of trust in the models and concerns over conformance.

The proliferation of data science tools being used in enterprises requires governance and adherence to compliance regulations. This is a crucial aspect of promoting trust in data science processes.

Achieving success with AI and ML requires trust in data, models, and processes. Using the IBM Trustworthy AI solutions produces an end-to-end AI workflow that creates that trust while leveraging automation across each stage of the AI pipeline.

How Trustworthy AI Solves Data Science ChallengesHow Trustworthy AI Solves Data Science Challenges

Collaborating on the IBM Cloud Pak® for Data platform allows trustworthy AI lifecycle management that reduces complexity, improves productivity, and mitigates bias. However your data is distributed across on-premises, cloud, multi-cloud, or hybrid cloud landscape, you can eliminate data siloes and enforce a governance framework that automates data protection policies.

The IBM Cloud Pak® for Data platform:

  • Operationalizes consistency
  • Manages policies and rules
  • Automates data privacy and security
  • Improves data quality

Trust in your analytics doesn’t happen automatically. You need the right collection, storage, cleansing, and data fabric to ensure an end-to-end solution to build the trust you need for your data science teams. IBM Cloud Pak® for Data creates the data fabric you need for advanced MLOps capabilities with core functionality you can trust.

The IBM Trustworthy AI Solution

IBM Cloud Pak® for Data provides an open, secure, and governed multi-cloud data and
analytics platform. It includes the following essential offers:

  • Intelligent cataloging with IBM Watson® Knowledge Catalog automates metadata collection and policy management to ensure all model details are automatically collected and stored for maximum transparency and repeatability.
  • Automated MLOps with IBM Watson® Studio simplifies model production from any tool, provides automatic model retraining, and monitors models over time for accuracy, explainability, bias, and fairness.
  • Governance, risk, and compliance platform with IBM OpenPages with Watson® identifies, manages, monitors, and reports on risk and regulatory compliance across the entire model development lifecycle without requiring you to switch the AI/ML tools you are using today.

With the right tools, you can instill trust in AI and deliver the outcomes you need:

  • Trust in data ensures data scientists get access to accurate data through a data fabric.
  • Trust in data science models is essential for machine learning, explainability, fairness, and monitoring.
  • Trust in process addresses the need for AI governance with automation at each stage of the AI lifecycle.

Download our Guide: Why You Need a Trustworthy AI Data Fabric.

Design and Deploy Trustworthy AI

To learn more about how we can help you leverage the power of analytics, contact us today.

Download Your Guide: Why You Need a Trustworthy AI Data Fabric - LPA

Topics: Data Science & AI, AI