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Now is the moment for responsible AI

Businesses are facing an increasingly complex, ever-changing global regulatory landscape when it comes to AI. The IBM approach to AI ethics balances innovation with responsibility, helping you adopt trusted AI at scale.

Foundation models: Opportunities, risks and mitigations.
Fostering a more ethical future by leveraging technology Case study: Fostering greater transparency across the data ecosystem
Our principles and pillars The Principles for Trust and Transparency are the guiding values that distinguish the IBM approach to AI ethics. Read the Principles for Trust and Transparency The purpose of AI is to augment human intelligence

IBM believes AI should make all of us better at our jobs, and that the benefits of the AI era should touch the many, not just the elite few.

Data and insights belong to their creator

IBM clients’ data is their data, and their insights are their insights. We believe that government data policies should be fair and equitable and prioritize openness.

Technology must be transparent and explainable

Companies must be clear about who trains their AI systems, what data was used in training and, most importantly, what went into the recommendations of their algorithms.

The Principles are supported by the Pillars of Trust, our foundational properties for AI ethics.
Explainability

Good design does not sacrifice transparency in creating a seamless experience.

Fairness

Properly calibrated, AI can assist humans in making choices more fairly.

Robustness

As systems are employed to make crucial decisions, AI must be secure and robust.

Transparency

Transparency reinforces trust, and the best way to promote transparency is through disclosure.

Privacy

AI systems must prioritize and safeguard consumers’ privacy and data rights.

Ethics for generative AI

When ethically designed and responsibly brought to market, generative AI capabilities support unprecedented opportunities to benefit business and society alike.

Foundation models: Opportunities, risks and mitigations Read the paper
The enterprise guide to generative AI

Find out strategies for capturing business value with generative AI while also building governance guardrails that build trust.

The urgency of AI governance

IBM and the Data & Trust Alliance offer insights about the need for governance, particularly in the era of generative AI.

A policymaker’s guide to foundation models

A risk- and context-based approach to AI regulation can mitigate potential risks, including those posed by foundation models.

Putting principles into action

The IBM AI Ethics Board is at the center of IBM’s commitment to trust. Its mission is to:

  • Provide governance and decision-making as IBM develops, deploys, and uses AI and other technologies
  • Maintain consistency with the company’s values
  • Advance trustworthy AI for our clients, our partners and the world

Co-chaired by Francesca Rossi and Christina Montgomery, the Board sponsors workstreams that deliver thought leadership, policy advocacy and education and training about AI ethics to drive responsible innovation and the advancement and improvement of AI and emerging technologies. It also assesses use cases that raise potential ethical concerns.

The Board is a critical mechanism by which IBM holds our company and all IBMers accountable to our values and commitments to the ethical development and deployment of technology.

Francesca Rossi

Learn more about Francesca

 Christina Montgomery

Learn more about Christina

watsonx.governance Accelerate responsible, transparent and explainable data and AI workflows. Learn more Get the AI governance ebook

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