AI Ethics
IBM’s multidisciplinary, multidimensional approach to AI ethics
Building trust
AI is embedded in everyday life, business, government, medicine and more. At IBM, we are helping people and organizations adopt AI responsibly. Only by embedding ethical principles into AI applications and processes can we build systems based on trust.
*Source: IBM’s From Roadblock to Scale: The Global Sprint Towards AI Study 2020
3 in 4 businesses are exploring or implementing AI.
78% of senior business decision-makers say it is very or critically important that they can trust that their AI’s output is fair, safe, reliable.
Featured issues
The IBM approach
Uniting insights from business, policy, research, and thought leadership
Responsible innovation
For more than 100 years, IBM has continuously strived for responsible innovation capable of bringing benefits to everyone and not just a few.
The purpose of AI
The purpose of AI is to augment human intelligence.
At IBM, we believe 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 ownership
Data and insights belong to their creator.
IBM clients’ data is their data, and their insights are their insights.
Transparency and explainability
New technology, including AI systems, must be transparent and explainable.
Technology companies must be clear about who trains their AI systems, what data was used in that training and, most importantly, what went into their algorithms’ recommendations.
Explainability
Good design does not sacrifice transparency in creating a seamless experience.
Fairness
Properly calibrated, AI can assist humans in making fairer choices.
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.
Policy
Selected positions and recommendations from the IBM Policy Lab
Facial recognition
IBM no longer offers general purpose IBM facial recognition or analysis software. We believe a precision regulation approach can inform a reasonably-balanced governance framework for facial recognition systems. Policymakers should employ precision regulation that applies restrictions and oversight to particular use-cases and end-users where there is greater risk of societal harm.
Data responsibility
Organizations that collect, store, manage or process data have an obligation to handle it responsibly, ensuring ownership and privacy, security, and trust.
Additional resources
Read more about IBM policies and practices on emerging technology
IBM Policy Lab
A new forum providing policymakers with a vision and actionable recommendations to harness the benefits of innovation while ensuring trust in a world being reshaped by data.
IBM Trust Center
Information about our commitment to protect our clients and business with security and privacy practices.
Putting AI Ethics into practice
Governance, accountability, and Good Tech across the organization
AI Ethics Board
The IBM AI Ethics Board is a natural evolution of the ethical decision-making IBM applies to AI.
The Board was established as a central, cross-disciplinary body to support a culture of ethical, responsible, and trustworthy AI throughout IBM.
Our mission is to support a centralized governance, review, and decision-making process for IBM ethics policies, practices, communications, research, products and services. By infusing our long-standing principles and ethical thinking, the Board is one mechanism by which IBM holds our company and all IBMers accountable to our values.
Francesca Rossi
IBM fellow and AI Ethics Global Leader
Christina Montgomery
Vice President & Chief Privacy Officer
Initiatives
IBM Research: Trusting AI
IBM Research is building and enabling AI solutions focused on trust.
Center for Open Source Data and AI Technologies: Trusted AI
The Center for Open Source Data and AI Technologies (CODAIT) helps maintain projects created by IBM Research that can increase fairness, explainability, robustness, and transparency in machine learning systems.
IBM Design for AI
A shared collection of ethics, guidelines, and resources to design human-centric AI.
Science for Social Good
Partnering IBM Research scientists and engineers with academic fellows, subject matter experts from a diverse range of non-governmental organizations (NGOs), public sector agencies, and social enterprises to tackle emerging societal challenges using science and technology.
Corporate Responsibility
IBM brings the power of its technology, resources, and people to help with initiatives around the world, from education to health.
Advancing AI ethics beyond compliance
As AI adoption rapidly increases, it’s critical that AI ethics progress from abstract theories to concrete practices.
Education and toolkits
Resources and open-source tools for building trust-based AI
Open-source community resources
We are dedicated to empowering the world with responsible AI through our educational resources. IBM donated three open-source projects to the Linux Foundation toward the mission of co-creating responsible AI-powered technologies with the larger community.
Resources
Watson OpenScale
Automate AI model risk management in new ways
Product offering
Manage regulatory compliance by tracing and explaining AI decisions across workflows, and intelligently detect and correct bias to improve outcomes. IBM Watson OpenScale will easily operate with model development environments from other vendors and open source tools. It provides an innovative set of monitoring and management tools that help you build trust and implement control and governance structures around your AI investments.
Serving the greater good
An open solution that helps remove barriers to enterprise-scale AI
Collaborations
Working with organizations, businesses and governments on ethical AI
Featured collaborations
Working together for ethical AI
IBM works with governments, academia, non-profits and industry partners to further the implementation of ethical AI.