In Embarking on AI Projects
IBM Consulting’s Approach
As business leaders investigate the best way to apply generative AI to their enterprise at scale, they need to consider trusted vendors and partners with expertise in data, machine learning and AI, data and AI governance, and proven capabilities of scaling applied AI within enterprises across industries and geographies.
Capabilites and Expertise
- IBM Consulting has capabilities in Foundation Models delivery at scale.
- IBM Consulting brings industry expertise to understand the regulatory constraints and how to derive value with AI by augmenting specific workflows.
- IBM has close strategic partnerships to scale AI projects and has won many awards in this regard, including the US 2022 AWS Innovation Partner of the year.
IBM’s Approach to AI
The mission of IBM Consulting is to drive business transformation with hybrid cloud and AI in a way that is valuable and responsible. We formally stood up our AI Ethics Board in 2018 to ensure that AI systems created at IBM are developed and deployed ethically.
Principles of Trust and Transparency
IBM has published its own principles of trust and transparency and offers them as a roadmap to others working with and implementing artificial intelligence. These principles focus on the following:
- The purpose of AI is to augment human intelligence;
- Data and insights belong to their creator; and
- New technology, including AI systems, must be transparent and explainable.
Pillars of Trust
IBM’s approach is guided by the following pillars of trust:
- Explainability: How an AI model arrives at a decision should be able to be understood.
- Fairness: AI models should treat all groups equitably.
- Robustness: AI systems should be able to withstand attacks to the training data.
- Transparency: All relevant aspects of an AI system should be available to the public for evaluation.
- Privacy: The data used in AI systems should be secure, and when that data belongs to an individual, the individual should understand how it is being used.
Social-Challenge of Trust and Transparency
Generative AI and large language models (LLMs) introduce new hazards into the field of AI, and driving trust and transparency in artificial intelligence is not a technological challenge, it is a socio-technological challenge.
How IBM Consulting Approaches AI
IBM brings together vast transformation experience, industry expertise, proprietary and partner technologies and IBM Research to work with clients wherever they are on their AI journey.
Our approach is uniquely suited to help businesses build the strategy and capabilities to operationalize and scale trusted AI to achieve their goals.
Resources
Services
- Analytics and AI to build, train and deploy AI and ML models for your business.
- AI and Automation Advisory to integrate best of breed AI and Automation solutions for full stack observation and orchestration.
- Full-Service Automation to leverage IBM’s full suite of technology and services platforms that enables straight through “touchless” processing with minimal human involvement.
Get Started with AI
Learn more about AI and Automation services including research about the open-source tools available to activate against trust & transparency and IBM AI Ethics. You can also learn more about this three-part series by reading the first or second installment, or reaching out to an expert for start a conversation about your needs.
Register for our webcast: What does ChatGPT mean for business? – How to drive disruptive value with Generative AI.
Q: What does IBM Consulting offer in AI projects?
A: IBM Consulting offers expertise in data, machine learning and AI, data and AI governance, and proven capabilities of scaling applied AI within enterprises across industries and geographies.
Q: What is IBM’s approach to AI?
A: IBM’s approach to AI is focused on driving business transformation with hybrid cloud and AI in a way that is valuable and responsible. We emphasize the importance of trust, transparency, explainability, fairness, robustness, and privacy.
Q: What are IBM’s principles of trust and transparency?
A: IBM’s principles of trust and transparency include the purpose of AI as augmenting human intelligence, data and insights belonging to their creator, and new technology, including AI systems, being transparent and explainable.
Q: How does IBM address the socio-technological challenge of trust and transparency in AI?
A: IBM addresses the socio-technological challenge of trust and transparency in AI by bringing together vast transformation experience, industry expertise, proprietary and partner technologies and IBM Research to work with clients wherever they are on their AI journey.
Q: What are the pillars of trust for IBM’s AI approach?
A: IBM’s AI approach is guided by the pillars of trust, including explainability, fairness, robustness, transparency, and privacy.
