How to start your responsible AI journey?

By Trishan Wickramasinghe 

Gen AI can help organisations reinterpret their business model to improve revenue and growth advantages by creating innovative new products. It can also support to speeding up commercialisation by redesigning innovative paths to get these products to market, but as companies interested in adopting an artificial intelligence (AI) strategy, it is necessary drive each use case with an AI Governance Model to ensure expected benefits of Gen AI Strategy as the adoption of Gen AI is not just a technology enablement, instead it will transform the business models along with connected stakeholders and processes. 

The ultimate obligation of adopting Gen AI strategy from business standpoint is to generate a beneficial productivity impact across the organisations but this won’t be enough to encourage demarcation, develop smart operations or innovative products and services. The business leaders need to identify and prioritise use cases that uniquely anchorage the organisation’s intellectual property, financial operations, and knowledge management systems by analysing their qualitative and quantitative data. Organisational leaders can personalise a foundational Gen AI large language model (LLMs) to design new applications that encourage a competitive advantage by utilising the valuable data available within the organisation effectively.

EY is committed on providing responsible and ethical design, implementation, and use of AI systems. EY teams have knowledge around AI governance and are able to help organisations with their Generative AI strategy and AI Governance Models, help the organisations to understand the value drivers of different AI services, the effort needed to deploy the solutions, the drivers of risk throughout the deployment and ways to limit that risk. EY teams have developed below Responsible AI Principles that teams must adhere to when developing and using AI. Accountability – There is unambiguous ownership over Al systems, their impacts and resulting outputs across the Al lifecycle.

Data Protection – Use of data in Al systems is consistent with permitted rights, maintains confidentiality of business and personal information and reflects ethical norms.

Reliability – Al systems are aligned with stakeholder expectations and continually perform at a desired level of precision and consistency.

Security – Al systems, their input and output data are secured from unauthorised access and resilient against corruption and adversarial attack. 

Transparency – Appropriate levels of disclosure regarding the purpose, design and impact of Al systems is provided so that stakeholders, including end users, can understand, evaluate, and correctly employ Al systems and their outputs.

Explainability – Appropriate levels of explanation are enabled so that the decision criteria and output of Al systems can be reasonably understood, challenged, and validated by human operators.

Fairness – The needs of all impacted stakeholders are assessed with respect to the design and use of Al systems and their outputs to promote a positive and inclusive societal impact.

Compliance – Ensures the design, implementation and use of AI systems and their outputs comply with relevant laws, regulations, and professional standards. 

Sustainability – Considerations of the impacts of technology are embedded throughout the Al lifecycle to promote physical, social, economic, and planetary well-being.

An organisation can excel several benefits by implementing a proper AI Governance model within the organisation such as future proof strategy enabling a clear communication plan to the various stakeholders, including the board, employees, investor and clients, multiple reusable assets (e.g., use case intake form, customised prioritisation framework) for ongoing expansion of Generative AI use cases across the organisation with short-term and longer-term Generative AI tech and adoption strategy to ensure responsible activation while keeping pace with the market. 

Our vision as the EY organisation is to be the provider of choice for clients and EY people to navigate the transformative change, leading with ethical and responsible AI, help enabling sustainable growth and empowering people and society for a better working world.

 (The writer serves as the Senior Manager – AI and Data Services of Ernst & Young Sri Lanka. He is a Post Graduate Diploma holder from OTHM Qualifications, UK, BSc in IT Graduate from University of West London, UK, Qualified in Scottish Credit and Qualification Framework Level 8 - Computer Science and Associate Degree holder in Mechanical Engineering from Auston Institute of Management, Singapore. The views reflected in this article are the views of the writer and do not necessarily reflect the views of the global EY organisation or its member firms.)