City Research Online

Abstract

Current Responsible AI (RAI) frameworks provide high-level ethical principles, but the development of practical procedures and tools for effective business implementation remains limited. Our pilot project “From ethical principles to practical implementation: Exploring the challenges of consulting in the implementation of RAI” investigated how Swiss organizations approach RAI implementation, explored their key challenges and opportunities, and established a foundation for developing practical solutions in a subsequent project aimed at narrowing the gap between RAI theory and business practice.

Eleven semi-structured interviews and a workshop revealed that:
— Organizations view RAI as synonymous with ethical AI but interpret “ethical” through different lenses
— Organizations lack a clear point of responsibility for RAI initiatives
— The main obstacles to RAI implementation are:
— Limited awareness of its significant costs
— Difficulty in defining and translating RAI components into metrics and practices
— A “wait-and-see” attitude
— Limited top management endorsement
— Regulatory ambiguity
— The primary drivers of RAI implementation are:
— Awareness of AI risks
— Top management support
— Regulatory pressure
— Organizations seek modular solutions adaptable to different use cases, industries, and daily workflows, including tools for measuring implementation progress
— Organizations anticipate significant growth in RAI services, tools, and skills

Based on these findings, we aim to develop a RAI Toolkit in collaboration with industry partners. This toolkit will be tailored to specific organizational use cases and AI technologies for integration into business operations. Our approach ensures the toolkit becomes an actionable tool for RAI implementation, embedded in organizational governance and daily decision-making processes. This represents an initial step toward developing modular solutions.

Publication Type:	Report
Additional Information:	This is an open access publication, available online and distributed under the terms of a Creative Commons Attribution - Non Commercial - No Derivatives 4.0 International licence (CC BY-NC-ND 4.0), a copy of which is available at http://creativecommons.org/licenses/by-nc-nd/4.0/.
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management H Social Sciences > HN Social history and conditions. Social problems. Social reform Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments:	Bayes Business School Bayes Business School > Management
SWORD Depositor:	Symplectic Administrator

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