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From ethical principles to practical implementation: Exploring the challenges of consulting in the implementation of responsible AI (RAI)

Researchers Involved

Dr. Eleonora Viganò

Dr. Eugenia Cacciatori

Prof. Dr. Christian Hauser

Jana Sedlakova

Dr. Andrea Ferrario

Dr. Christian Hugo Hoffmann

Stewart Palmer

research areas

AI ethics
corporate social responsibility
Digital Ethics
responsible AI

timeframe

2024 - 2024

contact

eleonora.vigano@ibme.uzh.ch
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From ethical principles to practical implementation: Exploring the challenges of consulting in the implementation of responsible AI (RAI) Project Image
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Putting AI ethics into practice is a major challenge, as existing ethical frameworks and laws are often too broad for organizations to apply effectively. Many companies and consultancies struggle to understand how to use these guidelines to reduce ethical risks in their specific context. This project aims to identify and categorize the main problems encountered when trying to apply ethical AI principles and establish a foundation for developing practical, context-specific best practices for implementing responsible AI.

Background

The adoption of AI entails ethical issues, such as fairness and transparency, which, in turn, manifest into significant strategic, operational, and compliance risks. These include challenges in justifying decision-making processes, possible consumer backlash, and legal liabilities. These risks are pervasive but often manifest in unexpected ways. Accordingly, organizations struggle to, first, develop tools and practices that can be used to limit the ethical risks of AI and, second, to attribute responsibility for the negative effects brought about by the use of AI. For these reasons, there is growing demand for consulting services in RAI. Yet, when providing RAI services, consultancies face difficulties in translating ethical AI principles into practical recommendations for the specific needs of their client organizations and the specificities of the Swiss business context. Our project will help in addressing these issues.

Detailed Project Description

In phase 1, we seek to identify and explore the current RAI needs and challenges that consultancies and client organizations face. We apply to the Innovation Booster Databooster – Call for Participation to seek companies interested in participating with us in the shaping of the workshop “Consulting in RAI: how to narrow the RAI implementation gap”. To fund this event, we aim to apply to the Innovation Booster Databooster – Shaping Workshop. In this workshop, participants from both consultancies and organizations in need of RAI consulting will have the opportunity to share experiences, talk about their challenges, and draft initial solutions to the most pressing ones.

In phase 2, building on the insights and outcomes of the workshop, we will partner with consultancies and/or client organizations on a project proposal on RAI. The project will deal with developing a set of tools helping organisations and consultancies in addressing RAI issues. The offering will include, among others, training material to improve staff’s RAI literacy, a toolkit (e.g., checklists, frameworks and best practices) for assessing and managing a company’s ethical risks in RAI, and supporting tools for designing RAI policies.

Project Aims

  1. Identifying and systematizing the issues that consultancies and their clients face in implementing RAI
  2. Laying the ground for the elaboration of operational best practices for implementing RAI in organizations

Relevance

The project fosters the responsible adoption of AI in Swiss organizations by advancing the understanding of the current supply and demand of RAI services in the Swiss market and providing initial solutions to the most pressing challenges that organizations must meet in RAI.

Methods

  1. Desk research on the offering of major and Swiss small consultancies in RAI
  2. Qualitative interviews of clients and consulting organizations

Calls for abstract, participation 

The call is closed

Specific Project Goals

Applying to Innovation Booster DataBooster – Shaping Workshop for funding a workshop entitled “Consulting in RAI: how to narrow the RAI implementation gap”. The event will gather academics, consultancies, and clients, who will have the opportunity share their experiences on RAI, talk about its challenges, and draft initial solutions to the most pressing ones

Applying to a funding scheme financing a larger project on RAI in organizations (e.g., Innosuisse)