Jan 23, 2024
                       

Responsible and Ethical AI for Future Actions

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The Research problem

Overview of Current AI and Responsible AI Practices

Artificial Intelligence (AI) is reshaping numerous sectors, impacting areas like education, healthcare, logistics, and the legal field. While AI introduces enhanced accuracy, innovation, and efficiency, it also brings about concerns related to potential risks, ethics, and long-term implications. The broader community often lacks a clear understanding of responsible AI practices, creating challenges. This has sparked a worldwide dialogue on AI’s governance, transparency, accountability, societal, legal, environmental, and ethical dimensions, as well as its unbiased application to prevent negative consequences and biases. Tools and guidelines for Ethical AI aim to address these concerns throughout AI’s development.

Why it is important to scholars and/or society generally.

Promoting responsible and ethical AI is challenging due to underdeveloped frameworks and varying progress rates across regions. Many organisations prioritise AI growth over responsible innovation. Existing frameworks often lack comprehensive implementation resources, and ethical tools don’t seamlessly connect theory with practice. No universal tool or platform captures the advancement of responsible AI globally. As AI integration grows across industries, there’s a pressing need for AI skills. Yet, there’s a significant gap in individuals proficient in responsible AI, underlining the need for online training programs in AI ethics and explainability.

Research Design

Our approach is threefold. First, we’ll launch online AI courses designed by multidisciplinary experts and share them on a YouTube playlist. Second, we’ll conduct an online symposium, gathering professionals from various sectors to share expertise; each network partner will bring in another participant. Finally, based on thorough research, we’ll craft a web article comparing responsible AI methodologies and tools.

Project Objectives

This project, therefore, plans to tackle above challenges with the following plans.

  1. Academic-Led Responsible AI Training Initiative: We’re launching an extensive training program that bridges technical and ethical aspects of AI. Targeted at future AI specialists and the current workforce, these online courses are a blend of expertise from multiple disciplines and regions. All sessions will be available on a YouTube playlist, making this the first academically curated free online playlist dedicated to comprehensive responsible AI education, accessible globally by WUN.
  2. Online Worldwide Symposium on Responsible and Ethical AI: Industry Insights and Global Standards in Application. Beyond training, we’re organising a symposium to foster global conversations on AI’s responsible usage, with an emphasis on industry insights. This platform will unite industry frontrunners, UNESCO members, and other key stakeholders to discuss the practical challenges and dynamics of AI. Unlike our training, this event promotes collective dialogues, workshops, and in-depth exploration of AI’s multifaceted concerns, ensuring AI’s responsible and relevant industry application.
  3. Ethical AI Web Article: Demystifying Guidelines with a Comparative Analysis of Frameworks and Practical Solutions. This web article aims to help organisations of all sizes to easily find toolkits that resonate with their ethos and operational methodologies. Collaborating with our WUN network partners ensures the presented information is exhaustive and globally pertinent.

Who's involved

Dr Benjamin Liu, Dr Yat Ming Ooi, Dr Fabio Morreale, Dr Amy Chan
The University of Auckland

Maastricht University

Dr Pattanasak Mongkolwat, Dr Thanapon Noraset
Mahidol University

Mutuzo Irene Esther Sevume
Makerere University

Professor Claudia Camacho-Zuñiga
Tecnológico de Monterrey

Distinguished Professor Dikai Liu, Dr Avinash Singh
University of Technology Sydney

Professor Tom Stoneham
University of York