Generative AI

WG 12.15 – Generative AI

Officers

Chair

Daniel E. O’Leary, University of Southern California, USA, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Vice-Chair

Guido Geerts, University of Delaware, USA, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Thomas Lampert, University of Strasbourg, France, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Secretary

Ciara Heavin, University College Cork, Ireland, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Website

https://ai4gs.org/ 

Aims

The Working Group on Generative AI, affiliated with the International Federation for Information Processing (IFIP), is a collaborative consortium of leading academics and practitioners dedicated to advancing the understanding, development, educational application and ethical application of generative artificial intelligence technologies.  Our general mission will be:

“To be the leading organization studying generative AI unswayed by political agendas and profitability.”

Our Mission will be to investigate several concerns in generative artificial intelligence.

1. Research Excellence: To foster interdisciplinary research at the forefront of generative AI, exploring innovative methodologies, algorithms, and applications that push the boundaries of knowledge and practice.
2. Knowledge Exchange: To facilitate vibrant discourse and knowledge sharing among scholars and practitioners worldwide, promoting cross-cultural perspectives and diverse insights into the opportunities and challenges posed by generative AI.
3. Ethical Considerations: To prioritize ethical considerations in the development and deployment of generative AI systems, emphasizing transparency, accountability, sustainability, and societal impact assessment to mitigate potential risks and ensure responsible innovation and resilience.
4. Educational Partnership: To foster mutual learning between AI developers and educational communities, where researchers, developers and practitioners share technical and pedagogical knowledge, ethical considerations, and societal impacts. This knowledge exchange and collaboration help shape AI development while preparing future generations to thoughtfully engage with and guide AI technologies.
5. Industry Collaboration: To establish strategic partnerships with industry stakeholders to bridge the gap between theory and practice, facilitating technology transfer, and fostering real-world applications of generative AI that address pressing societal needs and challenges.

6. Policy Advocacy: To advocate for evidence-based practices and policies and regulations that foster innovation while safeguarding against misuse and unintended consequences of generative AI technologies, contributing to the development of a sustainable and inclusive digital future.

 

Scope

We have identified several general themes identifying our scope.  This list is not comprehensive, but suggestive of some themes.  Those themes include the following.

AI for Good: Using GAI to focus on using AI to bring about a better world, including issues such as environment, social and governance (ESG).

Educational Applications:  We expect to analyse the unique issues associated with using large language models and generative AI systems in educational applications.

GAI as Knowledge Management: Recently researchers have proposed that GAI be used to integrate knowledge management into organizational processes, and organizational learning practices.  We expect to analyse the unique application of large language models and generative AI systems in knowledge management.

GAI as Commerce: Increasingly, there are important opportunities for using Gen AI and Large Language Models for commerce – embedding information about products and services and connecting users to those sources.

Human-Centred Intelligent Interactive Systems: Examining ways to enable seamless collaboration between humans and generative AI systems, leveraging human feedback and expertise to enhance the quality and relevance of generated outputs.

Risks of GAI: There are several risks of GAI, ranging from the further entrenchment of existing inequalities to manipulation and misinformation, to the loss of control of autonomous AI systems, potentially resulting in human extinction.

Equitable Access and Impact: Ensuring GAI benefits are distributed fairly across society while actively preventing the amplification of existing inequalities and creating mechanisms for inclusive participation.

Governance and Accountability: Developing frameworks for oversight, transparency, and responsibility in GAI development and deployment across different contexts and applications.

Life Cycle Concerns: Gen AI is early in its life cycle.  As a result, we expect to investigate issues associated with development and finetuning of systems.

GAI for Decision Making: Investigate and analyze the unique aspects associated with the use of Gen AI for making decisions, both autonomous and human-in-the-loop.

 

Members

 

• WG 12.15
• Generative AI
• LLMs
• LLM