The Mini Tracks at ICAIR
- Transforming the Future: How Generative AI and LLMs are Revolutionizing Digital Transformation
- Artificial intelligence, Machine Learning and Automation in the Aeronautics Sector
- Ethical and Societal Implications of AI
- AI and Educational Research and Researchers
Examining the Future of AI and Human Systems Integration
Transforming the Future: How Generative AI and LLMs are Revolutionizing Digital Transformation
Mini Track Chair: Dr. Mitt Nowshade Kabir, Ecole de Management Leonard De Vinci
"Transforming the Future" is set to explore the revolutionary impact of Generative AI and Large Language Models (LLMs) on digital transformation. This platform invites cutting-edge insights into how these technologies are redefining the business world by introducing advanced methods of interaction, creativity, and decision-making. Generative AI and LLMs are pushing the boundaries of customer engagement through personalized experiences, streamlining complex challenges, and fostering unparalleled content generation across sectors. Our goal is to delve into the myriad possibilities these technologies herald, establishing new standards for innovation and efficiency.
This session is dedicated to examining the broad influence of Generative AI and LLMs in driving forward digital transformation efforts. It will feature a rich tapestry of pioneering research, illustrative case studies, and analytical discussions to illuminate how these tools enhance organizational growth, adaptability, and strategic foresight. As we chart the course of digital evolution, propelled by Generative AI and LLMs, the mini track promises a critical examination of these technologies' current achievements and their future role in cultivating a digitally proficient society. We look forward to contributions that not only scrutinize the existing capabilities of these instruments but also explore their long-term impact on creating a digitally empowered world.
"Transforming the Future" at ICAIR 2024 represents an essential dialogue on the frontiers of digital innovation, inviting participants to shape the trajectory of a future influenced by the transformative power of Generative AI and LLMs. Join us in spearheading the next digital revolution, marking a significant leap towards a technologically advanced society. We invite thought leaders, innovators, and researchers to contribute insights on the following subtopics:
- Strategic Innovation: Examining Generative AI’s role in developing novel business strategies, models and market transformations.
- Cognitive Collaboration: Utilizing LLMs to augment decision-making and operational intelligence.
- Design and Customization: Leveraging AI in generative design for bespoke solutions across industry verticals.
- Interactive Experiences: Enhancing consumer engagement through LLM-driven interfaces and generative content.
- Operational Excellence: Implementing AI to refine business processes for efficiency and productivity.
- Visionary Impact: Projecting Generative AI’s long-term influence on industry standards and practices.
Artificial Intelligence for Behaviour Change and Transformation
Mini Track Chair: Dr. Carlos Pedro Gonçalves, Lusófona University - University Centre of Lisbon, Portugal
Machine learning and automation are key drivers of change and transformation in the aeronautics sector, with significant impact ranging from areas as diverse as the supply chain, operations, business processes, risk and crisis management systems and aeronautical security, as well as specific challenges linked to flight automation and robotics. Aeronautics’ entrepreneurship within the context of the Fourth Industrial Revolution also includes the field of civilian and military robotics, in which automation and artificial intelligence (AI) play key roles, with specific emphasis in the business line of Unmanned Aerial Vehicles. Besides the integration of AI in the aeronautics industry at its multiple levels, AI also presents new challenges on different fronts including aeronautical law regarding drones and AI, human resources management challenges from AI introduction as well as cybersecurity threats associated with the use of AI in hacking leading to new threats both regarding the safety of data as well as possible disruption targeting flight systems and aeronautical automation, physical security threats to airports are also present linked to the possible use of drones to attack airports. This mini track will explore the latest trends, developments and challenges presented by artificial intelligence, machine learning and automation in the aeronautics sector, providing valuable information for researchers, policy makers and industry professionals. Together, we will delve into both the transformative potential of AI and the possible threats and challenges from AI to the aeronautics sector. Examining how decision-makers and managers in the aviation sector are addressing these challenges and can harness AI technologies to face the major transformations resulting from the exponentially changing technological horizon associated with the cyber-physical-cognitive systems revolution that is driving the Fourth Industrial Revolution.
We are inviting submissions of abstracts for presentations including the following:
- Impact of artificial intelligence and automation in the business processes and value chain of the aeronautics sector.
- Unmanned Aerial Vehicle technologies and its integration in both the civilian and military sectors.
- Application of machine learning technologies in risk and crisis management in the aeronautics sector.
- The legal challenges presented by AI and automation in the aeronautics sector.
- The potential of AI and drone technologies in civil protection.
- Human resources management challenges from AI and automation in the aeronautics sector.
- The use of AI technologies in facing security threats to the aeronautics sector and the threats coming from AI and drone technologies.
Ethical and Societal Implications of AI
Mini Track Chair Prof. Ali Hessami, Vega Systems, London, UK
This track will cover the latest advances on technology ethics and the social and legal requirements for a responsible development and deployment of the technology. This is intended to provide a basis for raising awareness and offering support and a systematic social impact and assurance framework for the innovators, researchers and technologists as well as small and large, public and private enterprises involved in AI and technology innovation, development and deployment.
The main focus is on Autonomous Decision Making and Algorithmic Learning Systems, the emerging regulatory landscape and approaches to the impact assessment and societal harm/risk reduction and ethical assurance of these technologies.
Theoretical, as well as practical contributions, are invited to this mini track. Potential topics include, but are not limited to:
- Social and economic impact of AI technologies
- Emerging AI developments
- Ethical and well-being implications of AI
- Emerging regulations
- Emerging codes of practice and standards for AI
AI and Educational Research and Researchers
Mini Track Chairs: Belinda Gimbert with Raeal Moore, Dustin Miller, Dean Cristol and Nick Giester, Vega Systems, London, UK
This mini-track session explores the dynamic intersection of AI and educational evaluation from diverse perspectives. It will delve into the transformative potential of AI in revolutionizing the research process and enhancing researchers' skills. Discover how AI algorithms can refine research questions, analyse vast datasets, and augment evaluation methodologies, leading to deeper insights and more impactful outcomes. Explore innovative techniques for optimizing survey questions and methodologies, leveraging AI's analytical prowess to unlock new avenues of understanding in educational project evaluations. Additionally, critique the realm of AI-driven skill enhancement for researchers. Uncover strategies for leveraging AI to improve interviewing techniques, refine researcher performance, and cultivate a culture of continuous improvement. Learn how AI-powered tools can provide invaluable feedback, aiding in the optimization of evaluation procedures and fostering collaborative learning approaches among researchers. Join us as we navigate the cutting-edge applications of AI in educational project evaluation, empowering researchers to ask better questions, analyse data more effectively, and continuously refine their skills for enhanced evaluation outcomes.
We are inviting submissions of abstracts for presentations including the following:
- Explore how AI algorithms can assist in refining and optimizing research questions for educational project evaluations, leading to more focused and insightful investigations.
- Investigate innovative AI-driven data analysis techniques tailored for educational project evaluation, including machine learning algorithms and natural language processing methods.
- Examine how AI can enhance traditional evaluation methodologies, such as surveys and interviews, by automating processes, improving accuracy, and uncovering hidden patterns in data.
- Discuss strategies for using AI-powered tools to enhance researchers' skills in conducting evaluations, including improving interviewing techniques, data interpretation, and feedback analysis.
- Explore how AI-driven insights can facilitate collaborative learning and knowledge sharing among researchers, fostering a culture of continuous improvement and innovation in educational project evaluation practices.
Examining the Future of AI and Human Systems Integration
Mini Track Chairs: Lori D. Coombs, Marymount University, USA
Responsible Artificial Intelligence (AI) is required for developing a solid global framework that ensures AI considers the best interests of humanity. The scope of this mini track highlights how humanity-centered design influences Human-computer interaction (HCI) and impacts development of Human Machine Interfaces (HMI) and Human-computer Interfaces (HCI) for Human Systems Integration (HSI) purposes. Responsible AI should mitigate bias, ensure privacy, and consider humankind to yield reliable system outputs aimed at attaining the 17 sustainable development goals defined by the UN: no poverty, zero hunger, good health, quality education, gender equality, clean water, clean energy, economic growth, industry innovation, reduced inequalities, sustainable communities, consumption / production, climate action, marine life, terrestrial life, peace/justice, and partnerships for the goals. HSI is an approach for developing systems that focuses on interfaces between humans and complex intelligent systems in operator, maintainer, sustainer, trainer, and designer roles. From a business perspective, the goal is to integrate elements that enhance suitability of delivered systems at the lowest total ownership cost throughout the acquisition and design processes. This mini track studies how interfaces are used in everyday tasks such as touch ID sensors to access touchscreen tablets and mobile phones, as well as GPS voice command technology that allows users to control navigation systems using a voice user interface (VUI) in user-friendly ways. Talks will examine technical aspects of complex intelligent systems, AI bias, the importance of clean data sets, and how wealth created by machines may be distributed as the human workforce is reduced.
Theoretical and practical contributions, are invited to this mini track. Potential topics include, but are not limited to:
- How algorithmic prejudice, negative legacy, and/or underestimation bias in AI affects data collection
- Using AI, ML, Deep Learning, Reinforcement Learning and Neural Networks to enhance platforms (hardware and software)
- Cybersecurity implications associated with critical infrastructures that use HSI
- NextGen platforms and the evolution of human end-users in technology design
- Advances in policy to incorporate HSI planning in global frameworks
- How the draft text of the Recommendation on the Ethics of AI developed by 193 Member states and the United Nations Educational, Scientific & Cultural Organization (UNESCO) impacts HSI by supporting effective implementation