2026 Fall IEEE OKC Webinar Series | IEEE Computer Society Distinguished Visitor
IEEE Oklahoma City invites you to join the event below, organized by Oklahoma International Publishing, as part of its 2026 Fall OkIP Conferences on Thursday, October 1, 2026.
This virtual event is free of charge to IEEE members. Please register ahead of time to receive the proper instructions for remote participation:
>> IEEE Computer Society Distinguished Visitor Speaker:
Prof. Saman Halgamuge, Fellow of IEEE, IET, AAIA, and NASSL
Full Professor
The University of Melbourne, Australia
>> Talk:
AI Social Responsibility Perspectives
>>> Abstract:
The rapid adoption of Artificial Intelligence (AI) since the break through paper on Transformers in 2017, following breakthroughs in deep learning and Large Language Models (LLMs), has transformed almost every discipline and sector of society. In this talk, I will first examine why the unprecedented uptake of AI requires us to think seriously about the social responsibilities that accompany its development and use.
From a technical perspective, LLMs are trained on vast corpora of human-generated text and subsequently fine-tuned to produce user-friendly and task-specific outputs. Their capabilities arise from the collective knowledge, creativity, and experiences embedded in this human-curated data. However, the same dependence on human-generated content also makes these systems vulnerable to bias, manipulation, misinformation, and misuse.
The societal implications of deploying LLMs trained on largely unseen datasets deserve critical examination. Questions of fairness, accountability, transparency, and regulation become increasingly important when a small number of institutions control the development of systems that influence millions of people. I argue that several concerning trends have emerged alongside the rapid adoption of AI:
Overreliance on AI-generated answers: Many users increasingly assume that LLMs provide correct answers in the same way a calculator produces a correct numerical result. This misconception is particularly concerning when young people seek advice from AI systems on personal, educational, or emotional matters, potentially replacing trusted friends, educators, or trained professionals.
Unconscious influence on human behaviour: Commercial, political, or cultural biases embedded (e.g. marketing information) within training data may subtly shape opinions, preferences, and consumption habits without users being fully aware of the influence.
Erosion of human expertise: As AI tools increasingly automate writing, coding, design, and analytical tasks, professionals may lose important skills if education and assessment systems do not continue to cultivate and evaluate independent human capability.
Malicious adaptation of AI systems: AI technologies can be retrained or manipulated to spread misinformation, deepen social divisions, undermine cultures, or destabilise communities and nations.
AI privilege and geopolitical inequality: Access to advanced AI increasingly depends on computing infrastructure, specialised chips, data centres, and energy resources, which raises concerns that AI may reinforce existing global inequalities, concentrating power and influence among a small number of nations and corporations.
These concerns highlight the need for a broader discussion of social responsibility, extending beyond the technology itself to encompass the institutions, governments, and societies that develop and deploy it.
The second part of the talk will explore the social responsibility associated with the future trajectory of AI. Technologies and their future trajectories are rarely neutral; they are shaped by the priorities, values, and resources of the societies that create them. AI is no exception. Around the world, nations are competing to become regional or global AI powers, investing heavily in infrastructure, talent, and innovation.
Yet the benefits of AI should not be limited to those with economic, political, or technological advantages. While AI will undoubtedly transform labour markets, as previous technological revolutions have done, social responsibility demands that we also consider the wellbeing of those whose livelihoods and communities may be disrupted. Human dignity, fairness, and inclusion must remain central considerations in the AI transition.
Similarly, ethical claims about AI cannot be accepted uncritically if the values embedded within these systems are not transparent. Responsible AI requires openness about design choices, training processes, governance structures, and accountability mechanisms.
Finally, AI's environmental footprint must also be considered. Training and operating large-scale AI systems require substantial amounts of energy, water, computing hardware, and critical materials. The pursuit of AI advancement should not come at the expense of environmental sustainability or equitable access to resources.
The talk will conclude with a brief overview of our ongoing research addressing these challenges and exploring pathways towards a more socially responsible and inclusive AI future.
>>> About the speaker:
Prof Saman Halgamuge, Fellow of IEEE, IET, AAIA and NASSL is a Professor at The University of Melbourne. Previously, he was a member of the Australian Research Council grant assessment panel and the Head of Engineering School at Australian National University. He also served as Associate Dean for the Faculty of Engineering at the University of Melbourne.
He obtained the Dipl.-Ing and Ph.D. degrees in data engineering from the Technical University of Darmstadt, Germany. He is listed as a top 2% most cited researcher for AI and Image Processing in the Stanford database. He is a distinguished visitor appointed by the IEEE Computer Society (2025-27) and was a distinguished Lecturer of IEEE Computational Intelligence Society (2018-21).
His research is funded by Australian Research Council, National Health and Medical Research Council, US DoD Biomedical Research program and international industry (e.g. Bosch Germany, Google US).
He graduated over 50 PhD students in Australia. https://scholar.google.com.au/citations?hl=en&user=9cafqywAAAAJ&pagesize=80&view_op=list_works&sortby=pubdate
Co-sponsored by: Pierre Tiako
Agenda:
08:55am – 09:00am Virtual Meeting Speaker Introduction
09:00am – 09:45am Virtual Meeting Keynote
09:45pm – 10:00am Virtual Meeting Q &A
Virtual: https://events.vtools.ieee.org/m/567625