Multiplicity: The Curious Case of Arbitrariness in Machine Learning | AAAI-26 Edu Video Winner
➡️ AAAI-26 Educational AI Video Winner
➡️ https://aaai.org/about-aaai/aaai-awards/aaai-educational-ai-videos/
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Multiplicity: The Curious Case of Arbitrariness in Machine Learning
By: Prakhar Ganesh
What actually is AI? | AAAI-26 Educational Video Winner
➡️ AAAI-26 Educational AI Video Winner
➡️ https://aaai.org/about-aaai/aaai-awards/aaai-educational-ai-videos/
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🤖 The term AI is used everywhere, but what actually is AI and what can it do? 🤔
This is the English version of the first topic of a German Video Series on the topic AI, which is also published as articles at klaro-ki.de. 📝
Author: Felix Haase
Team: Chris Zimmerer, Sanne Grabisch, Carolin Wienrich, Ute Schmid
Sources for content and images:
Russell, Stuart J., and Peter Norvig. Artificial Intelligence: A Modern Approach. Pearson, 2016. https://thuvienso.hoasen.edu.vn/handle/123456789/8967.
Turing, A. M. “Computing Machinery and Intelligence,” 1950. https://cs.mcgill.ca/~dprecup/courses/AI/Materials/turing1950.pdf.
Weizenbaum, Joseph. “ELIZA—A Computer Program for the Study of Natural Language Communication between Man and Machine.” Communications of the ACM 9, no. 1 (January 1966): 36–45. https://doi.org/10.1145/365153.365168.
Melle, William van. “MYCIN: A Knowledge-Based Consultation Program for Infectious Disease Diagnosis.” International Journal of Man-Machine Studies 10, no. 3 (May 1, 1978): 313–22. https://doi.org/10.1016/S0020-7373(78)80049-2.
Dildar, Mehwish, Shumaila Akram, Muhammad Irfan, Hikmat Ullah Khan, Muhammad Ramzan, Abdur Rehman Mahmood, Soliman Ayed Alsaiari, Abdul Hakeem M. Saeed, Mohammed Olaythah Alraddadi, and Mater Hussen Mahnashi. “Skin Cancer Detection: A Review Using Deep Learning Techniques.” International Journal of Environmental Research and Public Health 18, no. 10 (January 2021): 5479. https://doi.org/10.3390/ijerph18105479.
AAAI Presidential Panel on Factuality And Trustworthiness
• Understanding Factuality: Why preventing false outputs from large language models remains AI's toughest problem
• Beyond Accuracy: How trustworthiness encompasses understandability, robustness, and human values—essential for deploying AI in high-stakes environments
• Practical Solutions: Explore proven approaches including fine-tuning, retrieval-augmented generation, output verification, and model simplification strategies
Expert Panel
Oren Etzioni, Founder TrueMedia.org, Professor Emeritus University of Washington
Henry Kautz, Professor of Computer Science, University of Virginia at Charlottesville
Kush R. Varshney, IBM Fellow and Co-Director IBM Science for Social Good
Moderator: Francesca Rossi, AAAI past president, IBM Fellow and AI Ethics Global Leader.
This panel brings together leading voices in AI research to provide balanced perspectives. Whether you're an AI professional, researcher, or simply curious about the future of artificial intelligence, this discussion will offer valuable insights into one of technology's most consequential frontiers.
AAAI Presidential Panel Zoom - AI Agents
AI agents have come a long way, starting from rule-based entities and evolving into multi-agent systems powered by a combination of traditional tools and large language models. This evolution has brought new opportunities but also raises new challenges.
What You'll Learn:
• How multi-agent systems evolved from rule-based systems to complex cooperative frameworks built on generative AI, and what is really different in the modern notion of an agentic AI system.
• The opportunities and challenges of agentic AI; exploring how LLMs enable more flexible decision-making while introducing new questions around efficiency, complexity, open-endedness, trust, and reliability.
• How to address issues of alignment and governance in agentic AI systems.
Expert Panel
Atoosa Kasirzadeh, Assistant Professor, Carnegie Mellon University.
Kartik Talamadupula, Distinguished Architect (AI), Oracle.
Michael Wooldridge, AAAI president elect, Ashall Professor of Foundations of Artificial Intelligence, University of Oxford.
Moderator: Francesca Rossi, AAAI past president, IBM Fellow and Global Leader for Responsible AI and AI Governance.
This panel brings together leading voices in AI research to provide balanced perspectives. Whether you're an AI professional, researcher, or simply curious about the future of artificial intelligence, this discussion will offer valuable insights into one of technology's most consequential frontiers.
Human-Centric AI and Collaborative AI Systems with Professor Andreea Bobu
About Professor Andreea Bobu:
Andreea Bobu is an Assistant Professor at MIT and leads the Collaborative Learning and Autonomy Research (CLEAR) Lab, where she develops autonomous agents that learn to act for, with, and around people. Her research focuses on aligning robot behavior with human expectations by studying how agents can acquire the right supervision—whether from direct human input or priors—build shared task representations with users, and address misalignment from differing human models. Drawing from deep learning, inverse reinforcement learning, and Bayesian inference, her work is grounded in experiments with systems like assistive robot arms and large language models. Prof. Bobu earned her Ph.D. in EECS from UC Berkeley with Anca Dragan, was a Research Scientist at the AI Institute, and previously interned at NVIDIA’s Robotics Lab. She holds a B.S. in Computer Science from MIT.
This replaces the original version uploaded June 30th, 2025, which had a technical issue in the recording.
AI & Sustainability
Artificial intelligence is rapidly transforming industries worldwide and holds immense potential to drive sustainability progress, from accelerating the net-zero energy transition to enhancing climate resilience. Its deployment also presents unique challenges, including increasing energy and water demands that are straining local electricity grids and water resources in certain regions.
Our expert panelists will explore the critical balance between harnessing AI's potential and managing its environmental impact, covering:
The Real Impact: While AI compute currently represents a very small share of global energy consumption, understanding its rapid growth and regional effects on infrastructure
Beyond Energy Consumption: Why AI's most significant sustainability impacts, both positive and negative, stem from how it's deployed and used rather than just the energy consumed in training models
AI as a Climate Solution: How AI is accelerating breakthroughs in advanced battery materials, carbon removal technologies, and high-precision climate modeling
Managing the Challenges: Strategies for investing in grid capacity and innovations that enhance hardware and software efficiency
Expert Panel
Eric Horvitz, Chief Scientific Officer, Microsoft
Hiroaki Kitano, President ＆ CEO at Sony Computer Science Laboratories (Sony CSL) and Chief Technology Fellow at Sony Group Corporation
Stuart Russell, Professor; Michael H. Smith and Lotfi A. Zadeh Chair in Engineering, University of California, Berkley
Moderator: Francesca Rossi, AAAI past president, IBM Fellow and AI Ethics Global Leader.
This panel brings together leading voices in AI research to provide balanced perspectives. Whether you're an AI professional, researcher, or simply curious about the future of artificial intelligence, this discussion will offer valuable insights into one of technology's most consequential frontiers.
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Multiplicity: The Curious Case of Arbitrariness in Machine Learning | AAAI-26 Edu Video Winner