Public Lecture, Keynotes & Panel Discussion

The following speakers have graciously agreed to give public lecture, keynotes, and panel discussion at ALTA 2024.

Public Lecture - Monday 2nd December 5.30pm-6.30pm, Birch Building, ANU

Professor Eduard Hovy - University of Melbourne

Generative LLMs: How they work and where they are headed (Public Lecture Slides)

Register for the Public Lecture

Abstract

Generative AI has unleashed hype and concern. But it is surprising how few people understand how simple it is at heart, and how some of its shortcomings spring from its essential nature and will remain hard to overcome. In this talk I briefly describe the essential process and explore the three principal directions of GenLLM research: making them usable, useful, and understandable.

Bio

Professor Eduard Hovy is Executive Director, Melbourne Connect - a dynamic collaboration between leading organisations and interdisciplinary institutions aimed at leveraging research and emerging technologies to address global challenge - and a Professor in the School of Computing & Information Sciences, University of Melbourne.

Keynotes

Professor Jing Jiang - Australian National University

LLM Evaluation: Writing Styles, Role-playing, and Visual Comprehension (Keynote Slides)

Abstract

Large language models (LLMs) have demonstrated exceptional abilities that extend beyond language understanding and generation. This underscores the need for a more comprehensive evaluation of LLMs that covers a broader spectrum of capabilities beyond traditional NLP tasks. In this talk, I will share some of our recent work on LLM evaluation, with a focus on LLMs’ writing styles and role-playing capabilities, and the abilities of large vision-language models to combine and interpret visual and linguistic signals in complex scenarios.

Bio

Jing Jiang is a Professor in the School of Computing at the Australian National University. Previously she was a Professor and Director of the AI & Data Science Cluster in the School of Computing and Information Systems at the Singapore Management University. Her research interests include natural language processing, text mining, and machine learning. She has received two test-of-time awards for her work on social media analysis, and she was named Singapore’s 100 Women in Tech in 2021. She holds a PhD degree in Computer Science from the University of Illinois Urbana-Champaign.

Professor Steven Bird - Charles Darwin University

Language Technology and the Metacrisis (Keynote Slides)

Abstract

Despite their manifold benefits, language technologies are contributing to several unfolding crises. Small screens deliver mainstream content across the world and entice children of minoritised communities away from their ancestral languages. The data centres that power large language models depend on the mining of ever more rare earth metals from indigenous lands and emit ever more carbon. Malicious actors flood social media with fake news, provoking extremism, division, and war. Common to these crises is content, i.e. language content, increasingly generated and accessed using language technologies. These developments – the language crisis, the environmental crisis, and the meaning crisis – compound each other in what is being referred to as the metacrisis. How are we to respond, then, as a community of practice who is actively developing still more language technologies? I believe that a good first step is to bring our awareness to the matter and to rethink what we are doing. We must be suspicious of purely technological solutions which may only exacerbate problems that were created by our use of technology. Instead, I argue that we should approach the problem as social and cultural. I will share stories from a small and highly multilingual indigenous society who understands language not as sequence data but as social practice, and who understands language resources not as annotated text and speech but as stories and knowledge practices of language owners. I will explore ramifications for our work in the space of language technologies, and propose a relational approach to language technology that avoids extractive processes and centres speech communities.

Bio

Over the past three decades, Steven Bird has been working with minoritised people groups in Africa, Melanesia, Amazonia, and Australia, and exploring how people keep their oral languages and cultures strong. He has held academic appointments at Edinburgh, UPenn, Berkeley, and Melbourne. Steven established the ACL Anthology, the Open Language Archives Community and the Natural Language Toolkit, and is past president of the Association for Computational Linguistics. Since 2017 he has been research professor at Charles Darwin University, where he collaborates with Indigenous leaders and directs the Top End Language Lab, http://language-lab.cdu.edu.au. Steven pursues other language-related projects at http://aikuma.org.

Kyla Quinn - Australian Department of Defence

LLMs are great but …

Abstract

Knowledge workers are crying out for ways to industrialise the boring parts of their jobs, company executives are looking for ways to get a computer to replace all the humans and everyone thinks an LLM will solve all of their problems. But how do we ensure that we aren’t creating a catastrophic failure when we deploy LLMs in situations where we can’t afford to fail?

In this keynote, I will explore some of the issues we need to contend with when we put LLMs and other language technologies into an enterprise. I will touch on data preprocessing, governance, user trust and interpretation.

Bio

Kyla Quinn is the Technical Director of Data and Analytic Services Branch at the Australian Signals Directorate. In this role she provides strategic direction for staff involved in developing analytic tooling, from the AI and ML used in the back end through to user interfaces. Kyla has a background in engineering and linguistics and has recently submitted her PhD which is an evolutionary exploration of paradigm syncretism in the world’s languages through Bayesian analysis and LLM embeddings.

Panel Discussion

Kyla Quinn - Australian Department of Defence

Professor Hanna Suominen - Australian National University

Prof Hanna Suominen is at the forefront of accelerating health impact from personalised precision medicine technology through the application of advanced Data Analytics and Machine/Deep Learning. She is a Professor of Computer Science at the Australian National University (ANU), the Associate Director (Neuroinformatics) of the ANU Eccles Institute of Neuroscience, and the Co-Chair/Executive Leader (Computing & Engineering) of the ANU Our Health in Our Hands strategic initiative. She previously worked for the ANU School of Computing as its first Associate Director (Engagement & Impact), establishing the portfolio. Before this, she was the Leader of the Theory and Applications in Multimodal Pattern Analysis and Natural Language Processing teams at Data61/CSIRO and NICTA, respectively. Hanna obtained her Master of Science (Applied Mathematics) in 2005, followed by a Doctor of Philosophy and Adjunct Professorship (a.k.a. docent) in Computer Science in 2009 and 2013, respectively, from the University of Turku, Finland. In 2019, she became a Senior Fellow of the Higher Education Academy from the ANU Educational Fellowship Scheme. In 2020, she graduated with a Master of Leadership (Curriculum & Pedagogy) from the Monash University. She has 20 years’ experience of working at the interface between technology, education, and health sciences, and is passionate about co-producing research and education with Lightcast and Konan Medical, among others. By bridging disciplines, professions, and areas of expertise, Prof Suominen is co-creating tools that will transform tedious tasks into AI-assisted workflows, thus releasing human labour for more meaningful duties and enhancing Australia’s prosperity.

Luiz Pizzato - Commonwealth Bank

Luiz is a Distinguished AI Scientist at Commonwealth Bank of Australia, where he focuses on building AI innovation that can improve people’s lives. At CommBank, he previously led a large number of data scientists across the business, including the innovation and R&D AI team that created the award winning detection of abuse using AI, weather data model and many early successes of the bank in Generative AI.

Luiz is a data scientist with over 20 years’ experience. Luiz has a PhD in Natural Language Processing (NLP) where he built retrieval algorithms for question answering systems and has deep expertise in Recommender Systems, being the person who defined the area of reciprocal recommender by developing the first algorithms for online dating recommenders. Luiz held previous positions in academia, start-ups and has led innovation labs in global consultant firms.