Emerging Trends in Data Science and AI in 2022

VIDEO OF THE WEBINAR:

Moderator:

Distinguished Professor Kerrie Mengersen QUT Centre for Data Science

Panellists:

Professor Will Browne ARM Hub, QUT School of Electrical Engineering & Robotics

Associate Professor Alice Payne QUT School of Design

Associate Professor Grant Hamilton QUT School of Biology & Environmental Science

Professor Richi Nayak QUT School of Computer Science

More about the Panel Session Topics:

Professor Will Browne – Three Data Science and AI tools Advanced Robotics in Manufacturing need to become more collaborative and effective

Artificial intelligence and data science tools are needed for Manufacturing Robotics to escape being stuck in assembly lines. In order to be more mobile and collaborate with humans on diverse tasks from welding complex shapes to dehanding bananas, three emerging technologies are needed. Firstly, Digital Twins need to become more available for small to medium enterprises to create digital models of systems that can capture data, determine essential features and enable AI to optimise processes. Imaginative solutions can be tested without damaging actual plant (or plants in the case of bananas). Secondly, eXplainable AI (XAI) is required for understandable and transparent interaction with the proposed solutions, such that long-held practices can be disrupted successfully. Finally, and most futuristic, abstract reasoning is needed to determine the higher-order patterns available in data. The manufacturing world is too complex, diverse and uncertain to produce location/state specific solutions where the ability to abstract just the important characteristics of a task/solution is essential for effective real-world operation.

Associate Professor Alice Payne – Digitising a material world: problems, promises and prospects for the global fashion systemData science and AI are leading to numerous innovations throughout the fashion system – from tools to increase supply chain transparency, to respond faster to consumer desire, to trace fibres from cradle to grave, or to create clothes that only ever exist virtually. However, which of these innovations will help create a system better for people and better for the living world? In a world of resource constraints, climate crisis and injustice – the most exciting tools promise genuine system change, rather than a digitised business-as-usual.

Associate Professor Grant Hamilton – Biodiversity is in crisis. Can AI help?

The recent listing of the koala as endangered in 3 states is a uniquely Australian symbol of the calamitous decline in biodiversity. If even the so called ‘charismatic megafauna’ are being driven to extinction, this is a clear demonstration that things need to change. While improved analytics may be part of the solution, we also need to think deeply about the connections – how we are collecting the data, what it means, and how it can be delivered to the people and organisations making meaningful on-ground changes. In this presentation I’ll give an overview of the Conservation AI Hub and how we are aiming to create a powerful new system for conservation

Professor Richi Nayak – Advances in Text Mining and Applications

Abstract: About 90 percent of data that exist in businesses is unstructured and its volumes are growing rapidly. Text Mining or Natural Language Processing is a subfield of AI and Machine Learning which enables computers to interpret, process and analyse text data. You may be familiar with many applications such as translation, chatbots or autocorrelation. Text mining offers the capability to businesses to analyse their text data reliably and build autonomous applications. I will present use cases and applications related to different text mining capabilities.