AI & MACHINE LEARNING | TECH IN GOV 2022



Frederic Clarke, Principal Data Scientist and Director, Machine Intelligence and Novel Data Solutions, Australian Bureau of Statistics, Australia

Frederic Clarke |  | Australian Bureau of Statistics » speaking at Tech in Gov

Dr Sue Keay, Chair, Robotics Australia Group, Australia

Simon Lucey, Director, Australian Institute for Machine Learning, Australia

Dr Ian Oppermann, NSW Chief Data Scientist and UTS Industry Professor, NSW Department of Customer Service, Australia

last published: 12/Jan/22 05:35 GMT

Artificial Intelligence & Machine Learning, Wednesday 9 February 2022

Dr Ian Oppermann
Artificial Intelligence & Machine Learning
11:10

Implementing the use of AI across government agencies

  • Use of AI comes with the same challenges of data sharing and use. It also comes with challenges unique to AI
  • Building assurance frameworks is an important step in deploying AI
  • This presentation will explore sensitivities, considerations and frameworks for use of AI in government.
Simon Lucey
Artificial Intelligence & Machine Learning
11:30

Efficient Government through AI?

  • AI is revolutionising all aspects of our economy and society, government is no exception.
  • It’s incumbent upon the Australian Government at local, state and federal level, to embrace this change.
  • AIML is attempting to lead this transition by acting as a conduit between world class researchers and major Australian stakeholders, including industry and government services.
Dr Sue Keay
Artificial Intelligence & Machine Learning
11:50

The State of the AI industry in Australia

  • Find out about the local AI capability accessible in Australia and where our strengths and weaknesses lie
  • Hear about the common challenges that AI companies face in dealing with government departments
  • Consider the policy and procurement changes required to embrace the opportunities promised by emerging tech such as AI
Frederic Clarke
Artificial Intelligence & Machine Learning
12:10

The use of AI and emerging methods for extracting insights from multisource data

  • Supporting the information needs of decision makers in a complex, volatile environment
  • Applying new machine reasoning and learning methods to knowledge representation and discovery
  • Enabling the analysis of massive heterogeneous data sets though high performance computing
last published: 12/Jan/22 05:35

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