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Regular discussions on AI things...

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Trustworthiness and hallucinations - we need critical analysis

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What is CAUDIT doing??

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Being AI augmented EAs!!

See Gartner AI in EA report

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https://go8.edu.au/group-of-eight-principles-on-the-use-of-generative-artificial-intelligence

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Linking GenAI with RPA and processes/Data - pull data from source systems and automate processes.

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Ethics in L&T and admin

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When should AI be limited, vs where it is mandatory?

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Hallucinations that people believe are truth. AI needs to know when to say "I don't know"

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Rethink out how we teach!

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Help us to scale our teaching and assessment management!

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Augmentation of our core learning capabilities

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To develop an AI strategy

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Come up with approaches to use AI to detect the usage of AI.

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Developing best practices...

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Harnessing AI to support the teaching of writing and providing the guardrails to enforce original content drafting.

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Policy to suffocate or enable?

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Our Digital Literacies group is establishing an advisory with a single focus on creating and maintaining a CoP for academics about the use of generative AI tools in learning and teaching

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Transparency of when AI generated data is in use; keeping human in the loop.

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immersive learning

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Quality assurance - teaching and learning.

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Sharing of use cases, learnings and challenges.

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misconceptions AI is a chatbot

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AI is still on the upward side of the Hype Cycle. Once it passes the peak, there will be lots of dis-enchantment and regret.

Try to imagine the state after and long-term value.

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Prompt libraries?

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Speed of change means by the time it's implemented it's close to obsolete.

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Writing a business case and article about potentially using Grammarly for Education and how free and individual license types allows some client data to train the LLM. This creates a concern for unpublished research data getting out in the wild.

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Teaching/Learning Assistance

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AI Embedded everywhere!

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Acting ethically, avoiding bias disadvantaging cohorts that may have biased inbuilt into model parameters.

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Cost, scale, no one really knowing what they're doing, vendors in candy pink striped blazers hawking GenAI solutions to everything to anyone who'll listen (and many who won't)

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Governance vs Rapid pace of AI development

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Virtual assistant / Chatbot

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Part of the Enterprise AI leadership team

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Decisions being driven by technology.

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Setting foundations and guidelines

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External drivers from governing bodies (e.g. TEQSA).

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Governance

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Understand product uptake and outcome of PoCs and other evals.

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Academic Integrity

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Consider competing AIs from different vendor and how they might work together - or not.

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After they have decided on solutions and looking to implement - Often resulting in turning them back to requirements and design

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Understanding business requirements, and making sure that AI is not a wild west within the University / appropriate policies and guidance are in place.

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On the T&L working party and the ICT working party

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Oversight and visibility of where AI is being used.

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Software development & finding it's way into formal documentation.

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Four pathways for regulatory and policy intervention:
1) Prevention, transparency and accountability
2) Access to justice and legal redress mechanisms
3) Diversity, inclusion, representation and participation
4) Democratic participation, public awareness raising and capacity building (this one is ours)

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Sorta - I advised on the paper that went to the VC, dunno how it'll play out when we get to the point of setting up organisational structures.

Created GenAI data use guidelines when Edge CoPilot (nee Bing Enterprise Chat) went live in September.

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Have a T&L AI working group and subgroups working on five themes to understand what we need to do.

Also have IT working out the approach to ensure we dont have privacy issues and we understand ROI

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The hope is: efficiency improvements, rather than rationalizing away FTEs.

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defining policies and controls to protect our people and information

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Yes, iam invoved in advice guidance, ethical use, guard rails and feeding into the policy and bestpractices.

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Data to feed the ravenous maw.

Seriously: infrmation structures and integration that allows the machine to access and match content across the entire enterprise.

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Researching capabilities/use cases. Writing Polices around usages

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Misconceptions of where it will provide benefits

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Informed but not involved as of yet. A lot of activity happening in the business which IT is getting a wrangle on.

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Microsoft 365 and Windows Copilots:

Challenges with security and access

Edge Copilot: Now fully integrated into our secure browser environment and staff can use it.

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Developing future state for AI governance.

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Have AI working group with RAG patterns & landing zones for AWS (Bedrock) and Azure (OpenAI). Using IBM Watson to drive chat. Bing Enterprise for end-users.

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curious requests for CoPilot at the M365 level

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data classification & sensitivity labelling

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Distributed and bitty. Now starting to put together an attempt at a central structure. Technology wise - all Microsoft all the time.

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Deakin: policies for T&L and research ethics are in place. Some automations in use (UiPath); setting up PoC for Copilot.

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information governance

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A time saver and a smarter way of working.

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leading creation of AI guardrail

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Poc's for a number projects in both Copilot and Amazon Q.

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writing an AI strategy

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sadly on all of the committees

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AI strategy panel has been formed includes all parts of the university from VC down

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magic wand

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At UTA , the Academic side is struggling with AI detection and the realization this is a losing battle.

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silver-bullet panacea

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everything everywhere all at once