[LINK] Australian Government Trial of Generative AI for Law, Education, Health, and Aged Care

[Tom Worthington]

On 7/3/24 12:53, Roger Clarke wrote:
> Why not ask Copilot what could possibly go wrong with a 6-month trial of 
> Copilot by 50 Australian Public Service (APS) agencies?

I asked Copilot what could go wrong with a trial by the APS. It gave me 
a reworded version of the APS media release, saying how wonderful the 
results would be.

But when I asked about "Generative AI", rather than "Copilot", I got a 
still mostly positive, but more more critical answer:

	"The trial of Generative AI by the Australian Public Service (APS), 
while promising, also carries potential risks and challenges. Let’s 
explore some of the possible pitfalls:

Bias and Fairness:
Generative AI models learn from existing data, which can inadvertently 
perpetuate biases present in that data.
If the training data contains biases related to gender, race, or other 
factors, the generated content may also exhibit these biases.
APS agencies must be vigilant in ensuring fairness and avoiding 
discriminatory outcomes.

Quality and Accuracy:
Generative AI tools can produce impressive results, but they are not 
infallible.
There’s a risk of generating inaccurate or misleading information, 
especially if the model encounters novel scenarios.
APS staff should critically evaluate the output and cross-check it with 
reliable sources.

Privacy and Security:
Copilot and similar tools may inadvertently leak sensitive information.
APS agencies must be cautious when using generative AI for drafting 
internal documents or handling confidential matters.
Proper security protocols and data protection measures are essential.

Dependency and Overreliance:
Relying too heavily on generative AI could lead to a dependency on 
automated content.
APS staff might become complacent and overlook critical thinking or 
creativity.
Striking the right balance between automation and human judgment is crucial.

Ethical Dilemmas:
Generative AI can create content that poses ethical dilemmas.
For instance, if the model generates potentially harmful advice or 
misinformation, APS staff must navigate how to address it responsibly.

Lack of Context Understanding:
AI models lack true understanding of context and intent.
Copilot might misinterpret nuances or fail to grasp the broader 
implications of its output.
Human oversight is necessary to ensure context-aware communication.

Unintended Consequences:
The trial could lead to unforeseen consequences.
APS agencies should closely monitor the impact of generative AI on their 
workflows and adjust accordingly.

User Training and Adaptation:
Staff need proper training to use generative AI effectively.
Learning how to interact with Copilot, interpret its suggestions, and 
provide feedback is essential.

Public Perception and Trust:
If generative AI produces subpar or controversial content, public trust 
in APS communications may erode.
Transparent communication about the use of AI can mitigate this risk.

Legal and Accountability Issues:
APS agencies must clarify accountability for AI-generated content.
Who is responsible if an error occurs? How do we handle legal implications?

These questions need clear answers.

In summary, while Generative AI offers immense potential, its 
implementation requires thoughtful planning, ongoing evaluation, and a 
commitment to responsible use within the APS ."



-- 
Tom Worthington http://www.tomw.net.au
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