The Use of Generative AI
January 2024
Position Statement
Summary
At Ausmed, we are at the forefront of educational innovation with the aim to leverage generative artificial intelligence (AI) to enhance the learning experience for our users. We are committed to a responsible and ethical approach to benefit health professionals while safeguarding the privacy of our users and complying with legal obligations.
Definitions
Generative AI
Generative AI is a technology that allows for the creation of content autonomously rather than relying solely on predefined rules or explicit programming. Unlike traditional AI, which is designed for specific tasks, generative AI possesses the ability to generate novel and diverse outputs, often mimicking human-like creativity and problem-solving.
At the core of generative AI is the concept of generative models, which are trained on vast datasets to understand patterns, correlations and structures inherent in the data. These models leverage this acquired knowledge, combined with probability weightings, to generate new, realistic data that shares similarities with the training examples. One of the groundbreaking advancements in generative AI is the development of models like GPT (Generative Pre-trained Transformer), which has demonstrated exceptional capabilities in language processing, image generation and even code synthesis.
This innovative technology has the potential to revolutionise various fields, including art, design, marketing and even scientific research.
However, as we delve into the promising realms of generative AI, it's crucial to address potential challenges and misconceptions. One common misconception is the notion that generative AI operates flawlessly without any risks. In reality, there may be instances where the generated content exhibits biases or unintended outputs. It's imperative to recognise that generative models learn from vast datasets, and any biases present in these datasets can be reflected in the generated content.
Moreover, another challenge lies in the interpretability of generative AI outcomes. The intricate nature of the underlying algorithms makes it challenging to precisely understand how the model arrives at specific conclusions, and challenging to reproduce consistent results. This lack of transparency can raise concerns about accountability and ethical usage.
By acknowledging these challenges, we underscore our commitment and position at Ausmed to not only harness the benefits of generative AI but also to actively address and mitigate these challenges. Our dedication to responsible and ethical use ensures that we continuously evaluate and refine our generative AI processes to deliver content that meets the highest standards of accuracy, fairness and reliability.
Ausmed Education’s position on the use of generative AI
Why we use generative AI
Generative AI assists the content team at Ausmed in generating closed captions and transcripts, and streamlines the content creation process. This allows us to offer a more diverse and dynamic range of educational material, benefiting learners across various disciplines. Automatically generated transcripts and closed captions also promote accessibility for learners living with a disability or who speak English as a second language.
Integral part of the future of teaching and learning
Generative AI is poised to be an integral part of the future of planning, learning and documenting by enabling adaptive, personalised and efficient educational experiences. The technology ensures that educational content and Ausmed’s various products remain current, aligning with the rapidly evolving landscape of various industries.
In support of its position, Ausmed Education mitigates risks to the technology
Privacy
We acknowledge the potential privacy concerns associated with generative AI. To address these concerns, we strictly adhere to data protection regulations such asthe General Data Protection Regulation (the EU regulation) and the Australia Privacy Act. This ensures that user data is handled responsibly and transparently.
Ausmed does not share personally identifiable information (PII) with third-party AI companies. Refer to our privacy policy.
Copyright
Copyright regulations are evolving around the use of generative AI. Our commitment to copyright compliance is unwavering. We respect intellectual property rights and ensure that all generated content complies with current and future copyright regulations.
Content Review
We recognise the risk of producing inaccurate or offensive content. For this reason, Ausmed reviews and curates generated content to ensure high standards of reliability and appropriateness.
References:
eSafety Commissioner 2023, Generative AI – Position Statement, Australian Government, https://www.esafety.gov.au/industry/tech-trends-and-challenges/generative-ai
Khan Academy 2023, New Tools For a New Age: FAQ, Khan Academy, https://www.khanacademy.org/college-careers-more/ai-for-education/x68ea37461197a514:ai-for-education-unit-1/x68ea37461197a514:ai-welcome-to-the-future-of-education/a/ai-faq
GOV.UK 2023, Generative Artificial Intelligence (AI) in Education, UK Government, https://www.gov.uk/government/publications/generative-artificial-intelligence-in-education/generative-artificial-intelligence-ai-in-education
Stanford HAI 2023, Generative AI: Perspectives From Stanford HAI, Stanford University, https://hai.stanford.edu/sites/default/files/2023-03/Generative_AI_HAI_Perspectives.pdf
Acemoglu, D, Autor, A & Johnson, S 2023, Can We Have Pro-Worker AI? Choosing a Path of Machines in Service of Minds, Massachusetts Institute of Technology, https://computing.mit.edu/wp-content/uploads/2023/11/Pro-Worker-AI-Policy-Memo20.pdf
Ausmed Education Pty Ltd 2024