Prof. Amandeep Sidhu is a prominent figure in the fields of artificial intelligence, machine ethics, health data science, and data security with over 20 years of experience. He has a strong commitment to using data and artificial intelligence (AI) for the benefit of society, as evidenced by his expertise in creating AI governance frameworks and solutions for the health and education sectors. Several important publications and papers on data integration, ontologies, and biomedical data management show his extensive contributions to academia. The Government of India honoured his outstanding performance in 2014 by granting him the esteemed Hind Rattan Award.
From PhD in Computer Science at La Trobe University, Melbourne, to Academic Dean of IHM Australia, it’s an incredible journey. Why did you not take the more traditional path as a computer science engineer? What was the reason for the motivational point that shifted to healthcare?
My very first work-life route led me to Computer Engineering in Chicago, USA where I was working on Neural Networks for data encryption. My passion for Applied AI developed strongly at this point and an interest in doing some research became mandatory. The chance arose when a joint US-Australia research group was examining AI applications in Cancer Proteins. This fell into my interests and refocused the effort on how AI might make a difference in healthcare.
You’ve had senior roles on committees for the Digital Transformation Agency and Cancer Australia. You’ve built relationships across various federal portfolios. Tell me an example of how you used those relationships to promote a meaningful initiative or leverage influence for policy.
A case in point was leading the Aboriginal Community Healthcare Research Project at Curtin University. In collaboration with BHP and the WA Department of Health, we designed a patient-practitioner framework for Type 2 Diabetes Mellitus (T2DM) in Aboriginal Communities in Rural and Remote WA. Using the Community Healthcare Ontology, this model brought clinical guidelines written in Standard Australian English into harmony with Aboriginal English. It provided a culturally sensitive purpose-driven support system to enrich disadvantaged patient communications and for alleviating risk of clinician task overload and burn out.
An Indian diasporic award for your academic contribution is probably one of the greatest honours anybody can receive. How did it affect your career, and how did recognition by such an award open up new doors?
The Hind Ratan Award by President of India in 2014 recognised my 12 years of AI in Health research efforts especially in Asia Pacific. The award solidified government collaborations and relationships at the time for Curtin University (Malaysia Campus). It further cemented my commitment to bringing together AI and healthcare, opening up more possibilities for further collaborative research and policy influence.
Over two decades in Health Data Science and AI, what do you think is the most significant transformation over this period?
Generative AI or GenAI – It has the potential to transform clinical workflows by harnessing disparate sources of unstructured data and automating tedious and error-prone operational work, bringing years of clinical data to a clinician’s fingertips in seconds. It represents a meaningful new tool that can help unlock a piece of the unrealised $1 trillion of improvement potential present in the industry.
Trust is essential if AI is to be an intrinsic part of the healthcare sector. What steps as developers and stakeholders, might we take, to make the AI tools trusted in the lives of our patients as much as they are in the lives of our healthcare providers?
First, the most important thing we need to ensure is that AI tools do not perpetuate existing biases and inaccuracies. While full potential seems promising in creating synthetic medical data for possible improvement in training and research, such data will need to be developed with human oversight to limit inaccuracies. More importantly, a solid risk and legal framework should guide such developments, focusing on data security, fairness, and regulatory compliance. AI should augment healthcare operations rather than replacing them, with human judgment remaining the foundation of patient care.
The COVID-19 pandemic worked as a fast accelerator for adopting digital health technologies. Can you give us some examples of how they developed during the pandemic and what it means for health care’s future?
The COVID-19 pandemic has been an accelerant for rapid development in digital health. Technology was useful and important not only in emergency type services that COVID-19 required, but also for the durability of routine health services. At the same time, the pandemic called attention to the need for foundational investments in connectivity as well as standards for data security and exchange. Increasing awareness and continued investment in infrastructure would be a critical step for ensuring digital health infrastructure incorporates into health care systems in the future.
Pull Quote:
“The Hind Ratan Award by President of India in 2014 recognised my 12 years of AI in Health research efforts especially in Asia Pacific. The award solidified government collaborations and relationships at the time for Curtin University (Malaysia Campus).”