Member Profile – Dr. Daniel Wilson

1. Tell us about yourself

Ko Daniel Wilson ahau. I whakapapa to Ngāpuhi (Te Popoto) and Ngāti Pikiao (Ngāti Hinekura). After finishing school in the late 90’s, my first job was in software development—back then, if you could code, you could get a job. Nearly a decade later, I went to Waipapa Taumata Rau | The University of Auckland and pursued degrees in Philosophy up to PhD, followed by a Master’s in Data Science. I’m a lecturer in Computer Science at Waipapa Taumata Rau, and I’m active in multiple Māori networks and initiatives focused on data ethics, AI ethics digital equity and innovation.

2. What are your areas of interest?

I’m interested in how AI and data can support the flourishing of a diverse range of people. My research focuses on the ethics and politics of digital technologies, particularly artificial intelligence. I’m also interested in articulating what Māori data sovereignty and Māori algorithmic sovereignty mean in various contexts, for example, in health and conservation. In terms of research methods, my philosophy background tends to favour conceptual analysis and framework development, though my more recent rangahau focuses on wānanga and thematic analysis to support more collaborative, culturally grounded inquiry.

3. Tell us about the research/projects you are involved with

I'm involved in several projects at the intersection of artificial intelligence, ethics, and Indigenous data sovereignty. One of the key initiatives is a three-year research project using AI to help diagnose and predict dementia in New Zealand. My role is to ensure different cultural perspectives are taken into account. As part of this, we conducted wānanga-style focus groups to understand the opinions and experiences of those affected by dementia. This generated a lot of discussion about consent and trust when it comes to the use of health data. Participants wanted acknowledgement that health information is tapu, and not to be used ‘willy-nilly’ for exploratory investigations. Nevertheless, there seemed to be general recognition that there are good intentions around the use of health data, which will help our mokopuna.

I’m also part of the Tikanga in Technology project, where we are exploring ways to create algorithms that Māori will benefit from. A lot of performance metrics in algorithms tend to be one-dimensional. So, you might be missing out on many different dimensions related to Māori health and hauora. That includes the spiritual, cultural, and social components.

4. What opportunities do you see for AI to have a real impact in health?

There are a large number of areas where AI can be used to assist in health. AI to identify drugs that can be repurposed for rare diseases is a neat case. AI can assist radiologists in identifying anomalies. And there are also time-savers in AI note-taking tools, among many other uses. A lot of the use cases are patient-centric, though I bet we may have many opportunities to develop tools in Aotearoa that provide support at the level of whānau. Perhaps AI systems could be useful for whānau to ask questions and find out more about how to navigate health systems, what to expect when a whānau member needs treatment, and what other supports may be available, all presented to them in language that they can easily understand. In Aotearoa, we might want to probe further into AI that we might want to develop for our cultural context: What AI support might be offered to make the lives of carers better (who are so important but often neglected by the system)? And what specifically could be created to help solve problems faced by Māori clinicians?

5. What steps should we take to ensure AI has equitable benefits? 

From the perspective of equity for Māori from AI there are a number of factors we should take into consideration. First, we need more Māori capability and capacity in AI health innovation. Second, AI finds patterns from the past and uses these to make inferences about the future. So we need to take care that as we create these AI models, we are not also reproducing patterns of health inequity for Māori. Third, the biomedical model of health needs to expanded to take in a more holistic, hauora approach (including social and spiritual wellbeing). This re-framing of health will lead to require AI tools bespoke to our local context. Fourth, we need to work more respectfully with people whose data is being used to make these models. An opportunity is being missed to inform and involve people—including Māori communities—and get everyone on the same page about what is acceptable. And of course, Māori AI projects need Māori governance as well as adequate resourcing.

This article is part of a series of profiles on our network’s members aimed at increasing collaboration. If you you’d like to get in touch with Daniel to learn more, contact him here: daniel.wilson@auckland.ac.nz