AI suicide surveillance with Turning Point
June 23, 2019
Wray, Dan and Debbie at Google Launchpad, 15/05/2019
Along with Prof. Dan Lubman’s team at Turning Point, and funded through Google’s innovative AI for Social Good programme, I’ll be developing an AI system to accelerate “coding” (a form of content analysis) of ambulance records so we can understand the nature of suicide in Australia. The local press has it so:
Google taps local addiction service to build AI suicide surveillance system
As the Google blurb says:
By using AI tools to analyze these records, Turning Point, a national center within Eastern Health, will uncover critical suicide trends and potential points of intervention to better inform policy and public health responses.
For us researchers, it means unifying a bunch technologies that I’ve been working in for a while like active learning, multi-label classification, multi-task learning and crowd-sourcing. But most importantly, all these need to be placed in the context of doing accurate and properly monitored coding while at the same time trying to minimise costly expert (human) effort. This is important stuff for NGOs and health organisations so we’re really excited by the application opportunities this can give us all.
In mid May, Dan Lubman, Debbie Scott and I flew off to Google’s Lauchpad Space in San Francisco to spend a week with other members of the programme for a bootcamp, to brainstorm about our project and get coaching from Google’s experts. Google has a lot of other plans for us to, in terms of supporting the development, which we are very grateful for! The Google advisors were fabulous. They have all sorts of practical tech and AI knowledge, and a real diversity of start-up experts.
Dan, Debbie and I left the event with a whole different perspective on what we could do and what we should be doing initially. We then set about the process of making change within Turning Point. Turning Point is a sophisticated organisation working on mental health. Yes, they’d integrated all sorts of computer systems and interfaces in their daily work, in fact a key reason behind their success to date, but we came away from the Google event realising just how much more we could do with AI.
Bayesian Models 
[…] has been successful in receiving a $1.2 million grant through the Google AI Impact Challenge. Prof Wray Buntine and Principle investigator Prof. Dan Lubman from Turning Point aim to adapt AI methodologies to […]
[…] here, I get a brief shots at 0:14 and 0:20 and Sam gets an interview at 0:49). Following our Launchpad event to San Francisco, the London event was an in depth technology review so we could help design our system. We had a […]