It was a summery evening in London on the 23rd September, and some of the best and brightest minds in AI and Health Equity were gathered for Goals House @ UNGA.
Zooming in from New York, and also together in London we heard from:
Miriam Sabin, Senior Editor at The Lancet
Regina Barzilay, School of Engineering Distinguished Professor of AI and Health, AI faculty lead for MIT Jameel Clinic
Dr. Edson Amaro Jr., Head of the Big Data Initiative at the Albert Einstein Hospital, São Paulo
Dina Katabi, Prof. Electrical Engineering and Computer Science at MIT, Director of the MIT Wireless Center
Dr. Najat Khan, Chief Data Science Officer at Janssen R&D
Ziad Obermeyer, Associate Professor at UC Berkeley
The evening covered everything from using AI to improve access by monitoring your health in your home, to questions of global health inequities due to the unequal digitisation of health systems.
Tariq Kokhar, Head of Data Science for Health at the Wellcome Trust, opened the London gathering by highlighting the complexity of the matter at hand: no single field, discipline or sector will hold the solution to achieving health equity. Tariq concluded with a call to action to bring together more like-minded people working to improving health equity through data science.
So... here we are! 🥳
Over the past few years we've noticed the growing research and innovation at the intersection of data science and health equity, and yet we've found that many groups, people and organisations have struggled to find one another, spread as we are across so many disciplines and sectors. Many of us have sought receptive audiences for our various questions, events, funding calls, or collaboration opportunities.
Data Science for Health Equity is an independent community that brings together experts, enthusiasts and hobbyists working at the intersection of data science and health inequalities to ensure that the latest research and innovations improve health equity.
We plan on doing this by:
Defining a shared space to bring together the disparate communities working to better understand and improve health inequalities
Providing a platform to share learnings, best practice and individual/institutional priorities
Curating the latest resources, funding, tools and research
Assimilating and generating new insights, tools or solutions from within the community's collective
We're open to anyone with an interest in data science, health equity, ethics and everything in-between but we've already seen interest from:
Academics (working in fairness/ethics, statistics/machine learning and public health/health inequalities)
Policy makers (both national and local) seeking to adopt and implement data-driven solutions
Private sector, particularly those developing products for clinical or public health environments
Funders looking to support projects and programs that enhance health equity through data science
Public media aiming to understand more of the challenges and inform the public debate around health inequalities
Third sector, particularly citizen voice bodies and justice advocacy groups
How can you get involved?
We're excited to get going but we also want to ensure we are developing this community (even at its earliest stages) in a way that is useful to all of those doing great stuff already, pulling together the excellent (but maybe a bit disconnected) work that's out there already.
There are three main ways you can get involved!
Be kept in the looping by signing up to hear updates, following us on Twitter (@DS_x_HE) and joining our Slack workspace
Getting your hands dirty behind the scenes by helping in organising and curating community activities
Partnering with us to support your organisation's work and activities
Or anything else, don't hesitate to get in contact!
As the event concluded:
...No one field of discipline alone will solve this. We need to come together as a community with a shared interest in using data science to achieve health equity!
We look forward to building this community together with you! Join the ride!
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