At DataKind, we use machine learning and AI to address complex challenges like global health, education and climate change. We’ve been using satellite imagery to detect crop disease in Ethiopia, open data to combat corruption in the extractives industry and predictive modeling to identify food bank users in need of extra help. We bridge the gap between visionary social impact leaders and expert technologists to create safer, more ethical technologies to not just battle the problems we have today, but to build a better tomorrow.
Many of our projects involve sensitive data on vulnerable groups. We acknowledge the responsibility we have to use this data and this power appropriately. In 2017 we crowdsourced a set of practical principles within our community. This is our Hippocratic oath:
1. I will actively seek to consider harms and benefits of my data work.
2. I will actively seek to understand the context of the data and tools I use.
3. I will actively seek to allow others to understand the data and analysis choices I have made, now and for the future.
4. I will actively seek to understand my own limits and the limits of the organisations involved.
5. I will debate and discuss the ethical choices
This talk will touch on examples of projects that have used machine learning and AI for social good, and discuss some of the ethical conundrums they raise.
Kate is a data scientist at the One Campaign and a Chapter Lead at DataKind UK. She first built a career in investment management at Värde Partners, where she worked in roles across risk management, trading, investment, data strategy and portfolio strategy. In late 2015, she left to pursue her passions for data science and social impact; today she consults with charities, NGOs and corporates to find stories and insights in data.
Gianfranco is a data scientist and crowdsourcing specialist and a DataKind UK Chapter Lead. Di.Co.Im. is the consulting startup he founded to explore how to best bring people, tech and data together.
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