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Machine Learning for the Developing World (ML4D): Improving Resilience

Tejumade Afonja · Konstantin Klemmer · Niveditha Kalavakonda · Oluwafemi Azeez · Aya Salama · Paula Rodriguez Diaz

Sat 12 Dec, 4 a.m. PST

A few months ago, the world was shaken by the outbreak of the novel Coronavirus, exposing the lack of preparedness for such a case in many nations around the globe. As we watched the daily number of cases of the virus rise exponentially, and governments scramble to design appropriate policies, communities collectively asked “Could we have been better prepared for this?” Similar questions have been brought up by the climate emergency the world is now facing.
At a time of global reckoning, this year’s ML4D program will focus on building and improving resilience in developing regions through machine learning. Past iterations of the workshop have explored how machine learning can be used to tackle global development challenges, the potential benefits of such technologies, as well as the associated risks and shortcomings. This year we seek to ask our community to go beyond solely tackling existing problems by building machine learning tools with foresight, anticipating application challenges, and providing sustainable, resilient systems for long-term use.
This one-day workshop will bring together a diverse set of participants from across the globe. Attendees will learn about how machine learning tools can help enhance preparedness for disease outbreaks, address the climate crisis, and improve countries’ ability to respond to emergencies. It will also discuss how naive “tech solutionism” can threaten resilience by posing risks to human rights, enabling mass surveillance, and perpetuating inequalities. The workshop will include invited talks, contributed talks, a poster session of accepted papers, breakout sessions tailored to the workshop’s theme, and panel discussions.

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Timezone: America/Los_Angeles