There is a growing desire to bring autonomous algorithms and systems into all aspects our daily lives to make our jobs, chores, and down time easier and more enjoyable. At the same time, there are unfortunately many people who are impoverished, in danger, gravely ill, or otherwise generally requiring assistance. AI can be used to detect bacteria in water more accurately and quickly than previous methods, identify children who are at risk of being a victim of sexual trafficking or exploitation, help a doctor identify cancer and diseases more quickly, and even develop drugs in a more cost efficient manner. This is using AI to not only solve for x, but also to “Solve for H”; solving problems for human kind.
We can use AI to protect wildlife, help restore historical landmarks, and monitor our planet. AI is also being used to increase crop production with a reduced amount of resources, helping feed a planet of more than 7 billion. It can be used to plan for and respond to disasters, saving countless lives in the process.
This talk will give an overview of several Solve for H projects at Intel. The use cases of AI is limitless, the trick is determining how to use or modify existing algorithms and systems in such a way that they truly aid the end users. Even more so than typical AI systems, it is important to ensure that user’s want and trust an algorithm’s aid. This presentation will highlight the steps necessary for creating AI for social good projects and various ways to become involved in a growing community around this type of work.
Anna Bethke is the Head of AI for Social Good of Intel's Artificial Intelligence Products Group where she is establishing partnerships with social impact organizations; enabling their missions with Intel's technologies and AI expertise. She is also actively involved in the AI Ethics discussion, collaborating on research surrounding the design of fair, transparent, ethical, and accessible AI systems. In her previous role as a deep learning data scientist she was a member of the Intel AI Lab, developing deep learning NLP algorithms as part of the NLP Architect open source repository. Anna received an M.S and B.S. in Aerospace Engineering from MIT in 2009 and 2007 respectively and previously worked as a data scientist at MIT Lincoln Labs, Argonne National Labs, and Lab41.