AI and Machine Learning: From Contact Tracing to Treating Neurodegeneration

'As technologies such as AI and machine learning continue to make an impact on the healthcare space, startups will play an increasing role in such transformation.'

The 2020 AI LA Life Summit drew together speakers from all areas of the life sciences, but common themes emerged throughout many of the talks. Vivienne Ming, the Founder and Executive Chair of Socos Labs, touched on two of those themes with her keynote address: the importance of AI during the pandemic and the synergy between human minds and machine learning. For Ming, the most interesting applications of AI are the best mix of what human brains and machines can do.

During her brief talk, Ming focused much of the time discussing the contact tracing. A hot topic during COVID, contact tracing uses technology and interviews to identify people who have potentially been exposed to a known infection. As Ming points out, even though contact tracing reached the public eye recently, this isn’t new technology. Several years ago, she was using contact tracing techniques to see how language spreads in educational institutions. She would trace conversations among groups of students to see how bilingual students talked when they were at home or at school, as well as what language styles undergrads and high school students use.

A large company also contracted Ming to use contact tracing in order to find the biggest untracked factor that affects productivity. She pointed out that this particular method allowed her to use near field technology to completely ignore the org chart and see into the actual social fabric of the company. Using this data, Ming took the math behind backpropagation and combined it with value added modeling to see how behaviors of individual people within the company changed the global operation. Amazingly, the largest determinant ended up being purpose: people who helped others as part of their natural demeanor would actually make a team function at a higher level. With this information, Ming was able to predict who could be added to a team to increase productivity.

Similarly, these methods can be used for developing the most efficient way to distribute vaccines by identifying the characteristics most likely to spread a disease. Ming pointed to recent studies that found elder care workers were one of the populations that spread the coronavirus at a higher rate than others, creating the possibility for measures to be put in place to mitigate the spread through these channels. Highlighting the importance of social determinants, Ming pointed out that the reason behind the increased spread of COVID through elder care workers was that these workers are not paid enough, resulting in many working multiple jobs in multiple facilities. Workers would move between elder care facilities, often using public transportation, and expose others to the virus. Simply by paying a living wage or by bubbling workers in a single facility for the pandemic could result in a significant impact to infection rates.

Beyond contact tracing, Ming identified other exciting uses of AI to help neurodegeneration in Alzheimer’s patients, treating traumatic brain injuries in children, and allowing locked-in patients to communicate. Without the ability of AI to make sense out of certain data types, none of these advances were possible. However, Ming underscores the importance of the human mind in this process. She ends her talk with a reminder to everyone that no matter how exciting new papers or research are, AI doesn’t work unless humans are the creative core of the process.

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