Chapter
The Power of Non-Medical Data Analysis with AI
10:25 - 18:29 (08:04)
Through the use of machine learning, non-medical data on stress, sleep, physical activity, phone usage, and social interaction can be assessed to predict an individual's future state of health, happiness or stress. There is a need to extend the current regulations around using emotion recognition in general, and protecting individuals with their data.
Clips
The concern about what is happening in society and the type of future people want to build is now starting to play a role in how we spend our time.
10:25 - 14:31 (04:06)
Summary
The concern about what is happening in society and the type of future people want to build is now starting to play a role in how we spend our time. Companies are becoming more conscious about building AI to make a positive impact on society rather than using it only to maximize profits.
ChapterThe Power of Non-Medical Data Analysis with AI
EpisodeRosalind Picard: Affective Computing, Emotion, Privacy, and Health
PodcastLex Fridman Podcast
Machine learning can use non-medical data, such as stress and sleep patterns, to predict a person's future mental health state.
14:31 - 18:29 (03:57)
Summary
Machine learning can use non-medical data, such as stress and sleep patterns, to predict a person's future mental health state. However, regulations need to be put in place to protect individuals' data and use of non-medical data for mental health predictions should be given the same protections as medical data.