Data and Minds: Forging Future Frontiers

We live in a world where data abounds and comes from cutting-edge technology, such as wearable devices that continuously collect body health information, novel brain-machine interface (BMI) technology to help impaired persons, high resolution video streams from devices with which we interact, or edge devices on the internet that collect massive amounts of data in a distributed manner. Unraveling the hidden secrets in this data can yield astonishing new opportunities, for instance in user-machine interaction, in medicine and rehabilitation, or to produce novel insights in neuroscience, to name just a few. Yet, collecting so much data also confronts us with ethical questions, for instance surrounding identity and privacy. What can we learn from data in emerging technologies, while addressing societal and ethical considerations at the same time?

The focus in the village is to use methods from mathematics, statistics, machine learning, computer science, and AI to exploit the secrets hidden in big data or to make them accessible, and to dig into the ethical and legal aspects of big data. The goal is to bring together teams with diverse backgrounds, to leverage their expertise and to tackle challenges in big data analytics. The data might come, for instance, from wearables, from neuroscience research, or brain-machine interfaces, but it will be up for each team to decide on this. Moreover, each team will have the flexibility to independently choose a problem aligned with their interests and adapt it to their unique perspectives. This collaborative approach promotes interdisciplinary solutions to address pressing societal issues.

Relevant competency

A background in a field related to data processing, such math, engineering, or computer science, is clearly helpful. However, depending on the concrete project, a background in legal or ethical aspects might be equally important! Further interest and experience in data analysis, programming, or mathematics, is an advantage but not a requirement.

About the village

The following are examples for topics that can be addressed in the village, or were addressed in the past

• Statistical machine learning and AI, e.g. algorithms to automatically extract states from EEG or EMG recordings.
• An evaluation of high-performance algorithms for data analytics, applied to streaming data from high-resolution video feeds
• Real-time processing algorithms for embedded devices to detect cardiac arrhythmia from EEG sensory data
• Using brain-machine-interfaces for playing chess
• Ethical implications and legal aspects in both Europe and Norway for the use of data from brain-machine interfaces

Groups might use models or methods and data (e.g. machine learning, optimization, statistics, AI, electricity) and can implement methods on a computer. Depending on background, groups might investigate societal or ethical impacts instead of mathematical analysis or programming. Also, groups will be encouraged to contact relevant external partners.

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