#Thebrain 9 local server software#
What we not yet have on a large-scale, but what many device and software companies are now actively developing, are consumer-directed wearable devices for recording and uploading our brain activity, mostly based on electroencephalography (EEG).
#Thebrain 9 local server license#
Most of the personal information that web-based software companies gather today is based on our voluntarily submitting our data-mostly by yielding to convoluted and mostly inscrutable “end-user license agreements” (EULAs). This growing mountain of data, however, would not be of much use was it not for the advanced machine learning algorithms, specifically artificial neural networks (ANN) for “deep learning” and related methods, that are now available for analyzing this data. “fitness trackers”), electronic health records, or our online footprint from using web-based software services. But the same technology, when applied in consumer-directed neurotechnological devices, whether for entertainment, the interactive use of web services, or other purposes, may lead to the uncontrolled collection and commodification of neural data that may put vulnerable individuals at risk with respect to the privacy of their brain states.īig data refers to collecting and storing vast amounts of data, for example from wearable devices (e.g. In basic and applied neuroscience, this impending age of “Big Brain Data” may lead to important breakthroughs, particularly for our understanding of the brain’s structure and function, for identifying new biomarkers of brain pathology, as well as for improving the performance of neurotechnological devices (such as brain-computer interfaces, BCIs). We currently witness converging technological macrotrends-big data, advanced machine learning, and consumer-directed neurotechnological devices-that will likely lead to the collection, storage, and analysis of personal brain data on a large scale. Finally, I discuss the implications of big brain data for national and international regulatory policies and models of good data governance. In the legal realm, I examine possible legal consequences that arises from the increasing abilities to decode brain states and their corresponding subjective phenomenological experiences on the hitherto inaccessible privacy of these information. I then discuss the impact of the “datafication” in basic and clinical neuroscience research on the just distribution of resources and access to these transformative technologies. Regarding ethical and legal ramifications of big brain data, I first discuss effects on the autonomy, the sense of agency and authenticity, as well as the self that may result from the interaction between users and intelligent, particularly closed-loop, neurotechnological devices. In this context, I then examine ways in which safeguards at the hardware and software level, as well as increasing “data literacy” in society, may enhance the security of neurotechnological devices and protect the privacy of personal brain data.
Then, I describe some of the technological, social and psychological barriers for securing brain data from unwarranted access.
First, I highlight the benefits of big data and machine learning analytics in neuroscience for basic and translational research. The focus of this paper are the ethical, legal and social challenges for ensuring the responsible use of “big brain data”-the recording, collection and analysis of individuals’ brain data on a large scale with clinical and consumer-directed neurotechnological devices.