Cognitive Utopia or Dystopia? Brain-Computer Interface Enhancement and the Technological Singularity

|


Futurists anticipate that technological advances in brain computer interface devices (BCIs) could revolutionize human cognitive enhancement. However, the more likely reality is that of BCIs as contributors to a dystopian rather than utopian near-technological singularity. BCIs collect, organize, review, synthesize, and translate data derived from brain recording devices attached to the scalp (electroencephalogram (EEG)), the brain’s cortex (electrocorticogram (ECoG)), or intracortically into an intelligible form to a machine which communicates information to the user. BCI devices can aid in converting thoughts into text or effectuate movement of prosthetic or motion-impaired limbs. As such, BCIs serve as potential vehicles for direct human and computer brain connection, interconnected brain communication, cognitive ability enhancement, and improved motor function. The technological singularity, according to the book of the same name by cognitive robotics professor Murray Shanahan, is the point at which “ordinary humans will someday be overtaken by artificially intelligent machines or cognitively enhanced biological intelligence, or both.” Mathematician and technology singularity nomenclature originator Victor Vigne described potentially “intimate” computer-human interfaces in The Coming Technological Singularity: How to survive in the Post-Human Era. Proponents of technological singularity believe BCIs could aid humanity in achieving near-utopia through merging brain data with supercomputers.

There are many potential beneficial uses for BCIs, which were initially developed to aid in the medical rehabilitation of paralytic patients and other patients afflicted with spinal cord injuries or diseases involving neuromotor dysfunction such as stroke or amyotrophic lateral sclerosis (ALS). Research studies have shown that brain computer interface devices (BCIs) help restore functionality in patients with neurological or neuromuscular disorders such as complete or partial paralysis, traumatic brain injuries, infection or other related diseases. Severely paralyzed individuals previously unable to speak can communicate through BCIs via the translation of brain wave signals detected through electroencephalography (EEG) into text. EEG detects minute electrical signals fired by the brain, which are called P300 signals, between 300 to 800 milliseconds after the electroencephalography test subject recalls the memory of an image, conversation, or thought. An electrocorticography array (ECoG) senses firing from nerve signals that control muscles in vocal cords. A recording device captures signals and translates the recorded information into words. The BrainGate2 system, a neural interface device, has been used in patients with amyotrophic lateral sclerosis (ALS). BCIs aid patients with neuromuscular disorders through algorithms which decode and translate neural signals into motor activity in the voluntary movement of extremities. EEG signals read from BCIs can be used to power prosthetic devices that can assist paralyzed patients with motor function. Another example of a potentially useful clinical application of the BCI is with the medical condition locked-in syndrome (LIS) a neurological disease caused by injury to the brain stem in which the patient has cognitive function but no motor or communicative function. EEG signals can be translated into text to significantly improve the quality of life for LIS patients. Researchers also propose that BCIs could offer some hope for treatment of patients with depression and anxiety

I.J. Good, former Oxford mathematician, postulated in 1965 in “Speculations Concerning the First Ultraintelligent Machine,” Advances in Computers, that one day super intelligent machines would “incorporate vast artificial neural circuitry” indispensable to humans. Good continued: “Until an ultraintelligent machine is built perhaps the best intellectual feats will be performed by men and machines in very close, sometimes ‘symbiotic’ relationship.” Accordingly, BCIs can monitor and augment brain function and ability. BCI regulation of cognitive ability is possible for learning, memory, dreaming, sensory perception, emotion recognition, monitoring cognitive fatigue, gaming, entertainment, and brain-computer interconnectedness and networking. Recent research implies that brain computer interfaces may be used to communicate and translate imagery from dreams into recognizable actions. Lucid dreamers are cognizant of their dream states and capable of exercising some level of control over their movement. Remington Mallett demonstrated these dreamers can move objects upon command using only their thoughts and the assistance of brain computer interface devices. Facial Emotion Recognition (FER) and detection of a range of psychological states are possible with BCIs through the measurement of facial landmarks. Mapping of facial features using deep learning model algorithms involves a convolutional neural network (CNN). Such deep learning studies have shown EEG patterns which detect happiness, fear, surprise, anger, and a host of other emotions

In addition to FER, BCIs can monitor cognitive fatigue in drivers who spend long hours on the road. In a similar fashion, research studies conducted by the National Aeronautics and Space Administration have shown that BCIs may aid in detecting cognitive fatigue in pilots and air traffic controllers. Such activities could contribute significantly to improving public safety. Precise and accurate neurocortical signals can be measured through the dense barrier of the skull without significant diffusion of the neuroelectric signal. Gaming using BCIs – also known as neurogaming, has been demonstrated, although additional research is needed before BCI such gaming becomes mainstream

As a neuronal network, the brain is anatomically designed to allow information to flow freely from one part of the brain to another, controlling neuronal signalling throughout the human body. BCI technology could extend the brain neuronal network by increasing the capacity of such networks with applications and utility for the internet, up to and idealistically uploading brain tasks, operations, and data onto computer networks.  The first BCI-like social network allowed three people to transmit thoughts to each other’s brains. This brain to-brain interface technology is entitled BrainNet, and it utilizes EEGs and transcranial magnetic stimulation to detect and transmit messages. Technology which allows humans to send messages to one another through brain sensor signaling,  however, is still in development. Further development of this technology will allow messages to be transmitted from individual to individual through cloud-based communication. The United States military has developed a neurocortical sensory device, the Utah array, which targets neurons more precisely than electocorticography (ECOG) devices. According to the Defense Advanced Research Projects Agency (DARPA), the Utah array is an even more refined device for reading neuroelectric signals in the brain. Currently, the military is also investigating a host of other possible uses for BCIs, including covert communications, improving soldier mental resilience and performance, and bolstering national security. 

Despite the positives, several negatives of BCI technology exist which could hinder BCI’s potential progress to futurist-described technological singularity. Traumatic brain injury can result from the implantation of an excessive number of BCI probes into the brain. Continued studies are ongoing as to whether the problem of traumatic brain injury can be resolved by altering the number of probes inserted into the brain. Moreover, scientific testing has shown that the BCI probes can become damaged over time via immune response to the BCI probes or normal wear and tear. Such damage has been associated with lost EEG signals or loss of functionality of the BCI devices. Evidence from the Physicians Committee for Responsible Medicine (PCRM) indicates improper storage of bacterially and virally contaminated brain-computer interface devices could place individuals at risk for infection. This could be particularly true for brain interface devices which operate using deep brain probes and stimulation. Stress may adversely impact BCI performance. Potential problems with BCIs include ensuring precision and accuracy of the BCIs and operation. Precision ensures that the brain computer interface devices and operation are consistent with every use. Accuracy ensures that the brain computer interface devices correctly measure, amplify, translate, and communicate brain signals into text with every use. Cross-task neural architecture EEG search (CTNAS-EEG) frameworks can improve the accuracy of EEG signal recognition for a more effective use of the brain computer interface. 

Users could consent to have their thoughts accessed. However, this may not be the wisest course of action. Currently, the European Union’s General Data Protection Regulation (GDPR) prohibits the collection of consumer data without the permission of the consumer. Despite BCI user permission, BCI technology would not necessarily be kept secure. Cyberattacks may occur, leaving the information gleaned from BCI devices vulnerable to malicious hackers. BCI hacking can result in damage to electrosensory devices or interconnected cloud-based computing communications systems. As such, BCI users must discern the integrity of BCI-enabled communications. Once BCI technology transitions from experimental to more widespread consumer use, the user consent could help mitigate responsibility of manufacturers and data network providers in the event that computer networks are hacked

Aside from cyberattacks, users would potentially be susceptible to intentional or unintentional third-party possession of highly personal brain EEG data, allowing those with commercial interests to profit from internal thought processes. In the United States, consumer data can be tracked through online consumer activity and ferreted to companies wishing to market to consumers via third-party cookies. However, the disadvantage is that advertisers can only target the demonstrated online activity of consumers. What if advertisers could access thoughts that consumers may not necessarily manifest through online browsing activity? For example, several technology companies have marketed direct-to-consumer (DTC) neuromonitoring BCI interface devices for commercial use. The EPOC X by San Francisco-based company Emotiv offers a $999 neuromodulation wireless headset device, advertised as: “Featuring 14 channels, advanced real-time data transmission, and consistent sensor conductivity, EPOC X is your versatile companion for capturing accurate brain insights.” Research has demonstrated accuracy of up to 69% in a similar device, Epoc+, which was previously marketed for $799 for the interpretation of mental commands but was so popular that it is now out of stock

Brain computer interface (BCI) devices seemingly continue to become more sophisticated with the passage of time, hurtling both man and machine to the point of futurist-predicted technological singularity. However, there are many unanswered questions regarding the feasibility of such technology – particularly in the areas of consumer and personal rights. The likelihood of a dystopian outcome of BCI technology use is far greater without consumer and personal rights safeguards in place. The manner of regulation of BCI devices is uncertain, at best, and is dependent upon the purpose of the use of the BCI device. Consumer regulation of BCIs likely falls under the jurisdiction of the Federal Communications Commission (FCC) and the Federal Trade Commission (FTC) in the United States. Experimental use of BCI technology for scientific testing in humans in the United States must be compliant with informed consent and human subjects regulations. Moreover, the Food and Drug Administration (FDA) has offered insight on in guidance documents on the regulation of BCIs for clinical purposes. The United States Health Information Portability and Accountability Act (HIPAA) adds an extra measure of protection for medical patients in whom BCI devices are used for medical purposes, ensuring their health care information is protected. HIPAA would classify brain-computer interface data as personal health information and be legally protected in such a manner. Like the United States, the United Kingdom promulgates the possibility of BCI device regulation via several different government entities. However, BCI manufacturers and distributors bristle at the idea of government regulation, citing concerns regarding impedance of commerce, revenues, and profits.

Beyond government agency regulation, the advent of brain reading technology raises concerns regarding how the government will protect the constitutional rights of those who submit to brain reading technology. The ability to scan, interpret, communicate, and translate language extracted from the brain to text raises privacy concerns. An individual maintains a Fourth Amendment right to a reasonable expectation of privacy unless he forfeits that right. Even more so, the First Amendment of the constitution guarantees the freedom of expression. However, intrusive action in obtaining neurodata from individuals using BCI devices could constitute First Amendment and Fourth Amendment violations. Questions surrounding privacy in bodily searches and seizures have persisted for decades. Legal scholars now question the constitutionality of brain searches and whether such searches constitute bodily searches. Protections of privacy in bodily searches and seizures could include that pertaining to information gleaned from brain-computer interface device searches. Considering these points, the current practicality of BCI-enabled cognitive enhancement leading to technological singularity, although hopeful, remains in the future.

This article was originally published in OPR’s Issue 12: Utopia.

Dorkina Myrick, MD, PhD, JD, LLM, LLM, MPP (Oxon) is a physician and policy advisor who resides in the Washington, DC area. She is a 2016 graduate of the Blavatnik School of Government of the University of Oxford.