Image by Neil Conway
The brain sciences are playing an increasingly powerful role in the development of the digital technologies that may augment everyday life in future years. ‘Neurotechnology’ is a broad field of brain-centred technical R&D. It includes advanced imaging systems for real-time brain monitoring and mining the mind via the collection of brain data, but also new and emerging brain stimulator systems that may have the capacity to influence brain activity. Along with new developments in data-driven ‘psycho-informatics’ in the field of psychology, the possibilities associated with brain-machine interaction have begun to attract educational interest, raising significant concerns about how young people’s mental states may in the future be governed through neurotechnology.
The human brain has become the focus of intense interest across scientific, technical R&D, governmental, and commercial domains in recent years. Neuroscientific research into the brain itself has advanced significantly with the development and refinement of brain imaging neurotechnologies. Driven by massive research grants and private partnerships, huge teams of neuroscience experts associated with international projects—such as the US-led BRAIN (Brain Research through Advancing Innovative Neurotechnologies) Initiative and European Human Brain Project—have begun to visualize and build ‘wiring diagrams’ and computational models of the cells and neural circuits of the brain at a highly granular, neuromolecular level of detail and fidelity, all based on the collection and analysis of massive records of brain data.
This knowledge of the brain developed by neuroscience is being applied to the design of new brain-machine interface technologies such as neuroprosthetic devices that can be implanted in the brain—with algorithms that can translate ‘thought’ into movement—and noninvasive neurostimulators that might modify cognition and emotions. In the last few months, technology entrepreneurs from some of Silicon Valley’s most successful companies have also begun to concentrate R&D resources on Brain-Computer Interfaces (BCI) and brain-signalled remote control of devices–as well as more speculative attempts to hybridize the human brain with artificial intelligence implants. Tesla boss Elon Musk, for instance, has established Neuralink to use brain implants to directly link human minds to computers and ‘augment the slow, imprecise communication of our voices with a direct brain-to-computer linkup.’ Facebook, meanwhile, has announced it is pursuing the development of a new kind of noninvasive brain-machine interface—possibly a cap or headband—that lets people text and ‘share’ their thoughts by simply thinking rather than typing. Its intention is to use optical technologies to use light, like LEDs or lasers, to sense neural signals emanating from the cerebral cortex.
At the same time, the brain is being treated as an inspiration for the design of neurocomputing systems. These complex cognitive computing, neural networks and AI systems are designed to emulate some of the brain’s capacities, especially for efficient low-energy information storage, processing, retrieval and learning, in order to maximize the efficiency and speed of big data processing and machine learning algorithms. Neural-network research, for example, focuses simultaneously on improving understanding of the human brain and nervous system, and on using that knowledge to ‘find inspiration’ to ‘construct information processing systems inspired by natural, biological functions and thus gain the advantages of these systems.’ The development of ‘bio-inspired’ or ‘bio-mimetic’ systems in neural-network research, and neurocomputing more generally, is already being applied in many settings, notably through companies like IBM. IBM’s recent advances in cognitive computing, such as Watson, take inspiration from neuroscience for the design of brain-like neural networks algorithms and neurocomputational devices that are now being deployed in healthcare, business and educational settings.
A huge field has developed around Brain-Computer Interface research and development too. BCI, or sometimes Brain-Machine Interface R&D, depends on signal processing of brain data to allow brain activities to control external devices or even computers through electrodes–‘the enabling technologies that allow brain information to be encoded by different techniques and algorithms providing input to control devices.’ Although previously largely confined to clinical and laboratory research, the possibilities of brain-machine mental control have begun to attract significant research grant funding along with commercial interest in recent years. The growth in interest at least partly stems from advances in BCI R&D which have seen the invasive implantation of microelectrodes within the brain itself being displaced by increasingly noninvasive techniques. Noninvasive BCI does not involve penetration of the scalp or skull with electrode implants but still holds the potential for mental control over devices through the real-time capture of brain activity data using portable EEG neuroimaging technologies.
Various portable and wearable EEG headbands that allow easy attachment of electrodes to the skull have become commercially and clinically available, with brand-names including Emotiv, Neurosky, BrainBand, Myndwave and BrainControl. Mental control videogaming is a major commercial application of BCI. Further out in R&D terms, other neuroscience inspired brain interface proposals include ‘neural dust’ consisting of microscopic free-floating sensors that could be spread around the brain.
The policy implications of neuroscientific and neurotechnological development have been articulated by, among others, the Potomac Institute for Policy Studies, a policy institute with its own Center for Neurotechnology Studies. Its report on ‘enhancing the brain and reshaping society’ has called for collaborative efforts between policymakers, scientists and the private sector to develop novel neurotechnologies that can improve individuals’ cognitive abilities and behaviours as well as the ‘social order,’ and thereby ‘ensure neuroenhancement of the individual will result in enrichment of our society as a whole.’
As with all technical development, neurotechnology is not merely technical. It is imprinted with powerful social visions of a future in which brain data can be used to know and monitor populations, and to enhance the mental states of individuals to meet certain objectives and aspirations for society at large.
Neurotechnological development and application of neuroenhancement techniques may seem far removed from education. However, neuroscience itself is currently enjoying fast growth within educational research and practice, with new research centres in educational neuroscience appearing, with support from grant awarding bodies, and research results and applications increasingly being shared by global community using the Twitter hashtag #edneuro. The journal Learning, Media and Technology ran a special issue in 2015 on neuroscience and educational technology.
Various neurotechnologies such as brain imaging are being used by ‘ed-neuro’ researchers in ways which are intended to generate insights for educational policymakers and practitioners. One ed-neuro study has made use of mobile, wearable EEG headbands to study students’ ‘brain-to-brain synchrony’ within the classroom context. EEG neuroimaging has even been used to visualize the brain ‘lighting up’ when students have adopted a ‘growth mindset.’ Attempts have also been made to use brain imaging technologies to analyse the possible biological mechanisms by which socio-economic status influences and effects brain and cognitive development in children. Studies have used neuroimaging to examine whether socioeconomic status correlates with differences in brain structure, and measured the electrical activity in the brains of children from lower SES groups to detect deficits in their selective attention. Such studies and conclusions have begun to influence policymakers, who can interpret the results to specify remedial interventions such as early years education provision. In these ways, neurotechnologies are becoming integral parts of new policy science approaches, the instruments that enable policymakers to see policy problems visualized in the neurobiological detail provided by highly persuasive brain images.
Neurotechnology-based cognitive computing systems developed by commercial organizations have also appeared in the educational landscape. The edu-business Pearson has partnered with IBM to bring IBM’s Watson system into the learning process, as previously detailed. For at least the last decade, IBM has been engaged in an extensive program of brain-based computing R&D, involving neurocomputing, neural-network research and the development of specific neurosynaptic and neuromorphic hardware and software. For IBM, as detailed in its white paper on ‘Computing, cognition and the future of knowing,’ cognitive tools are ‘natural systems’ with ‘human qualities’ which are inspiring the ‘next generation of human cognition, in which we think and reason in new and powerful ways’:
It’s true that cognitive systems are machines that are inspired by the human brain. But it’s also true that these machines will inspire the human brain, increase our capacity for reason and rewire the ways in which we learn.
Pearson has itself articulated a vision of AI teaching assistants and cognitive tutors using technologies based on advances in educational neuroscience and psychology. For both Pearson and IBM cognitive computing does not just mean smarter computing systems, but cognitively optimized individuals whose very brain circuitry has been rewired through interfacing and interacting with machine cognition.
Political support for commercial educational neurotechnology has also emerged. Recently-appointed head of the US Department of Education, the private-education advocate Betsy DeVos, is a major investor and former board member of Neurocore, a brain-training treatment company that specializes in ‘neurofeedback’ technology. The company uses real-time EEG with electrodes attached to the scalp to diagnose individuals’ symptoms by comparing their brainwaves to a massive database of others’ brainwaves. Its proprietorial neurofeedback software can then be applied to run a game that rewards the desired brain activity. Over time, Neurocore claims, the brain starts to learn to produce activity that was rewarded by the increase in stimulation. One of Neurocore’s targets is children with ADHD (Attention Deficit Hyperactivity Disorder); its ‘natural treatments’ with drug-free neurofeedback ‘work with a child’s natural ability to learn, helping them reach their full potential’ (though its underlying neuroscience has been contested).
From a more speculative perspective the Center for Neurotechnology Studies at the Potomac Institute has issued a report on ‘neurotechnology futures’ with some key implications for education. It describes how brain interface technologies could become applications for ‘augmented cognition’, including ‘non-invasive devices that complement or supplement human capabilities, such as tools for learning and training augmentation.’ It has detailed how ‘greater understanding of the neural mechanisms of learning and memory is needed to provide the appropriate theoretical basis for neurotechnologically enhancing learning’ and enabling the educational system ‘to significantly improve teaching techniques for iteratively more complex knowledge.’ It even suggests the ‘provocative possibility of technology that could “down-load” experience and facilitate learning in a time-compressed manner.’
The Potomac Institute provides advice to the US military. And the US military Defense Advanced Research Projects Agency (DARPA) has itself begun exploring the potential to boost the acquisition of skills and learning through its Targeted Neuroplasticity Training (TNT) program, itself part of the BRAIN Initiative. The program aims to develop safe, noninvasive neurostimulation methods for activating synaptic plasticity–the ability of the brain to connect neurons which is understood to be the neural requirement for learning. According to a press release from the TNT program manager,
Targeted Neuroplasticity Training (TNT) seeks to advance the pace and effectiveness of a specific kind of learning—cognitive skills training—through the precise activation of peripheral nerves that can in turn promote and strengthen neuronal connections in the brain. TNT will pursue development of a platform technology to enhance learning of a wide range of cognitive skills…. The TNT program seeks to use peripheral nerve stimulation to speed up learning processes in the brain by boosting release of brain chemicals, such as acetylcholine, dopamine, serotonin, and norepinephrine. These so-called neuromodulators play a role in regulating synaptic plasticity, the process by which connections between neurons change to improve brain function during learning. By combining peripheral neurostimulation with conventional training practices, the TNT program seeks to leverage endogenous neural circuitry to enhance learning by facilitating tuning of neural networks responsible for cognitive functions.
Although TNT is primarily aimed at military training, it clearly indicates how the scientific and technical possibilities of neurotechnology are being taken up in relation to education and learning.
At least one educational entrepreneur has leapt upon the potential of ‘frictionless’ brain-computer interfaces of the kind imagined by DARPA, Silicon Valley entrepreneurs like Elon Musk and the vision of neurotechnologically-enhanced learning promoted by the Potomac Institute. Donald Clark, the founder of the AI-based online learning company Wildfire Learning, the ‘world’s first AI content creation service’ for education, has imagined that invisible, frictionless and seamless interfaces between human brains and AI will have massive implications for education:
The implications for learning are obvious. When we know what you think, we know whether you are learning, optimise that learning, provide relevant feedback and also reliably assess. To read the mind is to read the learning process…. We are augmenting the brain by making it part of a larger network … ready to interface directly with knowledge and skills, at first with deviceless natural interfaces using voice, gesture and looks, then frictionless brain communications and finally seamless brain links. Clumsy interfaces inhibit learning, clean smooth, deviceless, frictionless and seamless interfaces enhance and accelerate learning. This all plays to enhancing the weaknesses of the evolved biological brain … and [to] think at levels beyond the current limitations of our flawed brains.
These aspirations for the future of education merge the scientific R&D of the emerging ‘ed-neuro’ field with the kind of techno-optimism often found in educational technology, or ‘ed-tech,’ development and marketing, to suggest the emergence of a new hybrid field of ‘ed-neurotech.’
Like the plans of Musk and Facebook, the ed-neurotech imaginary of a deviceless, frictionless and seamless neurotechnological future of education is likely to be highly controversial and contested. Part of this resistance will be on primarily technical and scientific grounds–neurotechnologies of brain imaging are one thing, and seamless neuroenhancement of the so-called flawed brain quite another. But another part of the resistance will be animated by concerns over the aspirations of either governments or commercial companies to engage in mental interference and cognitive modification of young people.
Neuroenhancement may not be quite as scientifically and technically feasible yet as its advocates hope, but the fact remains that certain powerful individuals and organizations want it to happen. They have attached their technical aspirations to particular visions of social order and progress that appear to be attainable through the application of neurotechnologies to brain analytics and even neuro-optimization. As STS researchers of neuroscience Simon Williams, Stephen Katz & Paul Martin have argued, the prospects of cognitive enhancement are part of a ‘neurofuture’ in-the-making that needs as much critical scrutiny as the alleged ‘brain facts’ produced by brain scanning technologies.
In a new article on neuroscience, neurotechnology and human rights, the bioethicists Marcello Ienca and Roberto Andorno have mapped out some of the challenges raised by these emerging ‘brain-society-computer entanglements.’ The ‘neurotechnology revolution’ in ‘neuroimaging’, they argue, highlights how the ‘possibility of mining the mind (or at least informationally rich structural aspects of the mind) can be potentially used not only to infer mental preferences, but also to prime, imprint or trigger those preferences.’ They note how brain imaging techniques have been taken up in ‘pervasive neurotechnology applications’ such as BCIs that ‘use EEG recordings to monitor electrical activity in the brain for a variety of purposes including neuromonitoring (real time evaluation of brain functioning), neurocognitive training (using certain frequency bands to enhance neurocognitive functions), and noninvasive brain device control.’
In addition to neuroimaging and brain-computer interface and device control, however, Ienca and Andorno also note the emergence of ‘brain stimulators’ or ‘neurostimulators.’ Unlike neuroimaging tools, these ‘are not primarily used for recording or decoding brain activity but rather for stimulating or modulating brain activity electrically.’ Available neurostimulators include portable, easy-to-use, consumer-based transcranial direct current stimulation (tDCS) devices aimed at optimizing brain performance on a variety of cognitive tasks, and applications based on transcranial magnetic stimulation (TMS), a magnetic method used to briefly stimulate small regions of the brain for both diagnostic and therapeutic purposes, which has also evolved into portable devices. ‘In sum,’ they state,
if in the past decades neurotechnology has unlocked the human brain and made it readable under scientific lenses, the upcoming decades will see neurotechnology becoming pervasive and embedded in numerous aspects of our lives and increasingly effective in modulating the neural correlates of our psychology and behaviour.
The emergence of neuroimaging, neuromodulation of behaviours, and cognition-stimulating neurotechnologies therefore raises considerable challenges, as Ienca and Androno articulate them:
- the use of pervasive neurotechnology for malicious ‘brain-hacking’ (or ‘brainjacking’–the unauthorized modification of emotions and cognition)
- third party eavesdropping on the mind
- illicit memory-engineering
- technology-induced personality change
- the neuromodulation of behaviours
- illegitimate access to and use of brain data generated by consumer-grade brain-computer interface applications.
These concerns reflect the emergence of what some social scientific critics of the brain sciences have begun to term ‘neurogovernance’ or ‘neuropower.’ As Victoria Pitts-Taylor puts it in her recent book The Brain’s Body, neuroscience-based programs designed to mould and modulate behaviour through targeting the brain for modification represent strategies of ‘preemptive neurogovernance’ that are intended to promote the economic and political optimization of the population. She notes how neuroscience concepts like ‘brain plasticity’ have been taken up by developers of ‘cognitive exercises, brain-machine interfaces, drugs, supplements, electric stimulators, and brain mapping technologies,’ in order to ‘target the brain for modification and rewiring.’ These technical advances clearly amplify the possibilities of preemptive neurogovernance, and the shaping of society and the social order through the modification of the mental states, affects and thoughts of individuals. The plasticity of the brain has become the basis for technoscientific ambitions to monitor, control and transform processes of life for political and commercial purposes, Pitts Taylor argues. And Nikolas Rose and Joelle Abi-Rached, in their book Neuro, have argued that the plastic brain is now the focus for attempts to ‘govern the future’–as is especially the case with interventions into the developing brains and hence future lives of children.
As a consequence, Ienca and Andorno suggest that neurotechnologies raise significant challenges for human rights. In particular they highlight recent debates about the right to ‘cognitive liberty,’ or the right to alter one’s mental states with the help of neurotools, and the associated right to refuse to do so. Ultimately, cognitive liberty is a conceptual update of the right to ‘freedom of thought’ that takes into account the power available to states and companies to use neurotechnology coercively to manipulate the embrained mental states of citizens. They also add the right to ‘mental privacy,’ defined as a ‘neuro-specific privacy right which protects private or sensitive information in a person’s mind from unauthorized collection, storage, use or even deletion in digital form or otherwise.’ Cognitive liberty and mental privacy, in other words, constitute new rights to take control of one’s own mental life in the face of creeping techniques of neurogovernance in spheres of life including social media, government, consumption, and education.
The application of neurotechnology to education that we are just beginning to detect needs to be undertaken in ways which are sensitive to issues of neurogovernance, cognitive liberty and mental privacy. As parts of an educational neurofuture in-the-making, optimistic aspirations towards neuroenhancement and cognitive modification of ‘flawed brains’ through neurotechnologically enhanced education need to be countered not just with technical and scientific scepticism. Greater awareness of the political, military and commercial interests involved in new and developing neurotechnology markets and interventions are required, as well as theoretically engaged studies of the sociotechnical processes involved in producing neurotechnologies and of their uptake and effects in education. Deeply social questions also need to be asked about the use of brain data to exercise neuropower over young people’s mental states, and about how to safeguard their cognitive liberty and mental privacy amid persuasive and coercive promises about neuroenhancement in the direction of personal cognitive improvement.
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