# The convergence of neurotechnology and digital technology in education: ethical and societal issues

Catherine Vidal

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RÉPUBLIQUE
FRANÇAISE

Liberté

Égalité

Fraternité

Inserm

La science pour la santé

From science to health

Inserm Ethics Committee

"Neurotechnologies
and
Artificial Intelligence"
Working Group

Note

The convergence of
neurotechnology and
digital technology in
education:
ethical and societal issues.

Rapporteur: Catherine Vidal

October 2024
# The convergence of neurotechnology and digital technology in education:
ethical and societal issues

## Summary

### Introduction: situating the topic

#### 1. Neurotechnology in education

1.1 Neurotechnology: definition and applications

1.2 Neurotechnology to enhance learning: myth and reality

2.2.1 Neurofeedback (NF)

*Neurofeedback and ADHD: review of clinical trials*

*Neurofeedback and private "study skills coaching"*

2.2.2 Transcranial brain stimulation

1.3 Neurotechnology in school and university education

#### 2. Digital technology and artificial intelligence in education

2.1 EdTech and AIEd for students

*Intelligent tutoring*

*AI for students with special needs*

*Digital Game-Based Learning (DGBL)*

*The metaverse in education*

2.2 EdTech and AIEd for teachers and institutions

*Learning analytics*

*Digital education tools: between the private and public sector*

2.3 Evaluating digital education systems: effectiveness yet to be demonstrated

#### 3. Ethical and societal issues concerning the convergence of neurotechnology and digital
technology in education

3.1 Protecting students' mental and physical integrity

3.2 Protecting minors' digital rights

3.3 Protecting the autonomy of education systems

3.4 Protecting the environment

#### 4. Recommendations

#### 5. Glossary

#### 6. Bibliographical references.

6.1 Institutional reports on the ethical aspects of digital technology in education, neurotechnology and the metaverse

6.2 Articles/reports published in scientific journals and referenced websites
"The domain of the mind and the information associated with it should be protected as the private domain par excellence, the last territory inaccessible to the erosion of private information and the rampant intrusion of the data society."

Marcello Ienca, Director of the Intelligent Systems Ethics research unit,
College of Humanities at EPFL (Swiss Federal Technology Institute of Lausanne).

Ref: Committee on Bioethics of the Council of Europe

Ienca M. 2021, Common Human Rights Challenges Raised by Different Applications of Neurotechnologies in the Biomedical Field, https://rm.coe.int/report-final-en/1680a429f3.
## Summary

Recent developments in digital technology and artificial intelligence (AI) in the field of education (EdTech and AIEd) have raised ethical concerns from major institutions, both internationally (UNESCO, Council of Europe, OECD and UNICEF) and in France (CCNE [National Ethics Advisory Committee for Health and Life Sciences], CNIL [French data protection authority] and the Ministry of Higher Education and Research). Specific questions surround the use of these technologies in schools with children and teenagers, especially concerning the impact on their physical, psychological and cognitive development and the protection of minors' digital rights.

Another emerging field of technology that is currently shaking up teaching methods is **neurotechnology**, which uses brain-computer interface devices that connect to the brain and record and/or modify neuronal activity. One example of their application in the field of education involves the real-time measurement of students' attention levels and emotional states, with a view to using these measurements to improve their learning performance.

The use of neurotechnology, which originates from the field of medical research, is being extended to other spheres of human activity, such as for augmenting video games, managing stress or sleep, and monitoring drivers. Lightweight wireless devices, such as headsets and headbands fitted with electrodes, glasses and in-ear sensors, are commercially available and used to capture brain waves (EEG), facial expressions, viewing direction, heart rate, and so on. These technologies are being trialed in education and at home to monitor students' behavior in learning situations. In the near future, research should give us clearer insights into neurotechnology's potential to enhance children's learning abilities, particularly children with neurodevelopmental disorders. Such approaches as "neurofeedback" and "transcranial brain stimulation" have already been in use for 10 years or so, especially in children/teenagers suffering from attention deficit hyperactivity disorder (ADHD). However, according to recent publications that have reviewed these studies, it appears that they are widely tainted by methodological bias, meaning that conclusions cannot be drawn on the therapeutic effectiveness of these technologies for ADHD or their effects on cognitive enhancement. Nevertheless, the "academic coaching" market with its scientifically unfounded claims is flourishing on the internet.

The convergence of neurotechnology, digital technology and AI in education is just around the corner. As such, it seems desirable to anticipate the ethical and societal challenges of these technological developments, which are primarily targeting children and teenagers. An important question concerns the use of neurotechnology in young subjects and the subsequent risk of interfering with the process of building their identity and personality while the brain is still developing. Other areas of concern include the protection of brain data when there is a risk of interference in children's mental privacy, and the unauthorized use of these data, which must be considered to be sensitive personal data (Ienca et al. 2022). Related concerns are the risk of seeing public education becoming dependent on private sector technology systems and also the environmental damage associated with the widespread use of digital technology in education.
Introduction: situating the topic

Recent developments in digital technology and artificial intelligence have led to a surge in their use in education (EdTech and AIEd). More and more online platforms (public and private) are designed to transform teaching practices through digital technology, such as access to online educational resources, analysis of students' navigation data on the web, learning pathways tailored to each student, and the organization of lessons in and out of the classroom.

Another emerging field of technology that is currently shaking up teaching methods is neurotechnology, which is derived from research into the brain activity that underlies sensory, motor and cognitive functions, especially in connection with learning mechanisms. It uses brain-computer interface devices that connect to the brain and record and/or modify neuronal activity. They can be applied in the field of education to measure students' attention levels and emotional states in real time with the aim of using the data to improve their learning performance. Trials are underway in schools and universities. Other applications concern the private sphere, such as academic coaching, particularly for children and teenagers suffering from attention deficit hyperactivity disorder (ADHD).

The convergence of neurotechnology, digital technology and AI in education is looming on the horizon. As such, the objective of the INSERM Ethics Committee working group is to focus on analyzing the ethical and societal challenges of these technological developments, which are primarily targeting children and teenagers. An important question concerns the use of neurotechnology in young subjects and the subsequent risk of interfering with the process of building their identity and personality while the brain is still developing. Other areas of concern include the protection of brain data when there is a risk of interference in children's mental privacy, and the unauthorized use of their personal data. Related concerns are the risk of seeing public education becoming dependent on private sector technology systems and also the environmental damage associated with the widespread use of digital technology in education.
# 1. Neurotechnology in education

The ability to control students' attention levels, motivation or confusion is a major objective in the development of digital learning interfaces. This involves linking the digital environment with systems for measuring such biometric data as facial expressions, viewing direction, body movements, heart rate and electrodermal activity. In addition to these parameters, brain wave recording is a valuable tool for assessing a student's mental disposition in real time.

## 1.1 Neurotechnology: definition and applications

Neurotechnology (NT) is a thriving field of research that combines neuroscience with digital technology. The International Bioethics Committee of UNESCO (IBC) offers the following definition:<fnref n="1" /> "neurotechnology is the field of devices and procedures used to access, monitor, investigate, assess, manipulate, and/or emulate the structure and function of the neural systems of human beings" (...) "it can also be seen more broadly as any device and/or application (apps, AI, big data, etc.) able to derive knowledge of an individual's brain activity and/or influence/modify an individual's brain activity". In addition to the technical tools specifically dedicated to exploring the brain, neurotechnology includes devices for capturing physiological and behavioral parameters that also provide information about the person's cognitive, affective and mental states, including eye movements, voice analysis, facial expressions, heart rate and blood pressure.

**Brain-computer interfaces** or **BCIs** use technology to establish a connection with the brain and record and/or modify neuronal activity.<fnref n="2" /> These innovative technologies are used in research and clinically in humans, particularly to compensate for specific physical and mental disabilities.

The most common systems for exploring brain activity are non-invasive, including electroencephalography (EEG), magnetic resonance imaging (MRI), positron emission tomography (PET) and magnetoencephalography (MEG). Other technologies use miniaturized recording systems (microchips fitted with electrodes) placed on the scalp or on the surface of the cerebral cortex. The recorded brain waves are processed by algorithms, and this process can enable paralyzed patients to remotely control an exoskeleton or computer pointer. More invasive procedures involve implanting stimulation electrodes inside the brain

<footnote n="1">¹ - UNESCO 2021: Report of the International Bioethics Committee of UNESCO (IBC) on the ethical issues of neurotechnology, https://unesdoc.unesco.org/ark:/48223/pf0000378724_en.</footnote>

<footnote n="2">² - La lettre de la Biomédecine 2023: État des lieux de la recherche en neurotechnologies : un défi pour la bioéthique, https://www.agence-biomedecine.fr/IMG/pdf/1-lettre_de_la_biome_decine_vf_revue.pdf.</footnote>

<footnote>- OPECST, Parliamentary Office for the Evaluation of Scientific and Technological Choices 2022, Neurotechnology: scientific and ethical challenges.</footnote>

<footnote>https://www.senat.fr/fileadmin/Office_et_delegations/OPECST/Notesscientifiques/OPECSTnote32.pdf.</footnote>
(e.g. to reduce the symptoms of Parkinson's disease) or the auditory nerve or retina (neuroprosthetics).

Other applications for neurotechnology extend beyond the borders of medical practice and concern "personal well-being" and monitoring mental states (Alharbi 2023, Wexler 2019). Many commercial companies offer lightweight wearable (wireless) devices that are capable of recording brain waves (EEG), such as headsets/headbands for recreational and wellness purposes (for playing video games, or managing stress, sleep and concentration), and alertness monitoring devices (vehicle drivers, production line workers and military personnel).

Recent innovations include glasses, in-ear sensors and smart rings that are easier to use than headsets for recording EEG readings, eye movements and heart rate. The overall worldwide market for neurotechnology products is expected to reach $40 billion by 2026³.

Therefore, as neurotechnology continues to gain in popularity, it is not surprising that the use of brain-computer interfaces in education is garnering increasing interest from private companies as well as public institutions (Williamson 2019, Wegemer 2019).

## 1.2 Neurotechnology to enhance learning: myth and reality

The neural foundations of learning have been the subject of prolific scientific research for several decades. Studies have highlighted the role played by attentional and emotional processes, which are often detected by recording brain waves (Al-Nafjan 2017, Fontanillo Lopez 2020, Kosmyna 2019). This work has laid the foundations for the development of brain-computer interfaces that aim to optimize the learning pathway. Research is looking at both children/teenagers with neurodevelopmental disorders (mainly ADHD and dys disabilities) and also healthy subjects, with the goal of increasing cognitive capabilities (Antal 2022, Wexler 2019, 2020, Williamson 2019.) The most widely documented types of experiments use "neurofeedback" and "transcranial brain stimulation".

### 1.2.1 Neurofeedback (NF)

NF is a brain training practice based on recording brain activity, usually through an EEG, and showing the data to the subject (feedback). Brain waves are recorded with electrodes placed on the scalp, which are then amplified, digitized and presented in visual format (and/or auditory format) as part of a video game that captures the subject's attention and encourages them to improve their performance. The subject becomes aware of their brain activity, and with each session they can learn to modify their brain activity in response to an instruction, such as by prioritizing fast beta waves linked to attention or slower theta waves associated with the state of relaxation.

<footnote n="3">³ - www.neurotechreports.com/pages/execsum.html.</footnote>
NF has proven to be particularly useful in specific medical situations to compensate for physical or mental disabilities. A prime example is enabling paralyzed patients to control an exoskeleton or a pointer on a computer screen to communicate with the outside world. Research is being pioneered to explore potential therapeutic applications for neurological and psychiatric disorders, including depression, autism, insomnia, epilepsy, and post-stroke deficits (Batail 2019).

Neurofeedback and ADHD: review of clinical trials

A field of application for neurofeedback that has attracted significant study is attention
deficit hyperactivity disorder (ADHD). The results are highly controversial, as highlighted by
recent reviews and meta-analyses (Kalokairinou 2022, Coghill 2021, Loriette 2021). Several
studies have shown positive effects on some ADHD symptoms in children and teenagers,
including a reduction in inattention periods ranging from 6 to 12 months (Arns 2020,
Hasslinger 2022, Purper-Ouakil 2022, Van Doren 2019).

However, most of this work presents experimental biases, i.e. no double-blind
randomized trials, no control groups, low participant numbers, and non-standard
neurofeedback protocols. These biases mean that it is hard to draw any conclusions about
whether NF is therapeutically effective for ADHD.

Eugene Arnold's laboratory team (Neurofeedback ADHD Collaborative Group, NACG, Ohio University & National Institute of Mental Health, NIH) is currently the only team to have conducted a double-blind randomized clinical trial with a sufficient number of subjects (n=144 children aged 7 to 10 years) with a standard NF protocol (theta/beta) and longitudinal follow-up at 13 months and 25 months (NACG 2021, 2023). The results show positive effects on attention levels, but no differences between the group of patients who received NF and the control group of patients who received "sham NF". The authors concluded that the observed gain in attention can be attributed to the neurocognitive component of training and operant conditioning, and not to a specific physiological effect of NF. The work performed by Anna Wexler's group (Department of Medical Ethics, University of Pennsylvania) also argues that NF has a placebo effect (Nagappan 2021, Kalokairinou 2022). In addition, the positive effects observed are modest and significantly behind those of pharmacological treatments (Loriette 2021, Purper-Ouakil 2021).

In a 2023 review, the European ADHD Guidelines Group (Coghill 2023) stressed the
difficulties in assessing the effectiveness of different therapeutic approaches to ADHD due to
the lack of studies conducted with rigorous protocols. For these reasons, NF is not included in
the recommended treatments. The same stance has also been taken by the French National
Health Authority (HAS) in its 2020 and 2024 guidelines. Note that the American Academy of
Pediatrics was initially in favor of NF back in 2011, before changing its position by 2019 in
its revised recommendations (Wolraich 2019).
Neurofeedback and private "study skills coaching"

Another fast-growing sector that applies NF is learning support (coaching) delivered at home or in private practices. Many companies offer "solutions" for boosting cognitive performance through the use of NF in children with or without neurodevelopmental disorders.

The promotional messages on most of the websites offering this service suggest that NF can improve intelligence, memory, attention, mood, etc. They sell their services using pseudo-scientific claims that are likely to mislead not only the general public but also uninformed healthcare and educational staff. Such abuses were analyzed by Anna Wexler's team in an article entitled "Neuroenhancement for Sale: Assessing the Website Claims of Neurofeedback Providers in the USA" (Wexler 2020). The article highlights how some websites exploit vulnerable parents who use private practices for NF sessions not covered by their health insurance. Session costs are estimated at between $3,000 and $10,000 (Thibault 2018). Equivalent situations can be found in France, where various self-proclaimed private "Institutes", "Practices" and "Clinics" offer NF sessions and training to become an NF practitioner. In France and abroad, there is no legal framework restricting access to NF training and practice. It only takes a few hours of training (between 14 and 36 hours, with an average cost €2,000) to practice NF in a clinic and receive patients (Pouch 2018). Some companies marketing NF specifically target the home tutoring market by offering differentiated teaching methods for children with dys disorders and ADHD.

Generally speaking, a certain audience (parents and caregivers) has put its faith in NF since it is presented as an alternative to a drug-based approach, with no undesirable side effects and scientifically proven. This promotional pitch was used by the company "Neurocore" in the United States, which has been sanctioned by the federal regulatory agencies for making misleading advertising claims. The case was leaked to the media, since a major investor in Neurocore was the first Trump administration's education secretary, Betsy Devos, leading to speculation that she planned to introduce NF into public schools<fnref n="4" />.

<footnote n="4">⁴ https://www.washingtonpost.com/posteverything/wp/2017/05/26/betsy-devos-neurocore/. https://rationalwiki.org/wiki/Neurocore.</footnote>
### 1.2.2 Transcranial brain stimulation

These are non-invasive techniques that involve applying electrical stimulation through the skull to alter neuron activity in the underlying brain areas. Research tends to focus on transcranial direct current stimulation (tDCS), which may have potential therapeutic applications, such as psychiatric disorders, depression and chronic pain (Antal 2022, Lefaucheur 2017). In practice, tDCS is delivered through electrodes attached to a lightweight headset that is remotely controlled to adjust the intensity of the current and duration of the stimulation. Typically, protocols include two to five 30-minute stimulation sessions per week over a period of at least three weeks.

Reviews and meta-analyses of experiments conducted in pediatric populations with neurodevelopmental disorders (autism, ADHD, dyslexia and Tourette syndrome) show overall positive effects (Antal 2022, Finisguerra 2019). However, these results cannot be used to draw conclusions about the true effectiveness of tDCS, because recurrent methodological biases can be found in most of the publications, namely too few patients, no control group, lack of long-term follow-up to assess effectiveness in everyday life, and uncertainty over the propagation of electrical current to the brain. In addition, there are known risks of adverse side effects, such as headaches, dizziness and neck pain (Lodewyk 2024). The therapeutic use of tDCS is not approved by the FDA (Food and Drug Administration) or any professional medical organization, including in France.

Recent studies have rigorously tested the effects of transcranial stimulation in different regions of the cerebral cortex (prefrontal and inferior frontal) in young subjects with ADHD. The results showed no improvement in clinical symptoms or cognitive performance (Westwood 2021).

In healthy subjects, some studies suggest the possibility of applications to improve memory and learning capabilities. However, the methodological shortcomings in the test conditions to date mean that no conclusions can be drawn about the effectiveness of these stimulation techniques (Jwa 2023, Wexler 2020, Nagappan 2021). A few research studies conducted with rigorous protocols have analyzed the effects of transcranial stimulation in the prefrontal cortex on episodic and associative memory in adults. Their results did not show any differences between stimulated and control groups in the memory tests (Bartl 2023, Habich 2020).

It is striking to see that there is a gap between the lack of scientific validation for the effects of transcranial stimulation and the booming online market in cognitive enhancement in several countries (USA, Canada, Sweden, UK, France, etc.). Startups are offering turnkey tDCS kits (headsets, smartphone/tablet apps, batteries, etc.) starting at $300. Their marketing claims of increasing brain capabilities play with the credulity of certain vulnerable people, especially parents of children with learning difficulties (Wurzmann 2016).
1.3 Neurotechnology in school and university education

The convergence of neurotechnology and digital technology in education is breaking out of laboratories and making inroads into classrooms and campuses. Until recently, studies on brain activity in learning situations were confined to experiments conducted outside school settings. Since 2019, research has shifted into the very real environment of elementary, middle and high schools, and universities.

Most experiments involve university students (18-25 years old). Studies involving small groups of students (n=20 to 30) have shown correlations between brain wave amplitude and frequency and their attention level during classes. These observations confirm the findings from many previous research studies carried out under experimental laboratory conditions (Grammer 2021, Ko 2017).

Most of the research conducted in high schools has been conducted by Suzanne Dikker's team from the Department of Psychology at New York University (Bevilacqua 2019, Dikker 2017, 2020). The results have shown that when teaching is delivered in the late morning, there is a stronger correlation between attention level, learning performance and EEG waves (low-amplitude alpha waves). A phenomenon of EEG synchronization between students when the attention of the whole class is shared has also been observed. The authors have concluded that EEG is useful for analyzing the dynamics of teaching times and classroom interactions.

The few studies published to date that look at elementary school have shown correlations between attention, EEG waves and learning (Vekety 2022, Xu K 2022). However, these observations lack reliability, since the experimental conditions are uncontrolled and open to motion artifacts and fatigue in young children (García-Monge 2023).

In conclusion, there is only preliminary and fairly unconvincing scientific and educational evidence that brain wave recording can make a contribution to real-world learning settings (García-Monge 2023, Xu J 2018). Experiments have only involved small numbers of learners, mostly adults and very few at a young age, and a comparison with a control group is often lacking. Learning tests are limited (reading and arithmetic) and not representative of the various cognitive functions that are used when acquiring and retrieving knowledge. In addition, EEG recording quality is often poor due to the use of inexpensive off-the-shelf headsets.

However, the lack of scientific evidence has not diminished the interest shown by academia, governments and private companies in jointly developing neurotechnology and digital technology in education. The United States and China have achieved the greatest progress in this area.
United States

In the United States, "Mind, Brain and Education" has been a university discipline in its own right for 20 years, equipped with research centers, dedicated journals, international conferences, and public and private funding<fnref n="5" />.

Current research is increasingly tending to incorporate commercial neurotechnology companies. For instance, startup BrainCo (https://brainco.tech), which was developed at the Harvard Innovation Lab, specializes in monitoring learning for high school students through personalized digital resources cross-referenced with EEG data. BrainCo claims that its headsets can help teachers identify students requiring additional support. Headsets display a blue light for students whose brain activity is below the class average, yellow for those within the average and red for those above (www.neuromakerstem.com/neuromaker-bci).

Several experiments are being conducted in private schools in the USA in partnership with brain-computer interface manufacturers. In California, the Synapse School is collaborating with the Brainwave Learning Center at Stanford University on a program to improve learning among students equipped with EEG headsets (www.synapseschool.org/innovation/blc).

Muse (https://chooseemuse.com/muse-research/), which specializes in EEG headsets, has partnered with the private Millennium Schools (www.themillenniumschools.com/). Similar experiments are being led by such companies as NeurOptimal (https://neuroptimal.com/education-zengar/), Neurocore (www.neurocore.tv), NeuroSky (http://neurosky.com/), SharpBrains (https://sharpbrains.com/pervasive-neurotechnology), and Emotiv (www.emotiv.com/).

As the expansion of the metaverse continues to gain momentum, headset designers are developing new features to incorporate biometric data into the immersive experience. Their application in school and university learning is currently being trialed (Refaat El Said 2023).

One neurotechnology leader, OpenBCI, has designed the Galea<fnref n="6" /> headset that will "allow researchers to measure emotions and facial expressions, including happiness, anxiety, depression, attention span and interest level". It is the first headset on the market to integrate so many biometric parameters, whether eye-tracking, electromyogram, cardiac activity, electrodermal activity and EEG. Manufacturers of mixed reality headsets (virtual + augmented) are expected to follow this example, like Apple (Vision Pro), Meta (Quest 3), HTC (Vive XR Elite), Sony and also French startup Lynx.

<footnote n="5">⁵ https://www.leARNINGANDtheBRAIN.com/BLOG/WHAT-IS-MIND-BRAIN-EDUCATION-DEFINING-THE-UNDEFINABLE/</footnote>

<footnote n="6">⁶ https://OPENBCI.COM/COMMUNITY/INTRODUCING-GALEA-BCI-HMD-BIOSENSING</footnote>
## China

In China, an experiment conducted by US company BrainCo in children aged five to six years led to a backlash following a Wall Street Journal report in 2019⁷. Students were equipped with EEG headsets to record their brain activity and monitor their attention levels. Teachers argued that the use of these headsets prompted to students to be more disciplined and work harder in class (Ryckmans 2023). Testing of the device was halted after a wave of criticism swept through Chinese state media and social media platforms.

Since 2019, other AI-powered educational projects have been rolled out in China. Chinese company Squirrel AI<fnref n="8" />, a leader in EdTech and AIEd, has implemented an AI system in more than 60,000 public schools, which tracks students' learning and interprets their emotions detected by a webcam. The use of EEG headsets is the next step.

These experiments have proven popular with the public, since they are supposed to maximize students' chances of passing the national undergraduate admission exam (the Gaokao), which is considered to be a condition for future success in professional life.

## 2. Digital technology (EdTech) and artificial intelligence (AIEd) in education

These technologies aim to improve learning through online educational data (Williamson 2024). They are aimed at students, teachers and educational institutions.

### 2.1 EdTech and AIEd for students

#### Intelligent tutoring

Many digital platforms are currently being developed for the education sector, but the Intelligent Tutoring System (ITS) is the most common. The aim is to provide students with automated teaching geared towards their personality. The ITS analyzes web browsing data, the tasks performed and the mistakes made to generate adapted questionnaires as part of a personalized learning pathway based on each student's strengths and weaknesses (Bocquet 2023, Holmes 2022).

An illustrative example of such a system is the ITS developed by Google<fnref n="9" />. The "Gooru Navigator for Learners", which is presented as an "interactive GPS for learning", guides students using the resources from the platform's data. IBM, Apple, Microsoft and Adobe are also producing AI-assisted educational applications (language learning, mathematical problem

<footnote n="7">⁷- https://www.wsj.com/articles/chinas-efforts-to-lead-the-way-in-ai-start-in-its-classrooms-11571958181 - https://www.theguardian.com/world/2019/nov/01/chinese-primary-school-halts-trial-of-device-that-monitors-pupils-brainwaves.</footnote>

<footnote n="8">⁸- https://almostism.com/china-experiments-squirrel-ai-education.</footnote>

<footnote n="9">⁹- https://play.google.com/store/apps/details?id=org.gooru.student navi gator&hl=ln&gl=US.</footnote>
solving, etc.) that are available in the leading app stores. According to estimates, the US
digital education market will be worth $30 billion by 2030 (GMI 2022).

AI for students with special needs

Some commercially available EdTech systems have been developed to help students with learning difficulties associated with attention disorders, including ADHD, dyslexia, dysgraphia or autism spectrum disorders (Asselborn 2020, Lundy 2019, Porayska-Pomsta 2018). These systems are set up as pilot experiments. Their effectiveness has yet to be demonstrated.

Digital Game-Based Learning (DGBL)

These are virtual reality and augmented reality simulations based on commercially
available games and adapted to educational learning contexts (Ragni 2023). DGBL is
presented as a valuable tool for capturing students' attention by transforming learning into a
fun activity that encourages teamwork between students and communication with the teacher
(Grudpan 2022).

The metaverse in education

The latest AIEd developments are increasingly being rolled out across metaverse-
based platforms<fnref n="10" /> (Knox 2022). Using the metaverse in education is intended to simulate the
physical experience of the classroom or campus in 3D. The aim is to transform online
learning, where students are alone in front of their screen, into a collective and interactive
experience (Refaat El Said 2023).

Microsoft, Meta and Google are plowing vast investments into developing the
metaverse in educational projects. China, South Korea and Japan are already well ahead in
this area.

In France, Meta<fnref n="11" /> entered into a partnership agreement in 2023 with France Immersive
Learning, the leading French association dedicated to the use of immersive technologies. The
aim is to develop the use of the metaverse in school and university learning and in vocational
training.

Higher education schools (Neoma Business School, Metaverse College, Kwark
Academy and Paris School of Technology & Business) already offer training courses that take
place in the metaverse. The metaverse concept is capable of appealing to students with its
image of an educational system on the cutting edge of innovation. Experimental programs are

<footnote n="10">¹⁰ - French National Pilot Committee for Digital Ethics (CNPEN) Opinion No. 9: Metaverses: ethical issues, April 2024, https://www.ccne-ethique.fr/sites/default/files/2024-04/CNPEN_A9_Metavers_2024-02-29.pdf.</footnote>

<footnote n="11">¹¹ - https://about.fb.com/news/2023/04/how-the-metaverse-can-transform-education/.</footnote>
underway at the ESCP Business School and Sciences Po Institute of Political Studies in Paris<fnref n="12" />.

## 2.2 EdTech and AIEd for teachers and institutions

### Learning analytics

Today, there are many education science research projects devoted to learning analytics (Bonnin 2015, Labarthe 2018, Williamson 2024). The digital traces that students leave behind are used to create more effective learning models that automatically adapt to the student's individual characteristics. They are intended to provide teachers with new educational tools for such uses as building learning pathways and detecting "drop-out" students.

### Digital education tools: between the private and public sector

In the private sector, Google's<fnref n="13" /> “Workspace for Education” app targets teachers and schools. The idea is to use digital tools to simplify the process of organizing teaching, improving collaboration and planning courses. The solution also protects the school's data. Experiments are also being carried out for automating homework scoring, detecting plagiarism and invigilating remote examinations (e-Proctoring). IBM (Watson Education Classroom), Microsoft and Adobe have developed similar systems (Holmes 2022).

The European Union has launched a Digital Education Action Plan (2021–2027) to support the adaptation of the Member States' education and training systems to the digital age. In 2022, ethical guidelines on the use of artificial intelligence and data in teaching and learning for educators were published<fnref n="14" />.

In France, the National Ministry of Education has set up the "Réseau Canopé" network<fnref n="15" />, which offers digital resources to train teachers. The spate of lockdowns caused by the Covid-19 pandemic saw teachers increase their use of digital education tools. Since 2000, the Directorate General of School Education has been providing online educational resources, such as Eduscol<fnref n="16" /> and Ma Classe à la Maison (my home class) from the CNED<fnref n="17" /> (French national center for distance learning).

<footnote n="12">¹² - https://start.lesechos.fr/apprendre/universites-ecoles/metavers-et-enseignement-gadget-ou-vraie-innovation-pedagogique-1409325.</footnote>

<footnote n="13">¹³ - https://edu.google.com/intl/ALL_fr/workspace-for-education/editions/overview/.</footnote>

<footnote n="14">¹⁴ - https://education.ec.europa.eu/fr/focus-topics/digital-education/action-plan.</footnote>

<footnote n="15">¹⁵ - https://www.reseau-canope.fr/congres-international-les-sciences-cognitives-dans-la-salle-de-classe/captations1551.html.</footnote>

<footnote n="16">¹⁶ - https://eduscol.education.fr/.</footnote>

<footnote n="17">¹⁷ - https://www.cned.fr/espace-presse/dispositif-de-continuite-pedagogique.</footnote>
According to a 2020 report by the French Ethics Committee for Educational Data<fnref n="18" />,
the vast majority of French schools have chosen software and digital platforms developed by
foreign private companies, since they offer better features than the tools available from the
French public sector.

## 2.3 Evaluating digital education systems: effectiveness yet to be demonstrated

According to the findings of meta-analyses conducted over the past two decades into the impact of digital technologies on learning, modest positive effects have been observed when compared to traditional teaching methods (Refaat El Said 2023). Preliminary studies on the metaverse suggest that the 3D virtual environment is associated with improved memorization of information, thereby promoting knowledge recall and learning processes (Almeida 2019).

These kinds of results must be put into perspective, especially due to the lack of independent evaluations. Most assessments have been conducted by commercial EdTech companies, most often with a relatively small number of learners.

**In conclusion,** for want of robust data on the effectiveness of the current digital education system, many questions remain unanswered, especially whether digital traces are representative of the acquisition of knowledge that is truly useful for students in their learning pathway<fnref n="19" />. Diagnostic criteria for assessing the quality of a teaching method and guiding teaching choices are lacking (Bocquet 2023, Holmes 2022, Williamson 2019, 2024).

Yet expectations are running high about the future impact of digital technology in education. According to one leading AI entrepreneur, Kai-Fu Lee (formerly a senior executive at Google, Microsoft, SGI and Apple): "Unlike human teachers, who have to consider the whole class, a virtual teacher can pay special attention to each student, whether it is fixing specific pronunciation problems, practicing multiplications, or writing essays. An AI teacher will notice what makes a student's pupils dilate and what makes a student's eyelids droop" (cited in Holmes 2022).

These kinds of perspectives see **automated teaching going hand-in-hand with the biometric monitoring of students' behavior in learning settings.** Whether personalized intelligent tutoring or interactive immersion in the educational metaverse<fnref n="20" />, the objective with

<footnote n="18">¹⁸ - French Ethics Committee for Educational Data, Opinion No. 2020-1 - Ethical issues for using educational digital data in the context of the pandemic, https://www.education.gouv.fr/le-comite-d-ethique-pour-les-donnees-d-education-12146.</footnote>

<footnote n="19">¹⁹ - UNESCO. 2023. Global Education Monitoring Report 2023: Technology in education – A tool on whose terms? https://unesdoc.unesco.org/ark:/48223/pf0000385723.</footnote>

<footnote n="20">²⁰ - French National Pilot Committee for Digital Ethics (CNPEN) Opinion No. 9: Metaverses: ethical issues, April 2024, https://www.ccne-ethique.fr/sites/default/files/2024-04/CNPEN_A9_Metavers_2024-02-29.pdf.</footnote>

<footnote>- https://about.fb.com/news/2023/04/how-the-metaverse-can-transform-education/.</footnote>
an effective educational innovation is to understand students' reactions and emotions by taking account of individual physical and behavioral parameters (Canal 2022, Marín-Morales 2020, Refaat El Said 2023).

## 3. Ethical and societal issues concerning the convergence of neurotechnology and digital technology in education

Ethical discussions about neurotechnology and digital technology in education are based on fundamental principles, such as the protection of brain data and privacy, informed consent for identified uses, respect for cognitive liberty and freedom of thought. Specific questions surround the use of these technologies in schools with children and teenagers, including the impact on their physical and psychological development, and the protection of minors' digital rights. Related concerns are the risk of seeing public education becoming dependent on private sector technology systems and also the environmental damage associated with the widespread use of digital technology in education.

### 3.1 Protecting students' mental and physical integrity

As technological developments currently stand, biometric data (EEG, facial expressions, viewing direction, etc.) can be captured to generate information about the nervous system's activity, which is mainly related to the subject's attention and emotional levels.

In the near future, it is likely that increasingly sophisticated recording devices and AI-powered algorithmic processing of data will provide a more accurate insight into certain mental states and personality traits. These data could be used to define the most appropriate learning conditions for each student's cognitive profile. Children with attention disorders would be the primary beneficiaries.

The downside is that these data could potentially be accessed by a third party with the risk of interfering with the privacy of the child's psychological life and exerting an influence for purposes other than academic success (Holmes 2022, Vidal 2022). Brain data are likely to be highly coveted sources of information for marketing, ideological or other purposes (insurance companies, corporations, police, cybercrime, etc.) (see UNESCO 2021, 2024, UNICEF 2021 reports). The convergence of these data with other digital data could culminate in the personalized monitoring and targeting of children, with the ability to influence their opinions, preferences, behavior, and so forth.

In addition, combining neurotechnology with digital tools raises unresolved questions about the impact on the child's brain and cognitive development, and the associated health risks (Gottschalk 2019, Holmes 2022, Williamson 2019, 2023, 2024). Brain-computer interfaces (neurofeedback and transcranial stimulation) could potentially disrupt the neuronal circuit formation process during the so-called critical phases of brain development, with negative cognitive (memory and reasoning) and emotional (self-control) effects.
Another area for concern is "neuronormalization", whereby procedures targeting children's brains (conditioning by neurofeedback and stimulation) are used to bring them into line with what is considered to be "standard". A related potential risk is "neurodiscrimination" based on "neural signatures" that do not fit the brain standards of the majority, when these are defined using a sample of subjects from affluent countries that are not representative of the neurodiversity present across all human beings (Ienca 2021, 2022). Their use by sectarian groups or non-democratic governments is a potential threat.

All these questions raise major ethical challenges and legal issues that have spurred international bodies into action, such as UNESCO, the OECD and the Council of Europe, which are calling for the development of ethical and regulatory frameworks based on "neurorights".

In a 2021 report, the International Bioethics Committee of UNESCO<fnref n="21" /> (IBC) states: "robust protective measures are required in order to preserve the human rights, including autonomy and liberty, of vulnerable human beings. This is especially the case for children, whose brain data could be defining not only in terms of shaping them (their perception as a human being) but could impact their future opportunities."

In France, the Ministry of Higher Education and Research drew up its "Guidelines for responsible neurotechnology development"<fnref n="22" /> in 2022, in alignment with the OECD's recommendations for personal data protection. These guidelines are aimed at shielding patients and consumers against potentially abusive and malicious uses of brain data, leading to a loss of cognitive liberty or a lack of respect for the confidentiality of such data.

Special focus should be given to children/teenagers in future versions of the guidelines.

<footnote n="21">21 - UNESCO - 2021: Report of the International Bioethics Committee of UNESCO (IBC) on the ethical issues of neurotechnology, https://unesdoc.unesco.org/ark:/48223/pf0000378724_en.</footnote>

<footnote n="22">22 - https://www.enseignementsup-recherche.gouv.fr/fr/charte-de-developpement-responsable-des-neurotechnologies-87964.</footnote>
Neurorights

The term neuroright was coined for the first time in 2017 by medical ethics researchers Marcello Ienca (University of Lausanne) and Roberto Andorno (University of Zurich) in an article entitled "A new category of human rights: neurorights" (Ienca 2017a).

The authors argue that "the possibilities opened up by neurotechnological developments and their application to various aspects of human life will force a reconceptualization of certain human rights, or even the creation of new rights to protect people from potential harm."

Neurorights are arranged into three main categories:

- Right to mental privacy: the need for specific provisions on the protection of private mind-related information.

- Right to mental integrity: the need to protect the person from psychological damage and mental interference.

- Right to freedom of thought, the right to cognitive liberty and the right to personal identity: the need to preserve and promote the freedom of the human mind and thereby prevent external manipulation.

International bodies, such as UNESCO, the OECD and the Council of Europe, recognize the fundamental rights of every individual to physical and mental integrity, a private mental life, freedom of thought and decision-making, and the right to benefit from advances in science and neurotechnology, and to make decisions freely and responsibly on the use of neurotechnology, without any form of discrimination, coercion or violence.

In October 2021, Chile became the first country in the world to adopt a law recognizing neurorights and prohibiting the exploitation of brain data without consent.

- Ienca M. 2021, *Common Human Rights Challenges Raised by Different Applications of Neurotechnologies in the Biomedical Field*
  Committee on Bioethics of the Council of Europe, https://rm.coe.int/report-final-en/1680a429f3.

- Ienca M, Andorno R (2017a) A new category of human rights: neurorights. http://blogs.biomedcentral.com/bmcblog/2017/04/26/new-category-human-rights-neurorights/.

- Ienca M, Andorno R (2017b) Towards new human rights in the age of neuroscience and neurotechnology. Life Sciences, Society and Policy, 13, 5, doi: 10.1186/s40504-017-0050-1.

- Yuste R et al. (2021) It's Time for Neuro-Rights. Horizons, Journal of International Relations and Sustainable Development 18, 154-165.

From a regulatory point of view, the question as to whether the General Data Protection Regulation (GDPR) applies to brain data has caused significant debate in Europe. If brain data are collected in a non-clinical context, they can only be described as "sensitive health data" if they are likely to reveal information about the individual's health. In terms of personal private use, they would not be subject to the GDPR. However, in light of the risks of violating mental
privacy and neurodiscrimination, the GDPR's application should be broadened to encompass brain data without any restrictions<fnref n="23" /> (Ienca 2021).

A few avenues warrant further investigation:

- Brain data are "sensitive" within the meaning of the GDPR, which deserves to be recognized.

- Compliance with all the main principles of personal data protection must be documented and controlled (principle of purpose, data minimization, non-discrimination, lawful nature of processing, right to be forgotten, etc.).

- Multidisciplinary discussions should be undertaken to examine the best conditions for informing and obtaining consent from children (Convention on the Rights of the Child) and look at the conditions for storing brain data collected from children with the consent of their legal representatives. When a child turns 18 and becomes an adult, the conditions for obtaining new consent, storing and/or erasing data should be redefined.

- Define ethical and responsible guidelines for neurotechnology companies (transparent measures to protect minors' brain data, conditions for sharing data with third parties, etc.) in accordance with the "privacy by design" principle enshrined in the GDPR.

On an international level, a UNESCO recommendations guide<fnref n="24" /> is nearing completion and will support the Member States in establishing a legislative framework for the development of neurotechnology and the protection of neurorights. Over 200 recommendations are included, including the protection of children and teenagers.

Protecting students' physical integrity is another area of ethical concern<fnref n="25" />. There is a consensus among the scientific community that massive screen use and immersion in virtual worlds affect our bodies and brains<fnref n="26" />. As their mainstream use in schools inches ever closer, this will raise specific risks for children and teenagers whose nervous systems are still developing. The visual system is particularly vulnerable: blue light, lack of exposure to natural light and greater strain on near vision have led to a sharp rise in myopia worldwide. Sensory and motor isolation from the physical environment, sedentary lifestyles and attraction

<footnote n="23">²³ - Council of Europe & OECD, 2022 "Neurotechnologies and Human Rights Framework: Do We Need New Rights?", https://rm.coe.int/round-table-report-en/1680a969ed.</footnote>

<footnote>- UNESCO, 2023, *The Risks and Challenges of Neurotechnologies for Human Rights*, https://unesdoc.unesco.org/ark:/48223/pf0000384185.</footnote>

<footnote n="24">²⁴ - UNESCO 2024 Recommendation on the Ethics of Neurotechnology, https://www.unesco.org/en/ethics-neurotech/recommendation.</footnote>

<footnote n="25">²⁵ - UNESCO. 2023. *Global Education Monitoring Report: Technology in education – A tool on whose terms?* https://unesdoc.unesco.org/ark:/48223/pf0000385723.</footnote>

<footnote n="26">²⁶ - Bousquet-Bérard C, 2024 "Enfants et écrans. À la recherche du temps perdu, www.vie-publique.fr/rapport/293978-exposition-des-enfants-aux-ecrans-rapport-au-president-de-la-republique.</footnote>

<footnote>- ANSES (2021), *What are the risks of virtual reality and augmented reality, and what good practices does ANSES recommend?* https://www.anses.fr/en/content/what-are-risks-virtual-reality-and-augmented-reality-and-what-good-practices-does-anses.</footnote>
to virtual worlds cut young people off from the social interactions that play a decisive role in
their cognitive and emotional development<fnref n="27" />.

3.2 Protecting minors' digital rights

In its 2023 Global Education Monitoring Report, UNESCO²⁴ highlighted the gaps in legislation to protect children's personal data and privacy:

"Only 16% of countries explicitly guarantee data privacy in education with a law. One analysis found that 89% of 163 education technology products recommended during the pandemic could survey children. Further, 39 of 42 governments providing online education during the pandemic fostered uses that risked or infringed on children's rights."

This observation calls for measures to reinforce minors' digital rights (Holmes 2022). Recommendations issued by the CNIL's Digital Innovation Laboratory<fnref n="28" /> and the French Defender of Rights<fnref n="29" /> state: "Specific attention must be paid to personal data relating to education, which mainly concern minors. It should be remembered that although personal education data is not considered to be sensitive data within the meaning of the GDPR, they may become sensitive if they are cross-referenced with other data.

In France, the age of internet adulthood is 15, meaning that young people aged 15 and above must be informed of their rights, so that they can give or refuse their consent to the use of their digital data. Below the age of 15, joint consent is required from the persons possessing parental responsibility and the child.

Protecting children also means educating them about digital technology and giving them the keys to play an active role in shaping their own digital lives.

The 2024 report to the French President on screen exposure in children<fnref n="30" /> emphasized that current training for pupils on digital technology and education on the media and information – as formalized by the National Ministry of Education – are wholly insufficient and "overlook issues that are specific to children and their digital environment, the functioning of their brains and their relationships with information, the reality of their daily uses and their needs".

<footnote n="27">²⁷ - UNICEF (2023), *The Metaverse, Extended Reality and Children*.</footnote>

<footnote n="28">²⁸ - CNIL, Digital rights of children 2021, https://www.cnil.fr/en/topics/digital-rights-children.</footnote>

<footnote>- LINC; CNIL Digital Innovation Laboratory, https://linc.cnil.fr/affective-computing-des-casques-qui-analysent-le-cerveau.</footnote>

<footnote n="29">²⁹ - Defender of Rights 2022 Report - Privacy: a right for the child, https://juridique.defenseurdesdroits.fr/doc_num.php?explnum_id=21507.</footnote>

<footnote n="30">³⁰ - Bousquet-Bérard C, 2024 "Enfants et écrans. À la recherche du temps perdu, www.vie-publique.fr/rapport/293978-exposition-des-enfants-aux-ecrans-rapport-au-president-de-la-republique.</footnote>
## 3.3 Protecting the autonomy of education systems

In 2023, UNESCO published a report entitled "Education in the age of artificial intelligence",<fnref n="31" /> which draws on examples from various countries. In the United States, an analysis of more than two million students found that learning inequalities widened when teaching was delivered exclusively through remote instruction. The report stressed that "technology must never replace well-trained, human teachers who guide their students in their holistic development, as individuals and members of society (...) to unlock the promise of digital opportunities for all, we must steer technology in education on our terms, guided by the principles of inclusion, equity, quality and accessibility".

The Council of Europe report<fnref n="32" /> written by Wayne Holmes et al. in 2022 highlights the risk of schools becoming dependent on digital companies and losing their autonomy, resulting in public education becoming dependent on private sector technology that has no accountability (Selwyn 2019). This kind of outlook calls for caution in response to the risk of diverting educational projects from their collective, cultural and social content, while raising questions about the extent of teacher autonomy when educational methods designed to meet the parameters measured by service providers' digital tools are imposed.

## 3.4 Protecting the environment

A study by ADEME (French environment & energy management agency) and ARCEP (French telecommunications regulatory authority)<fnref n="33" /> in 2022 found that digital technology currently accounts for 3 to 4% of greenhouse gas emissions worldwide and 2.5% in France. This figure could increase by 60% by 2040.

The increasingly widespread use of digital technology in schools is likely to contribute to accelerating environmental deterioration on a global scale.

<footnote n="31">³¹ - UNESCO 2023, report on education in the age of artificial intelligence, https://unesdoc.unesco.org/ark:/48223/pf0000387029_eng.</footnote>

<footnote>- Williamson B 2023, AI must be kept in check at school
The UNESCO Courier: Education in the age of artificial intelligence, https://unesdoc.unesco.org/ark:/48223/pf0000387029_eng.</footnote>

<footnote n="32">³² - Holmes W et al. 2022, Artificial intelligence and education: A critical view through the lens of human rights, democracy and the rule of law, Council of Europe, https://rm.coe.int/artificial-intelligence-and-education-a-critical-view-through-the-lens/1680a886bd.</footnote>

<footnote>- Bocquet F. 2023, State of the Art and Practice of Artificial Intelligence in Education (Translation from Holmes & Tuomi, 2022, Eur.J of Education, https://doi.org/10.1111/ejed.12533). https://edunumrech.hypotheses.org/8350.</footnote>

<footnote n="33">³³ - ADEME-ARCEP study 2022, https://www.arcep.fr/uploads/tx_gspublication/etude-numerique-environnement-ademe-arcep-note-synthese_janv2022.pdf.</footnote>
Neurotechnology and the metaverse are incredibly energy-intensive due to the high volumes of data collected and then processed by AI<fnref n="34" />.

## 4. Recommendations

These recommendations draw their inspiration from the major principles formulated in the various institutional reports on the ethical aspects of digital technology in education, neurotechnology and the metaverse.

- Carry out and repeat methodologically rigorous impact studies on the current and future use of new digital technologies in education (neurotechnology, metaverse and AI), including their benefits and risks.

- Support independent research on the use of digital technologies in education among potentially vulnerable people (children, teenagers and individuals with special needs, especially students with neurodevelopmental disorders) and on educational practices.

- Develop a code of conduct for educators on the use of neurotechnology and digital innovations in school settings for children/teenagers.

This code should enshrine the principle that these technologies must not replace human intervention or excessively infringe the rights and freedoms of children/teenagers whose autonomy and neurorights must be protected, including informed consent from minors and their legal representatives, protection of privacy, supervision and transparent use of these technologies, data minimization (pseudonymization or even anonymization), adoption of security measures to guarantee the confidentiality of the personal data collected, and limited data storage periods.

- Define an ethical framework that protects children from social sanctions and pressure from supervisors (parents, teachers, educators, etc.) who could encourage them to use neurotechnology in the hope of increasing their cognitive performance.

- Ensure equal access to new technologies in the education sector for all children/teenagers if such technologies enter widespread use. Consider the risk of individuals becoming accustomed from an early age to a form of near-permanent control, to the extent that they are no longer able to perceive it as intrusive.

<footnote n="34">³⁴ - French National Pilot Committee for Digital Ethics (CNPEN) Opinion No. 9: Metaverses: ethical issues, April 2024, https://www.ccne-ethique.fr/sites/default/files/2024-04/CNPEN_A9_Metavers_2024-02-29.pdf.</footnote>
- Implement the "Guidelines for responsible neurotechnology development" (Ministry of Higher Education and Research) by taking measures specifically aimed at protecting the brain data of children/teenagers who are learning to become autonomous and whose inherent freedom in their construction and development as individuals must be defended.

- Lead discussions into the potential purposes of neurotechnology that may be prohibited. For example, the European Union's AI Act<fnref n="35" /> prohibits practices that are contrary to EU values and fundamental rights, such as emotion recognition systems in the workplace and in educational institutions.

- Define good practice frameworks for neurotechnology companies, so that they are required to provide transparent information about the measures taken to guarantee the protection of the minors' brain data and not disclose such data to third parties. Encourage the use of the "Privacy by design" principle as a commercial argument (certification, label, etc.).

- Adapt regulations so that designers and operators of digital technologies in education are compelled to implement mechanisms to protect minors against the hacking of brain data and cyber-bullying.

- Assess how existing regulations in Europe, such as the GDPR, the Digital Services Act and the EU AI Act, apply to neurotechnology and digital innovations in school settings for children/teenagers.

- Organize information and training campaigns on the use of digital tools (neurotechnology, metaverse and AI) for students, parents and teachers, including the benefits and dangers, particularly for health.

<footnote n="35">³⁵ European Artificial Intelligence Act</footnote>

<footnote>- https://artificialintelligenceact.eu/high-level-summary/</footnote>

<footnote>- https://www.vie-publique.fr/questions-reponses/292157-intelligence-artificielle-le-cadre-juridique-european-en-6-questions</footnote>
# 5. Glossary

## Neurotechnology

Neurotechnology (NT) is a thriving field of research and innovation that combines neuroscience with digital technology. According to the UNESCO definition, neurotechnology consists of devices and procedures that can derive knowledge from an individual's brain activity or influence and modify it.

## Brain-computer interface

Neurotechnology uses invasive or non-invasive brain-computer interface devices that connect to the brain and record and/or modify neuronal activity. These devices are used in research and clinically in humans, but also outside the medical field in such areas as personal well-being, monitoring mental states, and education.

## Neurofeedback

A brain training practice based on recording brain activity (EEG), and showing the data to the subject. The aim is for users to learn to how to modulate their own brain waves based on this information, by responding to an instruction (cognitive training, monitoring alertness, etc.). Recording devices (headsets or headbands fitted with electrodes) are non-invasive and painless.

Neurofeedback is also used in medical situations (a paralyzed person controlling an exoskeleton, focusing attention in depressive disorders, etc.). Healthy subjects may also use it in "well-being therapies" to control their stress, sleep and concentration. Experiments are underway in school settings to improve attention and learning abilities.

## Transcranial stimulation (TCS)

This technique involves applying electrical pulses via electrodes through the skull to alter neuron activity in the underlying brain areas. Clinical applications of TCS are still in the experimental stages (psychiatric disorders, depression, chronic pain, etc.). TCS has yet to prove its effectiveness in improving cognitive performance.

## Metaverse

A metaverse is an immersive digital environment providing access to virtual reality (VR) and/or augmented reality (AR) simulations modeled in 3D. Users wear a headset fitted with sensors and can use an avatar to walk within these worlds and interact with other avatars.

## Educational technology (EdTech)

The term refers to an industry that aims to transform and enrich educational practices through digital technology. Online education platforms, which can be public or private, offer resources, activities and services, including access to information, assessment of learning, personalized training pathways, and organization of teaching in and outside the classroom. They are aimed at students, teachers and educational institutions.
## Learning analytics

A nascent discipline that collects and analyzes the digital traces that students leave behind to create more effective learning models that automatically adapt to the student's individual characteristics. They are intended to provide teachers with new educational tools for such uses as building learning pathways and detecting "drop-out" students.

## Neurorights

Neurorights can be arranged into three main categories.

- Right to mental privacy: the need for specific provisions on the protection of private mind-related information.

- Right to mental integrity: the need to protect the person from psychological damage and mental interference.

- Right to freedom of thought, the right to cognitive liberty and the right to personal identity: the need to preserve and promote the freedom of the human mind and thereby prevent external manipulation.

## General Data Protection Regulation (GDPR)

European regulation governing the protection of personal data (EU Regulation 2016/679 of 27 April 2016 on the protection of personal data and on the free movement of such data).

## Personal data

Any information relating to an identified or identifiable natural person, who must be able to retain control of such information.

A natural person can be identified:

- Directly (e.g. surname and first name).

- Indirectly (e.g. telephone number, social security number, postal address, email address, but also voice or image).

A natural person can be identified from:

- A single piece of data (e.g. name)

- Cross-referencing of a set of data (address, date of birth, private activities, etc.)

## Sensitive data

Data considered to be sensitive (Article 9 of the GDPR) are those that directly or indirectly show physical or mental health information, genetic data, biometric data for the purpose of uniquely identifying a natural person, and data that reveal sex life or sexual orientation, ethnic origin, or political, religious or philosophical beliefs.

The EU regulation prohibits the collection or use of these data, unless:

- The data subject has given their express consent (written, clear and explicit)

- These data are necessary for medical purposes or for research in the field of health
## Health data

Health data are a special category of personal data, since they are considered sensitive. As such, they are subject to special protection measures by legislation (GDPR, French Data Protection Act, French Public Health Code, etc.) to ensure that individuals' privacy is respected. The concept of health data does not include data from which no consequences can be derived with regard to the data subject's state of health.

# 6. Bibliographical references.

## 6.1 Institutional reports on the ethical aspects of digital technology in education, neurotechnology and the metaverse

### International

- European Commission 2022

Ethical guidelines on the use of artificial intelligence and data in teaching and learning for educators,

https://education.ec.europa.eu/focus-topics/digital-education/action-plan.

- Council of Europe 2022

Holmes W et al., Artificial intelligence and education: A critical view through the lens of human rights, democracy and the rule of law, Council of Europe,

https://rm.coe.int/artificial-intelligence-and-education-a-critical-view-through-the-lens/1680a886bd.

- Council of Europe & OECD 2022

O'Sullivan S et al. "Neurotechnologies and Human Rights Framework: Do We Need New Rights?", https://rm.coe.int/round-table-report-en/1680a969ed.

- Committee on Bioethics of the Council of Europe 2021

Ienca M. 2021, Common Human Rights Challenges Raised by Different Applications of Neurotechnologies in the Biomedical Field, https://rm.coe.int/report-final-en/1680a429f3.

- UNESCO 2021: Report of the International Bioethics Committee of UNESCO (IBC) on the ethical issues of neurotechnology, https://unesdoc.unesco.org/ark:/48223/pf0000378724_en.

- UNESCO 2021, AI and Education: Miao F and Holmes W, Guidance for policymakers

https://www.unesco.org/gem-report/en/technology.

- UNESCO 2023, Global guidance for generative AI in education and research,

https://www.unesco.org/en/digital-education/ai-future-learning/guidance.
- UNESCO 2023, The risks and challenges of neurotechnologies for human rights, https://unesdoc.unesco.org/ark:/48223/pf0000384185.

- UNESCO 2023, Global Education Monitoring Report: Technology in education – A tool on whose terms? https://unesdoc.unesco.org/ark:/48223/pf0000385723/PDF/385723eng.pdf multi.

- UNESCO 2023, Report on education in the age of artificial intelligence, https://unesdoc.unesco.org/ark:/48223/pf0000387029 eng.

- UNESCO 2023, Williamson B, AI must be kept in check at school. The UNESCO Courier: Education in the age of artificial intelligence, https://unesdoc.unesco.org/ark:/48223/pf0000387029_eng.

- UNESCO 2024, Recommendations on the ethics of neurotechnology, https://www.unesco.org/en/ethics-neurotech/recommendation.

- UNICEF 2021, Global insight data governance manifesto. Byrne J, https://www.unicef.org/innocenti/media/1031/file/UNICEF, Global Insight Data Governance Manifesto.pdf.

- UNICEF 2023, The Metaverse, Extended Reality and Children. https://www.unicef.org/innocenti/media/756/file/UNICEF-Innocenti-Rapid-Analysis-Metaverse-XR-and-children-2023.pdf.pdf.

## France

- French Agency for Biomedicine 2023, La Lettre no. 2, La rencontre des neurosciences et de l'intelligence artificielle : une fusion aussi prometteuse que dangereuse [Where neuroscience meets artificial intelligence: a fusion as promising as it is dangerous], https://www.agence-biomedecine.fr/IMG/pdf/2-lettre_de_la_biome_decine_vf_revue.pdf.

- ANSES (French Agency for Food, Environmental and Occupational Health & Safety) 2021 What are the risks of virtual reality and augmented reality, and what good practices does ANSES recommend? https://www.anses.fr/en/content/what-are-risks-virtual-reality-and-augmented-reality-and-what-good-practices-does-anses.

- CNIL (French data protection authority) 2023 + Digital rights of children, https://www.cnil.fr/en/topics/digital-rights-children.

+ LINC; the CNIL's Digital Innovation Laboratory https://linc.cnil.fr/affective-computing-des-casques-qui-analysent-le-cerveau.
- CCNE (National Ethics Advisory Committee for Health and Life Sciences) 2023

Opinion no. 141 CCNE & Opinion no. 4 CNPEN "Medical diagnosis and artificial intelligence: Ethical issues", https://www.ccne-ethique.fr/fr/publications/avis-141-du-ccne-et-4-du-cnpen-diagnostic-medical-et-intelligence-artificielle-enjeux.

- CNPEN (National Pilot Committee for Digital Ethics) 2024

Opinion no. 9, Metaverses: ethical issues, https://www.ccne-ethique.fr/sites/default/files/2024-04/CNPEN_A9_Metavers_2024-02-29.pdf.

- Ethics Committee for Educational Data, 2023,

https://www.education.gouv.fr/le-comite-d-ethique-pour-les-donnees-d-education-12146.

+ Opinion no. 2023-2 - The ethical issues raised by the development of the metaverse within the field of education and its consequences on the use of educational data

+ Opinion No. 2020-1 - Ethical issues for using educational digital data in the context of the pandemic

- Defender of Rights 2022, Report - Privacy: a right for the child, https://juridique.defenseurdesdroits.fr/doc_num.php?explnum_id=21507.

- Department for Digital Technology in Education 2023

+ Romero M. et al. 2023, Enseigner et apprendre à l'ère de l'intelligence artificielle [Teaching and learning in the age of artificial intelligence]

Canopé, white paper. Hal-04013223v2.

+ Contributions from academic research and issues for public policy,

https://edunumrech.hypotheses.org/files/2023/05/MEN_DNE_brochure_IA_WEB.pdf.

- Government

+ Report to the French President 2024:

- Bousquet-Bérard C, "Enfants et écrans. À la recherche du temps perdu", [Children and screens: In search of lost time]

www.vie-publique.fr/rapport/293978-exposition-des-enfants-aux-ecrans-rapport-au-president-de-la-republique.

+ 2022 Report from the interministerial exploratory mission on metaverses,

https://www.vie-publique.fr/rapport/286878-mission-exploratoire-sur-les-metavers.

+ Directorate General for Business. 2023. Éduquer à l'Intelligence artificielle. Stratégie nationale pour l'intelligence artificielle [Educating on artificial intelligence. A national strategy for artificial intelligence],

https://www.entreprises.gouv.fr/fr/numerique/enjeux/developer-ecosysteme-de-talents.

- Ministry of Higher Education and Research 2022

Guidelines for responsible neurotechnology development,

https://www.enseignementsup-recherche.gouv.fr/fr/charte-de-developpement-responsable-des-neurotechnologies-87964.
- UNESCO 2023, French National Commission for the Assessment of the Ethical Impact of Neurotechnology, [brochure_neurotechnologies_26_09_1.pdf](https://delegfrance.org/brochure_neurotechnologies_26_09_1.pdf) (delegfrance.org)

## 6.2 Articles/reports published in scientific journals and referenced websites

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Antal A et al. (2022), Non-invasive brain stimulation and neuroenhancement. Clin Neurophysiol Pract. 25, 146-165, doi: 10.1016/j.cnp.2022.05.002.

Arns M, et al. (2020), Neurofeedback and Attention-Deficit/Hyperactivity-Disorder (ADHD) in Children: Rating the Evidence and Proposed Guidelines. Appl Psychophysiol Biofeedback. 45, 39-48, doi: 10.1007/s10484-020-09455-2.

Arsalan A, Majid M (2022), A study on multi-class anxiety detection using wearable EEG headband. J Ambient Intell Human Comput 13, 5739-5749, https://doi.org/10.1007/s12652-021-03249-y.

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Bartl G, Allen P, Sandrini M. (2023), Left prefrontal tdcs during learning does not enhance subsequent verbal episodic memory in young adults: results from two double blind and sham-controlled experiments. Brain Sci. 13, 241, doi.org/10.3390/brainsci13020241.

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J Cogn Neurosci, 31, 401-411, doi: https://doi.org/10.1162/jocn_a_01274.

Bonnin G, Boyer A (2015). Apport des Learning Analytics. Administration & éducation, Association Française des Acteurs de l'Éducation, 10.3917/admed.146.0125, hal-01259230v2.
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Fontanillo Lopez C et al. (2020), Beyond technologies of electroencephalography-based brain-computer interfaces: a systematic review from commercial and ethical aspects, Frontiers in Neuroscience, 14, ID 611130.

García-Monge, A. et al. (2023), Potentialities and limitations of the use of EEG devices in educational contexts. Comunicar, 76, doi.org/10.3916/C76-2023-04.

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Habich A et al. (2020), No effect of anodal tdcs on verbal episodic memory performance and neurotransmitter levels in young and elderly participants. Neural Plast 22, 8896791, doi: 10.1155/2020/8896791.

Hasslinger J, Jonsson U, Bölte S (2022), Immediate and sustained effects of neurofeedback and working memory training on cognitive functions in children and adolescents with adhd: a multi-arm pragmatic randomized controlled trial. J Atten Disord. 26, 1492-1506, doi: 10.1177/10870547211063645.

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Holmes W (2022), Ethics of AI in Education: Towards a Community-Wide Framework
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