Introduction

Advances in artificial intelligence (AI) and neurotechnology are transforming the way researchers interpret brain activity. Technologies such as brain-computer interfaces (BCIs), electroencephalograms (EEGs) and functional magnetic resonance imaging (fMRI) can detect patterns in neural activity and, with the help of AI, may eventually decode thoughts, intentions and mental states more accurately (Hughes et al., 2020). Currently, these technologies are used predominantly in medical and accessibility settings, such as helping people with disabilities communicate or control prosthetic devices. 

A brain-computer interface is a rapidly developing technology that enables communication between the brain and neural decoders, using advanced neurotechnology to identify correlations between people’s mental states and cerebral activity and convert them into commands to operate external devices (Rainey et al., 2020). Neuroimaging techniques, such as EEGs, are used to record data from BCIs, and their affordability, convenience and safety make them the most widely used method (Yadav & Maini, 2025).  fMRI uses techniques similar to those of MRI but primarily measures blood flow in the brain to monitor cerebral activity (Hughes et al., 2020). Currently, fMRI is used to decode visual or auditory inputs, with future potential to recreate dreams or images in the mind (Yadav & Maini, 2025). Although these tools are still developing, they have already shown that brain activity can reveal more information than previously thought possible. Improvements in accuracy would lead to better interpretations of speech, images, emotions and other mental states, enabling researchers to gain the best possible understanding of how these technologies might be used in other fields.

However, as these technologies become more advanced, they also raise important questions about privacy, fairness and human autonomy. These issues are especially prevalent across education, law and employment. In education, mind-reading technologies might one day be used to measure attention to learning patterns, and their assistance could be crucial for those struggling with learning difficulties, helping them with personalised learning schemes. However, they could also threaten student privacy and expose already vulnerable students to greater surveillance, pressure and the misuse of personal information, including school-kept medical records. In law, these technologies could be used in criminal investigations or courtroom settings, though their accuracy and fairness would need careful evaluation to avoid errors in their application. Furthermore, in the workplace, focus or productivity could be assessed, leading to unfair monitoring or discrimination of individuals. Additionally, significant funding must be allocated to further develop these mind-reading devices, ensuring they are designed with the best intentions. This paper explores how mind-reading technologies might be used responsibly in education, law and employment, balancing innovation with ethics, privacy and human rights.

I. Neurotechnology and Law

ADVANCEMENTS

Currently, the developments of neurotechnology lie mostly in the realm of medicine, with implanted electrodes being used to treat Parkinson’s disease and obsessive-compulsive disorder (OCD) for over half a century. Following the introduction of the polygraph test, no further expansion of neurotechnology was allowed in the legal world, as polygraph evidence was deemed inadmissible in court due to its lack of reliability. However, polygraphs could be used as an auxiliary technical tool in criminal processing to eliminate innocent suspects, allowing cases to progress more rapidly (Opancina, Sebek & Janjic, 2024). Subsequently, the introduction of BCI and fMRI imaging techniques over the last 20 years, alongside scientific research, could be utilised in the future to determine whether a person on trial is withholding information and, in some circumstances, to infer intent by providing jurors and judges with correlations between different brain states, mental activity and a person’s behaviour (Opancina, Sebek, & Janjic, 2024). A level of further insight into the person’s thoughts could be demonstrated through these links, which show the active areas of the brain corresponding to different stimuli, thereby proving their credibility and checking whether they are proffering misleading information on the stand. Furthermore, in the future, with the continuous training of AI programs, the BCI and fMRI images could be used in memory recall, to piece together the scene from the person’s recollection, or in scenarios where memory loss has occurred, similar to the methods used for patients with Alzheimer’s disease (Danmaisoro et al., 2024).

This ever-expanding technology can be utilised throughout law, with potential for use in prisons to scan for psychopathic tendencies in inmates, such as a lack of empathy, guilt or remorse for their actions or a strong propensity for impulsive decisions. The core dysfunctional areas in psychopathy, including lack of fear, point to a problem within the amygdala, part of the limbic system, where emotions are processed (Hirstein & Sifferd, 2014). It was found that inmates with lower activity in their anterior cingulate had double the chance of being rearrested (Kiehl & Hoffman, 2014), meaning that when released, they are at a higher risk of recidivism. However, the algorithms do not always prove accurate, and they have been known to be excluded from cases due to four primary concerns: reliability issues, the unfair prejudice or bias invoked, general acceptance of the results without confirmation and the credibility of the neurotechnology as a whole (Langleben & Moriarty, 2013). The usefulness of the technology is also considered: a secondary testimony that corroborates the first is often seen as having little probative value to the jury (Faigman et al., 2023).

EVALUATION

Legal, ethical and moral dilemmas are raised alongside the increased availability and development of neurotechnology, particularly regarding neurorights and the legal consent for mind-reading within vulnerable populations. Neurorights are a specific set of human rights aimed at safeguarding the brain and neural activity, among which the right to neuroprivacy is of utmost importance (Kataoka et al., 2024). Neuroprivacy takes into account the rights that users have regarding the extraction, imaging and analysis of their brain data. This calls into question the intended commercialisation of BCIs, with many worried that it will be hard to prevent the coercion of those at risk and the misuse of mind-reading technology in the future. Respecting and maintaining human dignity is a key factor in the debate over whether these devices should be available to consumers in the future. With the advancement of AI, the risk of sensitive brain data exposure greatly increases. Non-invasive EEGs have recently been used alongside large language models (LLMs) in a study from the University of Texas, where the AI systems were able to decode what the participants were thinking with 82% accuracy (Kablo & Arias-Cabarcos, 2023). The further development of these AI technologies suggests they will become more accurate over time, raising concerns for misuse when accessing private brain data without first obtaining legal consent.

This is especially prevalent within vulnerable populations, such as children or those who have difficulty speaking, particularly patients with motor speech disorder, which occurs in 90% of Parkinson’s patients (Sato et al., 2024). There is hope that non-invasive EEGs will be able to decode patient thoughts into words in the future; however, with these advancements comes the very real possibility that the technology will not be able to differentiate between the user’s private thoughts and what they would like to say out loud. The idea of mental integrity being diminished or removed in this way is worrying to many and challenges the notion of freedom of thought, prompting questions about whether the technologies could directly manipulate our thoughts and feelings (Buller, 2025).

Similarly, ideas around who owns our brain data and ensuring responsible use of it by the companies that own the neurotechnologies are a main topic of discussion, with many suggesting that the patients themselves should be entitled to own their own data, with similar laws to current medical data (Xiao et al., 2025). There are also common fears about the use of neurotechnology in law and about the admission of incorrect evidence into court, leading to a user being wrongly convicted of a crime due to a mistake with the technology or its outputs. Therefore, it is critical that, before neurotechnology develops further and becomes commercialised, there is a structure in place to protect the users’ neuroprivacy and to maintain their human dignity and agency, while ensuring that the output provided by the technology is as accurate as it can be to avoid mistakes made by the AI and/or future advancements.

II. Neurotechnology and Education

ADVANCEMENTS

Currently, mind-reading technologies, although still emerging, are being applied in many educational scenarios, such as EEG headsets that monitor student attention levels, engagement and fatigue during class. Current uses include monitoring students’ mental workload during class, assisting people with severe physical disabilities using BCIs and providing neural feedback to students on their disabilities and how to self-regulate (Kosmyna & Maes, 2019; Apicella et al., 2022). Current applications of this technology for neurodivergent students include EEG feedback for patients with attention deficit hyperactivity disorder (ADHD), which can help them recognise when their attention levels drop and assist teachers in adjusting lesson plans accordingly (Franceschelli & Popa-Fabbre, 2025). In 2019, a Chinese experiment in an elementary school used headbands similar to EEGs in the classroom; the headbands lit up with different colours depending on the student’s level of focus, and teachers could adapt their lesson plans. This sparked interest in the many ways that neurotechnology could be used in a classroom environment (Privitera & Du, 2022). Newer research even suggests that neurotechnology can treat disorders of mood, sensation, learning, memory and cognition, thereby deeply enhancing a student’s ability to learn (CFG, 2025). Researchers have shown that neurotechnology can help teachers better understand neurodivergent disabilities and adapt more effectively; however, they caution that incorporating laboratory findings into classrooms must be done carefully (Alibigloo & Alipoor, 2023). Many researchers argue that understanding brain structure, how memory works and attention spans will help teachers improve teaching methods to accommodate students’ differences (Alibigloo & Alipoor, 2023).

EVALUATION

Many argue that research on the incorporation of neurotechnology into education focuses too much on the positives and not enough on its potential to reveal sensitive information about the user’s emotions, stress and cognitive capabilities. Additionally, as the research  largely focuses on the short-term effects, we do not know the potential long-term risks of using this technology, including dependence and adverse psychological effects. Other concerns include the effects of technology on children in particular, especially since childhood is a time of major hormonal and structural brain changes (Alibigloo & Alipoor, 2023). 

There is also the risk of schools evaluating students based on their brainwave data. This would be an issue, especially since intelligence comes in many different forms, and just because a student excels in one area does not guarantee success in others (Martschenko, 2017). A human rights commission in Australia even raised the concerning issue of bidirectional BCIs altering thought processes. If an external mechanism alters your thought processes, could the way you think even be considered yours (Humanrights.gov.au, 2024)? It would be irresponsible to use brain scans to evaluate a student since intelligence is not the only factor in success; education and hard work are also crucial. In education, traditional testing for intelligence has sparked significant controversy, as students are often placed in gifted or special education programmes based on these tests. This is not a new discussion: the inventor of the IQ test, Alfred Binet, also recognised that intelligence tests do not measure everything, since they cannot evaluate emotional intelligence or creativity, which are also crucial to success (Martschenko, 2017).

Questions about who owns and can access the data are also controversial. Although user data is considered private biological information, teachers would need access in order to enhance the learning experience, and not all students may agree to this. Other irresponsible uses of the technology include sharing private information with others, including specific diagnoses of neurodiversity, mood and feelings.  Schools and educators have a responsibility to protect students’ sensitive data from anyone other than the student and educator. It would be hard for a student to hide their disability and/or mood, if it were to be indicated on his headband as the Chinese experiment in 2019 showed.

Unless these ethical standards are met, incorporating neurotechnologies into education could come with devastating costs, but once these standards are fulfilled, neurotechnology could enhance the current learning environment.

III. Neurotechnology and Employment

ADVANCEMENTS

BCIs and other forms of neurotechnology are beginning to move beyond medical use and into the workplace, where they may reshape how work is monitored, measured and performed. Currently, BCIs are mainly used to help people with severe communication or motor impairments control external devices, communicate or regain a degree of independence (Awuah et al., 2024; Rainey et al., 2020). However, the workplace is already being affected by the wider rise of neurotechnology, especially in industries where attention, safety, productivity and cognitive performance are important. Sectors such as healthcare, transport, manufacturing, defence and office-based corporate work are most likely to be influenced first as these environments are where employers may see value in tracking concentration, stress, alertness or fatigue (IEEE Brain, n.d.; Withers, 2023). In high-risk settings, such as transport or industrial work, employers may argue that neurotechnology could improve safety by identifying when workers are distracted or overwhelmed before accidents happen (Withers, 2023).

In the future, these technologies may spread further into recruitment, training and performance management. The Information Commissioner’s Office has suggested that workplaces may increasingly use non-invasive neurotechnology to measure and process brain-based information, including attention and engagement, especially in health and safety schemes or wellness programmes (ICO, 2023). This means BCIs could move from being assistive devices to becoming tools for monitoring or enhancing employee behaviour. Some industries may also adopt these technologies for more specialised uses, such as elite sports, military settings, emergency response and high-performance research environments, where quicker reactions and stronger focus are seen as valuable (IEEE Brain, n.d.). As devices become more portable and less invasive, the idea of a “workplace” may also change, with neurotechnology used in remote, mobile or hybrid environments rather than just a single physical office (IEEE Brain, n.d.). If the technology continues to improve, employers may use it not just to measure what workers do, but also to infer how they feel while doing it, creating the possibility of more personalised support but also increasing the risk of surveillance.

EVALUATION

Neurotechnology could substantially improve safety, productivity and support for workers with disabilities. In physically demanding or dangerous jobs, brain-based monitoring could help employers detect fatigue or inattention before a serious mistake occurs (ICO, 2023). It could also support employees with disabilities by offering new ways to communicate, control equipment and work more independently, thereby improving access and inclusion (Awuah et al., 2024). In theory, this could reduce barriers in hiring and employment by creating more adaptable workplaces. Some people also believe that if the technology is used properly, it could help workers better understand their stress levels, concentration patterns and performance habits (IEEE Brain, n.d.). However, the risks are serious. One of the biggest concerns is unfair judgement because employers might over-rely on neurodata to make decisions about hiring, promotion, discipline or dismissal. The New Law Journal warns that neurotechnology could create problems in relation to unfair dismissal and discrimination, especially if algorithms misinterpret brain data or if managers treat ambiguous signals as proof of poor performance (Lambert & Neaman, 2025). This could be especially harmful for people with health conditions, disabilities or neurodivergent traits because their brain activity may not fit a “normal” pattern even when they are performing their job well (Withers, 2023; Lambert & Neaman, 2025). This would create stereotypes among peers by making assumptions about who is alert, productive or suitable for certain roles, even when those assumptions are inaccurate. In other words, neurotechnology could foster a new form of bias in which workers are judged not only by what they do but also by how their brains appear to work.

Privacy is another major issue. Brain data is far more sensitive than ordinary workplace data because it can reveal attention, stress, fatigue or possibly even mental states, making it difficult to separate work from personal life (IEEE, n.d.; The Conversation, 2024).  If employers had access to this information, the line between support and surveillance could easily disappear. An important question we need to ask is: at what point does the third party gain too much control? If employers can continuously monitor brain activity, workers may feel pressured to stay “mentally available” at all times, reducing autonomy and increasing stress. Some commentators argue that strong regulation is needed before these tools become widespread, including clear limits on consent, data storage, transparency and acceptable use (Withers, 2023; IEEE, n.d.). A “kill switch” or emergency off mechanism may also be necessary for workers to disable monitoring when it is no longer appropriate. While no single regulator currently serves as an exact equivalent of the FDA for neurotechnology across all employment contexts, many experts argue that sector-specific laws, data protection frameworks and workplace rights must be developed quickly if these technologies are to be used ethically (Lambert & Neaman, 2025; The Conversation, 2024).

Overall, workplace neurotechnology could bring real benefits, especially for safety, accessibility and communication, but if it is introduced without strict rules, it could also increase surveillance, discrimination and unequal power between employers and workers. The challenge is not only whether these technologies can be used in employment, but whether they should be and under what limits.

Discussion

When examining the rapid development of neurotechnology over the past decade, clear similarities emerge across education, law and employment. In all three areas, the technology is designed to interpret brain activity and turn it into useful information, whether that means tracking attention in classrooms, assessing stress or focus in the workplace or potentially identifying mental states in legal settings. Although the contexts differ, the core issue remains the same: neurotechnology offers new opportunities for support and improvement but also raises privacy concerns, including fairness and control over users’ personal information.

One of the strongest common themes is that neurotechnology is most widely accepted when it is used for medical or assistive purposes. At present, BCIs and related systems are most successful in helping people with disabilities communicate, regain movement or improve daily functioning. This shows that the technology has real value when it is used to support independence and inclusion. However, as its use expands into non-medical settings, the ethical concerns become more complex: in law, it could assist investigations, but it also risks unreliable judgements if brain data is overinterpreted; in education, it could help students with learning difficulties, but it could also expose vulnerable students to surveillance; in employment, it could improve safety and support workers, but it could also lead to unfair monitoring and discrimination.

Another important similarity across all three sectors is the question of power. Neurotechnology places sensitive information in the hands of institutions such as schools, employers and legal authorities, potentially allowing individuals to lose control over how their brain data is used, thereby challenging mental integrity. This makes consent especially important because people may agree to their data being monitored and used without fully understanding the consequences. It also raises the question of whether these technologies will truly be voluntary in the future, especially if students, workers or defendants feel pressured to accept them to succeed, keep a job or avoid suspicion.

Overall, across all three sectors, shared opportunities and similar dangers are evident, demonstrating the indispensability of neurotechnology for the future, though not without concerns and problems. Each area could benefit from greater efficiency, better support and more personalised decision-making to improve the user experience. At the same time, each raises the possibility of misuse, particularly if employers, teachers or legal authorities gain excessive access to sensitive brain data. This suggests that the future of neurotechnology will depend not only on how advanced it becomes, but also on how responsibly it is governed. Without clear safeguards, the line between assistance and surveillance could become increasingly blurred, provoking harsher regulations to be put in place to protect the mental integrity and brain data of the users.

Conclusion

In conclusion, the past decade of neurotechnology development shows that the same tools can offer both significant benefits and serious risks across education, law and employment. These leaps in neurotechnology could potentially improve justice, education and employment systems. Its ability to essentially “read minds” causes many experts to believe that protocols for the responsible use of the technology should be in place to protect the rights and privacy of those who will use it in the future. The central finding is that neurotechnology is most widely accepted for medical or assistive purposes, but ethical concerns become more complex when it moves into non-medical settings. Schools, employers and legal authorities may gain access to private information, raising risks of surveillance, discrimination and loss of autonomy. Clear protocols for responsible use must be established before these tools become widespread. These should include strong consent requirements, transparency about data collection, strict data protection rules and accountability mechanisms. A “kill switch” may also be necessary to allow individuals to disable monitoring when appropriate. Ultimately, any neurotechnological advancements in the future will depend on how conscientiously it is regulated by governments and corporations. The goal must be to protect human rights while allowing society to benefit. Without proper safeguards, the line between assistance and surveillance could blur, placing vulnerable people at greater risk. Both independence and fairness must guide development, not control or exploitation.

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