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Description and impact of neuroscience advances on the development of
artificial intelligence
..........................................
Descripción e incidencia de los avances de la neurociencia en el desarrollo de la
inteligencia artificial
Ferdy Carina Arguello Muñoz
Didier Eduardo Muñoz Vanegas
Mónica Isabel Herazo Chamorro
María Isabel Loaiza Hernández
Edita del Socorro Álvarez Serpa
ABSTRACT
The development of the research allows the
descriptive writing of this article, this writing is
the result of a research conducted to twenty-
five respondents with teaching training in the
field of education at undergraduate and
graduate level in Colombia and Spain, all the
actors involved participated voluntarily, where
they gave express and clear authorization for
the treatment and use of the answers in the
forms, The purpose of this research is to
describe in an exhaustive way the incidence of
the advances in neuroscience in the
development of artificial intelligence, this
research has a quantitative approach, which is
oriented to describe the incidence of
Neuroeducation in front of the reality of AI for
the education of the XXI century, in which
determines own characteristics and own steps
of the research, where Hernandez et al, (2014)
states that data collection occurs in natural and
participatory scenarios, using the survey as the
Received: October 08, 2023
Approved: December 04, 2023
...........................................
Tutor Virtual y director de tesis de Maestría
UMECIT, Panamá
https://orcid.org/0000-0001-5102-5986
Estudiante de Psicología, Almería, España
https://orcid.org/0009-0006-6114-5088
Docente de pregrado CECAR, Sincelejo Sucre
https://orcid.org/0000-0003-4193-832
Docente de la Fundación Universitaria María Cano,
Medellín, Antioquia.
https://orcid.org/0000-0002-4480-0507
Docente de la Fundación Universitaria María Cano,
Medellín, Antioquia.
https://orcid.org/0000-0003-0743-0970
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main instrument for data collection, finally,
and as a result it is defined that neuroscience
makes a significant contribution to the
improvement of AI digital tools in education,
since it allows understanding the learning
processes, designing friendly and appropriate
interfaces according to the content with human
cognition, are arguments that respondents
consider important, with a social, mental and
positive representation in various aspects,
from the condition of preparation, instruction
and even safety and ethics in the use of AI,
Corvalán, (2018).
Keywords: Neuroscience, Artificial
Intelligence, Teachers, Disruption, Resilience.
RESUMEN
El desarrollo de la investigación permite la
redacción descriptiva del presente artículo,
este escrito es resultado de una investigación
realizada a veinticinco encuestados con
formación docente en ámbito de educación a
nivel de pregrado y posgrados en Colomba y
España, todos los actores involucrados
participaron de manera voluntaria, donde
otorgaron la autorización expresa y clara el
tratamiento y uso de las respuestas en los
forms, estas indagación tiene como objeto de
estudio describir de manera exhaustiva la
incidencia de los avances en neurociencia en el
desarrollo de la inteligencia artificial, esta
investigación tiene un enfoque cuantitativo, la
cual esta orientada a describir la incidencia de
la Neuroeducación frente a la realidad de la IA
para la educación del siglo XXI, en la cual
determina características propias y pasos
propios de la investigación, en donde
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Hernández et al, (2014) afirma que la
recolección de datos ocurre en escenarios
naturales y participativos, utilizando la
encuesta como principal instrumento para la
recolección de la información, finalmente, y
como resultado se define que la neurociencia
hace una contribución significativa a la mejora
de las herramientas digitales de IA en la
educación, ya que permite comprender los
procesos de aprendizaje, diseñando interfaces
amigables y apropiadas de acuerdo al
contenido con la cognición humana, son
argumentos que los encuestados consideran
importantes, con una representación social,
mental y positiva en diversos aspectos, desde la
condición de preparación, instrucción e
incluso la seguridad y la ética en el uso de IA,
Corvalán, (2018).
Palabras Clave: Neurociencia, Inteligencia
Artificial, Maestros, Disrupción, Resiliencia.
Introduction
The correlation between neuroscience and artificial intelligence has made it possible
to generate a ground for exploring the complexities of the human mind and, in turn,
to enhance the capabilities of AI. In this paper, it is immersed in a description and
incidence of those advances that neuroscience has had in the development of artificial
intelligence, and that symbiotic relationship between these two disciplines that are
disparate but that reveal a horizon that promise a reflection from research and
neuroscientific discovery that allow to nurture the foundations from theory to practice
of artificial intelligence and neuroscience in construction of neurotechnology.
In this introduction, a detailed and clear contextual framework is leveled today, which
allows to lay the foundations for this deep understanding of the intersection between
what is neuroscience and artificial intelligence addressing the spaces of results in front
of neurotechnology as a tool to accompany the human being. Today we will address
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key concepts, which provide a vision of that historical evolution of these two
disciplines and that convergence in times of the XXI century, in this way, today we will
quote some authors within the entire article that highlights and has contributed
significantly to the dialogue on the integration of neuroscience and artificial
intelligence in educational, economic, social, cultural and highly intercultural fields
from diversity approaches.
The fundamental intent of this research is to explore how advances in neuroscience
have influenced and continue to influence the significant development of artificial
intelligence. By understanding these bases from biological human cognition,
researchers design efficient algorithms and models that are inspired by the complexity
of the brain of the real human subject, reflective and inspiring Meaningful spaces in
an increasingly changing world. In this sense, we detail those advances that impact
neuroscience and transform the algorithms that govern the conceptual core of this
research articulated to the 25 respondents who freely gave answers.
As we dive into the following pages, it will be possible to see the threads that connect
brain activity with AI algorithms in the face of deep learning, seeing achievements and
challenges that arise from this re significant convergence from the human being's own
work to focus selective understandings of the brain in the face of the learning process
in various scenarios. This not only promises to revolutionize, advance, reflect and
innovate those mysteries of the human mind that accompany the emergence of these
new advances in the disruption of information and communication technology.
Theoretical Context
Neuroscience, for Barrios et al, (2020) refers to lines applied to education and the
teaching-learning process, neurostructural bases in the study of the brain in action,
which actively participate in the processes that articulate cognition and emotion,
revealing a selective communication in the brain statement in front of the learning
process. Thus, Artificial Intelligence for Flores-Vivar, et al, (2023) is structured from
that disruption in which every day is immersed in the educational field, favoring the
influx of material for teachers and students, allowing an interpretation of information
and more sophisticated decision making. According to the UNESCO document (2021),
it recommends that AI are technologies that allow information processing by
integrating a high range of algorithms that learn according to the skills anchored to
result in various learning activities and the realization of cognitive functions in
disruptive ICT environments. The category of teachers for Arguello, (2020) "is called
the professional subject in education, which externalizes skills (innate aptitude), in the
production, realization and construction of specific activities from the attention and
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education for all from the approach of plurality - "diversitas" (p. 59). Teachers should
generate innovative tools in education, strengthen disruptive and change processes
according to the diverse learning rhythms of their disciples, as cited in Arguello et al,
(2020). To conclude, AA Resilience, (2013). In the Resilience Manual, it allows to
discover the ability to overcome critical moments and experience unexpected
situations, adversity and assertiveness to integrate fronts of diverse situations to the
learning of life, a change, a transformation from the disruption of new innovations,
where it configures the articulation of the resignification of knowledge, cognition and
reflection in changing environments.
Materials and methods
For the following research the quantitative approach was used, using methods and
techniques according to methods of measurement of the units of analysis of the
research project such as the survey and anonymous reflection of each respondent, in
this way, a rigorous sequence is organized for the testing of the hypothesis, therefore,
the type of descriptive research is chosen as shown in the following image:
Its purpose is to review the characteristics of a given group, 25 master voices at
national and international level, on the incidence that neuroeducation has against AI
for the education of the XXI century, to finally, undergo the analysis of the results,
according to Hernandez et al, 2014.
which allowed to meet the objective of the proposal, To comprehensively describe the
incidence of advances in neuroscience in the development of artificial intelligence,
exploring the convergence of these disciplines and assessing whether the resulting
applications are perceived as disruptive that radically transform the field or as resilient
solutions that integrate harmoniously into society and existing ICT, De La Cruz, et al,
(2023).
Results
The results of the research are presented below according to the study objectives,
followed by the analysis of each one.
In the first phase of findings, a 10-question Likert-type survey on neuroscience and
artificial intelligence was analyzed. Participants indicated their degree of agreement
with each statement on a scale of 1 to 5, where 1 means "Strongly disagree" and 5 means
"Strongly agree", where responses are 100% anonymous.
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The first section addressed demographic data such as gender, age and professional
level of each participant surveyed.
Table 1. Demographic data
Naturaleza
Variable
Frecuencia
Porcentaje
Genero
Masculino
15
60
Femenino
10
40
Edad
25 – 34
Años
8
32
35 – 44
Años
12
48
45 – 54
Años
4
16
55 o más
años
4
Nivel de educación
Pregrado
10
40
Posgrados
15
60
Source: Own elaboration
Sixty percent of the participants are male, while 40% are female. This indicates a slight
male predominance in the sample. The majority of the participants are in the 35 to 44
age range, with 48%. The second largest group is in the 25-34 age range, with 32%.
Sixteen percent belong to the 45 to 54 age range. There are 4% of participants aged 55
years or older. Sixty percent of the participants have postgraduate degrees, while 40%
have undergraduate degrees. This suggests that most of the participants are highly
educated.
Overall, the sample assumes a balanced gender distribution, with a majority in the 35-
44 age group and a hegemony of collaborators with postgraduate degrees compared to
those with undergraduate degrees. This analysis provides an overview of the
demographic composition of the research.
Table 2 Neuroscience and Artificial Intelligence
Item
Totalmente en
desacuerdo
En desacuerdo
Neutro
De acuerdo
Totalment
e de
acuerdo
F
%
F
%
F
%
F
%
F
%
The
incorporation of
neuroscientific
5
20
11
44
9
36
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principles in the
development of
artificial
intelligence
improves its
capacity to
understand and
adapt to the
environment.
The application
of techniques
inspired by the
functioning of
the human brain
contributes
significantly to
the advancement
of artificial
intelligence.
1
4
1
4
2
8
11
44
10
40
Neuroscience
can be key to
improving the
ability of
machines to
learn in a similar
way to humans.
7
28
1
4
12
48
5
20
Integrating
knowledge about
the structure and
functioning of
the brain into
artificial
intelligence
increases its
efficiency and
performance.
1
4
2
8
16
64
6
24
Understanding
human cognitive
processes
through
neuroscience is
essential for
1
4
4
16
13
52
7
28
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developing
ethical and safe
artificial
intelligence
systems.
The influence of
neuroscience on
artificial
intelligence
enables better
interpretation of
information and
more
sophisticated
decision making.
1
4
1
4
2
8
11
44
10
40
Collaboration
between
neuroscience
experts and
artificial
intelligence
developers is
crucial to
maximize the
potential of both
disciplines.
1
4
1
4
1
4
12
48
10
40
The
implementation
of
neuroscientific
concepts in
artificial
intelligence can
improve the
emulation of
human
intelligence in
specific tasks.
1
4
1
4
3
12
15
60
5
20
Neuroscience
can offer
solutions to
address current
1
4
17
68
7
28
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challenges in
artificial
intelligence,
such as model
interpretation
and applicability.
Neuroscience
research will
continue to be
fundamental to
the future
development of
artificial
intelligence.
1
4
8
32
16
64
Source: Own elaboration
On the first item, 80% of the participants agree (44% agree and 36% strongly agree).
This suggests strong support for the idea that the application of neuroscientific
principles improves the capability of artificial intelligence. Next, 48% of the
participants agree (44% agree and 4% strongly agree). There is a positive perception,
but to a lesser extent than in the first item. Thus, 76% of the participants agree (48%
agree and 28% strongly agree). The majority support the importance of neuroscience
in improving the learning capacity of machines. Thus, 88% of the participants agree
(64% agree and 24% strongly agree). There is strong approval for the effectiveness of
integrating neuroscientific knowledge into artificial intelligence. Similarly, 80% of the
participants agree (52% agree and 28% strongly agree). There is significant support
for the idea that neuroscience is essential for ethics and safety in artificial intelligence.
The influence of neuroscience yields 84% of participants agree (44% agree and 40%
strongly agree). The majority consider that neuroscience improves the ability to
interpret and make decisions in artificial intelligence. Collaboration between shows
that 88% of participants agree (48% agree and 40% strongly agree). There is strong
support for collaboration between neuroscience experts and artificial intelligence
developers. The implementation of neuroscientific concepts in artificial intelligence
results in 80% of the participants agreeing (60% agree and 20% strongly agree). Most
of them consider that the implementation of neuroscientific concepts improves the
emulation of human intelligence. Neuroscience can offer solutions so 96% of the
participants agree (68% agree and 28% strongly agree). There is strong support for the
idea that neuroscience can address current challenges in artificial intelligence. This is
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followed by 96% of participants agreeing (32% agree and 64% strongly agree). There
is significant consensus on the continued importance of neuroscience research for the
future development of artificial intelligence in the face of ICT disruption in the 21st
century, a globalized framework of skills that align with individual subject interests,
Sandoval, (2018).
Finally, the findings indicate strong support for incorporating neuroscientific
principles into artificial intelligence, with positive perceptions in a variety of areas
ranging from learnability to ethics and safety. Intelligence developers are also viewed
critically, Castro, M. F. Z. et al, (2019).
In a second moment, a second survey titled "Neuroscience and AI Digital Tools For
21st Century Education" is analyzed in which the following data is analyzed:
Table 3 Neuroscience and AI Digital Tools For 21st Century Education.
Nature
Variable
Frecuencia
Porcentaje
familiarity with
neuroscience and
artificial intelligence in
education
• Muy
familiarizado
• Familiarizado
• Neutral
• Poco
familiarizado
• No familiarizado
en absoluto
4
12
6
3
0
16
48
24
12
0
artificial intelligence
digital tools improve
teaching in the 21st
century.
• Personalización
del aprendizaje
• Mejora de la
retroalimentación
• Acceso a recursos
educativos en
línea
• Adaptación a
estilos de
aprendizaje
individuales
• Otras
6
2
8
9
0
24
8
32
36
0
Neuroscience can play
an important role in
improving pedagogical
strategies.
• Si
• No
• No estoy seguro/a
24
0
1
96
0
4
neuroscience
contributes to the
creation of more
• Comprendiendo
mejor los
procesos de
aprendizaje
8
2
9
6
0
32
8
36
24
0
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effective digital AI tools
in education.
• Diseñando
interfaces más
amigables.
• Adaptando el
contenido según
la cognición
humana
• Personalizando la
experiencia de
aprendizaje
• Otras
• Privacidad de los
datos
• Sesgo algorítmico
• Dependencia
tecnológica
• Falta de
accesibilidad
• Otras
7
3
8
7
0
28
12
32
28
0
concerns about the use
of neuroscience-based
digital AI tools.
• Si
• No
• Otras
19
3
3
76
12
12
The implementation of
these technologies could
benefit all students
equally.
• Si
• No
• No estoy seguro/a
14
5
6
56
20
24
Source: Own elaboration: Own elaboration
Open spaces for reflection by respondents are highlighted below: anonymous 3 "very
appropriate for today's society, emphasizing that everything must be in line with the
Psychosocial situation of the participants in the educational process", anonymous 4
"The integration of neuroscience and artificial intelligence presents a challenge for
teachers in the 21st century. Understanding how students' brains work at the neural
level can inform more effective pedagogical strategies, while artificial intelligence
offers innovative tools for personalizing instruction. However, it is essential that
educators approach these advances with caution, making sure to maintain an ethical
and humane balance in the use of technology, and continue to foster key social and
emotional skills in the educational process." anonymous 8 "Thanks to neuroscience
and AI tools, it allows neuroscientists to give the tools to make further discoveries and
interpret them." anonymous 10 "Artificial intelligence can contribute tools that when
thought about from pedagogy help create new learning with appropriate learning
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gains." anonymous 11 "Neurotechnology is widely linked to this interdisciplinary field
that combines neuroscience with ICT to develop tools that allow us to advance in
generating critical thinking and articulation of teaching the future generation to think
through technology" anonymous 12 "Neuroscience allows AI to provide relevant
aspects regarding the creation of new algorithms for an education personality in the
21st century" anonymous 14 "Neuroscience and artificial intelligence (AI) are
interrelated in several ways, and the impact of neuroscience in AI is significant",
anonymous 21 "I consider that the use of this tool helps us so that the learning process
can be understood much more easily", anonymous 22 "I think it is a very interesting
topic that as it advances in the future will be beneficial for the study" anonymous 24
"We cannot ignore that technologies are taking giant steps in current pedagogy, so they
should be included in teaching practices", anonymous 25 "Active processes, use of
methodology to strengthen critical thinking".
In conclusion, and as a result of the survey table 3, it is defined that neuroscience
makes a significant contribution to the improvement of AI digital tools in education,
since it allows understanding the learning processes, designing friendly and
appropriate interfaces according to the content with human cognition, are arguments
that respondents consider important, with a social, mental and real representation in
various aspects, from the condition of preparation, instruction and even safety and
ethics in the use of AI that must continue to advance to support quality processes.
As far as it is concerned, neurotechnology extends to the interdisciplinary field that
allows the combination of those principles of neuroscience guide applied to science
and research and the disruption of technology to study the activities of the human
subject in the reality of the brain with various interface, allowing a bidirectional
communication between these two and a deep stimulation that influences or
assimilates neural activities from the algorithms today that are implanted in these
artificial intelligences, and that will never overcome the human race, resignifications
own use and help that can provide the human. In this order of ideas, the technology
will always be neutral, being seen for better or for worse, the humanization, principle
and dimension of ethics in front of neurotechnologies that implies a reflection of
thinking about the ethical, social and cultural that impact society and the revolution
of this in the economy and in our own lives in front of diverse intercultural networks.
For Yuste, (2019). "New neurotechnologies are playing a crucial role in neuroscience
and will impact medicine, economy and society of the future" (p. 7). Thus, these
interdisciplinary fields merge and study that understanding from the self-
development of advanced devices and techniques for deep brain stimulation and the
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combination that we want to reach in the achievement of new algorithms in front of
AI, as a reward of technical help for human beings.
Conclusions
This research highlights relevant aspects of the importance of understanding the
structure and functioning of the human brain, so that artificial intelligence can design
and be inspired by the beginning of the search for similarities, configurations and
structures that have led to inspired and structuring models from the neuronal. Within
this framework, the trend of neuroscience and artificial intelligence today allows an
impulse to new active developments within the neurotechnological spaces, such as
ICT allowing to make use of an information from the study of the brain itself to go
improving the capabilities of AI, hence, to open new fields and possibilities in front
of brain vs computer interface. Consequently, the ethical and privacy challenges
within the incorporation of neuroscientific knowledge in AI should raise those
challenges in the use of data for individual autonomy of an information and a need to
regulate from ethics the development of these applications from the disruption of
information technology and communication. Indeed, the research highlights an
interdisciplinary boom today between various neuroscientists, researchers and AI
itself, allowing to bring those discoveries between innovation and the benefit of that
understanding that one has of the mind of the subject as the own development of new
technologies in front of the algorithms that have been opening paths in relation to the
interconnection of the two scientific fields that are named here.
Otherwise, neuroscience and AI are related, since from the diversity of advances in
Neuroscience positively influence the development of AI algorithms, in such a way,
that it has an impact on the inspiration of a structure and functioning of the brain
looking for the anatomy and function of a human brain, Clark, et al, (2019), in this
way, allows us to glimpse that artificial intelligence will never surpass human neural
processes, only artificial neural networks will remain according to their algorithms in
terms of imitation of structures and functionings of the human species.
Thus, the neural networks of the subject simplified model that emulates the
information process of the human brain, so that the relationship between artificial
intelligence and neuroscience or v / s neuroscience and artificial intelligence focuses
points such as deep learning from neural networks in mixed approach, Martinez,
(2021), in which are used according to multiple research plasticity and the influence
of human beings in the algorithms to design and train machines that serves from its
neuro technology in teaching processes, cognition and interface of various tools of
exchange between the human and information and communication technology in a
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disruption between the human mind and artificial intelligence, understanding that AI
will never surpass the understanding of cognition and rational information
processing of the human species facing the creation of new machines in operation and
support to the species, Martinez, & Mendez, (2013).
In conclusion, Gomez, et al, (2022), advances in neuroscience have had a great
significant impact on the development of artificial intelligence providing an
inspiration of diverse models and key points of knowledge to favor the efficiency and
effectiveness of human-created technological disruption algorithm systems, thus, the
intersection and inclusion between neuroscience and artificial intelligence will be an
active research area for the current century, thinking the transversal points of an
education in diverse intercultural, multicultural and highly diverse scenarios that
emulate the ability to inspire realities in the creation of super advanced and ethical
algorithms for insertion in educational, commercial areas among others.... It provides
a basis between theory, conceptual and ethical principles addressing privacy, equity
and transparency of processes, Mira, (1999).
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