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Ethical Aspects of Information Literacy in Artificial Intelligence

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The purpose is to analyse information literacy to provide ethical insight into artificial intelligence. The methodology was based on a systematic literature review of SCOPUS, Web of Science, Library and Information Science Abstracts, and Science Direct. The results demonstrated that there are only a few studies about the topic, so there is a research opportunity about this type of literacy and its ethical aspects in the context of artificial intelligence. As a conclusion, information literacy is crucial to the development of critical thinking in technology use. Information literacy should be applied in artificial intelligence courses to discuss ethical aspects of technology.
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Chapter 10
179
DOI: 10.4018/978-1-7998-4285-9.ch010
ABSTRACT
The purpose is to analyse information literacy to provide ethical insight into artificial
intelligence. The methodology was based on a systematic literature review of SCOPUS,
Web of Science, Library and Information Science Abstracts, and Science Direct.
The results demonstrated that there are only a few studies about the topic, so there
is a research opportunity about this type of literacy and its ethical aspects in the
context of artificial intelligence. As a conclusion, information literacy is crucial to
the development of critical thinking in technology use. Information literacy should
be applied in artificial intelligence courses to discuss ethical aspects of technology.
Ethical Aspects of
Information Literacy in
Articial Intelligence
Selma Leticia Capinzaiki Ottonicar
https://orcid.org/0000-0001-6330-3904
Sao Paulo State University (UNESP), Brazil
Ilídio Lobato Ernesto Manhique
Sao Paulo State University (UNESP), Brazil
Elaine Mosconi
https://orcid.org/0000-0001-5579-9997
Université de Sherbrooke (UdeS), Canada
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Ethical Aspects of Information Literacy in Articial Intelligence
INTRODUCTION
The fourth industrial revolution or Industry 4.0 (I4.0) is based on the connection
between machines, networks and humans (Adolphs & Epple, 2017; Almada-Lobo,
2015; Schwab, 2016). One part of I4.0 is artificial intelligence (McCarthy et al.,
1956), which has improved individuals’ lives through the human-machine interaction.
Despite its potential, artificial intelligence has created some ethical concerns. This
technology has implications for cybersecurity and data privacy. Therefore, there is
a dichotomy because artificial intelligence influences society both positively and
negatively.
Artificial intelligence is a topic of research of many fields, so it can be considered
multidisciplinary. The topic of this chapter is artificial intelligence in the context of
Ethics, Information Science and Computer Science fields. Only a few researches
have studied artificial intelligence in a multidisciplinary perspective, hence this
chapter helps to fill this knowledge gap. Information Science is a useful lens, since
it values the union of different knowledge.
Information Literacy is a very well-known topic in the field of Information
Science. It is the ability to access, evaluate and use information to construct critical
thinking. Ethics is a relevant aspect of information literacy (Vitorino & Piantola,
2011) because it guides individuals’ behavior in society. An ethical approach to
information has been recognized by Information Literacy Competency Standards
for Higher Education of American College & Research Association (ACRL). This
organization considers that an information literate person understands economic,
legal and social aspects of information use. Furthermore, ACRL (2000) understands
that information literacy helps individuals to access and use information in an ethical
and legal way.
Information literacy allows people to interpret information issues in a critical
way (Belluzzo, 2014; Yafushi, 2015; Ottonicar, Valentim & Feres, 2016) and it is the
means through which people experience information (Demasson, Patritdge & Bruce,
2016). It helps to develop critical thinking (Grafstein, 2017), so it is a sociocultural
element to allow individuals to deal with complex contexts (Lloyd, 2007).
Many countries have introduced laws and public policy focused on information
literacy. However, those actions are still limited, because the obscurity of the current
social system can create illusions in peoples’ minds (Slayton, 2018). The use of
ethical aspects of information literacy (Vitorino & Piantola, 2011) is the first step
to face the dichotomy of artificial intelligence. Professionals need to understand
the consequences of artificial intelligence to society. Bostron (2016) criticizes our
society and compares humans to “children who play with a bomb”.
Based on these ideas, this book chapter has the following question: how can
information literacy contribute to an ethical development of artificial intelligence?
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Ethical Aspects of Information Literacy in Articial Intelligence
The purpose of this chapter is to analyse information literacy to provide ethical insight
into artificial intelligence. Furthermore, this study aims to discuss the contribution
of information literacy to the ethical use of artificial intelligence and to identify
authors who have researched this topic.
The chapter is structured in six sections. First, it presents the introduction, research
questions and purpose of the chapter. Second, it shows the method, systematic
literature review, and some quantitative results. Third, the chapter discusses artificial
intelligence and its ethical issues. Fourth, a section about information literacy
concepts and ethics is introduced in the literature review. Fifth, the results showed
the papers retrieved and ideas of authors. In the final section, this chapter explains
the conclusions, limitations and future research.
BACKGROUND
Artificial Intelligence and Ethical Issues
In today’s society, there are some utopic ideas about the benefits of technology. In
a perfect world, information and communication technology would be the source
of transformation to society. That optimism is shared by some authors such as Bell
(1973). He believes that technology has an important role to determine people’s lives.
According to Lyon (1992) the relationship between technology and society
cannot be hierarchical and vertical, which means that technology and individuals
should be seen as equally important. The author (1992) explains that technology and
society have an interdependent relationship because technology influences social
relationships and it is also a social product.
The development of technology leads to some ethical problems related to the
use of knowledge. Morin (2005) provides an example of these dangers: nuclear
production contributed to national socioeconomic development, but it also nearly
caused the annihilation of humanity in the mid-20th century. People need to abandon
the naive idea of good or bad science and technology. The dichotomy of technology
must be discussed from an ethical and moral perspective in order to understand how
information literacy can contribute to artificial intelligence development.
Artificial intelligence emerges from technological changes in contemporary
society. This intelligence has challenged traditional ideas of time, space and
intelligence. These ideas can also be discussed by Philosophy of Information, which
is a new field of investigation of Information Science and Computer Science (Floridi,
2004). Philosophy of Information involves the critical nature of concepts and basic
principles of information. Furthermore, it helps to develop information theory and
computer methodology applied to philosophical problems (Floridi, 2004).
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Ethical Aspects of Information Literacy in Articial Intelligence
Floridi (2004) discusses artificial intelligence in the information processing view,
and he considers that artificial intelligence studies human cognition and information
systems. Information processing, cognition and intelligence are the most relevant
problems of Philosophy of Information. One of the problems is: Are there types of
cognition? Can cognition be understood in a non-biological perspective? There is
a relational perspective between human and computer intelligence which is a more
abstract and holistic way of building symbols upon reality. This idea presupposes a
distinction between natural and artificial intelligence (Floridi, 2004).
According to that author, artificial intelligence is limited to data processing (non-
interpreted patterns of differences and deviations) while natural intelligence mainly
processes information (patterns that are well-formed out of significant data). So
artificial intelligence should be described as a data system and natural intelligence
as an information system.
Araújo (2017) discusses the consequences of artificial intelligence to produce both
information and knowledge, since algorithms have been used to create information.
This author (2017) analyses artificial intelligence in many aspects of information
production. He also studies the challenges of the knowledge production field in the
context of artificial intelligence.
In the United States a business called Automated Insights uses a software program
called Wordsmith to create journalistic texts. Some newspapers have published
these articles, naming Automated Insights as the author. These algorithms are a
topic for ethical discussion that includes the fear of robots replacing journalists
(Araújo, 2017). Philip Parker is the author of dictionaries, financial reports, didactic
books, and medical texts that are created by an algorithm. His books are on sale at
Amazon. He constructs the steps to write a technical text that imitates an academic
researcher (Araújo, 2017).
The impacts of information technology have caused some ethical issues. Because
of that, many organizations have created a set of solutions. These solutions aim to
guide professionals, such as with rules and laws that regulate the use of artificial
intelligence. The generation of texts by technologies worry academics, because
technology can influence the way people write papers in the future (Araújo, 2017,
p. 90). The development of algorithms contributes to new demands in society. First,
algorithms demand the possibility of artificial intelligence of transforming science
and second, algorithms demand individuals to become lifelong learners. Furthermore,
this context requires the development of abilities to evaluate information sources,
so people can identify the author of a text.
Information literacy is lifelong learning through the critical interpretation of
information. This literacy is also focused on the ethical use and dissemination of
information. The increase of artificial intelligence tools will cause many challenges
to scientists, especially concerning the authorship and origin of scientific papers
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Ethical Aspects of Information Literacy in Articial Intelligence
(Araújo, 2017). According to Araújo (2017, p.95): “In the future, plagiarism will
become a smaller problem. The greatest challenge will be to know if researchers
are truly the authors of the papers they submit or if they should be considered
only meta-authors of their respective studies. The question is: Who is the author
of a paper? The algorithm that created the text or the person who programmed the
algorithm? The answer to this question implies a re-evaluation of the concept of
authorship of academic papers”.
Algorithms are created using a system called deep learning that allows automatic
correction without the programmer’s intervention (Araújo, 2017). Since they correct
themselves, could they become authors of scientific papers? According to Capurro
(2007) and Hjorland (2004) knowledge depends on the interaction between cognitive
and social interaction. Technology can generate data while humans create knowledge.
In this book chapter, we emphasize that humans can produce knowledge based on
the interactions with other people and technology. Technology alone cannot yet
construct knowledge, since knowledge depends on social, cultural and moral aspects.
Information Literacy
Information literacy is a set of abilities to evaluate information sources. Information
can be manipulated, so people need to be information literate to interpret that
information and identify fake news. In contemporary society, individuals have
access to a lot of information, and they need to know how to access, filter, organize
and share information.
Information literacy was coined in 1974 by Paul Zurkowski. Since then, researches
have studied the topic in many fields such as workplaces, libraries, schools, industry,
community, ethics and art. Therefore, Information literacy is interdisciplinary because
its concept is created by different fields. In 2009 the then-President of United States
Barack Obama announced Information Literacy Day. Obama helped to disseminate
this literacy worldwide to become more valuable to society. The document says:
Though we may know how to find the information we need, we must also know how
to evaluate it. Over the past decade, we have seen a crisis of authenticity emerge. We
now live in a world where anyone can publish an opinion or perspective, whether
true or not, and have that opinion amplified within the information marketplace. At
the same time, Americans have unprecedented access to the diverse and independent
sources of information, as well as institutions such as libraries and universities, that
can help separate truth from fiction and signal from noise (Obama, 2009).
One of the fields of research is ethics. Information literacy helps people to become
more ethical when using information. Information should be used to improve human
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Ethical Aspects of Information Literacy in Articial Intelligence
knowledge and socialization. Information literate people respect the rights of others
and value ethics in an artificial intelligence context.
The set of moral values of a group can be evaluated and interpreted in a critical
way. Information literacy contributes to this issue, helping people to learn how to
behave according to moral values and become an example to others. Individuals
can judge right from wrong in many aspects of their lives.
Furthermore, individuals can understand the consequences of information use
to society, and they need to know how to structure information (Bembem & Santos,
2014).
The document Framework of Information Literacy for Higher Education, released
in 2000, updated the information literacy standards (ACRL, 2015). Furthermore,
the ACRL (2015) also changed the concepts of information literacy, because they
introduced individuals’ experience as an element of learning. The ACRL (2015)
document is called Information Literacy Competency Standards for Higher Education
which demonstrates new concepts with a prescriptive interpretation.
Information literacy is the set of integrated abilities encompassing the reflective
discovery of information, the understanding of how information is produced and
valued, and the use of information in creating new knowledge and participating
ethically in communities of learning (ACRL, 2015, p. 11).
The Chartered Institute of Library and Information Professionals (CILIP) in the
United Kingdom also contributed to the development of the information literacy
concept. Initially, information literacy was considered the ability to identify
information needs, access it, evaluate it, use it, and communicate it ethically. In
2018 the CILIP expanded the concept of information literacy to consider different
contexts of learning: “Information literacy is the ability to think critically and make
balanced judgements about any information we find and use. It empowers us as
citizens to develop informed views and to engage fully with society” (CILIP, 2019).
Information literacy is a process that helps people to face ethical, legal and
political problems (Marti & Vega-Almeida, 2005). In order to solve these problems,
information literacy has been inserted into school curricula. Some organizations have
disseminated information literacy standards and indicators, such as the American
Association of School Libraries (1998) and the International Federation of Libraries
Association (IFLA). The American Association of School Libraries (1998) suggests
the following standards:
Standard 1 The student who is information literate accesses information efficiently
and effectively.
Indicator 1. Recognizes the need for information
Indicator 2. Recognizes that accurate and comprehensive information is the basis
for intelligent decision making
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Ethical Aspects of Information Literacy in Articial Intelligence
Indicator 3. Formulates questions based on information needs
Indicator 4. Identifies a variety of potential sources of information
Indicator 5. Develops and uses successful strategies for locating information
Standard 2 The student who is information literate evaluates information critically
and competently.
Indicator 1. Determines accuracy, relevance, and comprehensiveness
Indicator 2. Distinguishes among fact, point of view, and opinion
Indicator 3. Identifies inaccurate and misleading information
Indicator 4. Selects information appropriate to the problem or question at hand
Standard 3 The student who is information literate uses information accurately and
creatively.
Indicator 1. Organizes information for practical application
Indicator 2. Integrates new information into one’s own knowledge
Indicator 3. Applies information in critical thinking and problem solving
Indicator 4. Produces and communicates information and ideas in appropriate formats
Standard 4 The student who is an independent learner is information literate and
pursues information related to personal interests.
Indicator 1. Seeks information related to various dimensions of personal well-
being, such as career interests, community involve-ment, health matters, and
recreational pursuits
Indicator 2. Designs, develops, and evaluates information products and solutions
related to personal interests
Standard 5 The student who is an independent learner is information literate and
appreciates literature and other creative expressions of information.
Indicator 1. Is a competent and self-motivated reader
Indicator 2. Derives meaning from information presented creatively in a variety of
formats
Indicator 3. Develops creative products in a variety of formats
Standard 6 The student who is an independent learner is information literate and
strives for excellence in information seeking and knowledge generation.
Indicator 1. Assesses the quality of the process and products of personal information
seeking
Indicator 2. Devises strategies for revising, improving, and updating self-generated
knowledge
Standard 7 The student who contributes positively to the learning community and
to society is information literate and recognizes the importance of information
to a democratic society.
Indicator 1. Seeks information from diverse sources, contexts, disciplines, and cultures
Indicator 2. Respects the principle of equitable access to information
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Ethical Aspects of Information Literacy in Articial Intelligence
Standard 8 The student who contributes positively to the learning community and
to society is information literate and practices ethical behavior in regard to
information and information technology.
Indicator 1. Respects the principles of intellectual freedom
Indicator 2. Respects intellectual property rights
Indicator 3. Uses information technology responsibly
Standard 9 The student who contributes positively to the learning community and to
society is information literate and participates effectively in groups to pursue
and generate information.
Indicator 1. Shares knowledge and information with others
Indicator 2. Respects others’ ideas and backgrounds and acknowledges their
contributions
Indicator 3. Collaborates with others, both in person and through technologies, to
identify information problems and to seek their solutions
Indicator 4. Collaborates with others, both in person and through technologies, to
design, develop, and evaluate information products and solutions.
Association of College & Research Libraries (ACRL, 2015):
Standard 1 - The information literate student determines the nature and extent of
the information needed.
Standard 2 - The information literate student accesses needed information effectively
and efficiently.
Standard 3 - The information literate student evaluates information and its sources
critically and incorporates selected information into his or her knowledge base
and value system.
Standard 4 - The information literate student, individually or as a member of a group,
uses information effectively to accomplish a specific purpose.
Standard 5 - The information literate student understands many of the economic,
legal, and social issues surrounding the use of information and accesses and
uses information ethically and legally.
Council of Australian University Librarians (CAUL, 2004):
Standard 1 - The information literate person recognises the need for information
and determines the nature and extent of the information needed
Standard 2 - The information literate person finds needed information effectively
and efficiently
Standard 3 - The information literate person critically evaluates information and
the information seeking process
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Ethical Aspects of Information Literacy in Articial Intelligence
Standard 4 - The information literate person manages information collected or
generated
Standard 5 - The information literate person applies prior and new information to
construct new concepts or create new understandings
Standard 5 - The information literate person uses information with understanding and
acknowledges cultural, ethical, economic, legal, and social issues surrounding
the use of information
IFLA (Lau, 2008, p.16-17) information literacy standards are as follows:
1. Access. The user accesses information effectively and efficiently
a. Definition and articulation of the information need
i. Defines or recognizes the need for information
ii. Decides to do something to find the information
iii. Express and defines the information need Initiates the search process
b. Location of information
i. Identifies and evaluates potential sources of information
ii. Develops search strategies Accesses the selected information sources
Selects and retrieves the located information
2. Evaluation. The user evaluates information critically and competently
a. Assessment of information
i. Analyzes, examines, and extracts information
ii. Generalizes and interprets information
iii. Selects and synthesizes information
iv. Evaluates accuracy and relevance of the retrieved information
b. Organization of information Arranges and categorizes information
i. Groups and organizes the retrieved information
ii. Determines which is the best and most useful information
3. Use. The user applies/uses information accurately and creatively
a. Use of information
i. Finds new ways to communicate, present and use information
ii. Applies the retrieved information
iii. Learns or internalizes information as personal knowledge
iv. Presents the information product
b. Communication and ethical use of information
i. Understands ethical use of information
ii. Respects the legal use of information
iii. Communicates the learning product with acknowledgement of
intellectual property
iv. Uses the relevant acknowledgement style standards
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Ethical Aspects of Information Literacy in Articial Intelligence
MAIN FOCUS OF THE CHAPTER
Method
This is an exploratory and descriptive research, based on a Systematic Literature
Review (SLR). The SLR aims to identify, select, evaluate, synthesize and reproduce
relevant evidence about specific objects (Tranfield, Denyer & Smart, 2003). This
method follows some steps that validate the results as illustrated by Table 1.
The first step of the research uses a bibliographic review to construct the concepts
of information literacy and artificial intelligence focused on ethics. The second step
was to access international scientific databases such as Base de Dados de Artigos de
Periódicos da Ciência da Informação Brasileira (BRAPCI) [Brazilian Information
Science Database of Journal Papers] which is an important database of Information
Science. The database search only found one paper that connected information
literacy to artificial intelligence.
SCOPUS, Web of Science (WoS), Library and Information Science Abstracts
(LISA) and Science Direct are also part of the SLR in this chapter. These databases
are very important to science and they connect many fields of research. The data
gathering was based on advanced research in each database because that helps to
find precise results. The SLR was implemented using the expressions, “information
literacy AND artificial intelligence”. The papers were retrieved from any year, that
is, there were no time constraints.
Table 1. Phases of SLR
Step Phase
1. Planning of SLR
Identify the need for revision
Prepare the proposal
Develop the protocol of SLR
2. Application of SLR
Identify studies
Select research
Evaluation of the quality of the study
Data synthesis
Data extraction
3. Sharing the results
Recommendations and results
Demonstrate evidence that is useful to practical
contexts.
Source: Adapted from Tranfield, Denier and Smart (2003) and Bordeleau, Mosconi and Santa-Eulalia (2018,
p. 3946).
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Ethical Aspects of Information Literacy in Articial Intelligence
The paper selection followed these criteria: (i) academic papers or scholarly papers;
(ii) papers that are peer reviewed; and (iii) mention of both artificial intelligence
and information literacy together in one of the following sections of the retrieved
article: title, abstract, and keywords. After the analysis of papers (SCOPUS, WoS,
LISA and Science Direct), the research generated these results:
The papers retrieved from the databases were saved in RIS format, so they could
be organized at Endnote Software. This software helped to analyze papers based on
the inclusion criteria. After removing duplicates and filtering by topic relevance, this
research analyzed only 15 papers. Therefore, the SLR was based on fifteen scientific
papers. This demonstrates that there is a lack of research connecting information
literacy to the context of artificial intelligence.
Results
Systematic Literature Review
The results of the SLR show that there is not a lot of research connecting information
literacy and artificial intelligence. This type of research is still innovative to
Information Science and to other interdisciplinary fields such as Computer Science,
Education, etc.
This finding is supported by the fact that SCOPUS, an important scientific
database, did not find any paper about the topic. The other databases (Web of Science,
Science Direct and LISA) retrieved 14 (fourteen) papers that connect information
literacy to artificial intelligence (Table 3 below).
The papers in Table 3 are connected to four scientific fields: Information Science,
Computer Science, Communication and Education. These fields are multi- and
Table 2. Quantitative results of SLR
Database Papers Available
SCOPUS (Elsevier) 0
WoS (Clarivate Analytics) 10
Science Direct (Elsevier) 5
LISA 6
BRAPCI 1
Source: The authors - 2019
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Ethical Aspects of Information Literacy in Articial Intelligence
Table 3. Papers retrieved in databases
Authors Title Periódico/
Tipo de Documento Year
Mathews, E. C.; Jackson, G.
T.; Olney, A.; Chipman, P.;
Graesser, A. C.
Achieving domain independence in
AutoTutor Book Chapter 2003
Mathews, E. C.; Jackson, G.
T.; Olney, A.; Chipman, P.;
Graesser, A. C.
Achieving domain independence in
AutoTutor Book Chapter 2003
Terracina, A.; Mecella, M
Building an Emotional IPA Through
Empirical Design With High-School
Students
Book Chapter 2015
Forbes, J.; Garcia, D. D.
But What Do the Top-Rated Schools
Do?” A Survey of Introductory
Computer Science Curricula
Book Chapter 2007
Raycheva, L. The digital notion of the citizen-centred
media ecosystem
International Journal of
Digital Television 2018
Hesse, B. W.; Shneiderman,
B.
eHealth research from the user’s
perspective
American Journal of
Preventive Medicine 2007
Gonzalez-Rodriguez, Diego;
Kostakis, Vasilis
Information literacy and peer-to-
peer infrastructures: An autopoietic
perspective
Telematics and
Informatics 2015
Phoha, V. V.
An interactive dynamic model for
integrating knowledge management
methods and knowledge sharing
technology in a traditional classroom
Book Chapter 2001
Schulz, Peter J.; Nakamoto,
Kent
Patient behavior and the benefits of
artificial intelligence: The perils of
“dangerous” literacy and illusory patient
empowerment
Patient Education and
Counseling 2013
Durko, M.; Stoffova, V. Perception: determinants and nature of
direct and indirect experience Book Chapter 2016
Robinson, L.; Bawden, D.
The story of data” A socio-technical
approach to education for the data
librarian role in the CityLIS library
school at City, University of London
Library Management 2017
Troseth, Georgene L.;
Strouse, Gabrielle A.; Russo
Johnson, Colleen E.
Early Digital Literacy: Learning to
Watch, Watching to Learn Book Chapter 2017
Fagherazzi, G.; Ravaud, P.
Digital diabetes: Perspectives for
diabetes prevention, management and
research
Diabetes & Metabolism 2018
Gelles, Abby
Robotics and artificial intelligence
as educational tools for developing
self-sufficiency. Part I — Descriptive
overview
Microprocessing and
Microprogramming 1984
Dent, Valeda F. Intelligent agent concepts in the modern
library Library Hi Tech 2007
Viana, Cassandra Lúcia de
Maya
O impacto das inteligências artificiais na
formação dos bibliotecários e cientistas
da informação: revisão de literatura
Ciência da Informação 1990
Source: (The authors)
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Ethical Aspects of Information Literacy in Articial Intelligence
interdisciplinary which results from postmodern science. The papers show three
groups that differ theoretically, which is illustrated in Table 4 below.
Mathews et. al. (2003) and Terracina & Mecella (2015) suggest to adopt digital
tutors and mentors to simulate discussions and tutoring strategies in the field of
long-distance education. They propose that such mentors would act as teaching
agents with the aim of motivating the students with respect to 21st century aspects
of learning, such as autonomy, creativity, communication, critical thinking, and
information literacy. These systems could guide the student’s research by directing
him or her to reliable and relevant sources of information.
This triggers that ethical issue that was mentioned above, the fear that technology
will gradually replace human labor. On the other hand, it creates a new problem
for the advancement of the learning that contemporary society requires. Morin
(2003) states that this education demands people who can learn how to learn.
This is based on the idea of two entities whose functions are clearly defined: (i)
a mediator which stimulates learning by means of the effective and ethical use of
existing informational resources and (ii) the learner who develops the necessary
mental skills to build meaning.
This conclusion suggests that although algorithms and other elements of
artificial intelligence are present in various modern activities, they can’t replace
the humanizing aspect of communication, which implies the formation of symbols
by means of interlocution between thinking social beings. With that said, we can’t
ignore the fact that AI is very lucrative for long-distance education providers since
they can hire fewer online tutors.
Table 4. Theoretical groups of papers
Research Group Authors Topic
Group I
Phoha (2013); Durko & Stoffova (2017);
Troseth (2017); Strouse & Russo Johnson
(2017), Dent (2007); Mathews et. al.
(2003); Terracina & Mecella (2015).
Papers that propose computer models
to learning mediation. They focus on
digital literacy.
Group II
Raycheva (2018); Hesse & Shneiderman
(2007); Schulz & Nakamoto (2013);
Fagherazzi & Ravaud (2018)
Papers that study social, political and
economical changes as a result of
information technology. They analyze
ethical and legal issues related to
artificial intelligence.
Group III Gonzalez-Rodriguez & Kostakis (2015)
Papers that focus on information
literacy as a relevant factor to human
development. The aspects of artificial
intelligence help to develop flexible
processes such as information retrieval
and decision-making.
Source: (The authors)
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Ethical Aspects of Information Literacy in Articial Intelligence
This research is concerned with individuals’ lifelong learning since its objective
is to contribute to “learning to learn” using artificial intelligence. Regarding the
inference of categories, the articles point out the social consequences of technology
and express a concern with the ethical evaluation of information and its sources.
Hence, they correspond to the content analysis categories proposed by Bardin (2010).
The Group II research listed in Table 4 focuses on the social, political, and
economic implications of the use of AI. They highlight the ethico-legal aspects
linked to the use of AI, particularly for monitoring patient care. In those researches
(Hesse; Shneiderman, 2007; Fagherazzi & Ravaud, 2018) the term “information
literacy” only appears in a marginal way, even though those aspects are an integral
part of the learning that is stimulated by various literacy programs.
Other articles criticized the use of AI in the medical field. There is an increasing
production and sale of those advanced technologies, but physicians are not yet
ready to deal with them. In the USA, for example, there have been cases of surgical
complications due to the incorrect use of such tools.
The articles draw attention to the need to develop health literacy so that patients
become aware of which practices and technologies are associated with this intense
interest by capitalists of the medical industry (Schulz & Nakamoto, 2013). From a
more optimistic point of view, AI has been a major asset in interpreting exam results
and the large volume of data involved in diagnosing a disease.
Ethics must be applied by regulating the smart equipment which is used
indiscriminately. According to Pellegrini and Vitorino (2018, p.128): “[…] the
ethical aspect of information literacy is directly linked to the ethical and efficient use
of information, and the information professional is responsible for its ethical use.”
These articles fall into categories 1, 2, and 3 because they discuss the question of
ethics directly. They also point out the negative aspects and the capitalist interests of
large companies that want to sell this equipment at all costs. The articles highlight
the relevance of ethical information access and the importance of evaluating the
ethical quality of information. Quality information is collected in a critical way
in the health field and for the creation of equipment and smart systems based on
ethical principles.
The research that makes up Group III deal with information literacy as a
fundamental skill to learn in the 21st century. These studies do not focus on the
technologies themselves but rather the use of information. Gonzalez-Rodriguez
and Kostakis (2015) found that the inherent complexity of the enormous amount of
data and information requires heterogenous networks made up of both human and
artificial agents to improve the recovery of information, the inference of knowledge,
and decision-making.
According to the Italian philosopher Berardi (2015) society is a prisoner of social
networks, and many people believe the simple-minded information shared there.
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Ethical Aspects of Information Literacy in Articial Intelligence
“[…] the legal and responsible use of information, based in the laws and norms that
govern information use in each country, and the ethical principles of respect, justice,
solidarity, and compromise, which lead to citizenship and to collective well-being”
(Pellegrini; Vitorino, 2018, p.130).
The articles mainly focus on the third analytical category since they address the
question of sharing results in an ethical way: considering the consequences of the
product, respecting intellectual property, and developing strategies to avoid unethical
use of the product. These inferences fall into the third category, which is related
to the use of information in information literacy (Lau, 2008). Information literacy
also encompasses the other analytical categories. The use of information depends
on one’s effective access and evaluation.
In general, the articles concern the ethical development of technology. The
aim of the research is to improve people’s quality of life and to build meaningful
knowledge. Benasayag (UNESCO, 2018, p.15) concurs: “meaning is created by
humans, not by machines”.
The ethical aspects referred to above must be described within the context of
philosophy of information, which according to Floridi (2004) includes the need for
new codes of conduct with respect to technology, as well as new laws and regulations
that incorporate this new technological dynamic. An information literate person
criticizes the context of AI in an ethical way and proposes new solutions to confront
the challenges of that context.
Information Literacy Ethical Standards for Artificial Intelligence Use
Table 5 illustrates the categories created from the IFLA standards of information
literacy (Lau, 2007) and the basic principles of artificial intelligence created by
The United Nations Educational, Scientific and Cultural Organization (UNESCO,
2018) and The Asimov Laws of Robotics (1942) in his science fiction book known
as Robot. The basic principles and the laws can guide the ethical use of artificial
intelligence.
IFLA (Lau, 2007) standards and indicators have been used by some researchers
and organizations. They are flexible enough to be applied in practical contexts, so
IFLA standards are a reference for information literacy in Table 5. The UNESCO
(2018) document is based on specialists’ interviews and international papers in the
field of artificial intelligence. This is a relevant document to explain ethical aspects
of artificial intelligence. Asimov’s laws of robotics are also used as guidance for the
categories, and some scientific research in the field of robotics has used them as
ethical guidelines (Takahashi & Shimizu, 2014; Vadymovych, 2017; Butazzo, 2008).
Category 1 of ethical information access is connected to Standard 1 of information
literacy (Lau, 2007). Furthermore, category 1 is linked to the law that artificial
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Ethical Aspects of Information Literacy in Articial Intelligence
intelligence cannot hurt anyone (UNESCO, 2018). This category helps to analyze
if individuals define information needs and its consequences to society. In addition,
it allows someone to identify if people seek information properly and if they respect
intellectual property. Category 2, which evaluates the ethical quality of information,
is connected to Standard 2 of information literacy (Lau, 2007). This category helps
to fight against humans’ prejudice in machines (UNESCO, 2018). Furthermore,
category 2 identifies if individuals understand the consequences of information
analysis and if they filter information based on relevance. The third category verifies
Table 5. Categories and indicators to analyze the results
IFLA (Lau, 2007) Information
Literacy Standards
Basic Principles of Artificial
Intelligence (UNESCO, 2018)
Category and Indicators to
Analyze the Results
Access → The user accesses
information efficiently and
effectively
A robot cannot hurt a human being
or allow that someone suffers any
harm (Asimov, 1983). The same thing
occurs with artificial intelligence,
because it cannot threaten human life
(UNESCO, 2018).
Category 1
Individuals access information
in an ethical way
Indicators
• Define information needs
and its consequences to
society
• Seek information in the
right places and respect
copyrights
• Develop seeking strategies
ethically
Evaluation → The user evaluates
information in a critically
A robot must obey human orders
except in cases where they hurt other
people like Asimov (1983) First
Principle. The UNESCO (2018, p. 39)
proposes some questions: algorithms
trained in human language acquire
prejudices because of stereotypes
of data which are part of daily life”.
The UNESCO is worried about the
emergence of discriminatory, racist
and hostile machines.
Category 2
Individuals evaluate the
quality and ethics of
information critically.
Indicators
• Interpret and evaluate
information based on ethical
principles
• Consider the impacts of
information to society
• Filter information to decide
its quality and relevance
Use → The user applies
information critically and
precisely
A robot should protect its existence
as long as it does not conflict to the
First or Second Principle (Asimov,
1983). The systems and equipment of
artificial intelligence need to be safe
to avoid losing data and information.
Furthermore, according to UNESCO
(2018) our mission is to guide an
international ethical debate about
theses changes.
Category 3
Individuals develop
equipment and smart systems
based on ethical principles
Indicators
• Share the results ethically
• Consider the consequences
of a product and respect
intellectual property
• Develop strategies to avoid
the use of products in non-
ethical activities.
Source: (The Authors)
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Ethical Aspects of Information Literacy in Articial Intelligence
if individuals develop smart equipment and systems ethically. This category is
connected to the third standard of information literacy (Lau, 2007) and the security
of machines. The category helps to identify whether AI theory considers ethical
principles. Furthermore, the third category contributes to an analysis of whether
researchers share those technologies ethically and consider the consequences of AI
to society. Researchers and product developers need to develop strategies to avoid
the use of AI in non-ethical activities.
Some International Ethics Frameworks for Artificial Intelligence
Europe was the first region to share ethical guidelines for artificial intelligence.
The name of the document is Ethics Guidelines for Trustworthy AI which was
published in April 2019 by the High-Level Expert Group on Artificial Intelligence
(AI HLEG). This guideline inspired the Australian Ethical Principles for Artificial
Intelligence as well.
Trustworthy artificial intelligence must be developed based on three components:
it should be lawful, ethical and robust. These three dimensions helped to construct a
framework for AI which is based on fundamental human rights (AI HLEG, 2019).
This document considers privacy, transparency, safety and non-discrimination to
be important aspects of the framework. Figure 1 below illustrates the framework.
The framework for trustworthy AI is useful to guide courses and organizations.
The framework is based on three main aspects: Lawful AI, Ethical AI and Robust
AI. Lawful AI depends on the country and region, so the European Commission
decided not to discuss it in the document. Ethical AI is the ethical principles that
can guide AI research, courses and development. Robust AI is the result of Lawful
AI plus Ethical AI. Robust AI is focused on fairness, applicability, prevention of
harm and the respect for human autonomy (AI HLEG, 2018).
The Australian government consulted some specialists in the artificial intelligence
field to create a guide of ethical principles. These principles are illustrated by Table 6.
The Australian Ethical Principles for Artificial Intelligence was based on the
Framework for Trustworthy AI (Figure 1). These principles have eight dimensions
that guide professionals and organizations. The AI should be human-centered to value
individuals, fair to avoid discriminating against certain people, private to protect
data, transparent, contestable to receive feedback from the public and accountable.
SOLUTIONS AND RECOMMENDATIONS
Artificial intelligence is useful to solve some problems, and it can encourage the
development of technology. Furthermore, AI makes individuals’ work easier than in
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Ethical Aspects of Information Literacy in Articial Intelligence
the last century. However, ethical and moral issues need to be evaluated by scientists
and society. Some AI technology has been created to kill or to control people, and
it can also be used to reduce freedom of speech. Individuals need to debate the
limits of technology.
Information literacy can be applied in Computer Science, Analysis and
Development of Systems, Artificial Intelligence and Data Science. This literacy
can guide the ethical debate about the negative consequences to humans and the
environment. Therefore, information literacy must be applied in the syllabus of
courses and it should also be taught as a course. The aim is to graduate critical
thinkers, so that they access information ethically.
The first step to fight against unethical AI is to understand the difference between
the concepts of human and machine intelligence. The second step is to study artificial
intelligence to help people. Scientists and research organizations can ask public
opinion about the limits of technology, so that decisions can be made democratically
and no one social group prevails.
Figure 1. Framework for trustworthy AI
Source: (AI HLEG, 2019, p. 8)
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Ethical Aspects of Information Literacy in Articial Intelligence
FUTURE RESEARCH DIRECTIONS
Researchers from several fields have a common mission: they need to raise awareness
of the consequences and the problems of lack of ethics in innovation and artificial
intelligence. According to the authors in the discussion section, machines and
software can replace an ethical professional at work. However, employers need to
consider that machines do not yet have empathy towards others.
The code and functions of technology must be analyzed ethically before being
released to the public. Future research can apply information literacy in course
curricula in Computer Science. Technology courses must consider the ethical
implications of machines and systems. These technologies are helpful to people
and must respect human rights instead of threatening them.
International organizations have created documents to share ethical code. The
documents must be used to emphasize the relevance of information literacy and
critical thinking to artificial intelligence development. An international movement
and public policy are necessary to value this literacy and lifelong learning.
Table 6. Australian ethical principles for artificial intelligence
Principles Explanation
Human, social and environmental
wellbeing
Throughout their lifecycle, AI systems should benefit
individuals, society and the environment.
Human-centred values Throughout their lifecycle, AI systems should respect human
rights, diversity, and the autonomy of individuals.
Fairness
Throughout their lifecycle, AI systems should be inclusive
and accessible, and should not involve or result in unfair
discrimination against individuals, communities or groups.
Privacy protection and security
Throughout their lifecycle, AI systems should respect and
uphold privacy rights and data protection, and ensure the
security of data.
Reliability and safety Throughout their lifecycle, AI systems should reliably operate
in accordance with their intended purpose.
Transparency and explainability
There should be transparency and responsible disclosure to
ensure people know when they are being significantly impacted
by an AI system, and can find out when an AI system is
engaging with them.
Contestability
When an AI system significantly impacts a person, community,
group or environment, there should be a timely process to allow
people to challenge the use or output of the AI system.
Accountability
Those responsible for the different phases of the AI system
lifecycle should be identifiable and accountable for the
outcomes of the AI systems, and human oversight of AI
systems should be enabled.
Source (The Australian Government - Department of Industry, Innovation and Science)
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Ethical Aspects of Information Literacy in Articial Intelligence
CONCLUSION
These days, technology is present in all aspects of people’s lives. On the one hand,
there is intense optimism about the importance of Information Communication
Technology, but on the other hand, several problems arise, including ethical ones
related to their use. Artificial intelligence has transformed traditional ways of learning,
so it demands that people become information literate. This literacy allows effective
decision-making through critical thinking.
The ethical dimension of information literacy is fundamental to evaluate of the
consequences of artificial intelligence. Technological research has advanced quickly.
However, the debate about the results of these technologies is still slow.
The systematic literature review demonstrates that there is not a lot of papers
about information literacy and artificial intelligence. However, a few papers about
both topics are available internationally. These papers are focused on digital tutors
to help students learn online.
ACKNOWLEDGMENT
This research was supported by the Coordenação de Aperfeiçoamento de Nível
Superior (CAPES) and Conselho Nacional Científico e Tecnológico (CNPq) and
Fonds de Recherche du Québec – Nature et Technologie (FRQNT).
REFERENCES
Adolphs, P., & Epple, U. (2015). Status Report: Reference Architecture Model Industrie
4.0 (RAMI4.0). Retrieved from: https://www.zvei.org/fileadmin/user_upload/
Themen/Industrie_4.0/Das_Referenzarchitekturmodell_RAMI_4.0_und_die_
Industrie_4.0-Komponente/pdf/5305_Publikation_GMA_Status_Report_ZVEI_
Reference_Architecture_Model.pdf
Almada-Lobo, F. (2015). The Industry 4.0 revolution and the future of Manufacturing
Execution Systems (MES). Journal of Innovation Management, 3(4), 16–21.
doi:10.24840/2183-0606_003.004_0003
Association of College & Research Libraries. (2000). Information Literacy
Competency Standards for Higher Education. Retrieved from: https://alair.ala.org/
handle/11213/7668
199
Ethical Aspects of Information Literacy in Articial Intelligence
Australian Ethical Principles for Artificial Intelligence. (2019). The Australian
Government - Department of Industry, Innovation and Science. Retrieved from: https://
consult.industry.gov.au/strategic-policy/artificial-intelligence-ethics-framework/
Belluzzo, R. C. B. (2014). O conhecimento, as redes e a competência em informação
(CoInfo) na sociedade contemporânea: Uma proposta de articulação conceitual
[Knowledge, network and information literacy (IL) in current society: a conceptual
discussion]. Perspectivas em Gestão & Conhecimento, João Pessoa, 4, 48–63.
Bordeleau, A. F., Mosconi, E., & Santa-Eulalia, L. A. (2018). Business Intelligence
in Industry 4.0: State of the art and research opportunities. Proceedings of the 51st
Hawaii International Conference on System Sciences. Retrieved from: http://hdl.
handle.net/10125/50383
Bostron, N. (2016). Articial intelligence: ‘we’re like children playing with a bomb’.
Retrieved from: https://www.theguardian.com/technology/2016/jun/12/nick-
bostrom-artificial-intelligence-machine
Demasson, A., Partridge, H., & Bruce, C. (2016). Information literacy and the
serious leisure participant: Variation in the experience of using information to learn.
Information Research, 21(2).
Ethical Guideliness for Trustworthy Artificial Intelligence. (2019). European
Comission. High-Level Expert Group on Artificial Intelligence (AI HLEG). Retrieved
from: https://ec.europa.eu/futurium/en/ai-alliance-consultation
Floridi, L. (2004). Open problems in the philosophy of information. Metaphilosophy,
35(4), 2004. doi:10.1111/j.1467-9973.2004.00336.x
Grafstein, A. (2017). Information Literacy and Critical Thinking: Context and
Practice. Pathways into Information Literacy and Communities of Practice: Teaching
Approaches and Case Studies, 3-28.
Lau, J. (2007). Guidelines on Information Literacy for Lifelong Learning. The
Hague: IFLA. Retrieved from: https://www.ifla.org/files/assets/information-literacy/
publications/ifla-guidelines-en.pdf
Lloyd, A. (2007). Recasting information literacy as sociocultural practice: Implications
for library and information science researchers. Information Research, 12(4).
Mccarthy, J. (1955). A proposal for the Dartmouth summer research project on
artificial intelligence, 1955. Retrieved from: http://www-formal.stanford.edu/jmc/
history/dartmouth/dartmouth.html
200
Ethical Aspects of Information Literacy in Articial Intelligence
Obama, B. (2009). National information literacy awareness month. Retrieved
from: https://www.govinfo.gov/app/content/pkg/STATUTE-123/pdf/STATUTE-
123-Pg3711.pdf
Ottonicar, S. L. C., Valentim, M. L. P., & Feres, G. G. (2015). Competência em
informação e os contextos educacional, tecnológico, político e organizacional
[Information literacy and the educational, technological, political and organizational
contexts]. Revista Ibero-americana de Ciência da Informação, Brasília, 9(1), 24–142.
Schwab, K. (2016). The fourth industrial revolution. Crown Business.
Slayton, R. (2018). Policy Series: Beyond Cyber-Threats: The Technopolitics
of Vulnerability. Retrieved from: https://issforum.org/roundtables/policy/1-5bc-
technopolitics
The Australian Government - Department of Industry. (2019). Innovation and
Science. AI Ethics Principles. Retrieved from: https://www.industry.gov.au/data-
and-publications/building-australias-artificial-intelligence-capability/ai-ethics-
framework/ai-ethics-principles
Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a Methodology for Developing
Evidence-Informed Management Knowledge by Means of Systematic Review. British
Journal of Management, 14(3), 207–222. doi:10.1111/1467-8551.00375
United Nations Educational, Scientific and Cultural Organization (UNESCO). (n.d.).
Towards a global code of ethics for artificial intelligence research. In Artificial
Intelligence: the promises and the threats. Retrieved from: https://en.unesco.org/
courier/2018-3/towards-global-code-ethics-artificial-intelligence-research
Vitorino, E. V., & Piantola, D. (2011). Dimensões da competência informacional
(2) [Dimensions of information literacy]. Ciência da Informação, Brasília, 40(1),
99–110.
Yafushi, C. A. P. (2015). A Competência em informação para a construção de
conhecimento no processo decisório: estudo de caso na Duratex de Agudos (SP)
[Information literacy to construct knowledge in the decision-making process: a case
study at Duratex Agudos (SP)] (Master’s Dissertation). Retrieved from: https://
repositorio.unesp.br/handle/11449/126599
201
Ethical Aspects of Information Literacy in Articial Intelligence
ADDITIONAL READING
Capurro, R. (2006). Towards an ontological foundation of information ethics. Ethics
and Information Technology, 8(4), 175–186. doi:10.100710676-006-9108-0
Dignum, V. (2018). Ethics in artificial intelligence: Introduction to the special issue.
Ethics and Information Technology, 20(1), 1–3. doi:10.100710676-018-9450-z
Gomes de Andrade, N., Pawson, D., Muriello, D., Donahue, L., & Guadagno, J.
(2018). Ethics and Artificial Intelligence: Suicide Prevention on Facebook. Philosophy
& Technology, 31(4), 669–684. doi:10.100713347-018-0336-0
Lloyd, A. (2017). Information literacy and literacies of information: A mid-range theory
and model. Journal of Information Literacy, 11(1), 91–105. doi:10.11645/11.1.2185
Pellegrini, E., & Vitorino, E. (2018). A Dimensão Ética da Competência em
Informação sob a Perspectiva da Filosofia. Perspectivas em Ciência da Informação,
23(2), 117–133. http://portaldeperiodicos.eci.ufmg.br/index.php/pci/article/
view/2953. doi:10.1590/1981-5344/2953
Russel, S. (2015). Robotics: Ethics of artificial intelligence. Nature, 521(7553),
415–418. doi:10.1038/521415a PMID:26017428
Silva, H., Jambeiro, O., Lima, J., & Brandão, M. A. (2005). Inclusão digital e
educação para a competência informacional: Uma questão de ética e cidadania.
Ciência da Informação, 34(1), 28–36. doi:10.1590/S0100-19652005000100004
Steinerová, J., & Ondrišová, M. (2019). Research Data Literacy Perception and
Practices in the Information Environment. In Information Literacy in Everyday
Life. ECIL 2018. Communications in Computer and Information Science (Vol. 989).
Springer. doi:10.1007/978-3-030-13472-3_51
KEY TERMS AND DEFINITIONS
Artificial Intelligence: The intelligence of technology and machines.
Critical Thinking: The ability to criticize a text or information.
Ethics: Part of philosophy that studies human values.
Information Evaluation: It is the analysis of information quality.
Information Literacy: Ability to construct knowledge and interpret information.
Information Science: Scientific field that studies information in different contexts.
Interdisciplinarity: The knowledge produced by two or more scientific field.
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