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Bjelajac, Ž., Filipović, A., & Stošić, L. (2023). Can AI be evil: The criminal capacities of ANI, International Journal of Cognitive
Research in Science, Engineering and Education (IJCRSEE), 11(3), 519-531.
Introduction
People fear the unknown, everything they cannot comprehend, predict, or control, especially
phenomena beyond their volition. This psychological framework can be applied to the question of ‘Can AI
be evil?’ We fear this question because most people lack a deep understanding of articial intelligence,
shaping their perception of AI based on depictions in movies and literature. They often believe that such
dystopian AI scenarios could become our future. What people may not realize is that what’s commonly
depicted in most lms represents AI superior to humans in every aspect, called ‘Articial General
Intelligence’ or ‘AGI,’ but its full implementation isn’t expected by scientists before the end of this century
(Ford, 2018). This has led us to contemplate the aspects of the dark side of articial intelligence, which
we have ‘in agrante,’ preceding AGI, especially ASI, referred to by scientists as ANI.
Science currently operates with three levels of articial intelligence in theory: Articial Narrow
Intelligence or ANI, Articial General Intelligence or AGI, and Articial Super Intelligence or ASI. (IBM Data
and AI Team, 2023; Price, Walker and Wiley, n.d). ANI is considered ‘weak’ AI, while the other two forms
are classied as ‘strong’ AI. Weak articial intelligence is dened by its ability to perform specic tasks,
such as regulating air trafc, driving a car, or identifying a particular person. Some examples of ANI usage
include natural language processing, computer vision, advancements in human medical treatments, task
automation, and support for chatbots and virtual assistants.
Stronger or higher forms of AI, like AGI and ASI, involve replicating and simulating human thinking
and behavior. Strong AI is dened by its ability to successfully mimic or surpass cognitive concepts
Can AI be Evil: The Criminal Capacities of ANI
Željko Bjelajac1* , Aleksandar M. Filipović2 , Lazar Stošić3
1University Business Academy, Faculty of Law for Commerce and Judiciary, Republic of Serbia,
e-mail: zdjbjelajac@gmail.com
2University of Business Academy, Faculty of Economics and Engineering Management, Novi Sad, Serbia
e-mail: sasha.lipovic@gmail.com
3Union Nikola Tesla, Belgrade, Faculty of Management, Sremski Karlovci, Serbia, e-mail: lazar.stosic@famns.edu.rs
Abstract: Articial Narrow Intelligence (ANI) represents a captivating domain within technological advancement,
bearing the potential for profound societal transformations. While ANI holds the promise of enhancing various facets of human
existence, it concurrently engenders inquiries into its “darker aspects.” This study delves into the challenges associated with
ANI’s conceivable manifestation of harm and injustice, a phenomenon devoid of consciousness, intention, or responsibility
akin to that of human entities. A pivotal dimension of ANI’s “dark side” pertains to its susceptibility to malevolent utilization.
Despite its lack of awareness, ANI serves as a tool for malicious endeavors, encompassing the propagation of disinformation,
compromise of security systems, and consequential decision-making. This prompts contemplation on strategies to mitigate these
“precise manifestations of malevolence” arising from ANI’s technological progression. Additionally, ANI’s development introduces
profound ethical quandaries. Ensuring ANI’s alignment with moral principles while averting scenarios in which it generates
decisions conicting with human morality becomes a pressing concern. This research underscores the imperative for rigorous
regulatory frameworks and ethical directives to curtail potential hazards and unscrupulous utilization of ANI. The fundamental
objective of this investigation is to advocate for the responsible deployment of ANI in society. A comprehensive understanding
of potential risks, complemented by meticulous consideration of ethical dimensions, emerges as an indispensable prerequisite
to harmonizing technological advancement with safeguarding societal and individual interests.
Keywords: Articial narrow intelligence, evil, crime, ethics.
Review article
Received: October 19, 2023.
Revised: November 26, 2023.
Accepted: December 09, 2023.
UDC:
004.8:341.947
10.23947/2334-8496-2023-11-3-519-531
© 2023 by the authors. This article is an open access article distributed under the terms and conditions of the
Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
*Corresponding author: zdjbjelajac@gmail.com
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and capabilities of the human brain. The pinnacle of AGI would be equivalence with human intellectual
capacity, while articial superintelligence (ASI) would signicantly surpass human intelligence and the
cognitive abilities of the human brain. Research in this eld is ongoing, but no known form of strong
articial intelligence currently exists. Articial intelligence is emerging as the predominant driving factor
of the current era. ANI is becoming the central player in various sectors of life. Progress promises
innovations that will improve healthcare, education, trade, industry, and many other elds. However, along
with undeniable progress, which remains largely in the realm of predictions, the proliferation of ANI poses
an ominous threat of unknown provenance, intention, and form, as humanity increasingly relies on AI.
The omnipresence of ANI brings forth a series of profound ethical and legal questions and dilemmas that
require careful consideration and the establishment of responsible frameworks.
One of the central philosophical questions in the context of the ontological aspects of AI technology
is, ‘Can articial intelligence be evil?’ The concept of ‘evil’ is traditionally associated with the intent of
conscious beings to inict pain, harm, or injustice on other conscious beings. It is presumed that higher
forms of articial intelligence (AGI and ASI) might or should have consciousness and free ontological
existence, allowing them to choose evil as a form of behavior. However, concerning articial narrow
intelligence (ANI), the ontological paradigm of this noumenon excludes consciousness and intent,
shedding light on this matter in a different way. ANI is a product of human engineering and represents
a collection of algorithms and data that enable machines to autonomously perform tasks that typically
require human intelligence. This technology can cause harm, and it can exhibit activities and qualities
reminiscent of malevolence that we would attribute to conscious beings. The question that arises is how
to interpret and understand the negative consequences and whether, in the context of actions by articial
intelligence, we can classify them as ‘evil’.”
Moral Evil in the Behavior of Articial Narrow Intelligence (ANI)
An essential dialectical opposition exists between the ontological concepts of humans and articial
intelligence. Humans, upon gaining consciousness and reason, became free beings, possessing free
will that grants them the right and the ability to choose evil as a way of life. Human beings acquired their
freedom through hubris, a just rebellion against the cosmic or divine order. They survived this rebellion
but ceased to be ethically and mentally perfect, striving now to create an articial copy of themselves (AI)
that would be devoid of the imperfect attributes of humans—a replication of humans before committing
the original sin. Can humans, inherently free but mentally imperfect and ethically fragile, create a perfect
articial intelligence? To what extent are humans capable of, while crafting various forms of articial
intelligence, avoiding the implementation of their own limitations and the ‘dark side’ of their personalities
in AI, even if only in ANI? This is also an epistemological question. When an AI entity reaches singularity, it
will learn from the people around it (see more: Bostrom, 2014). What will an AI entity learn from observing
human interactions and behaviors? The answer must be rather grim and dystopian.
ANI lacks consciousness, intent, or the moral capacity of conscious beings, necessitating a different
approach. When we contemplate ‘evil’ in the context of ANI, we must exclude the copying of logical
and legal postulates of theories and practices related to human behavior, particularly the reasons for
‘culpability exclusion’ in humans who have committed a criminal act. With ANI, our focus should be on the
negative consequences, harm done, and the risks posed by this technology. From the perspective of the
ethics of the human community, the ethical characteristics of AI entities present a kind of ethical dilemma.
The concept of ‘evil,’ in the sense of an ethical, civilizational, normative category of human life, is regarded
as ‘intentionally and consciously inicting pain on a conscious being’ (Rasel, 1982). The fact that ANI has
no intent to cause harm, nor any consciousness to do anything wrong to anyone or anything, cannot be
a reason for excluding ANI’s culpability. Hence, among experts in ANI, concerns are growing that ANI
could engage in activities that people perceive as causing severe harm. This is particularly relevant in the
context of potential misuse of ANI for military purposes. ANI can be integrated into weapon systems to
enable autonomous tracking, targeting, and attacking of human targets. The technology of ‘autonomous
weapon systems’ controlled by ANI can be misused to target civilian objects or innocent people. ANI can
be used to generate false information, videos, and texts to spread misinformation and propaganda for the
purpose of destabilizing opponents. It can be used for mass surveillance of citizens’ communications and
movements, jeopardizing privacy and civil liberties. It can be used to conduct sophisticated cyberattacks,
including attacks on critical infrastructure, military systems, or communication networks. ANI can manifest
‘evil’ through bias and discrimination in its decisions. ANI algorithms created on unfair or biased data can
result in injustice and harm with very severe consequences. The automation brought by ANI can result in
job losses and changes in the labor market, which unemployed individuals may perceive as evil.
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Bjelajac, Ž., Filipović, A., & Stošić, L. (2023). Can AI be evil: The criminal capacities of ANI, International Journal of Cognitive
Research in Science, Engineering and Education (IJCRSEE), 11(3), 519-531.
People may strive to create AI that functions as close to perfection as possible, but complete
perfection is unattainable for humans. The reasons for this are multiple and are based on: (1) Inherent
human constraints, preventing the creation of awless articial intelligence due to limitations in human
knowledge and capabilities; (2) Flaws in decision-making arising from human biases and imperfections,
where personal experiences, prejudices, and values can introduce errors in the development of articial
intelligence; (3) The ever-changing nature of technology, which continually evolves and renders today’s
notion of ‘perfection’ in articial intelligence outdated in the future; (4) Ethical considerations, as the
denition of AI perfection may hinge on ethical and moral values, adding a subjective dimension to the
concept. What is ‘perfect’ for one person or group may be unacceptable for another. Instead of pursuing
complete perfection, a better approach to AI development may be to create systems that are highly
efcient, safe, transparent, scalable, and capable of learning and adapting.
Establishing the Culpability of Articial Narrow Intelligence (ANI)
Culpability is a crucial element in the consideration of criminal offenses and is based on the internal
state of mind and intentions of the entity or person suspected of committing a crime. In many legal systems,
culpability is examined beforehand to either establish or exclude the responsibility of the accused for the
commission of the offense.
Given that Articial Narrow Intelligence (ANI) is a product of a material nature, it is, according to
Heidegger’s views, an ‘entity,’ it ‘is,’ and thus represents an entity with its ontological being (see more:
Hajdeger, 2000). However, ANI lacks consciousness, free will, or the ability to possess logos that would
enable it to differentiate between right and wrong and good and bad. This ability to distinguish relies on the
power of reason and cognition. Since ANI lacks consciousness and reason, it cannot possess ‘intent’ as a
crucial condition for the existence of the ‘guilty party’ in humans. When the possibility of ANI’s culpability
is compared to the possibility of human culpability, the notion of culpability, as a possible psychological
or subjective element of ANI’s criminal offense, operates differently. ANI is developed to perform specic
tasks, basing its decisions and actions on algorithms, data, and programming provided by its creators.
During the execution of tasks, ANI cannot comprehend moral and ethical concepts in the way that the
human mind does.
Legal regulation of new phenomena always poses challenges for lawmakers, regardless of the
branch of law. At this stage of societal development, problematic questions arise in the elds of articial
intelligence, ICT, robotics, and more. Scientic and technological progress brings not only benets but
also new dangers to humanity. The use of robots, non-biological neural networks, and articial intelligence
in everyday life was, until recently, perceived as something brilliant, unattainable, existing only in the
pages of books. Neural networks are actively employed in various elds of applied science, and literature
describes positive examples of the use of autonomous devices in medicine (Hamet and Tremblay, 2017).
ANI has long been causing harm to individuals and human communities, and someone should be
held accountable for that harm under the law. However, current legal regulations do not include elements
of criminal offenses related to socially dangerous acts committed using articial narrow intelligence (ANI).
Laws generally do not recognize ANI as a perpetrator of a criminal offense or a subject of criminal liability.
ANI is now capable of fully executing the objective side of a range of criminal offenses stipulated by criminal
law, and this range will expand in the future. Scientic papers demonstrate that ANI activities can pose a
public danger and harm all subjects protected by criminal and other legislation (Mosechkin, 2019). Since
ANI seeks to replicate human behavior and conduct, the substance of ANI’s guilt resembles the content
of intellectual and volitional elements of human activity. It is argued that articial intelligence cannot be
an independent subject of a criminal offense unless it is recognized as a personality (Mosechkin, 2019).
This is supported by the view that ANI ‘can function in ways that are far from what program creators could
have foreseen. To be sure, we might be able to say what the comprehensive goal of articial intelligence
was, but ANI may do things in ways that the creators of articial intelligence may not understand or cannot
anticipate’ (Bathaee, 2018).
Criminal Potential of the Dark Side of ANI
Dark articial intelligence is a general term encompassing any malicious and malevolent acts
that autonomous ANI systems can perform with the appropriate malicious inputs and evil, even criminal,
intentions of the architects or creators of ANI algorithms (biased data, unveried algorithms, etc.). The
range of possible scenarios for the criminal use of dark articial intelligence is vast and incredible, ranging
from economic fraud and privacy violations to severe forms of war crimes, including murders and the
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Research in Science, Engineering and Education (IJCRSEE), 11(3), 519-531.
extermination of parts of the human community, be it ‘hostile’ nations or ethnic or racial groups within
one’s own country. For example, money laundering, a very complex criminal offense that typically requires
a serious and organized criminal group (Bjelajac, 2011a), is something that AI can do in a fraction of a
second if instructed to do so. Modern technological systems used in nancial transactions have signicantly
eased the process of money laundering (see more: Bjelajac, 2011b), but when you add the computational
and analytical capabilities that AI possesses, it paints a very worrisome picture, and that is only one form
of criminal activity. Research papers differentiate direct and indirect criminal risks associated with the use
of ANI (see more: Begishev and Khisamova, 2018).
Scenarios of malicious activities of the dark side of ANI have the potential to become a reality given
existing malicious ANI applications, such as ‘smart dust’ and drones, facial recognition and surveillance,
fake news and bots, as well as the eavesdropping of smart devices (Minevich, 2020). Drones and armies
of smart dust can collaborate to destroy energy grids and smart infrastructure systems. Facial recognition
provides autonomous systems with the ability to detect and store millions of individual characteristics,
which, due to cloning and bots, can be used to create deeply compromising false images and videos. Smart
home devices raise privacy invasion to unacceptable levels, as IoT (The Internet of Things) technologies
serve as efcient channels for spying by domestic cybercriminals or foreign agents. Unbridled access of
articial intelligence to population surveillance will rapidly create human rights issues related to individual
personality and freedom (Minevich, 2020).
Several characteristics of ANI make it desirable for criminal use (Stevens, 2023):
1. Speed and Effectiveness: AI has the capability to swiftly process vast volumes of data and
perform tasks efciently, presenting the potential to automate fraudulent activities.
2. Anonymity: AI can be harnessed to carry out deceptive actions covertly, leaving minimal to no
traces.3. Evasion of Detection: AI can generate deceptive information that is challenging to identify as
false. 4. Personal Gain: Fraud frequently stems from the pursuit of nancial or other advantages through
deceitful means, and AI can be employed as a facilitative tool for such objectives.
5. Fabrication of False or Misleading Content: AI can be utilized to fabricate counterfeit websites,
social media accounts, or other online materials with the intent of deceiving individuals. This encompasses
the creation of ctitious reviews or manipulation of online ratings to mislead consumers.
6. Automation of Deception: AI can automate fraudulent or deceitful schemes, such as the mass
dissemination of deceptive emails aimed at persuading individuals to disclose sensitive information or
transfer money.
7. Phone Number or Email Address Spoong: AI can generate counterfeit phone numbers or email
addresses, crafted to mislead individuals into believing they are interacting with a legitimate entity.
8. Forging Counterfeit Documents: AI can be instrumental in producing spurious documents,
including contracts and invoices, designed to deceive users.
9. Enhanced Attack Sophistication: AI can elevate the complexity of cyberattacks, such as the
creation of more convincing phishing emails or the customization of attacks targeting specic organizations
(see more: Stevens, 2023).
Criminal Models
We differentiate criminal offenses related to Articial Narrow Intelligence (ANI) based on the level
of danger and the extent of harm that malicious or “dark” ANI can inict. This shifts the current paradigm
of risks associated with ANI and brings the most extreme and damaging forms of ANI closer to existential
threats (see more: Bjelajac, Filipović and Stošić, 2022), a realm that was until recently reserved for
more advanced forms of articial intelligence, such as Articial General Intelligence (AGI) and Articial
Superintelligence (ASI).
At the forefront is the use of ANI for military purposes (Price, Walker and Wiley, n.d). Overreliance
on machine learning algorithms that we employ to obtain better and quicker responses can swiftly lead to
catastrophic outcomes. “One concerning example of excessive dependence on ANI arises in the context
of war when articial intelligence is enabled to autonomously decide whom to kill or when to engage a
nuclear bomber, without human knowledge. A less alarming scenario arises when an autonomous ANI
system determines whom to hire or re. Relying on articial intelligence to solve existential questions
means the elimination of crucial human inputs from key decision-making processes, which can swiftly
lead to disaster and provoke concerns about the redundancy of humans in general. To mitigate this dark
side of AI, we must establish a legal imperative that requires humans to have the nal say in any outcome-
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seeking process” (Minevich, 2020).
History teaches us that the military and criminals are typically the rst to embrace all fatal
technologies, while other state and societal actors tend to react more slowly (Ovchinskiy, 2022). The
military initially recognized the role of “smart dust” by rmly embracing this technology in an attempt to
manipulate the will of citizens through the manufacturing of consciousness. The study of this technology
commenced as a spin-off of Project RAND, involving collaboration between the Douglas Aircraft Company
and the United States Air Force. Subsequently, DARPA (the Defense Advanced Research Projects
Agency), a research and development organization under the jurisdiction of the United States Department
of Defense, tasked with the development of cutting-edge technologies for military applications assumed a
leading role (Bjelajac and Filipović, 2019). This prioritization places the manufacturing of consciousness
as a secondary risk in the hierarchy of threats to human communities. The concept of global dominance,
embodied in the idea of a new world order, is designed in leading closed centers of economic and political
power and is implemented through the ruthless and aggressive actions of media imperialism with a
monopoly on broadcasting and the manufacturing of consciousness. A specter of media manipulation
circulates the planet today, threatening to erode the society we know and the essence of the human being.
By amalgamating Information and Communication Technologies (ICT) with Articial Narrow Intelligence
(ANI) systems designed for information collection, we observe a profound and irremediable deterioration
and disintegration of the modern societal fabric.
Theorists argue that “this represents a new power above the power of citizens to recognize and
understand this force” (Encensberger, 1980). ICT and smart dust permeate society, lling gaps, sowing
unrest, convincingly promising solutions, and order. “This new power is incorporated into journalism,
fashion, religious teachings, tourism, the education system... However, while the new technical instruments
are fervently discussed in isolation, the consciousness industry as a whole remains outside the visible
spectrum. The question of who is the master and who is the servant is not decided solely based on who
possesses capital, factories, and weapons but on who controls the consciousness of others.” It only takes
having access to ICT and ANI, sufcient nancial resources, and enough time, and you can shape the
opinions of thousands and millions of people (see more: Filipović, 2019).
Although, according to Gartner’s research (Verma, 2020), it will take over a decade for smart dust
to wreak havoc on human life, its signicant technological potential already appears frightening, raising
questions about privacy protection and the ethics of its application (Marr, 2018). The commercialization
of smart dust will only increase the volume of data collected by microsensors. It remains uncertain what
those deploying microscopic sensors will do with the data they collect. Scientists typically do not focus on
security while developing such devices, and security concerns are only addressed once the technology
hits the market, often too late to mitigate potential risks.
Statista provides a list of other common criminal activities that may be associated with ANI
(Petrosyan, 2023), on which we will elaborate further and expand it:
1. Fraud
Fraud executed by Articial Narrow Intelligence (ANI) represents a signicant problem in the
digital world. ANI can be programmed or trained for various forms of fraud that can cause harm to users,
organizations, and society as a whole. A review of fraud that ANI can execute includes:
- Phishing Attacks: ANI can generate fake emails, websites, or social media proles to impersonate
a trusted source like a bank or a well-known company. Such phishing attacks can lead users to disclose
personal or nancial information.
- Media Manipulation: ANI can manipulate audio, video, and textual content to create false
information, fake recordings, or audio clips for spreading disinformation or damaging the reputation of
individuals or organizations.
- Fake Reviews and Comments: ANI can automatically generate fake positive or negative product,
service, or content reviews on the internet, inuencing consumer decisions and harming a company’s
reputation.
- False Identity: ANI can be used for identity theft, creating fake social media proles or other
platform accounts.
- Financial Fraud: ANI can engage in various forms of nancial fraud, including impersonation
related to banks, investments, or cryptocurrencies. It can also execute fraud through market manipulation
and rapid algorithmic trading.
- Intellectual Property Theft: ANI can be employed for the theft of trade secrets, copyrights, or
patents through automated analysis and copying of information.
- Extortion: ANI can be used for extortion against individuals or organizations through threats,
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Research in Science, Engineering and Education (IJCRSEE), 11(3), 519-531.
false accusations, or the disclosure of sensitive information.
- System Compromise: ANI can hack computer systems, servers, or networks to cause harm,
steal information, or block data access.
2. Data Theft via ANI
In the digital age, data has become a valuable resource that is frequently stored, exchanged, and
processed through computer systems and the Internet. Despite efforts to secure data, data theft remains
a serious issue. In this context, ANI represents a sophisticated tool that can be used to execute various
forms of data theft. These include:
- Phishing Attacks: ANI can be programmed to automatically send thousands or even millions of
fake emails resembling ofcial messages from banks, companies, or organizations. These messages may
contain fake links to websites that appear authentic but are designed to collect sensitive user information
such as usernames, passwords, credit card numbers, and other personal data.
- Ransomware Attacks: ANI can be used for the rapid and widespread distribution of ransomware,
malicious software that encrypts data on a victim’s computer. Subsequently, assailants demand a ransom
in return for the decryption key.
- Cryptocurrency Theft: ANI can track cryptocurrency transactions and attempt to hack digital
wallets.
- Manipulation of Payment Systems: ANI can be programmed to execute payment system fraud,
such as false transactions or refunds that were never made.
- Theft of Trade Secrets: ANI can be used to monitor and steal trade secrets, which can have
signicant business and legal consequences.
- Impersonation: ANI can generate fake proles on social media to access user’s personal
information and use it for manipulation or spreading disinformation.
- Medical Data Theft: ANI can be utilized for stealing sensitive medical data, including medical
histories and patients’ personal information.
3. Abuse of Systems and Hacking
This set of criminal activities carried out by ANI poses a threat to cybersecurity. ANI can be
programmed to execute various forms of system abuse and hacking with the goal of gaining unauthorized
access to information, causing damage, or extortion. These actions include:
- Unauthorized Access: ANI can be programmed to automatically breach system security barriers,
such as passwords and authentication, to gain unauthorized access to computers, servers, or networks.
This can allow access to sensitive data or control over the system.
- Distribution of Malware: ANI can be used for the rapid distribution of malicious software (malware)
through various methods, including email, USB devices, or vulnerable network points. This malware can
cause damage, data theft, or block access to resources.
- DDoS Attacks: ANI can coordinate attacks aimed at overwhelming services and servers,
temporarily disabling access to websites or online services.
- Theft of Authentication Data: ANI can attempt to steal authentication data such as passwords,
PINs, or digital keys to gain access to user accounts or systems.
- Manipulation and Sabotage of Systems: ANI can be programmed to alter system settings, delete
data, or create chaos within a network.
- Theft of Information and Trade Secrets: ANI can continuously monitor and spy on activities within
a network to steal sensitive information, including trade secrets, intellectual property, or condential
documents.
- Brute Force Attacks: ANI can execute brute force attacks by attempting all possible password
combinations to gain access to accounts or systems.
- Zero-Day Vulnerabilities: ANI can be programmed to seek and exploit zero-day vulnerabilities in
software applications or operating systems before manufacturers release patches.
4. Market Manipulation by ANI
ANI can be utilized for various forms of market manipulation, including:
- Algorithmic Trading: ANI can be programmed to rapidly and automatically make trading
decisions based on market analysis and data. This process is referred to as high-frequency trading (HFT)
and can be used to execute a large number of trading operations in a very short time.
- Dissemination of Disinformation: ANI can be employed to spread false news or disinformation
through social media and websites. Such disinformation can inuence investment decisions and trigger
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sudden market price uctuations.
- Front Running: ANI can detect the trading orders of other market participants before they are
executed and quickly react to them. This enables manipulators to exploit information and secure prots or
prevent losses.
- Pump and Dump: ANI can be programmed to manipulate the prices of stocks or cryptocurrencies
by heavily promoting certain investments to attract investors and then selling those positions when the
prices rise.
- Flash Crashes: ANI can cause sudden market price drops by mass selling of stocks or other
nancial instruments, creating panic among investors and market instability.
- Scalping: ANI can be programmed to execute a large number of small trading operations to
generate prots based on small price differences.
5. Abuse of Personal Data by ANI
ANI can be programmed or used in various ways to illicitly collect, use, or distribute personal
data, which can bring serious consequences for individuals and their private information. These abusive
practices include:
- Personal Data Theft: ANI can be programmed to attempt unauthorized access to databases,
cloud storage, or other sources where personal data is stored in order to steal or retrieve it.
- Distribution of Personal Data: ANI can automatically distribute stolen personal data over the
internet or other communication channels. This data may be sold on illegal markets or used for other
malicious purposes.
- Impersonation: ANI can be used to impersonate individuals through social media, email, or
other communication platforms to gather personal information from individuals.
- Targeted Advertising: ANI can analyze users’ personal data to create proles and target them
with personalized advertising. This may involve tracking online activity, internet browsing, and other forms
of surveillance.
- Identity Theft: ANI can use stolen personal data to commit identity theft, open fake accounts, le
fraudulent credit requests, or engage in other forms of nancial fraud.
- Creation of Fake Proles: ANI can automatically create fake proles on social networking sites
or other online platforms using stolen personal data to manipulate or spread disinformation.
- Social Engineering: ANI can use stolen personality and habit data to create convincing social
engineering scenarios to deceive individuals or organizations.
6. Attacks on Infrastructure
ANI can be programmed or used for various types of attacks on infrastructure, and these attacks
can have serious consequences for society and security. These attacks may include:
- Attacks on Energy Infrastructure: ANI can be used to target energy systems, including power
grids and power plants. This can involve attacks on distribution systems, destabilizing power supply, or
even disabling energy facilities.
- Attacks on Transportation Infrastructure: ANI can be used to target transportation networks,
including trafc lights, airports, trains, and other systems. This can cause dangerous situations, delays,
and disruptions in trafc.
- Attacks on Water and Sewage Systems: ANI can cause issues in water and sewage systems,
including water supply disruptions or water contamination.
- Attacks on Communication Infrastructure: ANI can target communication networks, including
telecommunication centers and servers. This can lead to communication out-ages or denial of internet
access.
- Attacks on Industrial Control Systems: ANI can target Industrial Control Systems (ICS) that
manage critical facilities such as chemical or nuclear power plants. This can result in production disruptions
or even serious incidents.
- Sabotage of Autonomous Vehicles: In the context of autonomous vehicles, ANI can be used
to launch attacks on autonomous driving systems, including manipulating trafc signals, taking control of
autonomous vehicles, or even causing trafc accidents.
7. Trafc Incidents
Trafc incidents that can be caused by Articial Narrow Intelligence (ANI) are particularly relevant
in the context of autonomous vehicles and the use of ANI in trafc. While autonomous vehicles are
developed with the aim of improving road safety, there are several ways in which ANI can lead to trafc
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incidents:
- Technical Failures: ANI may experience technical failures or software errors that control
autonomous vehicles. This can lead to unexpected situations on the road, such as sudden stops or
inappropriate maneuvers.
- Environmental Perception Errors: ANI uses sensors such as radar, cameras, and LIDAR
to gather information about the environment. Perception errors, such as misinterpreting signs or other
vehicles, can lead to accidents.
- Decision-Making Errors: ANI makes decisions based on the analysis of environmental data.
Decision-making errors can result in dangerous situations, such as miscalculations of distances or the
speed of other vehicles.
- Attacks and Hacking: ANI vehicles can be targeted by hackers who attempt to take control of
the vehicles or make them unpredictable. This can lead to serious incidents.
- Social Engineering and Manipulation: ANI vehicles can be exposed to social engineering or
manipulation by malicious individuals who aim to cause incidents, for example, by placing obstacles on
the road or creating confusion for autonomous vehicles.
- Unforeseen Situations: ANI may struggle to deal with unforeseen situations, such as emergencies
on the road, adverse weather conditions, or other extreme circumstances.
8. Risk of Combining Different Forms of ANI
The combination of two or more forms of ANI designed to achieve individual goals can signicantly
increase the risk of ANI misuse and multiply the harm. Such combinations, individually harmless software,
can, when combined, create a jointly orchestrated virtual system designed for malicious intent and aimed
at harming people and achieving malicious or criminal objectives. Combining facial recognition software
and software controlling armed drones can have signicant implications and elevate the importance of
addressing numerous ethical and security concerns. In November of 2017, the Future of Life Institute
in California, which focuses on “ensuring that articial intelligence benets all of humanity,” released a
video depicting “slaughterbots.” In the video, small (ctional) drones utilized facial recognition systems
and armed drones to target and eliminate civilians (Proudfoot, 2018). The institute is partially funded by
Elon Musk, who thinks that AI is potentially “more dangerous than nuclear weapons” (Piquard, 2023). The
dystopian video ends with the chilling words of computer scientist Stuart Russell from Berkeley: “We have
the opportunity to prevent the future you just saw,” he says, “but the window for action is closing fast.”
The video was released in conjunction with the UN Convention on Certain Conventional Weapons in the
condence that the UN would decide to ban the development of lethal autonomous weapons (Bjelajac and
Filipović, 2021). Combining dedicated forms of ANI has other malicious combinations as well. Attackers
often use a combination of malware and phishing techniques to deceive users into downloading and
installing malicious software on their devices. This can result in personal data theft, nancial harm, and
other unwanted consequences. The combination of ransomware (which encrypts data) and cryptojacking
techniques (which use the user’s computer resources for cryptocurrency mining) can harm individuals
and organizations. Botnets are combinations of software (bots) that run on infected computers and can
be used for large-scale DDoS attacks, spam distribution, or other malicious activities. Attackers may use
a combination of techniques like pharming and DNS spoong to redirect users to fake websites and steal
their credentials and personal information. Even three or more independent individual forms of ANI can
be integrated and complement each other to achieve various ethical or unethical, malicious objectives,
depending on needs and specic applications. Again, we start with the combination of multiple dedicated
ANI applications in the military and security services. ANI applications for satellite data analysis, combined
with facial recognition and speech analysis applications, can be used for military and security purposes,
including surveillance, intelligence gathering, and even assassinations of security-relevant individuals and
objects. ANI technologies can be combined and integrated for achieving other objectives that may not be
as destructive as military or intelligence but can harm individuals, organizations, and the community. The
combination of ANI for generating fake text, ANI for image manipulation, and ANI for sentiment analysis
can be used to create and spread disinformation and fake news to manipulate public opinion or cause
confusion. Integrating ANI for facial recognition, ANI for natural language processing, and ANI for biometric
data recognition can be used for illegal tracking and hacking of individuals for identity theft, extortion, or
other unethical purposes. Using ANI in cyberattacks to bring down websites, infect computers, or steal
sensitive data can cause signicant harm to individuals, organizations, or countries. Integrating ANI for
data analysis and ANI for decision-making can result in systems that discriminate against certain groups
of people in areas like employment or lending, which is unethical and against equality laws. Such unethical
and criminal uses of ANI pose serious threats and challenges to society. Therefore, it is essential to have
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Bjelajac, Ž., Filipović, A., & Stošić, L. (2023). Can AI be evil: The criminal capacities of ANI, International Journal of Cognitive
Research in Science, Engineering and Education (IJCRSEE), 11(3), 519-531.
responsible usage and oversight of these technologies to prevent potential abuses and ensure the ethical
use of ANI. Regulations and laws have a crucial role in preventing the unethical use of technology, but
the responsibility of technology companies and citizens is also necessary in promoting ethical principles.
Strategies to Combat the Dark Side of ANI
Throughout this paper, we have compellingly illustrated that articial narrow intelligence can indeed
present a substantial threat to human society. Under certain catastrophic conditions, it can even put
humanity at existential risk, and its misuse by malicious individuals or groups can lead to severe threats to
“life as we know it.” Despite philosophical uncertainties, these ndings should be sufcient to acknowledge
that ANI can be a malevolent entity and a dangerous machine, particularly when controlled by malicious
individuals or groups. In this section, we will outline basic methods and strategies for countering the dark
side of ANI.
The United Nations, the World Economic Forum, the UNICRI, the Center for AI and Robotics, G20,
and the OECD have initiated efforts against dark ANI. Companies like Microsoft have helped mobilize the
masses in the ght against dark ANI through a set of AI principles instrumental in dening a workplace
code of conduct surrounding responsible AI. Microsoft’s AI principles include fairness, reliability, safety,
privacy, inclusivity, transparency, and accountability. All of the above principles have contributed to the
formation of a modern movement determined to combat AI. A socially-driven campaign against autonomous
systems was launched through attempts to eliminate public facial recognition, ban drone surveillance, and
emphasize responsibility, accountability, and ethics in all AI frameworks.
On the front lines of combating dark autonomous systems, the UN Ofce for Disarmament
Affairs (ODA) has been expanded to include the threat of armed articial intelligence, and in 2018, the
Secretary-General of ODA submitted a plan entitled “Disarmament for Future Generations” dedicated to
suppressing dark articial intelligence in the years to come. UNICRI has also taken measures to work with
AI and global law enforcement agencies in an attempt to shut down support for AI in human trafcking,
corruption, terrorism, and crime. The U.S. government has shown commitment to building safer AI by
issuing a memorandum to federal departments and agencies stating ten AI principles and placing a
strong emphasis on public-private transparency for autonomous systems. G20 and the OECD have also
set specic goals for combating dark AI through ethical autonomous systemic frameworks that prioritize
responsibility and public trust.
Ethical standards for AI are essential to counter “dark ANI.” The current situation is not favorable.
When considering the use of ANI for military purposes or to subjugate the human population to global
interests, there is currently no effective defense. The commissioners of malicious technologies and dark
algorithms are states and their security agencies. In situations similar to the use of nuclear energy or
biohazard agents, the current solution appears to be a balance of power that exists between major military
and economic powers. This is where we should call for the consideration of an initiative to establish a UN
Ofce for Articial Intelligence. The nal decision on whether to establish a UN agency for AI control should
be made by taking into account all pros and cons, through broad international debate and collaboration.
Regardless of whether such an agency exists, it is crucial for the international community of leaders,
scientists, and experts to work together to develop and implement responsible regulations and guidelines
for AI to ensure its safe and ethical use. Without this, the aspiration to build impartial autonomous systems
and maintain ethical standards of accountability and privacy for ANI is challenging.
The potential impact of ANI on the development of AGI?
Following the course of each, or at least the majority, of inventions in history, ANI is expected
to be a precursor to more complex forms of Articial Intelligence. In this analogy, AGI should base its
development on the achieved level of ANI, taking from it, like an imago from a chrysalis, all achievements,
identifying and correcting all the limitations that ANI has. Based on this premise, the development of AGI
should, in the coming decades, eliminate and surpass the limits of ANI and continue to evolve, striving to
reach the intellectual level of humans and the thinking process of their cerebrum as quickly as possible.
But is it really so, and does the path of development, improvement, and enhancement of ANI represent a
dead end for the creators of AGI, and especially the ultimate gain, ASI?
Opinions are divided from optimism and excitement to concerns “that the hottest and most modern
branch of articial intelligence - machine learning - will degrade our science and destroy our ethics by
using fundamentally awed concepts of language and knowledge” (Chomsky, Roberts and Watumull,
2023). In other words, it could happen that the concept of ANI, no matter how perfected, may not be able
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Bjelajac, Ž., Filipović, A., & Stošić, L. (2023). Can AI be evil: The criminal capacities of ANI, International Journal of Cognitive
Research in Science, Engineering and Education (IJCRSEE), 11(3), 519-531.
to serve as the foundation for the development of AGI, precisely because of its primitive fundamental
concept that may prove inapplicable for AGI and ASI. Programs classied as ANI and already referred
to as “rst beacons on the horizon of the long-anticipated advent of articial general intelligence” are not
particularly intelligent. They process vast amounts of data, seek patterns in them, and become adept at
generating statistically probable results, such as human language and thought. However useful these
programs may be in certain narrow areas, from linguistics and the philosophy of knowledge, we know
how far they are from the way humans think and communicate (Chomsky, Roberts and Watumull, 2023).
Unlike ANI, the human mind, which AGI aims to reach and ASI aims to far surpass, is not a clumsy
statistical machine that absorbs hundreds of thousands of terabytes of data and costs (will cost) hundreds
of billions of dollars just to arrive at the most probable answer to a trivial question. The human mind is a
surprisingly efcient and elegant system for working with small amounts of information. It does not seek
to build rough correlations between specic inputs but rather to provide explanations. Jeffrey Watumull
argues that ANI programs are “stuck in the pre-human or non-human phase of cognitive evolution. Their
deepest aw is the lack of the central critical ability of any intellect: to say not only what is, what has been,
and what will be but also what is not, what could be, and what cannot be. These are the ingredients of
explanation, the hallmarks of true intelligence” (Chomsky, Roberts and Watumull, 2023).
Although the development and general concept of AGI cannot directly and simply continue from the
achieved level of ANI, ANI will nevertheless leave a signicant corpus of its achievements as a legacy to
higher forms of AI. Despite the ontological difference between the two AI systems, higher forms of AI will
not abandon advanced deep learning algorithms, nor will they ignore the massive datasets already stored
by ANI systems, even if they are stored only for a specic task. AGI will be intelligent enough to use that
data for other purposes. The vast experience ANI programs will gain by answering millions of questions
and solving millions of operational requests could be the virtual counterpart of the collective unconscious
in humans, as the total record of the quantum of knowledge acquired by all people who have ever lived
on the planet. AGI will be intelligent enough to unlock the treasures of that virtual collective unconscious
acquired through the use of ANI.
While in its responses to queries it cannot execute, ANI politely responds with learned phrases,
uncomfortably, even foolishly ignoring the client for whom it exists, ANI is not aware of the limitations it has.
Noam Chomsky and Ian Roberts write how ANI foolishly “demonstrates the ‘banality of evil’” (Smirnova,
2023). It is assumed that AGI, self-constituting its strategy, will use the experiences of ANI to identify,
understand, and overcome the limitations that ANI has failed to overcome.
We are witnessing serious and competent debates “for and against” AI. This is partly because AI is
a new technology that people fear simply because it is new and changes their usual way of life. However,
despite objections, ANI systems are becoming widely accepted and useful, which could lead people in the
future to be more open to higher forms of AI. Higher forms of AI should be able to act on ethical principles,
whether they be deontological or teleological moral principles. Experiences with ANI are completely
useless in this area because all known forms of ANI are not able to understand or balance creativity and
ethical constraints on their own, not even able to distinguish possible from impossible, which is not a good
recommendation for higher forms of AI. The amorality, pseudoscience, and linguistic inadequacy of ANI
make it either excessively produce both truths and lies, equally support ethical and unethical decisions or
avoid making decisions and remain indifferent to the consequences of such attitudes. Given the amorality,
pseudoscience, and linguistic simplicity of ANI systems, we can only mock or mourn their popularity
(Chomsky, Roberts and Watumull, 2023).
Discussion
In the previous chapters, we explored the concept of “evil” in the context of Narrow Articial
Intelligence (ANI) or articial intelligence (AI) in general. While ANI itself lacks consciousness or free will,
its potential for misuse or harmful actions that usually result in damage and suffering to humans poses a
signicant ethical and legal challenge. In this chapter, we continue our analysis and discuss fundamental
aspects of this controversial issue. Everything that happens on Earth is caused by either nature or people.
Therefore, the crucial aspect of the potential “evil” in ANI comes from human decisions and intentions.
ANI systems are inert and perform tasks according to their programming or training on examples and data
presented to them during software development and subsequent testing. Any negative consequences of
ANI can mostly be attributed to human decisions. This includes programming ANI algorithms, training
models with biased or incomplete data, and decisions about the use of ANI in specic contexts.
To understand and control the potential for “evil” use of ANI, it is important to analyze the role of
programmers, engineers, and other AI industry professionals. Programmers have a signicant inuence on
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how ANI behaves, even though they are often unaware of all the implications of their decisions. Therefore,
it is essential to educate programmers and engineers about the ethical aspects of ANI and provide them
with tools to identify and address potential issues.
One of the common ethical challenges related to ANI is bias and discrimination in software designed
to make decisions and perform tasks without human verication. ANI systems can inherit biases present
in the data sets provided to them by administrators. This can result in unfair decisions, discrimination,
and imbalances in the treatment of different groups of people. Research has shown that, despite the
fact that AI’s abilities in processing data far exceed human capabilities in terms of speed and volume,
ANI cannot always be trusted as fair and neutral. The underlying cause of ANI bias is linked to historical
human prejudices (Lifshitz, 2021). Human biases are deeply ingrained and extend to certain groups of
people, and these biases can be reinforced within computer models. AI systems, therefore, perpetuate
existing biases in elds including healthcare, criminal justice, and education. Cases like those of the
COMPAS algorithm (Correctional Offender Management Proling for Alternative Sanctions) in the United
States, which is more likely to arrest black individuals due to historical racism and differences in policing
practices, highlight the need for more consistent regulation and ethical guidelines for the development and
use of ANI, especially in sensitive sectors like security and justice (see more: Bjelajac and Filipović, 2021).
Another crucial aspect of the discussion about the potential “evil” use of ANI is the autonomous
nature of some ANI systems. Autonomous military drones can be programmed to execute destructive tasks
without human intervention. This raises profound ethical and moral questions in the military application of
ANI. To limit the potential abuse of autonomous AI systems, clear ethical guidelines and regulations are
needed in the military sector. These guidelines should dene the boundaries of autonomous ANI operations
and ensure that human responsibility and oversight are preserved. However, this will likely remain mostly
declarative, as the military, by default, acts against enemies in warfare, and in such contexts, rules and
laws have limited applicability.
One of the key elements in preventing the potential “evil” use of ANI is transparency. Organizations
developing ANI systems should be transparent about how they trained models and what data was used.
This allows independent experts and organizations to audit and assess ANI systems to ensure they
do not contain biases or malicious intentions. Additionally, it is important to establish mechanisms of
accountability for AI systems. If irregularities or harm arise from the use of ANI, responsible parties,
whether they are programmers, organizations, or owners of ANI systems, should face consequences.
This involves the establishment of clear regulations and laws dening responsibility in case of issues with
ANI systems.
The balance between progress and risk is often cited as the most important dilemma of the future
of AI. People fear non-human entities that could get out of control and begin to act as superhumans.
This is where the story of freedom and free will, or moral good and moral evil, in the world of articial
intelligence begins. These two noumena are proportionally dependent. The more one grows, the other
diminishes (see more: Kant, 1981). Therefore, governments of major countries want to maximize control
over the development and implementation of articial intelligence. The fundamental thesis with which the
European Union approaches thinking about AI is: “We are building trust in articial intelligence, and that is
possible only if we are able to manage risks” (Riegert, 2021). ANI brings tremendous potential to address
complex problems and improve human lives. In medicine, science, transportation, and many other areas,
ANI has the ability to accelerate progress and make daily life easier for people. Hence, the challenge
lies in nding a balance between the potential for positive impact of ANI and the need to limit its negative
consequences.
Conclusions
Without diminishing the manifold advantages ushered in by contemporary technologies, the scientic
community, with the exception of a substantial cohort encompassing roboticists, electronics specialists,
and similar domains, is not reticent in expressing deep-seated apprehension concerning the burgeoning
development of articial intelligence (AI) and its escalating foray into pivotal sectors of public and private
life. The deployment of systems founded on deep learning and self-learning neural networks, coupled with
the utilization of machines that, on numerous occasions, outpace human counterparts in data analysis
and expeditious decision-making, has led to concerns articulated by scientists, humanists, and futurists.
Over time, these technologies are not merely poised to displace human labor in many employment sectors
but also possess the potential to predict human consumer inclinations, modus operandi, communication
patterns, and even exert inuence over individual destinies, thereby encroaching upon the sacrosanct
citadel of privacy.
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Bjelajac, Ž., Filipović, A., & Stošić, L. (2023). Can AI be evil: The criminal capacities of ANI, International Journal of Cognitive
Research in Science, Engineering and Education (IJCRSEE), 11(3), 519-531.
Scientists posit that the concentration of metadata, power, and afuence in the hands of a select
few has the capacity to obfuscate and render the entire sociotechnical system non-transparent and
“opaque.” This eventuality is unequivocally predicted to give rise to heightened sociopolitical schisms
and to exacerbate, potentially leading to a draconian breach of democratic rights and personal freedoms
for both citizens and nations (Couldry and Meijas, 2019). Acknowledging that contemporary humanity, at
this stage of its historical progression, evinces a predilection for the encapsulation of its essence within
the realm of technology, scientists, particularly those within the domains of philosophy, sociology, and
theology, evince reluctance in relegating the stewardship of AI ethics to engineers and technicians. The
skepticism directed towards emerging technologies, particularly cognitive AI, can be expounded upon by
recourse to the prevailing societal concept of scientic neutrality, while differentiating the jurisdictions of
the scientic and legal spheres. It is our contention that the world is on the cusp of an academic schism,
a tug-of-war between champions of raw power and proponents of global security and the preservation
of “life as we know it.” This would not mark the inception of such a schism but would be resolved as in
instances past—with the facile triumph of power’s apologists. The conventional narrative dictates that this
innocuous dominion is destined to expeditiously metamorphose into nancial and military might. This is
not indicative of the world teetering on the precipice of dissolution; it serves as a clarion call for judiciously
overseeing the use, and potential abuse, of AI. History has persistently underscored that behind every
perilous contraption lurks an equally pernicious human agent. Our elucidation of this ethical aporia can be
attributed to divergent interpretations regarding the core tenets of AI ethics. Practitioners from the realm
of the natural sciences are preoccupied with the transliteration of prevailing, and occasionally antiquated,
ethical paradigms into the vernacular of machinery. In contrast, philosophers, sociologists, humanists, and
theologians grapple with the very essence of AI ethics, which must undergo an evolution commensurate
with the assimilation into its ontological and metaphysical corpus of a conspicuous novelty—an articial
entity furnished with its heretofore alien concepts of good and evil. This nascent ethical framework shall be
denominated a biomimetic ethos, one that may be adjusted on the y by humans to conform to emerging
entities, as this novel ethical framework is co-created in tandem with these entities.
Articial intelligence steadfastly advances, and each new application of this technology offers a
novel aperture for autonomous systems to harness data to effect harmful outcomes. The promulgation
of legislation emphasizing responsibility, transparency in AI, mitigation of bias, and the comprehensive
implementation of ethical precepts is posited as an efcacious strategy for contending with the “dark
AI.” The urgency of addressing the darker facets of AI mounts with each passing second. The present
juncture, more than any other, underscores the need to glean instructive insights from humanity’s historical
missteps and prepare judiciously for the impending challenges.
Conict of interests
The authors declare no conict of interest.
Author Contributions
Conceptualization: Ž.B., A.F., and L.S; methodology: Ž.B.; resources: A.F. and L.S., supervision:
Ž.B.; writing—original draft preparation: Ž.B, A.F., and L.S.; writing—review and editing: Ž.B., A.F. and
L.S. All authors have read and agreed to the published version of the manuscript.
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