Open Access Research Article
ARTIFICAL INTELLIGENCE AND TECHNOLOGY IN ARMED CONFLICT (By-Gaurav Kumar Arya & Arti Chauhan)
Published Paper
Article Details
ARTIFICAL
INTELLIGENCE AND TECHNOLOGY IN ARMED CONFLICT
Abstract
Artificial
Intelligence (AI) will change various aspects of the Global Economy, Security,
Communications, and Transportation by altering humans work, communicate &
decision. Intelligent Technology will either team up with humans or replace it
in broad range of activities. Such Evolution will boost the social, economic,
and political influence with game-changing capabilities. AI has crucial
connection for the roles of humans, technology, and human-machine interactions
in armed conflict as there are new forms of information warfare, and military
decision automated processor. The AI is motivating Global powers to exercise
advanced technologies with the goal of establishing their dominance in the
global power play.
Superiority
of AI is the new power which can be seen in present as the United States is the
leading AI power, while China is emerging as an aspirant challenger and Russia
yet not managed to be a part of the top tier in AI, autonomy, and robotic. The
integration of AI with regular military operations upgrade technology,
administration, training, personal management and even routine activities or
exercises, it reduces institutional workload and free up warriors to focus on
core functions. Collaboration exercises include cross-domain autonomous
systems, cyber-enabled tactics, and adversarial scenarios, as well as new
capabilities and various organizations, such as NATO Science and Technology
Organization and centers of excellence, help spread knowledge, create
awareness, stimulate research and development support, and attract national
expertise.
Under
International Humanitarian Law should be interpreted and applied, As New AI
weapon systems creates risks of harm for those affected by armed conflict,
both civilians and combatants, as well as dangers of conflict escalation,
raises challenges for compliance with International law &
International humanitarian law as rules on the conduct of hostilities for the
protection of civilians, fundamental ethical concerns for humanity,
substituting human decisions about life and death with sensor, software and
machine processors.
Global
Competition, Armed Conflict, Ai Weapons & Types, Ethic & Laws,
International Organization
Introduction
The
AI (Artificial Intelligence) is the ability of machines to perform tasks that
normally require human intelligence as by this definition many were confused by
its simplicity as in many researches and text book the same definition were
used. The first note determine in mind that AI is an extremely broad filed
which not only cover the breakthrough of past few years but also appreciated
the first electronic computers back to the 1940s. The definition of Artificial
Intelligence is a bit of a moving approach, when something is new and exciting;
people always have no doubt about labeling it Artificial Intelligence. Once the
ability of a particular approaches AI are familiar & more often called
merely software.[3] The AI
is the advance technology which enhances the program from past technical life.
For Example in Medical field the AI helping in action by scanning vast numbers
of cancer cells from normal cells in biopsies. AI is helping us by applying
Science & technology to something that previously relied by the human eye
itself as in many cases from handwriting recognition to passing math problems,
AI has already proved more accurate answers than human experts given till now.[4]
Artificial
Intelligence Tasks
AI
systems are excellent at pattern recognition means they can quickly spot
anomalies & make quicker predictions often & consistently, more
accurately and which is reliable than humans as they use essentially
probability and logic to make their analysis. However the AI is today limited
to only that which lack the ability to understand or able to develop the broad
context that human can do which we could call as general intelligence is still
far from current technologies and may never by realized. They are based on
neural networks as modelled loosely on the human brain with many processing
elements that manage the flow of information between one to another. In
computer science AI is not a particular well-defined entity; instead it is
incorporates many capabilities, models and methods as there are three elements
in particular account.
MACHINE
LEARNING - It is a
techniques which work differently on different situation by types like
algorithms, reinforcement learning, rule-based machine learning and decision
trees which show that it conclude many ways of resolution from enable machine
to learn from data without being explicitly programmers for the task.
NEURAL
NETWORKS - a
computing model that arranges large numbers of processing nodes or elements,
from ten thousand to millions which linked by a larger number of connections,
in a way that bear a resemblance how neurons and synapses are arranged in the
human brain. The system does not come from the individual nodes themselves, it
use algorithms to carry out only simple tasks of forwarding information to
other nodes, but is derived from the layered architecture of the neural network
as a whole, which becomes adept at recognizing complex patterns.
DEEP
LEARNING – A machine learning
technique that exploits the architecture of a neural network with several
layers, some of them possibly specialized for certain characteristics and
patterns. For example, deep learning can be used to recognize a picture of a
cat as image recognition. A typical neural network is six to seven layers deep
while the number of layers in the most sophisticated networks now runs into the
hundreds of them. Neural networks look as individual pixels, while higher
levels identify elements like tail, paws and ears of cat and may be the cat
itself. The technique requires data and lots of work, but having been trained
by looking at thousands or millions times to the pictures, a neural network
becomes excellent at its task, even better than a human. The crucial thing is
that the system only required learning once. Once learned, the system’s
knowledge for example as how does cat look like, a size & color of packets,
security breach & how unhappy the customer look like can be transferred to
other applications, where this learned recognition can provide instant help in
making decisions or recommending intervention or resolution. It is also worth
noting that we often bundle other technologies, such as robotics, into the
similar conversation as AI because AI & robotics are such complementary
technologies, with AI enabling automated decisionmaker and robotics enabling
decisions to be fed into physical actions. For instance, autonomous
self-driving vehicles are the result of combining AI and robotics.[5]
Types Of
Artificial Intelligence
Although
at the moment AI focuses on many different tasks in smaller domains, the idea
of simulating the whole expectation is on human intelligence is still there. AI
systems generally divided into three main categories[6] :
• Artificial Narrow Intelligence (ANI) as
Specific Domain AI or (Weak AI): This type of AI is characterized by
specific domains for which a model can be structured based on rules or boundaries
by governing the domain. For example, now there is no longer difficultly to
have an AI which is excellent in chess and other games as we already put the
rules of the games describing chess or other similar game. AI systems can
master simultaneously such specific related domains or provide intelligent
solutions for that domain. This is often called smaller Intelligence or can say
Weak AI as the intelligence attained here is far from general human-level
intelligence and is only specific domain.
• Artificial
General Intelligence (AGI) as Strong AI: In this type of AI systems, the intelligence learned in same domain
which generalized to similar domains or an unrelated domain as human beings do.
For example, humans learn to walk on smooth surfaces. But this behavior, as we
grow, is generalized to walk on uneven terrains. Generalization in AI is very
important both for domain-specific tasks and also for reaching human level
intelligence. However, from history of AI work, the issue of generalization is proved
to be hard especially at a human level mindset. Therefore, such problems are
often named as hard AI or strong AI problems to differentiate it from
domain-specific AI (weak AI) with smaller intelligence.
• Artificial
Super Intelligence (ASI): In this
AI system machines are considered more intelligent than humans in every
different aspect. This is an imaginary thing that may be possible in future as
current state of AI such machines are not discovered or around yet. This
scenario also touches issues such as robots which can be said as artificially
intelligent machines which controlling the humans and the world of
self-replicating super intelligence
dominating
future civilizations. At this moment there is not enough evidence to support
this hypothetical situation. It is important to differentiate these AI terms
and approaches in order to understand the real ability of AI and the boundaries
of hype around AI.[7]
Global
Competition Of Ai Companies
These
competitions transparently show the benefit of economy, security,
communications, and transportation by altering humans work in the following:-
UNITED
STATES
Ø DATA ROBOT- it was founded in 2012 by
Jeremy Achin & Tom de Godoy which is a Data Robot or Data Science company
in Boston. This Company expert in allowing business analysts to build
predictive nature of programming to have a prior knowledge of Analytics. Data
Robot was used in Universities, Healthcare & Financial Services and it’s
valued at or over $6.3 billion.
Ø Cloud Minds- it was founded in California
by Bill Huang & Rober Zhang which begin the journey on 2015. These
companies are based in Beijing, China and California but operate across the
globe. Cloud Minds operates cloud systems for AI structured based robots which
focusing on machine analysis, intelligence and robotic control units. It is
been used in variety of industries such as health, finance and military.
Ø Clarifai- it is an artificial
intelligence company which known for its use of machine learning & neural
networks to analyses images and videos. This company was found by Matthew
Zeiler and now has over 90 employees and is valued at $120 million.
Ø Cognitive Scale- it was founded
by Matt Sanchez in 2013 which is known as leading products and technology
in Cognitive Scale. The company specializes in data interpretation and
machine learning systems in order to improve decision maker, customer
engagement, employee productivity & include clients, Morgan Stanley, Dell
and Under Armor.[8]
CHINA
Ø SENSE TIME- it’s funding of $1.6B
which Sense Time develops face recognition technology that can be applied to
payment by picture analysis, which can be used, for bank card verification and
security systems.
Ø MOMENTA- It’s Funding of $1.2B,
Momenta is a developer of autonomous driving technology designed to improve
efficiency.
Ø UBTECH- It’s Funding of $940M, UBTECH
Robotics dedicated to commercialize humanoid robot which making it walk out of
the research institution and become available to ordinary society people.
Ø MEGVII- It’s Funding of $607M, Megvii
develops Face Cognitive Services as a platform offering computer vision
technologies that enable your applications to read and understand the world
better. Its deep learning-based image analysis recognition technologies, with
simple and powerful APIs and SDKs.[9]
RUSSIA
Ø Iterative- its Funding of $25M,
Iterative is an open-source startup which is building an Enterprise AI platform
to help the companies operationalize their models Structure.
Ø NtechLab- its Funding of $16.5M which
develops software products using techniques in the fields of artificial neural
networks and machine analysis.
Ø Cognitive Technologies- Cognitive
Technologies is an explorer of AI-based driver assistance systems. This company
developed C-Pilot mode, an intelligent autonomous driving system that installed
in cars and other vehicles.
Ø Vision Labs its Funding of $ 5.5M,
which is a world-leading visual recognition company. Based on this technology,
are successfully united in banking, retail, security, video surveillance.[10]
JAPAN
Ø Preferred Networking- its Funding of
$129.9M, it develops technologies related to autonomous driving which connected
to cars. They also apply machine learning and deep learning to robotics, and
research and development of object recognition & control detection, and
optimization technology, medical picture such as CT scan and MRI scan, and
develop systems to allow diagnosis of cancer using blood samples.
Ø Cinnamon- it’s Funding of $17M, A AI
startup that develops products aimed at reducing the amount of time spend on
tiresome tasks. Its Flax Scanner takes lengthy documents and then extracts only
the most pertinent information, it give recommendations for applications such
as e-commerce or a recruiting platform, and a chat bot which can also process
natural languages.
Ø Leap Mind- its Funding of ¥1.5B, its
carrying out research on original chip architectures in order to implement
Neural Networks on a circuit with low power.
Ø Heroz- its Funding of ¥100M develops
media, mobile marketing and SNS services. It developed the most cutting edge
artificial intelligence, programed to play Japanese chess Shogi which defeated
an active professional player in a public match for the first time ever.[11]
INDIA
Ø Tata Elxsi- Self-driving cars and
video analytics by AI and knowledge analytics. Stock came back 174.89 per cent
to investors, whereas the smashing IT returned 106.55 per cent. concerning in
operation revenues, interest charges accounted for fewer than 1% of total
revenues within the financial year that over March 31, 2021
Ø Hieronymus Bosch- Bosch Center for AI
was supported in 2017 to facilitate this integration, and Bosch established the
groundwork for artificial intelligence to own a real-world impact through
advanced technologies. Bosch’s six analysis areas are distinguished in six
ways, all of that have attention on core AI technology.
Ø Kellton school- Kellton School
Solutions limited company was established in 1993 and currently features a
capitalization of Rs 712.75; Kellton School produces fashionable AI solutions
that change from machine learning to deep learning for things that have
historically needed a major quantity of human expertise. Throughout constant
time, the stock came back 40.86 per cent, while the smashing IT returned 106.55
per cent for investors.
Ø Zensar Technologies- for Zensar
Technologies, AI is that the most important factor (AI). Before this week,
Zensar declared the launch of the initial set of platforms for seven crucial
sectors, together with sales and marketing, data technology, human resources, talent
offer chains and human resource management.[12]
Artifical Intelligence Armed Conflict
Three
Conflict implications of AI and machine learning :-
v The primary space is that the use of
AI and machine learning tools to manage military hardware, specifically the
growing diversity of remote-controlled robotic systems – within the air, on
land, and at sea. AI might modify larger autonomy in robotic platforms, whether
or not armed or unarmed. For the ICRC, autonomous weapon systems are the
immediate concern, particularly for automatic target recognition may become a
basis for future autonomous weapon systems, amplifying core considerations
concerning loss of human control and unpredictability.
v The second space is that the
application of AI and machine learning to cyber warfare: AI-enabled cyber
capabilities could mechanically look for vulnerabilities to exploit, or at the
same time defend against cyber-attacks whereas launching counter-attacks, and
will thus increase the speed, range and kinds of attacks and their
consequences. These developments are relevant to discussions concerning the
potential human value of cyber warfare. These digital risks will create real
dangers for civilians.
v The third area, and also the one with
maybe the foremost sweeping implications, is that the use of AI and machine
learning systems for decision-making. AI might modify widespread assortment and
analysis of multiple knowledge sources to spot folks or objects assess
“patterns of life” or behavior, build recommendations for courses of action, or
make predictions about future actions or situations.[13]
Legislation
On Artificial Intelligence
The
Legislation is Concerns about potential misuse or unintended of AI, Moreover
they have prompted efforts on examination and developed standards, such as
the United State; National Institute of Standards and Technology (NIST)
which initiative involving in workshops and discussions with public and
private sectors around the development of federal structure to create building
blocks for reliable and trustworthy AI systems. State lawmakers also
considering AI’s benefits and challenges for upcoming growing number of
measures are being introduced to study which impact the use of AI or algorithms
and potential roles of policymakers. However the
General artificial intelligence bills were introduced at least 17 States
in 2021 and enacted in Colorado, Alabama and Mississippi.[14]
The
AI Regulations by European Commission published draft which gives regulations
of governing the use of artificial intelligence. AI Regulations are the first
attempt to the world has been seen at creating a uniform legal framework which
governing the use and development of marketing.[15]
1. Scope of Regulation
The
AI Regulations will apply to the following principles:
·
Both
Public and Private offering or putting into AI service systems within the EU
irrespective of whether the providers are situated inside the EU
·
AI
company users located in the EU
·
AI
provider and user located outside the EU as output produced by the system is
utilized within the EU.
2. Risk-based approach
In
its 2020, European Commission proposed AI ecosystem into two general
categories: high risk & low risk. The European Commission's new graded
system is more shade and likely to ensure more targeted, since the level of
conformity requirements matches the risk level of a specific use case.
The New AI Regulations follow a risk
approach and differentiate between the following:
·
Prohibited
AI systems and use is considered unacceptable and that contravene union values
which violating fundamental rights.
·
Those
which create a limited risk as risk of manipulation, use of chat bots.
·
Use
of AI that create minimal risk.
However,
makers of limited or minimal risk- AI systems will be encouraged to adopt
non-legally binding of conduct. The high risk uses will be subject to specific
regulatory requirements before and after launching into the market to ensuring
the quality of data sets used to train AI systems, applying a level of human
oversight, creating records to enable compliance checks and providing relevant
information to users.
3. Database
According
to the AI Regulations, European Commission will be responsible for maintaining
a database for high-risk AI practices (Article 60). The database will contain
all the data of AI systems which considered high-risk. To ensure transparency
must have all information processed in the database which will be accessible to
the public. Its remains to be seen that whether European Commission will extend
this database to low-risk and practices to increase transparency, enhance the
possibility of supervision that are not high-risk initially but may become so
at a later stage.
Employment-Specific Observations
1. High-Risk
·
AI
practices involve employment; worker management and access to self-employment
are considered high-risk which include the following AI systems:
·
AI
systems is for the recruitment or selection of natural persons which including advertising
vacancies, screening or filtering applications, and evaluating candidates in
the course of interviews or tests
·
AI
systems intended to make promotion and termination decisions, engage in task
allocation, and monitor and assess individuals' performance and behavior
2. Biases
In
AI Regulation the training validation & testing of data must be subjected
to appropriate data which govern & manage the practice and include the
possible biases with continuously learning high-risk, it will ensure that biased
outputs are equipped with proper mitigation measure as input in future
operation. However the benchmark will be equality in opportunity & outcomes
companies should have to consider that which system affect individual with
disabilities or intersection of multiple social groups.
3. Special categories of personal data
to mitigate biases is permissible
If
there is strictly necessary to ensure bias monitoring, detection and correction
then AI providers have to process special categories of personal data. However
the personal data are still subject to safeguard of fundamental right and
freedom of person as privacy preserving measure must be in mind.it remains to
be seen whether individuals will sufficiently trust these systems to provide
them with their sensitive personal data.
4. Human oversight
·
High-risk
AI systems must be capability of human oversight.
·
Have
a complete understanding of the capacities and limitations of the high-risk AI
duly monitor its operation like nomalies, malfunctions and unexpected performance.
·
Remain
vigilant against the tendency to rely automatically as automation bias.
·
Able
to correctly interpret the output from a high-risk AI system, system's
characteristics, interpretation tools and available methods.
·
Must
be deciding if override or reverse the output of the high-risk AI system if
necessary.
·
Must
be capable of intervening or interrupting the operation of the high-risk AI
system through a "stop" button or a similar procedure.
·
As
indicated in our recent Trust Continuum report, this will require substantial
involvement from the human decision-maker, which proves to be challenging for
most companies.
Organizations
UNITED
NATIONS (UN)
The
United Nations chief of has called on member states to put a ban on the sale
& use of artificial intelligence
systems until the negative and even catastrophic risks they create can be
addressed. This remark was given by U.N. High Commissioner of Human Rights by
Michelle Bachelet in which a new report on the subject released in Geneva. This
report warned the AI use as forecasting & profiling tools, technology could
have an impact on Right to Privacy as major concern of the countries and the
people which include confidential documents too and freedom from arbitrary
arrest and detention and Right to Life also been violated.
There
are Reports which reveals that widespread use of spyware known as Pegasus to be
target thousands of phone number and dozens of device which belonging to
international journalists, human rights activists and head of State. AI can be
implement for good, helping societies for overcomes from challenge of our time,
as it suggest that it could bring outweigh the positives but also incompatible
with unprecedented level of surveillance across the globe by State and Private
Groups. By the release of the reports Tim Engelhardt the UNHRC human right
officer which purview rule of law and democracy section called that AI dire and
said it has not improved over the years and has become worse rather than good.[16]
HUMANITARIAN
ORGANIZATIONS
AI
and Machine Learning might be useful for humanitarian action as by ICRC which
likely to be very broad nature by explored by humanitarian organization for
scanning environment, monitoring and analysis of public source of data in
specific operational contexts. In this application can help to inform
assessments of humanitarian needs as type of assistance needed like food,
water, shelter, economic, health and where it is need. Similar use of the AI
data for help to understand humanitarian consequence on the ground which
include civilian protection, by image, video and other pattern analysis the
access to the damage to civilian infrastructure, population displacement,
viability of food crops, weapons contamination as these might also be used to
analyze by image and video in order to detect and assess the conduct of
hostilities and other consequence in the future. ICRC has developed environment
scanning dashboard using AI and machine which capture and analyze large volume
of data which inform and support to its humanitarian needs.
A
wide range of Humanitarian service could be benefit from the application of AI
and Technology by learning tools for specific tasks. For example identification
of the missing person by AI based facial recognition and can match the name by
natural language. The ICRC has been exploring and use the technologies to
support the Central Tracing Agency to reuniting family members which separated
by the Armed Conflict. It also exploring the benefit of AI and technology by
learning base image and pattern recognition for satellite imagery, whether to
map population density in support of infrastructure assistance project in urban
areas and to protection the civilian by complement its documentation of respect
for international humanitarian law.[17]
International
Committee Of The Red Cross (ICRC)
There
must be once significant application for the use of digital AI and Technology
learning to control physical and military hardware, as in particular increase
the bunch of unmanned robotic system in the air, land and sea with wide range
of size and functions, it may enable the increases in autonomy in these robotic
platform as whether armed or unarmed must be controlling the whole system of
specific functions as flight, navigation, surveillance or targeting. The ICRC
autonomous weapon systems in their critical function of selecting and attacking
the targets as most immediate concern of the humanitarian, legal and ethical
aspects which gives risk of loss of human control over weapons and use of the
force by the countries or by militaries. Loss of control raise risk of civilian
lives because unpredictable consequence must be a legal question because
combatants must make context specific judgement in carrying out attacks under
International humanitarian law and ethical concerns, as human agency on
decision of use of force is necessary to uphold moral responsibility and human
dignity. These reasons ICRC has been urging States to identify practical
elements of human control as the basis for internationally agreed limits on autonomy
in weapon systems with a focus.
The
most important to recognize that not all the autonomous weapons are incorporate
with AI and technologies as their existing weapons with autonomy in their
critical functions such as air-defense with modes on rule based, control
software to select and attack the targets. However the AI and technology
learning software as automatic target recognition is the form of future
autonomous weapons system which bring new dimension of unpredictability of
weapons as well as concern about lack of ability and bias and at the same type
of software might also be used in decision support application for targeting
rather than directly controlling the weapons system.[18]
Organisation
For Economic Co-Operation & Development (OECD)
v Its Principles promote use of AI that
is innovative and trustworthy and that respects human rights and democratic
values. Adopted in May 2019, they set standards for AI that is practical and
flexible enough to stand the test of time.
v The Government and developing
countries with their stake holders must cooperate to advance the principle of
progress on responsible stewardship of trustworthy AI.
v The Government, OECD and other global
and regional for a to foster must share AI knowledge as appropriate to
encourage international cross-sectoral and open multi-stakeholder initiative on
long term expertise on AI.
v Government should promote, encourage
and developed the multi-stakeholder, consensus driven global technical
standards for operable and trustworthy AI.
v Government Compare the metrics to
measure AI research for development and deployment and progress in the
implementation of these principles by gather evidence base of assess progress.
United
Nations Educational, Scientific & Cultural Organization
(UNESCO)
The
world must ensure that new technologies, based on AI, are used for the good of
our societies and their sustainable development. It should regulate AI
developments so that they conform to the fundamental rights that frame our
democratic horizon. Many businesses, Research Centre, science academies, United
Nations Member States, international organizations and civil society
associations are calling for an ethical framework for AI development. While
there is a growing of the issues, related initiatives need more robust
coordination, this issue is global, and reflection on it must take place at the
global level so as to avoid a pick & choose approach to ethics.
Furthermore, global approach, with the participation of United Nations funds,
agencies and programmers, is required to find ways of harnessing AI for
sustainable development.
UNESCO
will be an active participant in this global conversation. This organization
has many years of experience in the ethics of science and technology. Our
advisory bodies have produced numerous reports and declarations on robotics, as
the Report of the World Commission on the Ethics of Scientific Knowledge and
Technology on Robotics Ethics in 2017. The advisory bodies have experience in
developing normative instruments, including the Universal Declaration on the
Human Genome and Human Rights in 1997 and the Universal Declaration on
Bioethics and Human Rights in 2005. It is essential to ensure that a weaker
country fully participates in transformations related to AI for contributing
directly to its development. We must empower young people by providing them
with the skills they need for life in the twenty-first century for integration
in a changing Labor market. UNESCO, as a universal forum where everyone’s voice
is heard and respected, is performing its role to the fullest, informing the
global debate on the major transformations of our time while establishing
principles to ensure
that
technological advances are used to serve the common good.[19]
Conclusion
AI
is at the Centre of a new enterprise to build computational models of
intelligence. The main assumption is that intelligence (human or otherwise) can
be represented in terms of symbol structures and symbolic operations which can
be programmed in a digital computer. AI researchers need not wait for the
conclusion to that debate, or for the hypothetical computer that could model
all of human intelligence. Aspects of intelligent behavior, such as solving
problems, making inferences, learning, and understanding language, have already
been coded as computer programs, and within very limited domains, such as
identifying diseases of Cancer cells, AI programs can outperform human experts.
As the AI is a beneficial source of asset but if it is implemented at the war
or for Armed Conflict then many people would sacrifice with their life as to
protect from the armed conflict must have an advance AI & New laws for the
artificial intelligence for the Citizens protection & their properties to
create a better future with International Principles of Human Rights.
Article Information
ARTIFICAL INTELLIGENCE AND TECHNOLOGY IN ARMED CONFLICT (By-Gaurav Kumar Arya & Arti Chauhan)
Author Name: Gaurav Kumar Arya & Arti Chauhan
Title: ARTIFICAL INTELLIGENCE AND TECHNOLOGY IN ARMED CONFLICT
Email Id: Gaurav Kumar Arya-gaurav.arya949@gmail.com & Arti Chauhan-artichauhan1200@gmail.com
- Journal IJLRA
- ISSN 2582-6433
- Published 2022/07/06
About Journal
International Journal for Legal Research and Analysis
- Abbreviation IJLRA
- ISSN 2582-6433
- Access Open Access
- License CC 4.0
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