Artificial Intelligence in Human-Computer Interaction Report

This report provides an overview of Artificial Intelligence (AI) in Human-Computer Interaction (HCI). It explores the intersection of AI and HCI, detailing the advantages and disadvantages of AI implementation. The report highlights various applications of AI, including Natural Language Processing (NLP), computer vision, and gesture-based systems. It discusses the transformation of HCI through AI, focusing on conversational systems like Alexa and gesture-based interfaces. The role of AI in defense and transportation is also examined. The report covers advancements in eye tracking, cashierless stores, and the potential of neurotechnology. Finally, the report concludes with a summary of the benefits and challenges of AI in HCI, offering insights into its future impact on human-computer interactions.

Running head: ARTIFICIAL INTELLIGENCE
ARTIFICIAL INTELLIGENCE
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Abstract
This report aims to discuss about Artificial intelligence in HCI or Human Computer
Interaction. The advantages and the disadvantages about of artificial intelligence is briefly
discussed in this report. The various fields where the implementation of artificial intelligence
has provided additional opportunities have been discussed in this report. The AI or Artificial
Intelligence is the sector of computer science that focuses on the production of machines that
are intelligent and these machines can react and work like human beings. The major activities
that can be performed by AI machines are speech recognition and learning. This report
concludes with an appropriate conclusion for the report.

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Introduction
The aim of this report is to discuss about Artificial Intelligence and the application
areas. The benefits and the challenges of the implementation of Artificial Intelligence is
briefly stated in this report. Several areas where the implementation of artificial intelligence
has proven to be advantageous are provided in this report. Lastly, this report concludes with
an appropriate conclusion for this report.
AI or Artificial Intelligence is commonly called as machine intelligence, which means
the intelligence that is presented by machines that is different from the intelligence presented
by humans. The communities of AI and the HCI are commonly characterised as consisting of
several views that are opposing of the methods of interaction among computers and humans.
As the development of HCI and AI increases, there is certainly a division among these
communities. The field of HCI or Human Computer Interaction is the field that researches the
designing and the utilisation of the technology of computer by focusing on the interfaces
among the computers and the users. Several researchers in the HCI field have concluded that
the implementation of artificial intelligence in the HCI can help humans achieve greater goals
in less time (Cohen & Feigenbaum, 2014).
Discussion
A common AI studies the environment and then takes the required actions that helps
in increasing the chances of successful achieving the goals. The intent of an AI along with the
goal function can be simple or complex. The determining of the goals can be done explicitly
or it can be also induced. If the programming of the AI is done for the reinforcement learning,
there is an opportunity of implicitly inducing the goals for the rewarding various kinds of
behaviours and also punishing others.

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Methods by which HCI is getting transformed by Artificial Intelligence
The increasing advancements in the technology has impacted in the creation of better
relationships among the computer interactions and humans. These fields are coming together
and the bridging of the gap has been done by the keyboards and touch screens. The aspect of
Artificial Intelligence is major breakthrough that has impacted the life of humans. The main
part of artificial intelligence is the NLP or Natural Language Processing. There is a decrease
in the requirement of commands of voice with rigidity and interfaces that are less user
friendly. The results of Google searches have been improved with the implementation of NLP
and this has also helped in the improvement of the authentication of two factor that is also
referred and 2FA. Apart from the artificial intelligence of google normal search, the quality
and popularity of the voice search has improved. The introduction of chatbots that are
empowered with the artificial intelligence is additional important discovery that is improving
the computer interactions and humans (Wenger, 2014).
Another breakthrough discovery is the computer vision combined with artificial
intelligence. The field of eye tracking is the most benefitted from the implementation of
artificial intelligence. The measurement and the understanding of the movements of the
activities of the gaze of humans is done with this technology that is highly advanced. The
availability of this technology is made easier with artificial intelligence, that was restricted
earlier to the labs of research, by owing the cost to which it is associated. With the addition of
artificial intelligence in the computer vision, the efficiency and the pocket friendly nature of
the eye tracking has increased. This technology has provided the possibility of new
discoveries with the tracking of eye (Bond & Gasser, 2014).
The technology has proved to be advantageous to several domains that includes the
research in marketing, gaming and virtual reality. The major benefit of eye tracking is the
enabling of the human interactions of an individual who have disabilities with a computer

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system. This has been successful with the gaze keyboards and the eye tracking comprising in
the panels. The technology of computer vision has provided the advancement of the
interaction with several customers that has been made successful with the hand gestures with
the elimination of the props use and the controllers. The technology of artificial intelligence
has created this possibility of with the computer vision that the vision of humans are easily
interpreted by the computer systems and there is no requirement of active involvement. The
best example of this technology is the introduction smart vehicles, which has the ability of
interpreting the state of the driver, such as whether the driven has fallen asleep or not and
whether the driver is distracted or not. With the help of AI, the software can interpret the
expressions on the face and the react according to the needs. The technology has also helped
Amazon in the implementation of cashierless stores all over the world.
The aspect of neurotechnology that can be only seen in the movies can also become
possible with the help of artificial intelligence. Several efforts have been made by Facebook,
where there the company is trying a establishment of a relation among the human brain in a
manner which can provide that ability of typing hundred of words with the utilisation brain in
a short duration of time (Zang et al., 2015).
Pointing devices like mouse and the touchscreen and keyboards are the major
components of human computer interaction. By the introduction of AI in the recent times, it
is considered that the importance of text and touch will disappear.
The communication among the humans are majorly natural that consists of hand
gestures and speech. These methods of communication are considered to be complex and the
modalities that are complex can provide complementary methods of conveying information
with the addition of richer context and effectively than the methods that are simple and
unimodal. The utilisation of the channels that are complex and multimodal are not used until

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now in the applications of enterprise software. With the implementation of AI in the
enterprises, the systems are now powered speech based and gesture based, that helps in the
fundamental alteration of the HCI from channels that are simple and unimodal to the channels
that are complex and multimodal. The next advantage can be that the communication
modality that is natural among the computers and humans can be modified with the
combination of the signals of verbal and non-verbal for acting as the foundation for the
cooperation among the systems of AI and the people.
Conversational systems
The systems for conversation such as Alexa are becoming increasingly smarter with
the learning of the speech patterns of the user, which is possible by the implementation of
Artificial intelligence in the device. These devices adapt to the preferences, along with the
understanding of context and even create the vocabulary in a duration of time. With the
development of several skills by 3rd parties, Alexa can help in performing several tasks for the
humans, which ranges from offering the updates of weather to the pizza ordering, providing
the updates of traffic to thermostat controlling (Ghahramani, 2015).
Systems of gesture based
The Myo armband of Thalmic Labs provides the user with the ability of performing
interaction with the gesture of hand with computer system. The hand poses are studied by the
armband and then it can link them with the actions such as start/stop, moving forward,
moving backward, and control. The signals of EMG can be measured by the sensors of the
armband from the activities that are electrical for identifying several poses of hand, the
signals are combined with the data of motion from gyroscope, accelerometer and the
magnetometer for detecting a gesture in which the users make a fist and the raises the arm.
The gesture recognition of Myo is getting improved constantly, which classifies the several
methods of performing of a gesture naturally.

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Assistance in the systems of Human-computer
The emerging area of concern in the field of artificial intelligence is the creation of
the cooperation of agents of AI among one another. The behaviour of the humans are
characterised by the intelligence that is general and adaptive, and much of the concept is built
on the communication, awareness among the society and the anticipation ability and the
interpretation of the intentions of other.
Importance of HCI with AI in Defence
The advancements in the HCI that is embedded with AI has been focused for
implementation in the sector of defence in several countries. The Defence department has
benefitted from the quick advancement in the goal of the improvement of national security
with the reduction of the risks that are faced by the individuals in the environment that are
hostile (Rich & Waters, 2014).
This goal has established itself in the rigid support for pressure to advance the
technologies that
 Allows the total replacement of the humans from the environments that are hostile
by the method of perceiving, reasoning and the surrogates that are mechanical-
electronic.
 Allows the combination of humans and robots for executing the required functions
in the aggressive environments with minimised or reduced risk to any individual.
 Allows the remote control of the robots or the systems of human robot in the
aggressive environments for the sustainable reduction of the risk to human beings.
Advantages of Artificial Intelligence
The nature of artificial intelligence is complex. It utilises several difficult mixtures of
complex sciences, mathematics, and computer science. The applications of AI (Artificial

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Intelligence) is used for the simulation of the intelligence of humans to solve a problem or
take a decision. The application areas of AI varies from medicine, law, linguistics,
economics, engineering, and various forms of modelling, decision support, and prediction.
The most promising area of application of AI is the extensive use in Internet like search
engines. Even though the AI efficacies are significant, it is limited in several application in
both the capability and the functionality.
In the sector of transportation, several applications and researches have been
conducted and the result demonstrated the various advantages of the AI, and important
research has offered the evidence of the advantages of particular tools of AI. Some of the
examples of the technology of AI that are currently utilised are the conversion of sensors of
traffic into agents that are intelligent, which can detect automatically and then report the
accidents in traffic or even predict the conditions of traffic. With the utilisation of the data
that is microscopic, the security of transportation is another sector where the use of AI can be
significant.
The popular advantages and the efficacies of the AI makes this technology useful in
development and the management of the systems of transportation. Particularly, in the
transportation systems that are intelligent, the sensing in real-time, control, detection, and
response are highly essential, and the effective utilisation of AI can be done in these
applications. A traffic sensor that is distributed and the network of control is considered to be
the future of the control and traffic management that is real-time. In this realm, where the
sensor networks are distributed, consisting of the various stages of sensor networks that is
intelligent, can automatically detect and respond to the incidents and the network of roadway
that can be controlled as per the requirement. This sensor network that is intelligent
comprises of the tools of AI that can support the growth of next generation system of traffic
management.

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Disadvantages of artificial intelligence
Even though the AI has so many advantages, there are several disadvantages of AI
that has to be considered. The major concern of the paradigms of AI is that the technology of
AI is considered as the black boxes that can merely attempt the mapping of a connection
among the variables of input and output on the basis of the data set of training. This raises the
concern about the capability of the tool of generalising the situations that were not properly
represented in the set of data. The solution that has been presented for addressing of the
problem of black box is the integration or combination of several paradigms of AI in a
solution that is hybrid or the coupling of the paradigms of AI with increased conventional
techniques of solution (Nourani et al., 2014).
The other limitation of the search methods that are AI-based, like the optimisation of
ant colony and the genetic algorithms, is the inability of the algorithms of reaching the
optimal solution. When the solving of a problem is done with the help of search methods
based on AI, the gaining of true insight in the problem is difficult and the solution nature is
also difficult, which can be easily done with the programming methods that are mathematical.
The inability of performing quick analysis of sensitivity is the main proof of this limitation.
Conclusion
Therefore, it can be concluded that the integration of the HCI and Artificial
intelligence has helped the several sectors in recent times. AI or Artificial Intelligence is
commonly called as machine intelligence, which means the intelligence that is presented by
machines that is different from the intelligence presented by humans. The communities of AI
and the HCI are commonly characterised as consisting of several views that are opposing of
the methods of interaction among computers and humans. A common AI studies the
environment and then takes the required actions that helps in increasing the chances of

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successful achieving the goals. The increasing advancements in the technology has impacted
in the creation of better relationships among the computer interactions and humans. These
fields are coming together and the bridging of the gap has been done by the keyboards and
touch screens. The aspect of Artificial Intelligence is major breakthrough that has impacted
the life of humans. Another breakthrough discovery is the computer vision combined with
artificial intelligence. The field of eye tracking is the most benefitted from the
implementation of artificial intelligence. The advancements in the HCI that is embedded with
AI has been focused for implementation in the sector of defence in several countries. The
major concern of the paradigms of AI is that the technology of AI is considered as the black
boxes that can merely attempt the mapping of a connection among the variables of input and
output on the basis of the data set of training. The other limitation of the search methods that
are AI-based, like the optimisation of ant colony and the genetic algorithms, is the inability of
the algorithms of reaching the optimal solution

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References
Bond, A. H., & Gasser, L. (Eds.). (2014). Readings in distributed artificial intelligence.
Morgan Kaufmann.
Cohen, P. R., & Feigenbaum, E. A. (Eds.). (2014). The handbook of artificial
intelligence (Vol. 3). Butterworth-Heinemann.
Ghahramani, Z. (2015). Probabilistic machine learning and artificial
intelligence. Nature, 521(7553), 452.
Nourani, V., Baghanam, A. H., Adamowski, J., & Kisi, O. (2014). Applications of hybrid
wavelet–Artificial Intelligence models in hydrology: A review. Journal of
Hydrology, 514, 358-377.
Rich, C., & Waters, R. C. (Eds.). (2014). Readings in artificial intelligence and software
engineering. Morgan Kaufmann.
Wenger, E. (2014). Artificial intelligence and tutoring systems: computational and cognitive
approaches to the communication of knowledge. Morgan Kaufmann.
Zang, Y., Zhang, F., Di, C. A., & Zhu, D. (2015). Advances of flexible pressure sensors
toward artificial intelligence and health care applications. Materials Horizons, 2(2),
140-156.

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