You can find the website for the Research Report on Issues with Robots here. It was written by Mohammad Al Amin, Kiara Candelario, Neil Domingo, and Ali Hossain.
Author: Neil Domingo
Neil Domingo’s Instructional Manual for How To Create An Ethernet Cable
For this project, I wrote an instructional manual for How To Create An Ethernet Cable.
Expanded Definition of Artificial Intelligence
Expanded Definition of Artificial Intelligence
TO: Prof. Jason Ellis
FROM: Neil Domingo
DATE: 3/30/21
SUBJECT: Expanded Definition of Artificial Intelligence
Introduction
The purpose of this document is to further explore and define the term Artificial Intelligence. The term would be discussed by expanding the general definition of Artificial Intelligence. First, this document will define the term with its definitions. Then, this document will provide context for the given definitions. Lastly, this document will provide a working definition of the term of Artificial Intelligence.
Definitions
Artificial Intelligence is defined by Britannica as “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings” [1]. This definition is a simple definition best for those that are unaware of what the term means. the definition given by Britannica, defines Artificial Intelligence simply as a “computer” or “robot” that performs tasks associated with “intelligent beings”. This definition is associated with systems that are embedded with “intellectual processes” with characteristics of humans. These characteristics include “ability to reason, discover meaning, generalize or learn from past experiences”. [1] Another definition that is similar to the Britannica definition of Artificial Intelligence is given in an article entitled Artificial intelligence-definition and practice. The article defines Artificial Intelligence as “The term artificial intelligence denotes behavior of a machine which, if a human behaves in the same way, is considered intelligent” [2]. In this definition, a system, computer, or robot would be considered as a machine. Then, the definition states that the machine would display a behavior that is considered “intelligent”. It is only considered intelligent if it behaves in the same way as a human. There is another definition that is similar to the two given. A journal article entitled, Artificial intelligence, machine learning and deep learning: definitions and differences, refers Artificial Intelligence “to a field of computer science dedicated to the creation of systems performing tasks that usually require human intelligence” [3]. This given definition is similar to the others as it discusses systems and human intelligence. Systems are considered as machines or computers act in a way of a human.
Human intelligence refers to a “mental quality that consists of the abilities to learn from experience, adapt to new situations, understand and handle abstract concepts, and use knowledge to manipulate one’s environment” [4]. All three definitions of Artificial Intelligence given are all similar as they define Artificial Intelligence as a machine or a computer/system that perform tasks in such fashion with characteristics of a human. In simplest terms, a computer that acts or thinks like a human. One might lean towards the definition given in Artificial intelligence-definition and practice, because it best describes the machine denoting a behavior in a way of a human.
Context
The term Artificial Intelligence is found in many journals such as Artificial Intelligence in the 21st Century. The journal discusses Artificial Intelligence and its growth throughout the 21st century. The journal utilizes different journals and conferences to dig into the impactful evolution of Artificial Intelligence. The journal states, “In simple terms, AI aims to extend and augment the capacity and efficiency of mankind in tasks of remaking nature and governing the society through intelligent machines, with the final goal of realizing a society where people and machines coexist harmoniously together” [5]. The purpose of Artificial Intelligence is to further extend the limitations of how tasks are executed and greatly increase the capacity and efficiency of these tasks. Ultimately, it will reshape nature and society that would lead to a world where humans and machines such as computers/robots can work together as a “well oiled machine”. Another journal entitled AIR5: Five Pillars of Artificial Intelligence Research discusses Artificial Intelligence and its five pillars. The five pillars of Artificial Intelligence are rationalizability, resilience, reproductivity, realism, and responsibility. The journal states that the five Rs “represent five key pillars of AI research that shall support the sustained growth of the field through the 21st century and beyond” [6]. The journal discusses how these five pillars are essential in maintaining the growth of Artificial Intelligence. The journal also states “The original inspiration of artificial intelligence (AI) was to build autonomous systems capable of matching human-level intelligence in specific domains” [6]. The intentions of Artificial Intelligence was to build a system that can match human intelligence in specific aspects. A blog entitled Artificial Intelligence in Medicine: Applications, implications, and limitations, discusses how Artificial Intelligence can be used in medicine. The blog also states “AI algorithms also must learn how to do their jobs. Generally, the jobs AI algorithms can do are tasks that require human intelligence to complete, such as pattern and speech recognition, image analysis, and decision making. However, humans need to explicitly tell the computer exactly what they would look for in the image they give to an algorithm, for example. In short, AI algorithms are great for automating arduous tasks, and sometimes can outperform humans in the tasks they’re trained to do” [7]. This quote details the capabilities of Artificial Intelligence and what it must do to be effective. Artificial Intelligence must learn algorithms and read data in order to produce results that are useful. However, they must be told what to do by a human. Once they learn their tasks, they can have the potential to outperform humans, as if “beating them at their own game”.
Working Definition
Artificial Intelligence is the ability of a computing machine such as a computer to learn algorithms and interpret data in order to perform tasks of a human’s capability. Artificial Intelligence can have the potential to troubleshoot problems of a human’s computer or a computer in general. Artificial Intelligence can also have the potential ability of solving a human’s computer through a series of questions and ultimately lead to a solution.
References
- Copeland, B. (2020, August 11). Artificial intelligence. Encyclopedia Britannica. https://www.britannica.com/technology/artificial-intelligence
- A. B. Simmons and S. G. Chappell, “Artificial intelligence-definition and practice,” in IEEE Journal of Oceanic Engineering, vol. 13, no. 2, pp. 14-42, April 1988, doi: 10.1109/48.551
- D. Jakhar and I. Kaur, “Artificial intelligence, machine learning and deep learning: definitions and differences,” in Clinical and Experimental Dermatology, vol. 45, issue 1, pp. 131-132, June 2019, doi:10.1111/ced.14029
- Sternberg, R. J. (2020, November 6). Human intelligence. Encyclopedia Britannica. https://www.britannica.com/science/human-intelligence-psychology
- Liu, Jiaying & Kong, Xiangjie & Xia, Feng & Bai, Xiaomei & Wang, Lei & Qing, Qing & Lee, Ivan. (2018). Artificial Intelligence in the 21st Century. IEEE Access. PP. 1-1. 10.1109/ACCESS.2018.2819688
- Ong, Yew & Gupta, Abhishek. (2018). AIR5: Five Pillars of Artificial Intelligence Research.
- Ariel, et al. “Artificial Intelligence in Medicine: Applications, Implications, and Limitations.” Science in the News, 19 June 2019, sitn.hms.harvard.edu/flash/2019/artificial-intelligence-in-medicine-applications-implications-and-limitations/.
Summary of Feng Shi’s et al. “Review of Artificial Intelligence Techniques in Imaging Data Acquisition Segmentation, and Diagnosis for COVID-19”
TO: Prof. Ellis
FROM: Neil Domingo
DATE: 3/3/2021
SUBJECT: 500-Word Summary of Article About Utilizing Artificial Intelligence In Fighting COVID-19
The following is a 500-word summary of a peer-reviewed article about the use of artificial intelligence in medical imaging during the COVID-19 pandemic. The journal’s goal is to further discuss the use of medical imaging with artificial intelligence in fighting against COVID-19 and discuss machine learning methods in the imaging workflow. Medical imaging such as CT scans and X-rays have been found to play a critical role in restraining the transmission of COVID-19. CT scans is one of the imaging-based diagnoses that is used for COVID-19 and includes three stages: pre-scan acquisition, image acquisition, and disease diagnosis. Artificial Intelligence contributes to the fight against COVID-19 as it allows for safer, accurate, and efficient imaging solutions. Imaging facilities, and workflows should be considered important to reduce the risks and save lives from COVID-19. According to authors “AI-empowered image acquisition can significantly help automate the scanning procedure and also reshape the workflow with minimal contact to patients, providing the best protection to the imaging technicians” (F. Shi et al., 2020, pg 4). The use of contactless and imaging acquisition is necessary to reduce the risks of technicians and patients being infected as there is contact between them. Artificial intelligence can be used to help the contactless scanning as it will be able to identify the pose and shape of a patient by using data from visual sensors. Scan range, the start and end point of a CT scan, can be estimated by the use of visual sensors with artificial intelligence, and scanning efficiency can be improved. A mobile CT platform with artificial intelligence implemented, is an example of an scanning automated workflow allowing for the prevention of unnecessary interaction between technicians and patients. The patient positioning algorithm will capture the patient’s pose.
Segmentation is crucial in image processing and analysis in order to assess COVID-19 as it covers the region of interest (ROIs) (organs that are affected by COVID-19/ infected areas). CT produces high-quality 3D images, and ROIs can be segmented into it. Proposals such as human knowledge,and machine learning methods can be integrated with a segmentation network in order to allow for adequate training data for segmentation tasks. Image segmentation allows radiologists to accurately identify lung infection, and analyzing and diagnosing COVID-19.
Patients that are suspected of COVID-19 are in need of diagnosis and treatment, and with COVID-19 being similar to pneumonia, in which AI-assisted diagnosis using medical images can be highly beneficial. Deep learning models were proposed such as ResNet50 to detect COVID-19 through X-ray images. The ResNet50 model contains two tasks: classification between COVID/non-COVID and anomaly detection (allows for optimization of the COVID-19 score that is used for classification). Studies have separated COVID-19 patients from non-COVID-19 patients, with the help of artificial intelligence and the reading time of radiologists was reduced by 65%.
With many studies proposing CT-based COVID-19 diagnosis show promising results, it is important for early detection and predictions of severity. It is challenging for artificial intelligence to be used in a procedure regarding the incubation period and infectivity. X-rays and CT scans are not often available for COVID-19 applications which slows down any artificial intelligence methods from continually being researched and developed.
Reference
F. Shi et al., “Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation, and Diagnosis for COVID-19,” in IEEE Reviews in Biomedical Engineering, vol. 14, pp. 4-15, 2021, doi: 10.1109/RBME.2020.2987975.
