Edward Dominguez’s Expanded Definition of Artificial Intelligence (AI)

TO: Prof. Jason Ellis
FROM: Edward Dominguez
DATE: MARCH 26, 2021
SUBJECT: Expanded Definition of Artificial Intelligence (AI)

INTRO

This is an expanded definition that explores the term “artificial intelligence” as a general introduction for undergraduates that are studying computer information technology. I chose the term artificial intelligence because it is relevant in today’s society. In the following document, I discuss several definitions of artificial intelligence, then I compare and contrast different contextual uses of artificial intelligence and finally, I write my own working definition of the term based on these definitions and contextual examples.

DEFINITION

“The capacity of computers or other machines to exhibit or simulate intelligent behaviour; the field of study concerned with this. Abbreviated AI.” (McGraw-Hill, 1977). In this definition, artificial intelligence is the magnitude of machines that can show intelligent behavior.

“Computer systems that can perform intelligent human tasks, such as decision-making. Intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. In some cases artificial intelligence is applied when a machine mimics cognitive functions that humans associate with other human minds, such as learning and problem-solving.” (Oxford University Press, 2020). In this definition, artificial intelligence is defined as computer systems that can accomplish complex human tasks. Also, artificial intelligence can be applied to machines that copy cognitive functions that are associated with the human mind. Certain tasks that machines are able to do can be defined as artificial intelligence, include learning, decision-making, and problem-solving. This definition relates to the previous definition of (McGraw-Hill, 1977), the particular reason for this circumstance is both definitions state that artificial intelligence is when machines are able to replicate intelligent behavior. One may use this definition (Oxford University Press, 2020), instead of the previous definition (McGraw-Hill, 1977) because it has a much deeper definition and because more examples of artificial intelligence is given. Even though the first definition was written in 1977, it is still holds up as a valid definition.

CONTEXT

“Amazon.com also groups together people with similar interests and uses all of their data to make better recommendations to the group. The more a person uses any of these services, the better the recommendations get. Users’ actions train the AI to better understand what they like.”(Hulick, 2016). In this quote, the term artificial intelligence is used as a way to show how artificial intelligence learns from the user’s data to figure out what that specific user likes. This shows how AI is being used in our daily lives today. This context relates to the definition of (Oxford University Press, 2020), because AI is learning and picking up things from the user in order to help recommend items for that specific user. This context also relates to the definition of (McGraw-Hill, 1977), because the system is showing intelligent behavior by learning.

“Humans decided to give to driverless cars and many other AI equipped machines the power to make sometimes life-critical decisions. As such, ethical and moral dimensions must be taken into consideration and attention given to this aspect. Furthermore, if we are even capable of making an algorithm which will be able to use ethical patterns of humans” (Nikolic, Yang, 2020). The context uses the term “artificial intelligence” as technology that is being used today to make life or death decisions. The important decisions that artificial intelligence has to make and the consequences if something goes wrong, makes us questions if AI like this, is morally right to have in society. The context’s use of artificial intelligence also relates to the second definition (Oxford University Press, 2020) where AI can perform intelligent human tasks such as a driverless car. The way artificial intelligence is used in this context relates to the last context of (Hulick, 2016) where artificial intelligence is used by companies to help users find recommendations for items online while in the context of (Nikolic, Yang, (2020) artificial intelligence is used to make driverless cars. Both contexts show different ways artificial intelligence can be used to help people. Although artificial intelligence can help many people, it can also raise many questions about how ethical and moral due to the fact that many things that errors and mistakes can happen, especially because AI technology still isn’t

WORKING DEFINITION

            Artificial intelligence is when machines are able to learn on their own to make complex decisions that mimic human intelligence such as learning, problem solving and much more.  Artificial intelligence can be found everywhere in today’s society, we use it every time we use our smartphones, media applications, and much more. We are becoming more and more dependent to artificial intelligence. As time progresses, artificial intelligence will continue to grow. AI technology is important now and will become even more important in the future.

References

Gorse, C., Johnston, D., & Pritchard, M. (Eds.). (2020). A Dictionary of Construction, Surveying and Civil Engineering (2 ed.). Oxford University Press Retrieved March 4, 2020, from  https://www.oxfordreference.com/view/10.1093/acref/9780198832485.001.0001/acref-9780198832485-e-8189?rskey=7AdcY1&result=1

Hulick, K. (2016). Artificial intelligence . Essential Library

McGraw-Hill. (1977). Oxford English Dictionary. Retrieved March 4, 2021, https://www-oed-com.citytech.ezproxy.cuny.edu/view/Entry/271625?redirectedFrom=artificial+intelligence#eid

Nikolic, P. K., & Yang, H. (2020). Artificial Intelligence Clone Generated Content toward Robot
Creativity and Machine Mindfulness. Mobile Networks & Applications, 25(4), 15041513. https://doi-org.citytech.ezproxy.cuny.edu/10.1007/s11036-019-01281-z

Summary of Yin et. al’s. “Health-CPS: Healthcare Cyber-Physical System Assisted by Cloud and Big Data”

TO: Prof. Ellis

FROM: Edward Dominguez

DATE: 3/3/2021

SUBJECT: 500-word Summary of Article About Healthcare CPS

The following is a 500-word summary of a peer-reviewed article about how Cloud and Big Data is helping the Healthcare Cyber-Physical System. The authors discuss the Healthcare CPS which is a cyber-physical system for patient-centric healthcare applications and services that is built on cloud and big data analytics technologies. The results of this study show that the technologies of cloud and big data can be used to enhance the performance of the healthcare system so that humans can then enjoy various smart healthcare applications and services. Information technology is very important to the healthcare field. As time passes more data is used than ever before, which can lead up to challenges for data management, storage and processing. In healthcare the volume of data keeps increasing as new technologies are released such as, wearable health devices, etc. It is important for medical equipment to collect data very quickly to respond to emergency. Healthcare devices create different types of data which include text, image, audio and video that may be structured or non-structured. The value from healthcare data can be maximized through data fusion of EHR and electronic medical records. Cloud Computing, big data can also help organize health care data. Even though there are many innovations in the healthcare field, there are some issues need to be resolved. Healthcare data that is stored together on the physical later are still logically separated which is an issue. The biggest challenge of building a comprehensive healthcare system is in the handling of heterogenous healthcare data that is from multiple sources. In the healthcare industry cloud and big data are very important and it is becoming a trend in healthcare innovation. Medicine relies in specific data and analysis. The system must support different types of healthcare equipment. It’s important to have different data structures to deploy suitable methods for efficient online or offline analysis. The system is expected to provide many applications and services for different roles. The data collection layer collects raw data in different structures and formats to ensure security. Data management layer which includes Distributed File Storage (DFS) and distributed parallel computing (DPC). The application service layer which gives users visual data and analysis results. There also is a data collection layer. According to the authors, “in the data collection layer, various healthcare data are collected by the data nodes and are transmitted to the cloud through the configurable adapters that provide the functionality to preprocess and encrypt the data” (Zhang et al., 2017, p. 90). Data nodes can be divided into four groups: research data, medical expense data, clinical data, and individual activity and emotional data. Digital data has been a new way for scientific research in identifying side effects of drugs and its new effects. Medical expense data is using a non-traditional healthcare data like medical insurance reimbursement and medical bills are geographically dispersed because it can estimate medical cost. Clinical data is served in many medical services like EMR and medical imaging, while keeping the privacy of the patients.

References

Zhang, Y., Qiu, M.,  Tsai, C.,  Hassan, M. M., & Alamri, A. (2017). Health-CPS: Healthcare cyber-physical system assisted by cloud and big data. IEEE Systems Journal, 11(1), 88-95. https://doi.org/10.1109/JSYST.2015.2460747