國立虎尾科技大學 |

The Technology Adoption Model for Cloud Computing, Storytelling Artificial Intelligence, and the Federal Risk and Authorization Management Program.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	The Technology Adoption Model for Cloud Computing, Storytelling Artificial Intelligence, and the Federal Risk and Authorization Management Program./
Author:	Jackson, Freeman Augustus.
Description:	1 online resource (271 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-09, Section: B.
Contained By:	Dissertations Abstracts International85-09B.
Subject:	Computer science. -
Online resource:	click for full text (PQDT)
ISBN:	9798381947045

The Technology Adoption Model for Cloud Computing, Storytelling Artificial Intelligence, and the Federal Risk and Authorization Management Program.
Jackson, Freeman Augustus.

The Technology Adoption Model for Cloud Computing, Storytelling Artificial Intelligence, and the Federal Risk and Authorization Management Program. - 1 online resource (271 pages)

Source: Dissertations Abstracts International, Volume: 85-09, Section: B.

Thesis (D.C.S.)--Aspen University, 2024.

Includes bibliographical references

This dissertation examines challenges and opportunities in federal government Conversational AI and Machine Learning (CAIML) integration. It emphasizes Conversational AI (CAI)'s impact on decision-making across sectors and its improvement of human-technology interactions, particularly in IoT and cloud computing. The study reviews AI storytelling, including NLP, character generation, VR/AR, deep learning, leadership, and FedRAMP compliance.Qualitative research follows PRISMA and uses NVivo for data analysis. A comprehensive literature review, qualitative analysis, and expert interviews reveal CAIML adoption challenges and opportunities. Leadership, economic and legal factors, privacy, data protection, and national security are studied. The dissertation concludes with a summary of its findings and research questions on federal agency CAI and ML adoption barriers, operational improvements, legal/regulatory issues, privacy, data protection, security threats, and effective leadership strategies. CAI and ML integration into federal infrastructure and national security and intelligence implications are also discussed. The dissertation recommends federal agencies prioritize personnel training, migration planning, and solution sustainability to advance CAIML adoption. It helps federal policymakers and practitioners adopt CAIML technologies by highlighting their transformative potential and challenges.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798381947045Subjects--Topical Terms:

573171
Computer science.
Subjects--Index Terms:

Conversational AI and Machine LearningIndex Terms--Genre/Form:

554714
Electronic books.

The Technology Adoption Model for Cloud Computing, Storytelling Artificial Intelligence, and the Federal Risk and Authorization Management Program.
LDR:02900ntm a22003977 4500 001 1145499
005 20240624103710.5
006 m o d
007 cr bn ---uuuuu
008 250605s2024 xx obm 000 0 eng d
020 $a 9798381947045
035 $a (MiAaPQ)AAI30640477
035 $a AAI30640477
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Jackson, Freeman Augustus. $3 1437775
245 1 4 $a The Technology Adoption Model for Cloud Computing, Storytelling Artificial Intelligence, and the Federal Risk and Authorization Management Program.
264 0 $c 2024
300 $a 1 online resource (271 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 85-09, Section: B.
500 $a Advisor: Nguyen, Daniel Schilling Weiss.
502 $a Thesis (D.C.S.)--Aspen University, 2024.
504 $a Includes bibliographical references
520 $a This dissertation examines challenges and opportunities in federal government Conversational AI and Machine Learning (CAIML) integration. It emphasizes Conversational AI (CAI)'s impact on decision-making across sectors and its improvement of human-technology interactions, particularly in IoT and cloud computing. The study reviews AI storytelling, including NLP, character generation, VR/AR, deep learning, leadership, and FedRAMP compliance.Qualitative research follows PRISMA and uses NVivo for data analysis. A comprehensive literature review, qualitative analysis, and expert interviews reveal CAIML adoption challenges and opportunities. Leadership, economic and legal factors, privacy, data protection, and national security are studied. The dissertation concludes with a summary of its findings and research questions on federal agency CAI and ML adoption barriers, operational improvements, legal/regulatory issues, privacy, data protection, security threats, and effective leadership strategies. CAI and ML integration into federal infrastructure and national security and intelligence implications are also discussed. The dissertation recommends federal agencies prioritize personnel training, migration planning, and solution sustainability to advance CAIML adoption. It helps federal policymakers and practitioners adopt CAIML technologies by highlighting their transformative potential and challenges.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Computer science. $3 573171
650 4 $a Information technology. $3 559429
653 $a Conversational AI and Machine Learning
653 $a Cloud computing
653 $a Data protection
653 $a Federal government
653 $a Leadership strategies
655 7 $a Electronic books. $2 local $3 554714
690 $a 0984
690 $a 0800
690 $a 0489
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Aspen University. $b School of Business & Technology. $3 1437776
773 0 $t Dissertations Abstracts International $g 85-09B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30640477 $z click for full text (PQDT)