Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userمخاطر الذكاء الصنعي على الأمن ومستقبل العمل
1300
4 6
0.0
(
0
)
Added by
رند ورقة بحثية
Publication date
2021
fields
Informatics Engineering
and research's language is
العربية
Created by
Shamra Editor
Ask ChatGPT about the research
يستكشفة هذا المنظور التحليلي أثار انتشار الذكاء الاصطناعي في مجالين رئيسين يتعلقان بالسياسات هما الأمن والتوظيف. وقد ركزنا ههنا نقاط الضعف وعدم الانصاف التي قد يفرضها استخدام الذكاء الاصطناعي على هذين البعدين للمجتمع. حدد فريق من الزملاء في مؤسسة رند ذوي خبرات وتجارب متنوعة هذين المجالين من بين سواهما باعتبارهما يستحقان اهتماما دقيقا في عصر الذكاء الاصطناعي. ومن المجالات التي تمت الاشارة إليها أيضا نذكر: تأثير الذكاء الاصطناعي على الصحة وصنع القرارات وتسوية النزاعات في المنازعات والأمن الالكتروني. وتوضح الطبيعة متعدد التخصصات التي تتسم بها المشاكل التي خلصنا إليها الحاجة إلى مواصلة إشراك الباحثين والمحللين الذي يتمتعون بمجموعة متنوعة من الخبرات والتجارب من أجل اطلاع صناع القرارات المتعلقة بالسياسات على المواقف والخطوات الواجب القيام بها في ما يتعلق بالأدوات الاصطناعية والذكاء الصنعي على اوسع نطاق. يبين هذا البحث المحارو الشاملة لأثار الذكاء الاصطناعي: ١- الأدوات الاصطناعية هي في الواقع مضاعفات للانتباه قادرة على ان تحدث اثارا نظامية غير متوقعة وخطيرة. ٢- يزيد الاعتماد على الادوات الاصطناعية خطر تقلص المرونة. ٣- للذكاء الاصطناعي القدرة على التسبب بفوضى اقتصادية اجتماعية سريعة غير مسبوقة. ٤- تعد تفضيلات هجرة وتوظيف ذوي المواهب في مجال بحث وتطوير الذكاء الاصطناعي حول العالم من المخاوف الجغرافية السياسية المهمة.
No English abstract
References used
Autor, David H., David Dorn, Lawrence F. Katz, Christina Patterson, and John Van Reenen, “The Fall of the Labor Share and the Rise of Superstar Firms,” CEPR Discussion Paper No. DP12041, May 2017b. As of October 11, 2017: https://ssrn.com/abstract=2968382
Baiocchi, Dave, and D. Steven Fox, Surprise! From CEOs to Navy SEALs: How a Select Group of Professionals Prepare for and Respond to the Unexpected, Santa Monica, Calif.: RAND Corporation, RR-341-NRO, 2013. As of November 16, 2016: http://www.rand.org/pubs/research_reports/RR341.html
rate research
Read More
In Artificial Intelligence field, Knowledge Engineering phase is considered
the most crucial phase of the development life cycle of the Knowledge Base
Systems [1]. In fact, Formal Logic in general and Modus Ponens specifically has
been the dominan
t tools for structuring this knowledge [3]. This led for forming
a gap between the knowledge area and the information area, which depends
structurally on the Set Theory in general and on the Relational Algebra in
particular [1]. Thus, trying to introduce a bridge to pass this gap in structuring
and treating knowledge, we have conducted a new knowledge representation
model that depends structurally on (Classical and Fuzzy) Set Theory. Then we
used it as the base for conducting an inference model that attempt, using a set
of algebraic operations and by going through a series of stages, to reach a
solution of the problem under study, in a manner very close to the one that
humans usually use in treating their knowledge, taking into consideration the
speed and accuracy as much as the problem allows.
Through our research we develop an Expert System called
Transformer Fault Detection and abbreviation Exformer, to help
engineers and technical's in detecting and diagnosis of oiled power
transformer faults before it going out of service. We also u
se Fuzzy
Logic in ambiguous data cases about gas ratios in transformer oil,
which require use of fuzzy rules in knowledge base of expert
system. We also discuss basis of using Artificial Neural Networks
and choose number of layers, number of neurons and suitable neural
network for power transformers faults analysis and compare.
The Research Aims:
Syrian organizations keep large amounts of information and data about their
personnel in their IT systems. This information, however, is often left unutilized or
may be analyzed through statistical methods. In this study, DM is
considered a
solution for analyzing HR data and explore knowledge from data stored in some
Syrian organization through two major stages:
Stage A: Using results of Semi-Annual performance evaluation process to build
prototype showed in (Fig. 6) to accomplish two tasks:
1. Building a models to predict appropriate job function for an employee
through majority principle and using high accuracy result to increase the
number of training data and make it self-learning model.
2. Choose most important attributes that used in classify methods to use it in
personnel selection and recruitment.
Stage B: Using data of Time & Attendance to analysis personnel activity through
clustering methods and building many meaningful groups.
The entry of computer to many areas, such as medical field, led to develop new
technique that has led to the prosperity of these areas, and helped doctors to detect and
diagnose diseases accurately and credibility, where the experience of the docto
r in addition
to the accuracy of computer lead to access to the credibility of high patient and save
human lives.
A new approach for cardiac diseases detection and classification in ECG signals
images is proposed using Adaptive Neuro Fuzzy Inference System ANFIS.
The proposed approach is applied on database containing (147) ECG images,
each of them accompanied with its medical report. The medical reports were used to
validate the detection and classification.
The proposed method achieved a relatively high accuracy (97%) in detection and
classification processes.
The proposed approach is developed using MATLAB, and based on its libraries,
image processing, neural network and fuzzy logic.
Part of a 2017 Master’s Degree in Web Science research, which includes the definition of marketing intelligence in an expanded theoretical study, the method of building an Internet-based system as a data source, processing methodology, and applied results.
suggested questions
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
