2021
BOLIVARIAN REPUBLIC OF VENEZUELA
BICENTENARY UNIVERSITY OF ARAGUA
ACADEMIC VICE-RECTORATE
DEANERY OF RESEARCH, EXTENSION AND POSTGRADUATE
SAN JOAQUIN DE TURMERO - ARAGUA STATE
EFFECTS OF ARTIFICIAL INTELLIGENCE ON THE IMMEDIATE
PRINCIPLE IN CRIMINAL SENTENCES
Degree Work to opt for the Title of
lawyer
Author Jefferson Jose Montoya Anaya
:
, San Joaquin de Turmero, April 2021
GENERAL INDEX
pp.
GUARDIAN ACCEPTANCE……………………..………………….. III
DEDICATION……………………………………………………….. IV
RECOGNITION………………………………………………… v
GENERAL INDEX…………………………………………………… sa
w
LIST OF TABLES……………………………………………….. viii
LIST OF GRAPHICS……………………………………………….. viii
ABSTRACT……………………………………………….…….………. ix
INTRODUCTION…………………………….…………………....…. 1
CHAPTERS
Y REALITY PERSPECTIVE………………………….…. 02
o Characterization of Reality………………………. 02
Research objectives………………………..…..…….… 08
General objective…………………………………………….. 08
Specific objectives………………………………………. 08
Justification of the Investigation………………………. 09
THEORETICAL PERSPECTIVE……………………………. 10
II ……… 10
Research Background…………………….…….. 10
At the international level……………………………...…. ele
In the National Scope………………………….……...….... ve
Theoretical n
Bases…………………………………………………… 12
Artificial Intelligence……………………………………… 12
Types of Expert Systems………………………………. 23
Symbolic Processing Model………………… 26
Connectionist Model and Neural Networks…………. 27
Legal Expert Systems (SEJ)………………… 28
SPLIT UP Expert System based on rules and neural
networks……………………………………………… 31
Expertius (Expert system based on the constructivist model
and neural networks)……………………………. 33
Expert Judgment System SIES…………………. 3.
Automatic Learning or Machine Learning………… 4
Representation of Knowledge, Logic and Rules…… 37
Precedents of Artificial Intelligence in Law…… 37
, Artificial Intelligence AI in the Practice of Law… 37
AI used in Surveillance…………… 39
C. AI and "Users" of the Law…………… 39
Artificial intelligence and the principle of immediacy…… 40
Immediacy Principle…………………………………….. 40
Institutional Elements……………………………………. 41
Cultural and Ideological Elements………………………… 42
Psychosocial Elements…………………………………….. 42
SIRI (2004)……………………………………………………. 42
Descartes (Google)………………………………………….. 43
Omnius (2015)……………………………………………….. 43
British Nationality Page………………………….. 53
TSJ Judgment Finder (2000)………………….. 55
Legal Tech (2008)…………………………………………… 55
Luminance (2015)………………………………………….. 55
Split-Up………………………………………………………. 55
The Chinese Cyber Court (2017)………………………….. 55
Legal Foundations……………………………………….….. 55
III 55
METHODOLOGY………………………………………………..
…. 66
Method……………………………………………………………… 66
Nature and Type of Research…………………………….. 66
Design of the investigation……………………………………… 66
Type or Level of Investigation………………………. 66
Population…………….…………………………………………. 66
Sample………………………………………………………….. 66
Process………………………………………………….. 66
Data Collection Techniques and Instruments……….. 66
Data Processing and Analysis Techniques………….. 66
IV Validation and Reliability of the instrument…………………. 66
FINAL CONSIDERATIONS…………………………….…. 77
Results………………………………………………………… 77
Contributions……………………………………………………… 77
……..
REFERENCES……………………………………………………….. 58
, LIST OF TABLES
FRAME pp.
1. Data Collection Instrument…………………………….. 00
2. Instrument Reliability. Crombach's Alpha Internal Consistency
Index…………………………………………… 00
3. Frequency and percentage of responses for each of the
categories of item 1………………………………………………….. 00
4. Frequency and percentage of responses for each of the
categories of item 2………………………………………………. 00
5. Frequency and percentage of responses for each of the
categories of item 3………………………………………………. 00
6. Frequency and percentage of responses for each of the
categories of item 4………………………………………………. 00
7. Frequency and percentage of responses for each of the
categories of item 5……………………………………………….. 00
8. Frequency and percentage of responses for each of the
categories of item 6……………………………………………….. 00
9. Frequency and percentage of responses for each of the
categories of item 7………………………………………………….. 00
10. Frequency and percentage of responses for each of the
categories of item 8………………………………………………. 00
11. Frequency and percentage of responses for each of the
categories of item 9………………………………………………. 00
12. Frequency and percentage of responses for each of the
categories of item 10………………………………………………. 00
13. Frequency and percentage of responses for each of the
categories of item 00
11…………………………………………………….
14. Frequency and percentage of responses for each of the
categories of item 12………………………………………………. 00
15. Frequency and percentage of responses for each of the
categories of item 00
13…………………………………………………….
16. Frequency and percentage of responses for each of the
categories of item 00
14…………………………………………………….
BOLIVARIAN REPUBLIC OF VENEZUELA
BICENTENARY UNIVERSITY OF ARAGUA
ACADEMIC VICE-RECTORATE
DEANERY OF RESEARCH, EXTENSION AND POSTGRADUATE
SAN JOAQUIN DE TURMERO - ARAGUA STATE
EFFECTS OF ARTIFICIAL INTELLIGENCE ON THE IMMEDIATE
PRINCIPLE IN CRIMINAL SENTENCES
Degree Work to opt for the Title of
lawyer
Author Jefferson Jose Montoya Anaya
:
, San Joaquin de Turmero, April 2021
GENERAL INDEX
pp.
GUARDIAN ACCEPTANCE……………………..………………….. III
DEDICATION……………………………………………………….. IV
RECOGNITION………………………………………………… v
GENERAL INDEX…………………………………………………… sa
w
LIST OF TABLES……………………………………………….. viii
LIST OF GRAPHICS……………………………………………….. viii
ABSTRACT……………………………………………….…….………. ix
INTRODUCTION…………………………….…………………....…. 1
CHAPTERS
Y REALITY PERSPECTIVE………………………….…. 02
o Characterization of Reality………………………. 02
Research objectives………………………..…..…….… 08
General objective…………………………………………….. 08
Specific objectives………………………………………. 08
Justification of the Investigation………………………. 09
THEORETICAL PERSPECTIVE……………………………. 10
II ……… 10
Research Background…………………….…….. 10
At the international level……………………………...…. ele
In the National Scope………………………….……...….... ve
Theoretical n
Bases…………………………………………………… 12
Artificial Intelligence……………………………………… 12
Types of Expert Systems………………………………. 23
Symbolic Processing Model………………… 26
Connectionist Model and Neural Networks…………. 27
Legal Expert Systems (SEJ)………………… 28
SPLIT UP Expert System based on rules and neural
networks……………………………………………… 31
Expertius (Expert system based on the constructivist model
and neural networks)……………………………. 33
Expert Judgment System SIES…………………. 3.
Automatic Learning or Machine Learning………… 4
Representation of Knowledge, Logic and Rules…… 37
Precedents of Artificial Intelligence in Law…… 37
, Artificial Intelligence AI in the Practice of Law… 37
AI used in Surveillance…………… 39
C. AI and "Users" of the Law…………… 39
Artificial intelligence and the principle of immediacy…… 40
Immediacy Principle…………………………………….. 40
Institutional Elements……………………………………. 41
Cultural and Ideological Elements………………………… 42
Psychosocial Elements…………………………………….. 42
SIRI (2004)……………………………………………………. 42
Descartes (Google)………………………………………….. 43
Omnius (2015)……………………………………………….. 43
British Nationality Page………………………….. 53
TSJ Judgment Finder (2000)………………….. 55
Legal Tech (2008)…………………………………………… 55
Luminance (2015)………………………………………….. 55
Split-Up………………………………………………………. 55
The Chinese Cyber Court (2017)………………………….. 55
Legal Foundations……………………………………….….. 55
III 55
METHODOLOGY………………………………………………..
…. 66
Method……………………………………………………………… 66
Nature and Type of Research…………………………….. 66
Design of the investigation……………………………………… 66
Type or Level of Investigation………………………. 66
Population…………….…………………………………………. 66
Sample………………………………………………………….. 66
Process………………………………………………….. 66
Data Collection Techniques and Instruments……….. 66
Data Processing and Analysis Techniques………….. 66
IV Validation and Reliability of the instrument…………………. 66
FINAL CONSIDERATIONS…………………………….…. 77
Results………………………………………………………… 77
Contributions……………………………………………………… 77
……..
REFERENCES……………………………………………………….. 58
, LIST OF TABLES
FRAME pp.
1. Data Collection Instrument…………………………….. 00
2. Instrument Reliability. Crombach's Alpha Internal Consistency
Index…………………………………………… 00
3. Frequency and percentage of responses for each of the
categories of item 1………………………………………………….. 00
4. Frequency and percentage of responses for each of the
categories of item 2………………………………………………. 00
5. Frequency and percentage of responses for each of the
categories of item 3………………………………………………. 00
6. Frequency and percentage of responses for each of the
categories of item 4………………………………………………. 00
7. Frequency and percentage of responses for each of the
categories of item 5……………………………………………….. 00
8. Frequency and percentage of responses for each of the
categories of item 6……………………………………………….. 00
9. Frequency and percentage of responses for each of the
categories of item 7………………………………………………….. 00
10. Frequency and percentage of responses for each of the
categories of item 8………………………………………………. 00
11. Frequency and percentage of responses for each of the
categories of item 9………………………………………………. 00
12. Frequency and percentage of responses for each of the
categories of item 10………………………………………………. 00
13. Frequency and percentage of responses for each of the
categories of item 00
11…………………………………………………….
14. Frequency and percentage of responses for each of the
categories of item 12………………………………………………. 00
15. Frequency and percentage of responses for each of the
categories of item 00
13…………………………………………………….
16. Frequency and percentage of responses for each of the
categories of item 00
14…………………………………………………….