Artificial Intelligence in Social Research and Political Science

Course Information
TitleΤεχνητή Νοημοσύνη στην Κοινωνική Έρευνα και τις Πολιτικές Επιστήμες / Artificial Intelligence in Social Research and Political Science
CodeΚΕ0Ε73
FacultySocial and Economic Sciences
SchoolPolitical Sciences
Cycle / Level1st / Undergraduate
Teaching PeriodWinter/Spring
CoordinatorKostantinos Bougioukas
CommonYes
StatusActive
Course ID600027872

Programme of Study: PPS Tmīma Politikṓn Epistīmṓn 2023-sīmera

Registered students: 19
OrientationAttendance TypeSemesterYearECTS
KORMOSElective CoursesSpring-4
Class Information
Academic Year2025 – 2026
Class PeriodSpring
Instructors from Other Categories
Weekly Hours3
Total Hours39
Class ID
600287724
Course Type 2021
Specific Foundation
Mode of Delivery
  • Face to face
Digital Course Content
Language of Instruction
  • Greek (Instruction, Examination)
Learning Outcomes
By the end of the course, students will be able to: 1. Understand the fundamental principles and techniques of AI and their applications in the social sciences. 2. Critically analyze the social, political, ethical, and epistemological implications of AI. 3. Apply AI tools to process quantitative and qualitative data for research purposes. 4. Design and conduct small-scale research studies using AI methods. 5. Evaluate the role of AI in governance, public policy, and social relations, proposing responsible and participatory approaches.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Work in an interdisciplinary team
  • Generate new research ideas
  • Demonstrate social, professional and ethical commitment and sensitivity to gender issues
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Course Content (Syllabus)
The course “Artificial Intelligence in Social Research and Political Science” introduces the key concepts, techniques, and applications of AI, focusing on its social and political dimensions. Through theoretical frameworks, methodological tools, and applied case studies, students will explore the role of AI in political analysis, governance, public policy, social research, and everyday life. The course integrates theoretical discussion, practical skills, and critical analysis to help students understand both the potentials and limitations of AI.
Keywords
Artificial Intelligence, quantitative and qualitative research, public policies, goverance, methods
Educational Material Types
  • Notes
  • Slide presentations
  • Video lectures
  • Podcast
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
  • Use of ICT in Student Assessment
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures421.5
Reading Assigment431.6
Written assigments130.5
Exams120.4
Total1104
Student Assessment
Description
1) midterm examination with multiple choice questions (30% on the final grade) 2) final written exam (50% on final grade) 3) Participation in the course (10% on the final grade)
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Formative, Summative)
  • Written Exam with Short Answer Questions (Formative, Summative)
  • Written Assignment (Formative, Summative)
  • Performance / Staging (Formative, Summative)
  • Written Exam with Problem Solving (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
Bryson, J., Gabriel, I., & άλλοι. (2023). Η ηθική της τεχνητής νοημοσύνης: Εγχειρίδιο της Οξφόρδης (μετ. στα ελληνικά). Εκδόσεις Παπαζήση.
Additional bibliography for study
Μαυρόπουλος, Α. (2024). Τεχνητή νοημοσύνη: Άνθρωπος, φύση, μηχανές. Εκδόσεις Τόπος. Σχισμένος, Α. (2025). Τεχνολογία και Βαρβαρότητα. Κριτική της τεχνητής νοημοσύνης. Athens School. ISBN: 9786188485198.
Last Update
01-09-2025