Admission requirements
Not applicable
Description
This course addresses Communicative AI: its history, and current instantiations with Large Language Models. We will look at Communicative AI through the lense of the Gricean Maxims of Quantity, Quality, Relation and Manner, and at behavioral (and sometimes problematic) aspects of LLMs that affect the quality of communication with these models. The course will address papers on a weekly basis and provide self-contained course (slide) material. Additionally, students will be provided with Python scripts and notebooks (no prior programming experience required) for carrying out small homework experiments.
Course objectives
Students will acquire a grasp of the various aspects of Communicative AI. They will learn about machine learning and the technical details of LLMs, and will be guided through relevant literature. They will additionally learn how to work together on a group assignment, how to write a short scientific paper together, to carry out small experiments and to present their work to the group with a formal presentation.
Timetable
The timetables are available through My Timetable.
Mode of instruction
Seminar
Assessment method
Assessment
Paper, presentation
Weighing
The grade is a weighted average of the paper (group) and the personal contribution to the paper and the presentation; students will indicate in the paper explicitly what they contributed and will present their contribution in the joint group presentation. The weighting is : 1 times paper, 1 times personal contribution (divided by 2).
The final mark for the course is established by determining the weighted average. To pass the course, the weighted average of the partial grades must be 5.5 or higher.
Resit
The resit consists of a rewrite of the personal contribution to the paper, and a 1:1 presentation (teacher-student) of their revised work.
Inspection and feedback
How and when an exam review will take place will be disclosed together with the publication of the exam results at the latest. If a student requests a review within 30 days after publication of the exam results, an exam review will have to be organized.
Reading list
Not applicable
Registration
Enrolment through MyStudyMap is mandatory.
General information about course and exam enrolment is available on the website.
Registration Contract teaching and Exchange
Information for those interested in taking this course in context of Contract teaching (with taking examinations), eg. about costs, registration and conditions.
For the registration of exchange students contact Humanities International Office.
Contact
For substantive questions, contact the lecturer listed in the right information bar.
For questions about enrolment, admission, etc, contact the Education Administration Office Reuvensplaats
Remarks
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