Artificial intelligence and the future of scientific thinking
7405-AC-AI-2
Academia Copernicana short course: Artificial Intelligence and the future of scientific thinking, USOS Id: 7405-AC-AI-2
Unfortunately, we have only 10 hours and there is a lot of material that we should cover. Each week we shall have two topics.
To join, you have to enroll yourself for this course. You may download the presentation from the course Moodle page before the lecture.
If you need my contact information, please Google my name to find my web page, where you will find all the details.
Topic 1. General introduction to Artificial Intelligence
Topic 2. History of AI
Topic 3. Symbolic AI: heuristic search-based methods.
Topic 4: Games and Cognition
Topic 5: Knowledge Representation
Topic 6: Expert Systems and Natural Language Processing
Topic 7: Large AI projects.
Topic 8: Machine Learning, available tools, large language models.
Topic 9. State of the art and recent trends in AI.
Topic 10. Natural intelligence and human enhancements.
Total student workload
The course presents the current state of AI, focusing on methods that may be of use for work in different fields, such as ChatGPT or other large language models. It should give you an idea how AI tools may help in you're work. This will require reading and exploration of Internet resources.
Learning outcomes - knowledge
Students understand:
• the need for multilevel phenomics, from molecules to behavior;
• organization of biological organisms at molecular level;
• general anatomical structure of the brain;
• cognitive functions, relations to other fields of science;
• mechanisms of visual, tactile, auditory and other forms of perception at biological, structural level;
• mechanisms of visual, tactile, auditory and other forms of perception at functional, information flow level;
• mechanisms of learning, neuroplasticity and memory at biological, cellular level;
• mechanisms of learning and memory at functional, brain network level, examples of some mental disorders;
• mechanisms of attention and consciousness.
The course should lead to development of the following outcomes:
K_W01, K_W02, K_W03, K_W04, K_W05, K_W06, K_W07.
Learning outcomes - skills
Students are able to:
• Find and critically assess information in the Internet and in scientific and popular science journals related to cognitive neuroscience;
• summarize main points of the lectures,
• collect and interpret information from different sources,
• formulate important questions and think about implications of learned material,
• recognize false assumptions about brain functions and brain disorders;
• find interesting software tools and databases that may be used to elucidate cognitive mechanisms discussed during lectures.
The course should lead to development of the following outcomes:
K_U01, K_U02, K_U04, K_U06
Learning outcomes - social competencies
Students are:
• aware of the complexity of issues related to brain research;
• critically asses information in media related to new discoveries in cognitive and biological sciences related to the brain research;
• understand contributions of cognitive and biological sciences to fathoming human nature;
• analyze and assess available information to understand possible implications of the knowledge gained;
• understand the need to follow scientific literature to catch up with rapid progress in this field;
• understand ethical and social problems created by rapid development of brain research.
The course should lead to development of the following outcomes:
K_K01, K_K02, K_K03, K_U08, K_U09, K_U11.
Teaching methods
Lecture notes in Moodle/WWW.
• reference to the web pages of important projects in bio/neuro areas;
• demonstrations, using video clips.
Discussion and short presentations at the end of the course.
Expository teaching methods
- participatory lecture
- informative (conventional) lecture
Exploratory teaching methods
- project work
Online teaching methods
- exchange and discussion methods
- content-presentation-oriented methods
Type of course
(in Polish) przedmiot obowiązkowy
Prerequisites
None
Course coordinators
Assessment criteria
Short presentation of AI relevance to student's work. All students have to show how they will be able to use various AI tools.
Practical placement
Additional information
Additional information (registration calendar, class conductors,
localization and schedules of classes), might be available in the USOSweb system: