Natural and Artificial Intelligence
Code: 106229Credits: 6
| Degree programme | Type | Course |
|---|---|---|
| Science, Technology and Humanities | OB | 2 |
Contact lecturer
- Name :
- Xavier Roque Rodriguez
- Email :
- xavier.roque@uab.cat
Teaching staff (external to UAB)
- Gonzalo Génova Fuster
Group languages
You can consult this information at the end of the document.
Prerequisites
There are none.
Objectives
To understand the classical concept of biologically based human intelligence.
To understand the technological concept of artificial intelligence based on the processing of information in a computational machine.
To understand the concept of computability introduced by Alan Turing, the basis of all computer science.
To understand the concept of a program stored in a computer as a set of instructions to execute an algorithm.
To understand the difference between a machine with a fixed program and a self-programming machine.
To understand the concept of technological singularity, and the limits faced from the computational paradigm.
To understand precisely the similarities and differences between natural intelligence and artificial intelligence.
Learning outcomes
- Produce creative papers and personal projects in the corresponding area of study.
- Gain familiarity with the different programmes of naturalistic study of the mind and their functioning.
- Identify formally correct and incorrect arguments by translating natural language utterances to formal language, and applying first-order logic to make demonstrations and deductions.
- Understand the concepts of numbering system, algorithm and computability, and appreciate their historical and practical importance.
- Programme simple algorithms and appreciate the logic of their functioning.
- Identify and evaluate the importance of the human factor in the development and use of symbolic systems.
- Make an informed judgement on the social and ethical challenges posed by artificial intelligence.
- Understand the notion of computability, and the concept of programme stored on a computer, as a set of instructions for executing an algorithm, and identify the difference between a machine with a fixed programme and a self-programmable machine.
- Integrate elements from different areas of knowledge to analyse a situation and suggest actions or solutions.
- Promote team spirit and the integration of others' points of view.
Contents
1. The classical conception of intelligence. Intelligence, rationality and self-consciousness. Theoretical reason, productive reason, practical reason.
2. The sciences of the artificial. Machines and artifacts. Structure and purpose of a machine.
3. Intelligence understood as the capacity to solve problems. What problems can be solved. Computability.
4. Computational machines as a substrate of artificial intelligence. Turing and Von Neumann.
5. The paradigm shift: explicit programming vs. machine learning. Problem solving. Emulation of human behavior.
6. The future and limits of artificial intelligence. The technological singularity. Machines ethics: freedom and responsibility.
7. The way back: natural intelligence understood in the light of artificial intelligence.
Learning activities and methodology
| Title | Hours | ECTS | Learning outcomes |
|---|---|---|---|
| Individual student work | 62.25 | 2.49 | 2, 3, 4, 5, 6, 7, 8, 9 |
| Essay supervision | 4.25 | 0.17 | 1, 9, 10 |
| Group work | 32.5 | 1.3 | 1, 9, 10 |
| Lectures | 33 | 1.32 | 2, 3, 4, 5, 6, 7, 8, 9 |
| Practical-theoretical lectures | 16 | 0.64 | 1, 2, 3, 4, 5, 6, 7, 8, 9 |
Theoretical classes.
Theoretical-practical classes.
Tutorials.
Group work.
Individual student work.
Assessment
Continuous assessment activities
| Title | Weight | Hours | ECTS | Learning outcomes |
|---|---|---|---|---|
| Partial examinations | 40% | 2 | 0.08 | 2, 3, 4, 5, 6, 7, 8, 9 |
| Final essay | 30% | 0 | 0 | 2, 3, 4, 5, 6, 7, 8, 9 |
| Group and individual essays | 30% | 0 | 0 | 1, 9, 10 |
Final essay.
Group and individual essays.
Partial examinations.
There will be a reevaluation exam. To be reevaluated, the student must have been evaluated in a set of activities whose weight equals to a minimum of two thirds of the total grade of the subject (continuous evaluation) or have completed all the required assessment activities (single assessment). The student will be deemed NOT AVALUABLE if he/she has not participated in all the assessment activities
In the event of a student committing any irregularity that may lead to a significant variation in the grade awarded to an assessment activity, the student will be given a zero for this activity, regardless of any disciplinary process that may take place. In the event of several irregularities in assessment activities of the same subject, the student will be given a zero as the final grade for this subject.
Single assessment
Students who opt for the single assessment system will have to submit an essay (50%) and take an exam (50%), on the indicated date.
This subject allows the use of AI technologies as an integral part of the submitted work, provided that the final result reflects a significant contribution from the student in terms of analysis and personal reflection. The student must clearly (i) identify which parts have been generated using AI technology; (ii) specify the tools used; and (iii) include a critical reflection on how these have influenced the process and final outcome of the activity. Lack of transparency regarding the use of AI in the assessed activity will be considered academic dishonesty; the corresponding grade may be lowered, or the work may even be awarded a zero. In cases of greater infringement, more serious action may be taken.
Bibliography
Basic References
Dreyfus, H. L. What Computers Can't Do: The Limits of Artificial Intelligence. New York: Harper and Row, 1972.
Gelernter, D. The Tides of Mind: Uncovering the Spectrum of Consciousness. New York: Liveright, 2016.
Tallis, R. Why the Mind Is Not a Computer: A Pocket Lexicon of Neuromythology. Exeter: Imprint Academic, 2004.
Basic Electronic Resources
Reaktor, Universidad de Helsinki. Elementos de IA. Curso online gratuito: https://www.elementsofai.com/es/
Software
No specific software is required.
Course groups and languages
The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE
| Type of teaching | Group | Language | Semester | Shift |
|---|---|---|---|---|
| (TE) Theory | 20 | Spanish | first semester | morning-mixed |
| (PAUL) Classroom practices | 20 | Spanish | first semester | morning-mixed |