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JOHN CABOT UNIVERSITY

COURSE CODE: "PH 323"
COURSE NAME: "The Ethics of Artificial Intelligence"
SEMESTER & YEAR: Spring 2022
SYLLABUS

INSTRUCTOR: Stefan Sorgner
EMAIL: [email protected]
HOURS: MW 7:30 PM - 8:45 PM
TOTAL NO. OF CONTACT HOURS: 45
CREDITS: 3
PREREQUISITES: Prerequisites: One previous philosophy course or Junior Standing Co-requisites: EN 110; Recommended Junior Standing
OFFICE HOURS:

COURSE DESCRIPTION:
This course examines some of the most important contemporary issues in the field of ethics of AI to help you to develop a familiarity with the debates and stimulate your ability to discuss, reflect on, and defend your own views. It is structured such as to provide all participants with a comprehensive understanding of ethical issues related to AI, which means that participants will be introduced to general concepts related to AI (Weak and strong AI, artificial general intelligence, artificial special/narrow intelligence, artificial superintelligence, machine learning), specific moral challenges such as AI and discrimination (e.g. racism, sexism), and wider ethical issues, which have to do with the spiralling power consumption and increasing carbon emissions due to data centres and cloud computing services.
SUMMARY OF COURSE CONTENT:
This course examines some of the most important contemporary issues in the field of ethics of AI to help you to develop a familiarity with the debates and stimulate your ability to discuss, reflect on, and defend your own views. It is structured such as to provide all participants with a comprehensive understanding of ethical issues related to AI, which means that participants will be introduced to general concepts related to AI (Weak and strong AI, artificial general intelligence, artificial special/narrow intelligence, artificial superintelligence, machine learning), specific moral challenges such as AI and discrimination (e.g. racism, sexism), and wider ethical issues, which have to do with the spiralling power consumption and increasing carbon emissions due to data centres and cloud computing services.
LEARNING OUTCOMES:
This course examines some of the most important contemporary issues in the field of ethics of AI to help you to develop a familiarity with the debates and stimulate your ability to discuss, reflect on, and defend your own views. It is structured such as to provide all participants with a comprehensive understanding of ethical issues related to AI, which means that participants will be introduced to general concepts related to AI (Weak and strong AI, artificial general intelligence, artificial special/narrow intelligence, artificial superintelligence, machine learning), specific moral challenges such as AI and discrimination (e.g. racism, sexism), and wider ethical issues, which have to do with the spiralling power consumption and increasing carbon emissions due to data centres and cloud computing services.
TEXTBOOK:
Book TitleAuthorPublisherISBN numberLibrary Call NumberCommentsFormatLocal BookstoreOnline Purchase
The Oxford Handbook of Ethics of AI Edited by Markus D. Dubber, Frank Pasquale, and Sunit DasOUP9780190067397     
An Introduction to Ethics in Robotics and AI (SpringerBriefs in Ethics) Bartneck, C., Lütge, C., Wagner, A., Welsh, S.Springer978-3-030-51110-4     
REQUIRED RESERVED READING:
NONE

RECOMMENDED RESERVED READING:
NONE
GRADING POLICY
-ASSESSMENT METHODS:
AssignmentGuidelinesWeight
Class Participation 10
Midterm examThe mid-term written assignment will be a ‘take-home’ assignment of 1000-2000 words (incl. bibliography), written in response to one of a selection of questions which I will provide. I will distribute the questions during week 6 and the assignment should be submitted by Friday of week 7. An electronic version of the project must be uploaded on moodle. (Title of Course/Term/Year) 30
PresentationsIn-class Presentation: Students are required to give two short individual presentations (5 - 10 minutes). The presentation will be well-organized, concise, and include (when opportune) audiovisual and electronic materials. An electronic version of the presentations must be uploaded on moodle. (Title of Course/Term/Year) The deadline is the last class. No materials will be accepted past the deadline. Please ask your instructor about your grade immediately after the class, in which you will have given the presentation.10
Final examThe final exam will consist in an essay. All students will have to answer the same question.20
Final projectFinal Project: The final paper (1000-2000 words, incl. bibliography) will be on any topic of the student’s choice related to the class program. The topic should be precisely defined and worthy of investigation. An electronic version of the project must be uploaded on moodle. (Title of Course/Term/Year) The deadline is the last class (session 28; the deadline is not the date of the final exam). No materials will be accepted past the deadline.30

-ASSESSMENT CRITERIA:
AWork of this quality directly addresses the question or problem raised and provides a coherent argument displaying an extensive knowledge of relevant information or content. This type of work demonstrates the ability to critically evaluate concepts and theory and has an element of novelty and originality. There is clear evidence of a significant amount of reading beyond that required for the course. 94 to 100 A; 90 to 93 A-
BThis is highly competent level of performance and directly addresses the question or problem raised.There is a demonstration of some ability to critically evaluatetheory and concepts and relate them to practice. Discussions reflect the student’s own arguments and are not simply a repetition of standard lecture andreference material. The work does not suffer from any major errors or omissions and provides evidence of reading beyond the required assignments. 87 to 89 B+; 84 to 86 B; 80 to 83 B-
CThis is an acceptable level of performance and provides answers that are clear but limited, reflecting the information offered in the lectures and reference readings. 75 to 79 C+; 70 to 74 C; 65-69 C-
DThis level of performances demonstrates that the student lacks a coherent grasp of the material.Important information is omitted and irrelevant points included.In effect, the student has barely done enough to persuade the instructor that s/he should not fail. 60 to 65 D+; 55 to 59 D; 50-54 D-
FThis work fails to show any knowledge or understanding of the issues raised in the question. Most of the material in the answer is irrelevant. 0 to 49 F

-ATTENDANCE REQUIREMENTS:
This course examines some of the most important contemporary issues in the field of ethics of AI to help you to develop a familiarity with the debates and stimulate your ability to discuss, reflect on, and defend your own views. It is structured such as to provide all participants with a comprehensive understanding of ethical issues related to AI, which means that participants will be introduced to general concepts related to AI (Weak and strong AI, artificial general intelligence, artificial special/narrow intelligence, artificial superintelligence, machine learning), specific moral challenges such as AI and discrimination (e.g. racism, sexism), and wider ethical issues, which have to do with the spiralling power consumption and increasing carbon emissions due to data centres and cloud computing services.
ACADEMIC HONESTY
As stated in the university catalog, any student who commits an act of academic dishonesty will receive a failing grade on the work in which the dishonesty occurred. In addition, acts of academic dishonesty, irrespective of the weight of the assignment, may result in the student receiving a failing grade in the course. Instances of academic dishonesty will be reported to the Dean of Academic Affairs. A student who is reported twice for academic dishonesty is subject to summary dismissal from the University. In such a case, the Academic Council will then make a recommendation to the President, who will make the final decision.
STUDENTS WITH LEARNING OR OTHER DISABILITIES
John Cabot University does not discriminate on the basis of disability or handicap. Students with approved accommodations must inform their professors at the beginning of the term. Please see the website for the complete policy.

SCHEDULE

SCHEDULE

 

Explanation:

Read 2, 5 means Read Book 2, chapter 5 (see textbooks)

 

Class schedule and topics

 

1Introduction

2 Introduction

Clarification of General Concepts

3 What is AI? Weak and strong AI, artificial general intelligence, artificial special/narrow intelligence, artificial superintelligence, machine learning, what is a robot? What is a cyborg? What is an embodied algorithm?

Read: 2, 2.1-2.2; 2, 2.3

4 Intelligence Explosion; Turing Test; Moore’s law; the Chinese room

Read: 1, 1

Surveillance

5 The Internet of Things, Security, and the Panopticon

Read: 1, 2

6 Intellectual Property Theories of Privacy vs Sanction Theories of Privacy

Read: 2, 8-8.2

7 Smart Cities need Upgraded Humans with an Internet of Bodily Things.

Read: 1, 44

Transportation

8 Autonomous Cars

Read: 2, 5

9 Hyperloop, Space X

Read: 1, 35

Money, Work, Law

10 Cryptocurrencies & Banking

Read: 1, 25

https://www.youtube.com/watch?v=fTTGALaRZoc

https://www.youtube.com/watch?v=s4g1XFU8Gto

11 Future of Work

Read: 1, 14

12 Algorithms and Work

Read: 1, 43

13 AI and Law 1

Read: 1, 38

14 AI and Law 2

Read: 1,39

15 AI and Law 3

Read: 1,40

16 Nudging, Advertisement, Social Media and Authenticity

Read: 2, 9.3.2

Politics

17 Global South, Global Justice, and the Digital Divide

Read: 1, 31

18 USA vs China

Read: 1, 32

19 China, Africa and Developmental Aid; or the Silk Road as Neo-Colonialization?

Read: 1, 33

20 Data Protection Laws and Europe

Read: 1, 34

21 AI and Refugees

Read: 1, 41

22 Sustainability, Climate Change, Blockchain Technologies, RFID Chips and Waste

https://www.youtube.com/watch?v=58xtN6Dw8kw

https://www.youtube.com/watch?v=B3JqCTWlzV8

https://www.youtube.com/watch?v=qsfr_HNdHZo

The Young and the Old

23 Digital Humanities

Read, 1, 37

24 Robots as Old-Age Companions; Psychological Care, and Exoskeletons

Read: 2, 9.3

Discrimination

25 Discrimination (e.g. Racism, Sexism)

Read: 2, 11.2.1; 1, 8; 1, 13

26 Deep Porn

Read: 1, 21

27 Getting ready for the finals 1

28 Getting ready for the finals 2