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Tim Miller, Kobi Leins, Simon Coghlan, Marc
Cheong
School of Computing and Information Systems
Centre for AI & Digital Ethics
The University of Melbourne
3Subject
overview
Who are we?
4
Simon
Kobi
Tim
Marc
Tutors
5
Kate
Michael
Matt
COMP90087 Learning outcomes
On completion of this subject, students should:
? Understand and describe the social and ethical issues raised by technology in
various contexts
? Apply established ethical theories to reason about social and ethical issues
related to technology
? Critically examine, analyse, and apply ethical perspectives to design, develop
and deploy of digital technologies responsibly
? Communicate perspectives to other technical professionals and the
community at large
? Demonstrate a profound respect for that fact that just because you can, does
not mean you should create a technology
6
COMP90087 Assessment
7
Description Timing Percentage
Tutorial participation and
contributions to online discussion.
Two hours per week. Intended
Learning Outcomes (ILO's) 1 to 4 are
addressed by tutorial participation
and contributions to online
discussion.
2% each; best 10 of 12
Throughout the teaching period 20%
Critical evaluation essay. ILO's 1 to 5
are addressed in the essay.
? 35-45 hours
Week 7 30%
Research essay. Due first week of
examination period. ILO's 1 to 5 are
addressed in the essay.
? 35-45 hours
During the examination period 30%
Online quiz. ILO's 1 and 2 are
addressed in the online quiz.
? 1 hours
End of semester 20%
COMP90087 Agenda
One module per week
Each module:
? Readings (1-2 papers)
? Video playlist (30-60 minutes), with notes
? Consultation & discussion hour: 9-10am on Thursdays (on Wednesday in
week 2)
? Tutorial
? Group discussion on relevant topic
8
Interaction
When you need advice, input, direction:
? Check Canvas for announcements.
? Check the relevant discussion forum for existing answers.
? Post a question to the relevant discussion forum
? Feel free to answer others�� questions!
? Attend a consultation hour (Thu 9am Melbourne time).
? Ask your tutor during the tutorial.
? For personal matters, send an email:
? Please do not email more than one staff member independently
about the same issue. It duplicates work between us.
? We commit to responding within 1 working day
? Please do not expect replies over the weekend
9
10
The Ethics
of Artificial
Intelligence
Six types of ethical concerns
11
Inscrutable evidence
Inconclusive evidence
Traceability
Transformative effects
Unfair outcomes
Misguided evidence
Epistemic
concerns
Normative
concerns
Tsamados, Andreas, et al. "The ethics of algorithms: key problems and solutions." Available at SSRN 3662302 (2020).
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3662302
Six types of ethical concerns
12
Inscrutable evidence
Inconclusive evidence
Traceability
Transformative effects
Unfair outcomes
Misguided evidence
Caused by:
? Incomplete data sets
? Data sets with structural inequalities
Impact:
? Erroneous actionable insights
Six types of ethical concerns
13
Inscrutable evidence
Inconclusive evidence
Traceability
Transformative effects
Unfair outcomes
Misguided evidence
Caused by:
? Lack of appropriate tools for transparency
? Cognitive impossibility of interpretation
Impact:
? Erroneous actionable insights
? Shirk responsbility
Six types of ethical concerns
14
Inscrutable evidence
Traceability
Transformative effects
Unfair outcomes
Inconclusive evidence
Misguided evidence
Caused by:
? Use of unsuitable features/variables
? Use of model in different context
Impact:
? Biased algorithms
Six types of ethical concerns
15
Inscrutable evidence
Traceability
Transformative effects
Misguided evidence
Inconclusive evidence
Unfair outcomes
Caused by:
? Inconclusive or misguided evidence
Mitigations
? Third-party auditing
? Collaborative community-based design
Six types of ethical concerns
16
Inscrutable evidence
Traceability
Unfair outcomes
Misguided evidence
Inconclusive evidence
Transformative effects
Caused by:
? Users�� limited understanding of algorithms
? Choices constrained by algorithms
? Insufficient recourse
Impact:
? Reduction in human autonomy
Six types of ethical concerns
17
Inscrutable evidence
Transformative effects
Unfair outcomes
Misguided evidence
Inconclusive evidence
Traceability
Caused by:
? Lack of transparency, explainability, and
accountability
Impacts:
? Lack of moral responsbility
? ��Agency laundering��
18
Syllabus
COMP90087 Syllabus
19
Week Module Coordinator
1 Trust, machine, and digital ethics Tim
2 The History of Artificial Intelligence Tim
3 Philosophy and ethics Simon
4 Fairness and accountability Simon
5 Data governance Marc
6 Accessibility and equity Marc
7 Transparency: Decisions & processes Marc
8 Explainability Tim
9 Politics and policy Kobi
10 Frameworks and implementation Kobi
11 Reliability and safety Kobi
12 Bringing it together Simon
Have fun!
Tim Miller, Kobi Leins, Simon Coghlan, Marc
Cheong
School of Computing and Information Systems
Centre for AI & Digital Ethics
The University of Melbourne
3Subject
overview
Who are we?
4
Simon
Kobi
Tim
Marc
Tutors
5
Kate
Michael
Matt
COMP90087 Learning outcomes
On completion of this subject, students should:
? Understand and describe the social and ethical issues raised by technology in
various contexts
? Apply established ethical theories to reason about social and ethical issues
related to technology
? Critically examine, analyse, and apply ethical perspectives to design, develop
and deploy of digital technologies responsibly
? Communicate perspectives to other technical professionals and the
community at large
? Demonstrate a profound respect for that fact that just because you can, does
not mean you should create a technology
6
COMP90087 Assessment
7
Description Timing Percentage
Tutorial participation and
contributions to online discussion.
Two hours per week. Intended
Learning Outcomes (ILO's) 1 to 4 are
addressed by tutorial participation
and contributions to online
discussion.
2% each; best 10 of 12
Throughout the teaching period 20%
Critical evaluation essay. ILO's 1 to 5
are addressed in the essay.
? 35-45 hours
Week 7 30%
Research essay. Due first week of
examination period. ILO's 1 to 5 are
addressed in the essay.
? 35-45 hours
During the examination period 30%
Online quiz. ILO's 1 and 2 are
addressed in the online quiz.
? 1 hours
End of semester 20%
COMP90087 Agenda
One module per week
Each module:
? Readings (1-2 papers)
? Video playlist (30-60 minutes), with notes
? Consultation & discussion hour: 9-10am on Thursdays (on Wednesday in
week 2)
? Tutorial
? Group discussion on relevant topic
8
Interaction
When you need advice, input, direction:
? Check Canvas for announcements.
? Check the relevant discussion forum for existing answers.
? Post a question to the relevant discussion forum
? Feel free to answer others�� questions!
? Attend a consultation hour (Thu 9am Melbourne time).
? Ask your tutor during the tutorial.
? For personal matters, send an email:
? Please do not email more than one staff member independently
about the same issue. It duplicates work between us.
? We commit to responding within 1 working day
? Please do not expect replies over the weekend
9
10
The Ethics
of Artificial
Intelligence
Six types of ethical concerns
11
Inscrutable evidence
Inconclusive evidence
Traceability
Transformative effects
Unfair outcomes
Misguided evidence
Epistemic
concerns
Normative
concerns
Tsamados, Andreas, et al. "The ethics of algorithms: key problems and solutions." Available at SSRN 3662302 (2020).
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3662302
Six types of ethical concerns
12
Inscrutable evidence
Inconclusive evidence
Traceability
Transformative effects
Unfair outcomes
Misguided evidence
Caused by:
? Incomplete data sets
? Data sets with structural inequalities
Impact:
? Erroneous actionable insights
Six types of ethical concerns
13
Inscrutable evidence
Inconclusive evidence
Traceability
Transformative effects
Unfair outcomes
Misguided evidence
Caused by:
? Lack of appropriate tools for transparency
? Cognitive impossibility of interpretation
Impact:
? Erroneous actionable insights
? Shirk responsbility
Six types of ethical concerns
14
Inscrutable evidence
Traceability
Transformative effects
Unfair outcomes
Inconclusive evidence
Misguided evidence
Caused by:
? Use of unsuitable features/variables
? Use of model in different context
Impact:
? Biased algorithms
Six types of ethical concerns
15
Inscrutable evidence
Traceability
Transformative effects
Misguided evidence
Inconclusive evidence
Unfair outcomes
Caused by:
? Inconclusive or misguided evidence
Mitigations
? Third-party auditing
? Collaborative community-based design
Six types of ethical concerns
16
Inscrutable evidence
Traceability
Unfair outcomes
Misguided evidence
Inconclusive evidence
Transformative effects
Caused by:
? Users�� limited understanding of algorithms
? Choices constrained by algorithms
? Insufficient recourse
Impact:
? Reduction in human autonomy
Six types of ethical concerns
17
Inscrutable evidence
Transformative effects
Unfair outcomes
Misguided evidence
Inconclusive evidence
Traceability
Caused by:
? Lack of transparency, explainability, and
accountability
Impacts:
? Lack of moral responsbility
? ��Agency laundering��
18
Syllabus
COMP90087 Syllabus
19
Week Module Coordinator
1 Trust, machine, and digital ethics Tim
2 The History of Artificial Intelligence Tim
3 Philosophy and ethics Simon
4 Fairness and accountability Simon
5 Data governance Marc
6 Accessibility and equity Marc
7 Transparency: Decisions & processes Marc
8 Explainability Tim
9 Politics and policy Kobi
10 Frameworks and implementation Kobi
11 Reliability and safety Kobi
12 Bringing it together Simon
Have fun!