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Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Software Engineering Institute
Carnegie Mellon University
Pittsburgh, PA 15213
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
PyCon 2020
Implementing Ethics:
Developing Trustworthy AI
Carol J. Smith
Sr. Research Scientist - Human-Machine Interaction
Twitter: @carologic @sei_etc
2
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Legal
Copyright 2020 Carnegie Mellon University.
This material is based upon work funded and supported by the Department of Defense under Contract No. FA8702-15-D-0002 with Carnegie Mellon University for the
operation of the Software Engineering Institute, a federally funded research and development center.
The view, opinions, and/or findings contained in this material are those of the author(s) and should not be construed as an official Government position, policy, or
decision, unless designated by other documentation.
References herein to any specific commercial product, process, or service by trade name, trade mark, manufacturer, or otherwise, does not necessarily constitute or
imply its endorsement, recommendation, or favoring by Carnegie Mellon University or its Software Engineering Institute.
NO WARRANTY. THIS CARNEGIE MELLON UNIVERSITY AND SOFTWARE ENGINEERING INSTITUTE MATERIAL IS FURNISHED ON AN "AS-IS" BASIS.
CARNEGIE MELLON UNIVERSITY MAKES NO WARRANTIES OF ANY KIND, EITHER EXPRESSED OR IMPLIED, AS TO ANY MATTER INCLUDING, BUT NOT
LIMITED TO, WARRANTY OF FITNESS FOR PURPOSE OR MERCHANTABILITY, EXCLUSIVITY, OR RESULTS OBTAINED FROM USE OF THE MATERIAL.
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This material may be reproduced in its entirety, without modification, and freely distributed in written or electronic form without requesting formal permission.
Permission is required for any other use. Requests for permission should be directed to the Software Engineering Institute at permission@sei.cmu.edu.
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Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Goal: Create AI systems
that are safe
and trustworthy
4
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
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Early, purposeful work
Not just algorithms
Conduct, interactions, intents
5
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Start with a diverse team
Gender, race, culture,
education (school, program,
etc.), thinking process,
disability status,
and more…
Image:https://www.flickr.com/photos/byrawpixel/45739276192/in/photostream/
Createdwithlovebyrawpixel.com.
DownloadthisimageinhighresolutionunderCreativeCommons0atwww.rawpixel.com.
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Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
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Not lowering bar
– extending it
7
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
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Diverse, Talented and Multi-Disciplinary
Includes skill set and problem framing approach
Data Scientists
Machine learning experts
Programmers
System architects
Product managers, etc.
(context dependent)
8
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Curiosity Experts
Understand
•Situation
•Abilities of people who will use system
•How system will be used
Activate curiosity in others via UX activities
Social scientists, ethicists and more…
9
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
High value in diverse teams
Focus more on facts
Process facts more carefully
More innovative
“…become more aware of their own potential biases”
Why Diverse Teams Are Smarter. Harvard Business Review.
https://hbr.org/2016/11/why-diverse-teams-are-smarter
10
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
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Great Minds Think Different
11
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Inclusive Workplace Requirements
Representatively diverse leadership = retention
Individuals differences are acknowledged and accepted
•Bring "whole selves" to work
•Welcoming community environment
•Feel valued, connected, that we belong
11
12
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Adopt Technology Ethics
•Harmonize cultural variations
•Balance to pace of change,
industry pressure
•Explicit permission to consider
and question breadth
of implications
13
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
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Coalesce on Shared Set of Technology Ethics
1. Well-being
2. Respect for autonomy
3. Protection of privacy and intimacy
4. Solidarity
5. Democratic participation
6. Equity
7. Diversity inclusion
8. Prudence
9. Responsibility
10. Sustainable development
Montréal Declaration for a responsible development of artificial intelligence.
https://www.montrealdeclaration-responsibleai.com/the-declaration
14
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Diverse,
inclusive
leaders
Diverse,
Multi-
Disciplinary
Teams
Shared
Tech Ethics
15
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
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UX Framework
Designing Trustworthy AI
16
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
How do we get there?
Montréal Declaration for a responsible development of artificial intelligence.
https://www.montrealdeclaration-responsibleai.com/the-declaration
? Trustable,
Ethical AI
17
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
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release and unlimited distribution. Please see Copyright notice for non-US
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Conversations for Understanding
UX Framework guides AI development teams
Difficult Topics
•What do we value?
•Who could be hurt?
•What lines won’t our AI cross?
•How are we shifting power?*
•How will we track our progress?
*“How is this ML model shifting power?" @riakall
#NeurIPS2019
18
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
New uncomfortable work
“Be uncomfortable”
- Laura Kalbag
Ethical design is not superficial.
19
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
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release and unlimited distribution. Please see Copyright notice for non-US
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Prompt conversations with a checklist
Paired with Technical Ethics
•Bridge gap between
“do no harm” and reality
Reduce risk and unwanted
bias
Mitigation planning
Support inspection
Checklist and Agreement - Downloadable PDF:
https://resources.sei.cmu.edu/library/asset-view.cfm?assetid=636620
20
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Prompts in checklists help reveal hidden tasks
21
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
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release and unlimited distribution. Please see Copyright notice for non-US
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UX Framework for Designing Trustworthy AI
Ethical
AI
1.Accountable
to humans
1.Cognizant
of speculative risks
and benefits
Respectful
and secure
1.Honest and
usable
22
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
RightStaff Scenario
AI shift scheduling system
Users: Store managers of fast food restaurants
Goals of RightStaff:
• Faster staffing decisions and scheduling
• Reduced bias of shift selection
23
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Accountable to Humans
Ensure humans have ultimate control
•Able to monitor and control risk
Human responsibility for final decisions
•Person’s life
•Quality of life
•Health
•Reputation Ethical
AI
1.Accountable
to humans
1.Speculative
Respectful
and secure
1.Honest
and usable
24
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
“Ensure humans can unplug the machines”
– Grady Booch
TED Talk, Grady Booch, Scientist, Philosopher, IBM’er
https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
25
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Significant decisions
Significant decisions made by the AI system will be
• explained
• able to be overridden
• appealable and reversible
RightStaff
• Manager able to reschedule people as needed
26
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Responsibilities explicitly defined
Between AI system and human(s)
RightStaff (AI System or Manager?)
• Picks employees to schedule?
• Defines shifts?
• Method to integrate new information?
• Sick time
• Resignations
27
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
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Would we want
RightStaff to turn
off by itself, if noticed issues?
Implications?
28
Implementing Ethics: Developing Trustworthy AI
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[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Cognizant of Speculative Risks and Benefits
Identify full range of
•Harmful, malicious use, as well as good, beneficial use
•Blind spots and unwanted/unintended consequences
Ethical
AI
1.Accountable
to humans
1.Speculativ
e
Respectful
and secure
1.Honest
and usable
29
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Speculative: Conduct UX research
and activate curiosity
Speculate about misuse
and abuse
Create “Black Mirror”
episodes
Potential severe abuse
and consequences
Abusability Testing
Template by: Anna Abovyan & Allison Cosby, IxDA
Pittsburgh, Sep 2019
30
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Potential Abusability of RightStaff
RightStaff goals:
• Faster staffing decisions and scheduling
• Reduced bias of shift selection
Abusability of RightStaff:
• System begins prioritizing people with easier schedules
• Managers approve these schedules, reinforcing bias
• People who were previously discriminated against
are still discriminated against
31
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Speculative: Create communication
& mitigation plans
Plan for unwanted consequences
Misuse and abuse of AI system
•Who can report?
•To whom?
•Turn off?
•Who notified?
•Consequences?
32
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
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release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Respectful and Secure
Values of humanity, ethics, equity, fairness,
accessibility, diversity and inclusion
Respect privacy and data rights
Make system robust, valid and reliable
Provide understandable security
Ethical
AI
1.Accountable
to humans
1.Speculative
Respectful
and secure
1.Honest
and usable
33
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
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release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Respectful and Secure
RightStaff
• Who has visibility to reasons for changing schedules?
• How is that information used?
• How is PII* of employees protected?
*PII is Personally Identifiable Information (social security number, address, etc.)
34
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
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release and unlimited distribution. Please see Copyright notice for non-US
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Honest and Usable
Value transparency with the goal of engendering trust
Explicitly state identity as an AI system
Ethical
AI
1.Accountable
to humans
1.Speculative
Respectful
and secure
1.Honest
and usable
35
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
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release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Fair: Remove unwanted bias in data
Show awareness of known and desirable bias
Acknowledge issues
Overcommunicate on issues
RightStaff
• System built to reduce the known bias in existing data
• Make it easy to report bias (or prevent it)
36
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
UX Framework: Being intentional, keeping
people safe
Ethical
AI
1.Accountable
to humans
1.Cognizant
of speculative risks
and benefits
Respectful
and secure
1.Honest and
usable
37
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
We aren’t perfect, AI won’t be perfect
Diverse teams, inclusive environments
Adopt technical ethics
Encourage deep conversations (Checklist)
Activate curiosity; be speculative; imaginative
Ethical
AI
1.Accountable
to humans
1.Speculative
Respectful
and secure
1.Honest
and usable
38
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Reward team members for finding ethics bugs
Dr. Ayanna Howard
- on the Artificial Intelligence Podcast with Lex Fridman
39
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Evangelize
for human values
Ethical. Transparent. Fair.
40
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
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release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Learn More
SEI on HMT: https://sei.cmu.edu/research-capabilities/all-
work/display.cfm?customel_datapageid_4050=197910
41
Implementing Ethics: Developing Trustworthy AI
© 2020 Carnegie Mellon University
[DISTRIBUTION STATEMENT A] This material has been approved for public
release and unlimited distribution. Please see Copyright notice for non-US
Government use and distribution.
Carol J. Smith
cjsmith@sei.cmu.edu
Twitter: @carologic
SEI Emerging Technology Center
Twitter: @sei_etc

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Implementing Ethics: Developing Trustworthy AI PyCon 2020

  • 1. 1 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Software Engineering Institute Carnegie Mellon University Pittsburgh, PA 15213 [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. PyCon 2020 Implementing Ethics: Developing Trustworthy AI Carol J. Smith Sr. Research Scientist - Human-Machine Interaction Twitter: @carologic @sei_etc
  • 2. 2 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Legal Copyright 2020 Carnegie Mellon University. This material is based upon work funded and supported by the Department of Defense under Contract No. FA8702-15-D-0002 with Carnegie Mellon University for the operation of the Software Engineering Institute, a federally funded research and development center. The view, opinions, and/or findings contained in this material are those of the author(s) and should not be construed as an official Government position, policy, or decision, unless designated by other documentation. References herein to any specific commercial product, process, or service by trade name, trade mark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by Carnegie Mellon University or its Software Engineering Institute. NO WARRANTY. THIS CARNEGIE MELLON UNIVERSITY AND SOFTWARE ENGINEERING INSTITUTE MATERIAL IS FURNISHED ON AN "AS-IS" BASIS. CARNEGIE MELLON UNIVERSITY MAKES NO WARRANTIES OF ANY KIND, EITHER EXPRESSED OR IMPLIED, AS TO ANY MATTER INCLUDING, BUT NOT LIMITED TO, WARRANTY OF FITNESS FOR PURPOSE OR MERCHANTABILITY, EXCLUSIVITY, OR RESULTS OBTAINED FROM USE OF THE MATERIAL. CARNEGIE MELLON UNIVERSITY DOES NOT MAKE ANY WARRANTY OF ANY KIND WITH RESPECT TO FREEDOM FROM PATENT, TRADEMARK, OR COPYRIGHT INFRINGEMENT. [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. This material may be reproduced in its entirety, without modification, and freely distributed in written or electronic form without requesting formal permission. Permission is required for any other use. Requests for permission should be directed to the Software Engineering Institute at permission@sei.cmu.edu. DM20-0164
  • 3. 3 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Goal: Create AI systems that are safe and trustworthy
  • 4. 4 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Early, purposeful work Not just algorithms Conduct, interactions, intents
  • 5. 5 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Start with a diverse team Gender, race, culture, education (school, program, etc.), thinking process, disability status, and more… Image:https://www.flickr.com/photos/byrawpixel/45739276192/in/photostream/ Createdwithlovebyrawpixel.com. DownloadthisimageinhighresolutionunderCreativeCommons0atwww.rawpixel.com.
  • 6. 6 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Not lowering bar – extending it
  • 7. 7 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Diverse, Talented and Multi-Disciplinary Includes skill set and problem framing approach Data Scientists Machine learning experts Programmers System architects Product managers, etc. (context dependent)
  • 8. 8 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Curiosity Experts Understand •Situation •Abilities of people who will use system •How system will be used Activate curiosity in others via UX activities Social scientists, ethicists and more…
  • 9. 9 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. High value in diverse teams Focus more on facts Process facts more carefully More innovative “…become more aware of their own potential biases” Why Diverse Teams Are Smarter. Harvard Business Review. https://hbr.org/2016/11/why-diverse-teams-are-smarter
  • 10. 10 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Great Minds Think Different
  • 11. 11 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Inclusive Workplace Requirements Representatively diverse leadership = retention Individuals differences are acknowledged and accepted •Bring "whole selves" to work •Welcoming community environment •Feel valued, connected, that we belong 11
  • 12. 12 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Adopt Technology Ethics •Harmonize cultural variations •Balance to pace of change, industry pressure •Explicit permission to consider and question breadth of implications
  • 13. 13 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Coalesce on Shared Set of Technology Ethics 1. Well-being 2. Respect for autonomy 3. Protection of privacy and intimacy 4. Solidarity 5. Democratic participation 6. Equity 7. Diversity inclusion 8. Prudence 9. Responsibility 10. Sustainable development Montréal Declaration for a responsible development of artificial intelligence. https://www.montrealdeclaration-responsibleai.com/the-declaration
  • 14. 14 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Diverse, inclusive leaders Diverse, Multi- Disciplinary Teams Shared Tech Ethics
  • 15. 15 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. UX Framework Designing Trustworthy AI
  • 16. 16 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. How do we get there? Montréal Declaration for a responsible development of artificial intelligence. https://www.montrealdeclaration-responsibleai.com/the-declaration ? Trustable, Ethical AI
  • 17. 17 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Conversations for Understanding UX Framework guides AI development teams Difficult Topics •What do we value? •Who could be hurt? •What lines won’t our AI cross? •How are we shifting power?* •How will we track our progress? *“How is this ML model shifting power?" @riakall #NeurIPS2019
  • 18. 18 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. New uncomfortable work “Be uncomfortable” - Laura Kalbag Ethical design is not superficial.
  • 19. 19 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Prompt conversations with a checklist Paired with Technical Ethics •Bridge gap between “do no harm” and reality Reduce risk and unwanted bias Mitigation planning Support inspection Checklist and Agreement - Downloadable PDF: https://resources.sei.cmu.edu/library/asset-view.cfm?assetid=636620
  • 20. 20 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Prompts in checklists help reveal hidden tasks
  • 21. 21 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. UX Framework for Designing Trustworthy AI Ethical AI 1.Accountable to humans 1.Cognizant of speculative risks and benefits Respectful and secure 1.Honest and usable
  • 22. 22 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. RightStaff Scenario AI shift scheduling system Users: Store managers of fast food restaurants Goals of RightStaff: • Faster staffing decisions and scheduling • Reduced bias of shift selection
  • 23. 23 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Accountable to Humans Ensure humans have ultimate control •Able to monitor and control risk Human responsibility for final decisions •Person’s life •Quality of life •Health •Reputation Ethical AI 1.Accountable to humans 1.Speculative Respectful and secure 1.Honest and usable
  • 24. 24 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. “Ensure humans can unplug the machines” – Grady Booch TED Talk, Grady Booch, Scientist, Philosopher, IBM’er https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
  • 25. 25 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Significant decisions Significant decisions made by the AI system will be • explained • able to be overridden • appealable and reversible RightStaff • Manager able to reschedule people as needed
  • 26. 26 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Responsibilities explicitly defined Between AI system and human(s) RightStaff (AI System or Manager?) • Picks employees to schedule? • Defines shifts? • Method to integrate new information? • Sick time • Resignations
  • 27. 27 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Would we want RightStaff to turn off by itself, if noticed issues? Implications?
  • 28. 28 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Cognizant of Speculative Risks and Benefits Identify full range of •Harmful, malicious use, as well as good, beneficial use •Blind spots and unwanted/unintended consequences Ethical AI 1.Accountable to humans 1.Speculativ e Respectful and secure 1.Honest and usable
  • 29. 29 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Speculative: Conduct UX research and activate curiosity Speculate about misuse and abuse Create “Black Mirror” episodes Potential severe abuse and consequences Abusability Testing Template by: Anna Abovyan & Allison Cosby, IxDA Pittsburgh, Sep 2019
  • 30. 30 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Potential Abusability of RightStaff RightStaff goals: • Faster staffing decisions and scheduling • Reduced bias of shift selection Abusability of RightStaff: • System begins prioritizing people with easier schedules • Managers approve these schedules, reinforcing bias • People who were previously discriminated against are still discriminated against
  • 31. 31 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Speculative: Create communication & mitigation plans Plan for unwanted consequences Misuse and abuse of AI system •Who can report? •To whom? •Turn off? •Who notified? •Consequences?
  • 32. 32 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Respectful and Secure Values of humanity, ethics, equity, fairness, accessibility, diversity and inclusion Respect privacy and data rights Make system robust, valid and reliable Provide understandable security Ethical AI 1.Accountable to humans 1.Speculative Respectful and secure 1.Honest and usable
  • 33. 33 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Respectful and Secure RightStaff • Who has visibility to reasons for changing schedules? • How is that information used? • How is PII* of employees protected? *PII is Personally Identifiable Information (social security number, address, etc.)
  • 34. 34 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Honest and Usable Value transparency with the goal of engendering trust Explicitly state identity as an AI system Ethical AI 1.Accountable to humans 1.Speculative Respectful and secure 1.Honest and usable
  • 35. 35 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Fair: Remove unwanted bias in data Show awareness of known and desirable bias Acknowledge issues Overcommunicate on issues RightStaff • System built to reduce the known bias in existing data • Make it easy to report bias (or prevent it)
  • 36. 36 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. UX Framework: Being intentional, keeping people safe Ethical AI 1.Accountable to humans 1.Cognizant of speculative risks and benefits Respectful and secure 1.Honest and usable
  • 37. 37 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. We aren’t perfect, AI won’t be perfect Diverse teams, inclusive environments Adopt technical ethics Encourage deep conversations (Checklist) Activate curiosity; be speculative; imaginative Ethical AI 1.Accountable to humans 1.Speculative Respectful and secure 1.Honest and usable
  • 38. 38 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Reward team members for finding ethics bugs Dr. Ayanna Howard - on the Artificial Intelligence Podcast with Lex Fridman
  • 39. 39 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Evangelize for human values Ethical. Transparent. Fair.
  • 40. 40 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Learn More SEI on HMT: https://sei.cmu.edu/research-capabilities/all- work/display.cfm?customel_datapageid_4050=197910
  • 41. 41 Implementing Ethics: Developing Trustworthy AI © 2020 Carnegie Mellon University [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Carol J. Smith cjsmith@sei.cmu.edu Twitter: @carologic SEI Emerging Technology Center Twitter: @sei_etc