Presentation at Chief Data & Analytics Officer Conference Sydney, 20 March 2018

1. Data & Digital Ethics
Kate Carruthers
Version 1.0
March 2018
Classification: PUBLIC

2. Slides are available
https://www.slideshare.net/carruthk
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3. Agenda
1. Ethics and data
2. Why this important
3. Some traditional approaches
4. Some new approaches
5. What we need to do
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4. Ethics
Moral principles that govern a person's behaviour or the
way in which they conduct an activity…
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“We ask ethical questions whenever we think
about how we should act. Being ethical is a
part of what defines us as human beings.”
The Ethics Centre, Sydney

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6. Areas of focus
• Ethics of data - how we generate, record & share
data
• Ethics of algorithms - how we interpret data via
artificial intelligence, machine learning and robots
• Ethics of practices - devising responsible
innovation and professional codes to guide this
emerging science
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What is data ethics?
Luciano Floridi, Mariarosaria Taddeo
Phil. Trans. R. Soc. A 2016 374
20160360; DOI: 10.1098/rsta.2016.0360. Published
14 November 2016

7. 5 Propositions about data
1.Data is not neutral
2.There is no such thing as raw data
3.The signal to noise ratio has changed
4.Data is not inherently smart
5.The more data we have the less anonymity
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Privacy
Data
Governance
Cyber
Security
Ethics
The essentials

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http://www.informationisbeautiful.net/visualizations/worlds-biggest-data-breaches-
hacks/

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This Photo by Unknown Author is licensed under CC BY-NC-SA

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https://www.arnnet.com.au/article/609309/australian-red-cross-launches-investigation-after-massive-data-cock-up/

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http://www.news.com.au/technology/online/australias-2016-census-had-significant-and-obvious-oversights-report-
finds/news-story/6edcf8f897b2361965bd72683ee6edbe

13. Facebook study
“We show, via a massive (N = 689,003) experiment on Facebook,
that emotional states can be transferred to others via emotional
contagion, leading people to experience the same emotions without
their awareness. We provide experimental evidence that emotional
contagion occurs without direct interaction between people
(exposure to a friend expressing an emotion is sufficient), and in the
complete absence of nonverbal cues.”
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Kramer, A. D., Guillory, J. E., & Hancock, J. T. (2014). Experimental evidence of
massive-scale emotional contagion through social networks. Proceedings
of the National Academy of Sciences, 111(24), 8788-8790.

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http://thehackernews.com/2017/07/sweden-data-breach.html

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******
https://www.theverge.com/2016/3/24/11297050/tay-microsoft-chatbot-racist

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“Revealed: 50
million Facebook
profiles harvested
for Cambridge
Analytica in major
data breach”
https://www.theguardian.com/news/2018/mar/17/cambridge-analytica-facebook-influence-us-election

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https://medium.com/textifire/cambridge-analytica-microsofts-exploitative-ad-tech-c2db8633f542
May 2017: Cambridge Analytica: Microsoft’s Exploitative Ad-Tech
Trump & Brexit’s infamous data firm was allegedly grown in the Microsoft-funded
advertising research labs at Cambridge University.

18. Traditional approaches
• Security by Design
• Privacy by Design
• Examples:
oIEEE CS/ACM Code of Ethics
oACM Code of Ethics
• Guidelines
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19. 1. Minimize attack surface area
2. Establish secure defaults
3. Principle of Least privilege
4. Principle of Defence in depth
5. Fail securely
6. Don’t trust services
7. Separation of duties
8. Avoid security by obscurity
9. Keep security simple
10. Fix security issues correctly
OWASP Security by Design Principles
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Open Web Application Security Project
https://www.owasp.org/index.php/Security_by_Design_Principles

20. Privacy matters
Privacy by Design
1. Proactive not Reactive; Preventative not
Remedial
2. Privacy as the Default Setting
3. Privacy Embedded into Design
4. Full Functionality – Positive-Sum, not Zero-Sum
5. End-to-End Security – Full Lifecycle Protection
6. Visibility and Transparency – Keep it Open
7. Respect for User Privacy – Keep it User-Centric
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“Privacy is an inherent
human right, and a
requirement for
maintaining the human
condition with dignity and
respect.”
- Bruce Schneier
https://www.schneier.com/essays/archives/2006/05/the_eternal_value_of.html

21. IEEE CS/ACM Code of Ethics & Professional Practice
Software engineers shall commit themselves to making the analysis, specification, design, development, testing and maintenance of software a
beneficial and respected profession. In accordance with their commitment to the health, safety and welfare of the public, software engineers
shall adhere to the following Eight Principles:
1. Public: Software engineers shall act consistently with the public interest.
2. Client and Employer: Software engineers shall act in a manner that is in the best interests of their client and employer, consistent with the
public interest.
3. Product: Software engineers shall ensure that their products and related modifications meet the highest professional standards possible.
4. Judgement: Software engineers shall maintain integrity and independence in their professional judgment.
5. Management: Software engineering managers and leaders shall subscribe to and promote an ethical approach to the management of
software development and maintenance.
6. Profession: Software engineers shall advance the integrity and reputation of the profession consistent with the public interest.
7. Colleagues: Software engineers shall be fair to and supportive of their colleagues.
8. Self: Software engineers shall participate in lifelong learning regarding the practice of their profession and shall promote an ethical
approach to the practice of the profession.
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https://www.computer.org/web/education/code-of-ethics

22. ACM Code of Ethics
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As an ACM member I will
1. Contribute to society and human well-being.
2. Avoid harm to others.
3. Be honest and trustworthy.
4. Be fair and take action not to discriminate.
5. Honor property rights including copyrights and patent.
6. Give proper credit for intellectual property.
7. Respect the privacy of others.
8. Honor confidentiality.
From the ACM Code of Ethics http://www.acm.org/about/code-of-ethics

23. Accenture: 12 guidelines for developing data ethics codes
1. The highest priority is to respect the persons behind the data.
2. Attend to the downstream uses of datasets.
3. Provenance of the data and analytical tools shapes the consequences of
their use.
4. Strive to match privacy and security safeguards with privacy and security
expectations.
5. Always follow the law, but understand that the law is often a minimum bar.
6. Be wary of collecting data just for the sake of more data.
7. Data can be a tool of inclusion and exclusion.
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https://www.accenture.com/t20160629T012639__w__/us-en/_acnmedia/PDF-24/Accenture-Universal-Principles-Data-Ethics.pdf

24. Accenture: 12 guidelines for developing data ethics codes
8. As much as possible, explain methods for analysis and marketing to data
disclosers.
9. Data scientists and practitioners should accurately represent their
qualifications, limits to their expertise, adhere to professional standards,
and strive for peer accountability.
10.Aspire to design practices that incorporate transparency, configurability,
accountability, and auditability.
11.Products and research practices should be subject to internal, and
potentially external ethical review.
12.Governance practices should be robust, known to all team members and
reviewed regularly
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https://www.accenture.com/t20160629T012639__w__/us-en/_acnmedia/PDF-24/Accenture-Universal-Principles-Data-Ethics.pdf

25. Issues with Codes of Ethics
• Often nobody knows they exist
• Even if they do, nobody follows them
• If they do follow them it turns into work to rule
• It’s hard to articulate all ethical requirements in a code
• Needs strong institutional support
• Guidelines have similar issues
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“One Zettabyte is approximately equal to a
thousand Exabytes, a billion Terabytes, or a trillion
Gigabytes.”
https://blogs.cisco.com/sp/the-zettabyte-era-officially-begins-how-much-is-that

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Technology has no
ethics.
People demonstrate
ethics.

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Technology inherits
the biases of its
makers – therefore
we need diversity

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“Complexity is a defining
feature of the digital era, &
we are not adjusting our
governance structures to
manage it.” Kent Aiken, Prime Minister’s Fellow,
Public Policy Forum Canada, 2017

31. Some new approaches
• FATML – Fairness, Accountability and Transparency in
Machine Learning
• IEEE Global Initiative on Ethics of Autonomous and
Intelligent Systems
• Algorithmic Justice League
• Education in digital ethics
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http://www.fatml.org/

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https://standards.ieee.org/develop/indconn/ec/autonomous_systems.html

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Education

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We cannot leave
ethics to volunteer
groups!

37. Digital Ethics?
“A few guidelines are useful in most situations:
• Use the golden rule: ask yourself how you would like to
be treated as a human being, citizen or customer.
• There are always unintended consequences: embrace
new positive uses of technology, and block undesirable
uses.
• Success usually comes from exercising discipline and
self-restraint in using technology, rather than pushing the
limits.”
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Goasduff, C. L. (2016, March 07). Kick-Start the Conversation on Digital Ethics. Retrieved August 15, 2017, from
http://www.gartner.com/smarterwithgartner/kick-start-the-conversation-on-digital-ethics/

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We need formal ways
to consider the ethical
implications of data
and its uses

39. Slides are available
https://www.slideshare.net/carruthk
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40. Resources
Georgetown University, Kennedy Institute of Ethics, Ethics Lab
Causeit Data Ethics
The BIG Data Ethics Cheat Sheet, Hackermoon
Digital Ethics Lab - Oxford Internet Institute - University of Oxford
Guidelines on Ethical Research - British Sociological Association
What is data ethics? Luciano Floridi, Mariarosaria Taddeo. Phil. Trans. R. Soc. A 2016 374
20160360; DOI: 10.1098/rsta.2016.0360. Published 14 November 2016
Digital Enlightenment Forum: Digital Ethics. Workshop Report. (2016, March 1). Retrieved August 16, 2017, from
https://digitalenlightenment.org/sites/default/files/users/14/Digital%20Ethics%20Workshop%20Report%20v2.pdf
A deep study on the concept of digital ethics. Maggiolini, Piercarlo. (2014).. Revista de Administração de
Empresas, 54(5), 585-591. https://dx.doi.org/10.1590/S0034-759020140511
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41. Thank you
Kate Carruthers
k.carruthers@unsw.edu.au
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