There is a common agreement that ethical concerns are of high importance when it comes to systems equipped with Artificial Intelligence (AI). Demands for ethical AI are declared from all directions. As a response, in recent years, public bodies, governments, and universities have rushed in to provide a set of principles to be considered when AI-based systems are designed and used. We have learned, however, that high-level principles do not turn easily into actionable advice for practitioners. Hence, also companies are publishing their own ethical guidelines to guide their AI development. These guidelines do not seem to help the developers. To bridge this gap, we present a method for implementing AI Ethics in practice. The ECCOLA method has been developed in collaboration with researchers and practitioners in the field, and it is under proof-testing in several AI companies. The presentation outlines the method and its practical use cases.

1. From Principles to Action:
A Method for Ethically Aligned AI
Design and Implementation
Professor Pekka Abrahamsson
University of Jyväskylä, Finland
17th International Conference on Emerging
Technologies for a Smarter World (CEWIT 2021)
November-3rd, 2021, Online
Photo by Markus Spiske from Pexels

2. Pekka Abrahamsson
• Dr. Pekka Abrahamsson works as a full professor of information systems and
software engineering at the University of Jyväskylä in Finland. He received his
PhD in Software Engineering in 2002 from the University of Oulu. His research
is in the area of emerging software technologies, empirical software
engineering, software startups, and the ethics of artificial intelligence.
• Before his current position, he has served as a full professor at the University
of Helsinki (Finland), Free University of Bolzano (Italy), Norwegian University
of Science and Technology (Norway). He also worked at VTT Technical
Research Centre of Finland as a research professor of software technologies.
• He is widely recognized for his academic achievements. He is a pioneer in the
field of research on agile software engineering methods and processes.
Abrahamsson is the most cited researcher in his field in Finland. He is the first
Professor of Software Engineering to be invited to the Finnish Academy of
Science and Letters.
• He has published broadly in his areas of expertise and received many awards
and recognitions. Arnetminer named him among the 100 most influential
software engineering scientists in the world in 2016. Abrahamsson was
awarded the Nokia Foundation Award 2007. He is the Software Startup
Research Network (SSRN) co-founder and a seasoned expert in leading large
research projects.

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ETHICAL CONCERNS TO DEAL WITH
Data Ethics
Safety
Concerns
Normative
Concerns
‘Existential’
Concerns
Epistemic
Concerns
Justice
Related

7. Manipulatibity
Safety
Vulnerability
Volalitility
Robustness
Sustainability Depentability Friendliness Shameability
Pleasurability Substitution of human contact
Normative recognition Data quality
Moral de/re/upskilling Alientation Dignity
Virtuousness Trustability
Benevolence Care concerns Abusability
Responsibility Value sensitivity Malevolence Lethality
Maleficence
Fairness Unpredictability Social sorting
Social solidarity Universal service
Respect for autonomy
Legality
Consent
Access to data
Data collection limitation
Privacy Foreseeability
Predictability
Deceptability Liability
Transparency Righteousness
Blamability
Biasness
Source: Vakkuri, V. and Abrahamsson, P., 2018. The key concepts of ethics
of artificial intelligence. In 2018 IEEE International Conference on
Engineering, Technology and Innovation (ICE/ITMC) (pp. 1-6). IEEE.

8. 211 companies
were surveyed.
It is a jungle out
there…
Source: Vakkuri, Kemell, Kultanen, and Abrahamsson. "The Current State of Industrial
Practice in Artificial Intelligence Ethics." IEEE Software 37, no. 4 (2020): 50-57.
- Similar response trends whether the company
develops AI or not
- Mixed maturity in dealing with ethical concerns
- Public and academic discussion not transferred
to practice yet
- Only 51% of companies were confident there
system could not be misused

9. “I am sure
someone
[else] takes
care of this”
Source: Vakkuri, V., Kemell, K.K., Jantunen, M. and Abrahamsson, P., 2020, June. “This is Just a Prototype”: How Ethics
Are Ignored in Software Startup-Like Environments. In International Conference on Agile Software Development (pp.
195-210). Springer, Cham.

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11. How to fix the problem?
Source: C. Ebert, P. Abrahamsson and N. Oza, "Lean Software
Development," in IEEE Software, vol. 29, no. 5, pp. 22-25, Sept.-Oct.
2012, doi: 10.1109/MS.2012.116.

12. Research Gap
JYU Focus
95% of current AI Ethics research does not translate to practice
Current research

13. 211 companies
were surveyed.
It is a jungle out
there…
For Ethically Aligned AI Development
Source: Vakkuri, V., Kemell, K.K., Jantunen, M., Halme, E. and Abrahamsson, P.,
2021. ECCOLA—A method for implementing ethically aligned AI systems. Journal
of Systems and Software, 182, p.111067.

14. ECCOLA in a nutshell
• A method for empowering teams to do
ethically aligned software/AI development
• ECCOLA is card-deck of 21 cards covering 8
thematic areas: Analysis, Data,
Transperancy, Human agency, Security &
Safety, Wellbeing, Fairness &
Accountability
• ECCOLA is used by the development team,
product owner and/or an external
consultant
• Proof-tested in academic and industrial
projects
Download your copy at bit.ly/eccola-method

15. Practical advice!
Source: Vakkuri, Kemell, Kultanen, and Abrahamsson. "The Current State of Industrial Practice in
Artificial Intelligence Ethics." IEEE Software 37, no. 4 (2020): 50-57.

16. Ethical requirements stack
Source: Halme, E., Vakkuri, V., Kultanen, J., Jantunen, M., Kemell, K.K., Rousi, R. and
Abrahamsson, P., 2021. How to Write Ethical User Stories? Impacts of the ECCOLA Method.
In International Conference on Agile Software Development (pp. 36-52). Springer, Cham.
Portfolio
Program
Team

17. Ethical requirements stack
Source: Halme, E., Vakkuri, V., Kultanen, J., Jantunen, M., Kemell, K.K., Rousi, R. and
Abrahamsson, P., 2021. How to Write Ethical User Stories? Impacts of the ECCOLA Method.
In International Conference on Agile Software Development (pp. 36-52). Springer, Cham.
Portfolio
Program
Team

19. Passenger flow use case

20. Key takeaways
Source: (Halme et al., 2021, accessible at bit.ly/Halme2021b)
An extract of ethical user stories for passenger
flow use case

21. Key takeaways
• AI ethics concerns needs to be addressed by
companies and public organizations
• Concepts, values and principals are important but
they rarely help in practice
• ECCOLA is method the empowers the developers to
do ethically aligned software and ai design in
practice
• In practice AI ethics concerns are managed as non-
functional software requirements
• ECCOLA is made available at bit.ly/eccola-method

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