This is a short presentation as part of my participation as a mentor in a teens in AI event.

1. AI Ethics :
Path to an
emerging
field.
BY: SELASE WILMOT KWAMI

2. AGENDA
• Introduction
• Definition of AI Ethics.
• Specialties of the field
• What AI Ethicists do.
• Societal Impact of AI
Ethics.
• Ways to become an AI
Ethicist
• Career paths to AI Ethics.
• Skills & Qualities
• Ethical guidelines
• Future trends and challenges
• Conclusion
• Questions & Discussions
• Further reading

4. Definition of AI Ethics.
 The 2010s witnessed a significant increase in public awareness and concern
about AI ethics, driven by advancements in AI technologies, high-profile
incidents of algorithmic bias and discrimination, and debates surrounding
AI safety and governance.
 The establishment of research institutes, centers, and initiatives focused
on AI ethics, such as the AI Ethics Lab at the University of Toronto and
the Partnership on AI, further solidified AI ethics as a distinct field of
study.
Rise of AI Ethics as career path
AI ethics is the systematic examination of the ethical implications of artificial
intelligence technologies, including the development, deployment, and impact of AI systems on
individuals, communities, and societies. It seeks to promote responsible AI practices that
uphold human rights, fairness, accountability, and transparency. (By Centre for AI and
Digital Policy)
AI ethics is the study and application of moral principles and values in the development,
deployment, and use of artificial intelligence systems. It involves ensuring that AI
technologies are designed and utilized in ways that uphold ethical standards, promote
fairness, transparency, accountability, and consider their societal impacts. (ChatGPT
generated)

5. SPECIALITIES OF AI
ETHICS
Algorithmic
Bias
Privacy and
Surveillance
Autonomous
Weapons
Accountability
and
Transparency
Fairness and
Equity
Ethical AI
Design

6. WHAT AI ETHICISTS DO
Ethical assessment
Developing ethical
guidelines
Policy advocacy
Educational
outreach
Addressing ethical
dilemmas
Monitoring/auditing
AI systems.
Research and
thought leadership

7. Societal Impact
of AI ethics
• Fairness & equity
• Privacy and data
protection
• Accountability and
transparency
• Safety and security
• Human dignity and
autonomy
• Economic and employment
outcomes

8. WAYS TO
BECOME AN AI
ETHICIST
• Get a University degree in Computer
science, Law or Social Science.
• Acquire professional certifications such
as Certified Information Systems Security
Professional (CISSP) or Certified
Information Privacy Professional (CIPP)
• Read and write blogs or articles in the
field of AI ethics.
• Stay current with trends in AI, Data
Science and AI regulations and legal
issues.
• Do online courses via various platforms
such as Udemy, Coursera, EdX etc.
• Get hands-on experience by working for tech
companies, volunteering or freelancing.
• Build a resume, CV or profile that matches
the field or career.
NB: Probable salary for an AI Ethics
practitioner is $173,000 per year.
(Glassdoor.com)

9. Skills and
qualities.
• Ethical reasoning
• Critical thinking
• Interdisciplinary knowledge
i.e., IT/data science and
social science.
• Communication skills
• Collaboration and teamwork
• Adaptability and flexibility
• Problem solving skills
• Empathy and cultural
sensitivity
• Commitment to continuous
learning
• Leadership and influence

10. Career paths in
AI ethics
AI ethics researcher
Ethical AI researcher
AI policy analyst
AI ethics consultant
Ethics review board member
Corporate ethics officer
AI ethicist in Law and Policy
Educator or trainer

11. ETHICAL GUIDELINES
Transparency
Accountability
Fairness and equity
Privacy and data protection
Safety and security
Human centered design
Bias mitigation and diversity
Social and environmental responsibility

12. ETHICAL FRAMEWORKS
IN AI
• IEEE Global Initiative on
Ethics of Autonomous and
Intelligent Systems
• The Asilomar Principles
• The Montreal Declaration
for Responsible AI

13. FUTURE TRENDS AND
CHALLENGES
Emerging trends in AI ethics
include:
AI governance and AI for
social good.
AI is faced with challenges
such as enforcement of
guidelines and global
collaboration.
As research and innovation in
the field of AI continues to
grow, it is expected that
there will be new concepts

14. CONCLUSION
Building ethical AI is essential to ensuring that the
needs of humanity are considered and addressed with the
proliferation and growth of AI tools and systems.
It is the responsibility of government, the policy
analysts, AI engineers, tech companies etc., to ensure
that AI is properly regulated. All these institutions need
to serve as a watchdog in a rapidly evolving field.
Although, it is advisable to specialize when building a
career, it is also important to have some broad knowledge
in many inter-related fields in technology, law and social
science. The knowledge you gain from other related fields
would compliment your skills and make you more valuable in
the job market of the future.

15. QUESTIONS & DISCUSSIONS

16. FURTHER
READING
• Chen, Angela; Chander, Sarah
(2021) Automating Bias? The Risks
of the EU’s New AI Regulation.
Green European Journal. 20th May
edition
https://www.greeneuropeanjournal.eu
/automating-bias-the-risks-of-the-
eus-new-ai-regulation/
• UNESCO: Artificial Intelligence:
examples of ethical dilemmas
https://en.unesco.org/artificial-
intelligence/ethics/cases
• University of San Diego: Who is
an AI ethicist and how to become
one
https://onlinedegrees.sandiego.edu/
ai-ethicist-career/