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AI in Education in need for ethics?
Inge de Waard (at gmail dot com)
Slideshare.net/ignatia
@ignatia
http://ignatiawebs.bl...
Discuss and compare ideas on implementing an
ethical layer within Artificial Intelligence for
education.
Artificial Intelligence: mathematical models that
enable communication, enhanced decision
making, semantic reasoning, resp...
Algorithms: a process or set of rules to be followed
in calculations or other problem-solving
operations. Algorithms are c...
Who makes algorithms?
Algorithms are all around us. We are a
product of algorithms that surround us.
Algorithms enter our homes, work, schools,
institutes, habits… but in most cases they are
invisible.
Being non-transparent results in unexpected
outcomes: filter bubbles (un)professional hairstyle
AI risks to replicate the norm (filter bubbles prove
it).Explained in part by the similar profiles of the
creators of thes...
Frank Pasquale (law prof) argued, “authority is
increasingly expressed algorithmically.”
Audrey Waters (fab thinker, talki...
Algocratic governance based on black boxes?
Information and software systems rule.
Artificial Intelligence is a eufemistic term.
Utopian belief in AI is forgetting or neglecting
human brain diversity
Building an AI that can defeat the human
GO/chess champions (alphago created by
Deepmind). But does it provide mental athl...
Emotions drive learning.
Affective computing is on the rise: computer
science, psychology & cognitive science.
Which teacher do you remember and
changed your life? Why?
What is happening with AI in education?
AI in formal education: semi-automated
assessments, gamification, learning analytics,
predictive analytics, scientific app...
AI in informal learning: browser searches, personal
apps, quantified self, learning locker based
learning, course suggesti...
In short, AI in Ed can go both ways, and all the
ways in between…
Positive scenario
• Primary school assessment reveals a never-gonna-formally-learn student
but enthusiastically yells out ...
Negative scenario:
• AI looks only for those profiles that are deemed to be able to
contribute to society. The other human...
Transparency to learn what is happening with AI in
e.g. learning analytics and why => ethical rules.
What do we need to build an ethical layer?
Explained AI is a first step for understanding
algorithmic effects.
Ethical layer: where do we want to go to as a
society? Multiple sided stories?
We interpret the world using our moral compass: a
complex set of cultural and philosophical
preferences. For or against cl...
Maybe an Ethics commission at UN/Unesco.
Ethics board every software output company.
Ethics layer on top of AI, reviewing ...
Artificial Intelligence promoting inquiry, agency,
activism and critical thinking & action?
Maybe it is just natural to increase the dominant
norm? And does not need ethics? History has
always kept mostly words fro...
What would be part of your ethical layer, which
outcomes of AI in education would you like to see?
artificial intelligence - in need of an ethical layer?
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Slides accompanying the OEB_Midsummit talk 8 June 2017, discussing the need to embed an ethical layer inside artificial intelligence for education.

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artificial intelligence - in need of an ethical layer?

  1. 1. AI in Education in need for ethics? Inge de Waard (at gmail dot com) Slideshare.net/ignatia @ignatia http://ignatiawebs.blogspot.com
  2. 2. Discuss and compare ideas on implementing an ethical layer within Artificial Intelligence for education.
  3. 3. Artificial Intelligence: mathematical models that enable communication, enhanced decision making, semantic reasoning, responding and learning between machines and humans.
  4. 4. Algorithms: a process or set of rules to be followed in calculations or other problem-solving operations. Algorithms are coded into software.
  5. 5. Who makes algorithms?
  6. 6. Algorithms are all around us. We are a product of algorithms that surround us.
  7. 7. Algorithms enter our homes, work, schools, institutes, habits… but in most cases they are invisible.
  8. 8. Being non-transparent results in unexpected outcomes: filter bubbles (un)professional hairstyle
  9. 9. AI risks to replicate the norm (filter bubbles prove it).Explained in part by the similar profiles of the creators of these algorithms.
  10. 10. Frank Pasquale (law prof) argued, “authority is increasingly expressed algorithmically.” Audrey Waters (fab thinker, talking tomorrow) wrote “Algorithms — their development and implementation — are important expressions of power and influence.”
  11. 11. Algocratic governance based on black boxes? Information and software systems rule.
  12. 12. Artificial Intelligence is a eufemistic term.
  13. 13. Utopian belief in AI is forgetting or neglecting human brain diversity
  14. 14. Building an AI that can defeat the human GO/chess champions (alphago created by Deepmind). But does it provide mental athletic well-being to the Go player? Can it read emotions?
  15. 15. Emotions drive learning. Affective computing is on the rise: computer science, psychology & cognitive science.
  16. 16. Which teacher do you remember and changed your life? Why?
  17. 17. What is happening with AI in education?
  18. 18. AI in formal education: semi-automated assessments, gamification, learning analytics, predictive analytics, scientific apps, automated student assistants, identity confirmation …
  19. 19. AI in informal learning: browser searches, personal apps, quantified self, learning locker based learning, course suggestions …
  20. 20. In short, AI in Ed can go both ways, and all the ways in between…
  21. 21. Positive scenario • Primary school assessment reveals a never-gonna-formally-learn student but enthusiastically yells out poems => gets a one-on-one tutor for language, and ultimately learns poetry. • Pre-school reveals personal skills compatible with satisfaction through skilled labor. Learning trajectory is provided, mentorship is arranged. • Humans are enhanced with technology => post-human is evolving and emotions are supported to lead to satisfied lives. Personal learning paths, enhancing strengths and intrinsic motivation based on enthusiasm and emotions and personal learning goals …
  22. 22. Negative scenario: • AI looks only for those profiles that are deemed to be able to contribute to society. The other humans are second class citizens with less opportunities. Emotions are screened for violent potential. • AI evolves and looks at humans as an inefficient species (based on existing human-build algorithms coding efficiency and moral codes such as peace must be achieved. Humans are put into reservations to protect them against themselves. AI develops into space exploring entitities.
  23. 23. Transparency to learn what is happening with AI in e.g. learning analytics and why => ethical rules.
  24. 24. What do we need to build an ethical layer?
  25. 25. Explained AI is a first step for understanding algorithmic effects.
  26. 26. Ethical layer: where do we want to go to as a society? Multiple sided stories?
  27. 27. We interpret the world using our moral compass: a complex set of cultural and philosophical preferences. For or against climate change and sustainable energy.
  28. 28. Maybe an Ethics commission at UN/Unesco. Ethics board every software output company. Ethics layer on top of AI, reviewing the AI.
  29. 29. Artificial Intelligence promoting inquiry, agency, activism and critical thinking & action?
  30. 30. Maybe it is just natural to increase the dominant norm? And does not need ethics? History has always kept mostly words from those in power. Does power always win, or do those win who we want to remember?
  31. 31. What would be part of your ethical layer, which outcomes of AI in education would you like to see?
  • zahernourredine

    Dec. 25, 2018
  • anacristinapratas

    Jun. 8, 2017

Slides accompanying the OEB_Midsummit talk 8 June 2017, discussing the need to embed an ethical layer inside artificial intelligence for education.

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