AI ETHICS DEBATE UNIT
Artificial Intelligence, Ethics & Society
TEACHER GUIDE
Philosophy • Ethics • Critical Thinking • Academic Debate • CLIL / ESL Friendly
ESSENTIAL QUESTION
Is Artificial Intelligence harmful to society?
Recommended level Grades 10-12 / Upper Secondary / 1st Bachillerato
Language level B1-B2, with differentiated support
Duration 5 lessons of approximately 50-60 minutes
Final performance Structured academic debate
Philosophy, Ethics, Critical Thinking, Social Studies,
Core disciplines
CLIL/EFL
Created by Luna Hernández García -
AI Ethics Debate Unit - Teacher Guide | Luna Hernández García
,1. Quick Start Guide
This unit is a five-session inquiry into the ethical, epistemological and social implications of Artificial
Intelligence. Students move from initial opinions about AI to evidence-based philosophical
argumentation and a final formal debate. The presentation is designed for whole-class instruction,
while the printable resources provide language support, argument scaffolding, comparison tasks
and assessment.
LOW-PREP OPTION
Print the student handouts, assign heterogeneous teams, display the presentation and follow the session
notes in this guide. For a shorter version, combine Sessions 2 and 3 and run the debate in Session 4.
Recommended materials
Student presentation: AI Ethics Debate Unit.
Agree / Disagree statement cards.
Vocabulary Sheet.
Cultural reading texts and Comparison Chart.
ARE Argument Builder / Substitution Table.
Argument and Rebuttal Builder.
Connectors and Debate Language Cheat-Sheet.
Conclusion Template.
Teacher debate rubric, student jury rubric, peer feedback and self-assessment forms.
Projector or interactive display, timer, notebooks and optional digital classroom platform.
2. Unit Rationale
Artificial Intelligence provides a strong context for philosophical inquiry because it forces students
to examine questions that have no purely technical answer: What counts as reliable knowledge? Can
an automated system be biased? Who is morally responsible for algorithmic decisions? How should
privacy, autonomy, innovation and collective welfare be balanced? The unit therefore treats AI not
as a technology lesson, but as a contemporary philosophical problem.
The academic debate is the culminating task rather than an isolated speaking exercise. Students first
acquire concepts and language, then analyse evidence and cultural perspectives, then construct
arguments and rebuttals, and finally respond to an opposing team in real time.
3. Essential and Enquiry Questions
Essential question: Is Artificial Intelligence harmful to society?
Can AI distinguish truth from falsehood?
Can a machine be biased if it has no intentions?
Who is responsible when an AI system causes harm?
Should people have a right to understand important automated decisions?
AI Ethics Debate Unit - Teacher Guide | Luna Hernández García
, When should privacy limit technological innovation?
Can the same technology be judged differently in different cultural contexts?
What makes an opinion into a philosophical argument?
4. Learning Objectives
Content objectives
Explain key ethical and epistemological issues related to Artificial Intelligence.
Understand the relationship between knowledge, truth, evidence, bias and post-truth.
Analyse moral responsibility, privacy, autonomy, transparency and accountability in AI systems.
Apply consequentialist, deontological and virtue-ethical perspectives to technological dilemmas.
Examine the relationship between technoscience, power, interests and social consequences.
Compare culturally situated approaches to AI governance and social responsibility.
Cognitive objectives
Identify and define key concepts.
Distinguish claims, reasoning and evidence.
Apply philosophical concepts to real and hypothetical cases.
Analyse similarities and differences between perspectives.
Evaluate evidence and detect weaknesses in arguments.
Create coherent arguments, counterarguments and rebuttals.
Adapt a response to an opponent's argument during live debate.
Language objectives
Express and justify opinions using academic English.
Agree and disagree appropriately.
Compare perspectives and signal contrast.
Introduce evidence and explain its relevance.
Request clarification and respond to questions.
Formulate counterarguments and rebuttals.
Summarise a position and deliver a concise conclusion.
5. Success Criteria
Students should be able to say:
I can explain at least three ethical issues related to AI.
I can distinguish a claim from a reason and from evidence.
I can build an ARE argument.
I can compare two culturally situated perspectives.
I can use academic debate expressions.
I can respond to an opposing argument.
AI Ethics Debate Unit - Teacher Guide | Luna Hernández García
, I can support my ideas with relevant evidence.
I can participate respectfully and effectively in an academic debate.
6. CLIL 4Cs Framework
Dimension How it appears in the unit
Epistemology, ethics, philosophy of technology, AI
Content governance, privacy, bias, responsibility and cultural
values.
Progression from remembering and understanding to
Cognition
applying, analysing, evaluating and creating.
Language OF learning (key terminology), FOR learning
Communication (interaction and debate functions), and THROUGH
learning (new language emerging during inquiry).
Comparison of culturally situated priorities such as
Culture privacy, individual rights, innovation, collective
wellbeing, social harmony and regulation.
7. Core Philosophy Notes for the Teacher
Knowledge, truth and AI
AI-generated output should not be treated as automatically true. AI systems work with data, models
and probabilistic processes; their outputs may reflect incomplete, inaccurate, biased or context-poor
information. Use this topic to distinguish information from knowledge and to ask what justifies a
belief.
Bias
A useful philosophical distinction is between intention and outcome. An AI system does not need a
human-like intention in order to produce systematically unfair outcomes. Students should consider
where bias can enter a system: training data, labels, design decisions, objectives, deployment context
or existing social inequalities.
Transparency and accountability
Transparency concerns whether a system and its decisions can be understood or meaningfully
explained. Accountability concerns who must answer for the consequences of those decisions. These
concepts are related but not identical.
Three ethical frameworks
Framework Central question AI example
What produces the best overall Does an AI moderation system reduce
Consequentialism
consequences? harm overall, despite privacy costs?
What rights, duties or principles must Does the system respect privacy,
Deontology
be respected? consent and equal treatment?
Would a responsible developer deploy
What would responsible and ethically
Virtue ethics a system whose risks are poorly
good practice look like?
understood?
AI Ethics Debate Unit - Teacher Guide | Luna Hernández García
Artificial Intelligence, Ethics & Society
TEACHER GUIDE
Philosophy • Ethics • Critical Thinking • Academic Debate • CLIL / ESL Friendly
ESSENTIAL QUESTION
Is Artificial Intelligence harmful to society?
Recommended level Grades 10-12 / Upper Secondary / 1st Bachillerato
Language level B1-B2, with differentiated support
Duration 5 lessons of approximately 50-60 minutes
Final performance Structured academic debate
Philosophy, Ethics, Critical Thinking, Social Studies,
Core disciplines
CLIL/EFL
Created by Luna Hernández García -
AI Ethics Debate Unit - Teacher Guide | Luna Hernández García
,1. Quick Start Guide
This unit is a five-session inquiry into the ethical, epistemological and social implications of Artificial
Intelligence. Students move from initial opinions about AI to evidence-based philosophical
argumentation and a final formal debate. The presentation is designed for whole-class instruction,
while the printable resources provide language support, argument scaffolding, comparison tasks
and assessment.
LOW-PREP OPTION
Print the student handouts, assign heterogeneous teams, display the presentation and follow the session
notes in this guide. For a shorter version, combine Sessions 2 and 3 and run the debate in Session 4.
Recommended materials
Student presentation: AI Ethics Debate Unit.
Agree / Disagree statement cards.
Vocabulary Sheet.
Cultural reading texts and Comparison Chart.
ARE Argument Builder / Substitution Table.
Argument and Rebuttal Builder.
Connectors and Debate Language Cheat-Sheet.
Conclusion Template.
Teacher debate rubric, student jury rubric, peer feedback and self-assessment forms.
Projector or interactive display, timer, notebooks and optional digital classroom platform.
2. Unit Rationale
Artificial Intelligence provides a strong context for philosophical inquiry because it forces students
to examine questions that have no purely technical answer: What counts as reliable knowledge? Can
an automated system be biased? Who is morally responsible for algorithmic decisions? How should
privacy, autonomy, innovation and collective welfare be balanced? The unit therefore treats AI not
as a technology lesson, but as a contemporary philosophical problem.
The academic debate is the culminating task rather than an isolated speaking exercise. Students first
acquire concepts and language, then analyse evidence and cultural perspectives, then construct
arguments and rebuttals, and finally respond to an opposing team in real time.
3. Essential and Enquiry Questions
Essential question: Is Artificial Intelligence harmful to society?
Can AI distinguish truth from falsehood?
Can a machine be biased if it has no intentions?
Who is responsible when an AI system causes harm?
Should people have a right to understand important automated decisions?
AI Ethics Debate Unit - Teacher Guide | Luna Hernández García
, When should privacy limit technological innovation?
Can the same technology be judged differently in different cultural contexts?
What makes an opinion into a philosophical argument?
4. Learning Objectives
Content objectives
Explain key ethical and epistemological issues related to Artificial Intelligence.
Understand the relationship between knowledge, truth, evidence, bias and post-truth.
Analyse moral responsibility, privacy, autonomy, transparency and accountability in AI systems.
Apply consequentialist, deontological and virtue-ethical perspectives to technological dilemmas.
Examine the relationship between technoscience, power, interests and social consequences.
Compare culturally situated approaches to AI governance and social responsibility.
Cognitive objectives
Identify and define key concepts.
Distinguish claims, reasoning and evidence.
Apply philosophical concepts to real and hypothetical cases.
Analyse similarities and differences between perspectives.
Evaluate evidence and detect weaknesses in arguments.
Create coherent arguments, counterarguments and rebuttals.
Adapt a response to an opponent's argument during live debate.
Language objectives
Express and justify opinions using academic English.
Agree and disagree appropriately.
Compare perspectives and signal contrast.
Introduce evidence and explain its relevance.
Request clarification and respond to questions.
Formulate counterarguments and rebuttals.
Summarise a position and deliver a concise conclusion.
5. Success Criteria
Students should be able to say:
I can explain at least three ethical issues related to AI.
I can distinguish a claim from a reason and from evidence.
I can build an ARE argument.
I can compare two culturally situated perspectives.
I can use academic debate expressions.
I can respond to an opposing argument.
AI Ethics Debate Unit - Teacher Guide | Luna Hernández García
, I can support my ideas with relevant evidence.
I can participate respectfully and effectively in an academic debate.
6. CLIL 4Cs Framework
Dimension How it appears in the unit
Epistemology, ethics, philosophy of technology, AI
Content governance, privacy, bias, responsibility and cultural
values.
Progression from remembering and understanding to
Cognition
applying, analysing, evaluating and creating.
Language OF learning (key terminology), FOR learning
Communication (interaction and debate functions), and THROUGH
learning (new language emerging during inquiry).
Comparison of culturally situated priorities such as
Culture privacy, individual rights, innovation, collective
wellbeing, social harmony and regulation.
7. Core Philosophy Notes for the Teacher
Knowledge, truth and AI
AI-generated output should not be treated as automatically true. AI systems work with data, models
and probabilistic processes; their outputs may reflect incomplete, inaccurate, biased or context-poor
information. Use this topic to distinguish information from knowledge and to ask what justifies a
belief.
Bias
A useful philosophical distinction is between intention and outcome. An AI system does not need a
human-like intention in order to produce systematically unfair outcomes. Students should consider
where bias can enter a system: training data, labels, design decisions, objectives, deployment context
or existing social inequalities.
Transparency and accountability
Transparency concerns whether a system and its decisions can be understood or meaningfully
explained. Accountability concerns who must answer for the consequences of those decisions. These
concepts are related but not identical.
Three ethical frameworks
Framework Central question AI example
What produces the best overall Does an AI moderation system reduce
Consequentialism
consequences? harm overall, despite privacy costs?
What rights, duties or principles must Does the system respect privacy,
Deontology
be respected? consent and equal treatment?
Would a responsible developer deploy
What would responsible and ethically
Virtue ethics a system whose risks are poorly
good practice look like?
understood?
AI Ethics Debate Unit - Teacher Guide | Luna Hernández García
