Summary of Ethical Theories and Modern Dilemmas

Ethical Theories and Modern Dilemmas: A Student Guide

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Introduction

Technology shapes how we learn, communicate and make decisions. While it brings many benefits — faster communication, better healthcare and new learning tools — it also raises serious ethical questions. This guide breaks down the main ethical issues linked to technology, offers clear definitions, real-world examples, and shows how different ethical lenses help us judge actions and policies.

Definition: Ethical accountability in technology means that people, companies and governments are responsible for the social effects of their technologies and must act transparently, fairly and accountably.

Key concepts broken down

1. Misinformation and social media

  • What it is: False or misleading information shared online.
  • Why it spreads: Speed of sharing, emotional content, and engagement-driven algorithms.
  • Real-world effects: Political polarisation, public panic during crises, reduced trust in institutions.

Definition: Misinformation is information that is false or misleading regardless of intent; disinformation is deliberately false information spread to deceive.

Practical example: During a pandemic, an unverified post claiming a fake cure can lead people to avoid proper treatment and endanger public health.

💡 Did you know?Did you know that social media algorithms often prioritise content that gets more likes and shares, even if it is inaccurate?

2. AI, surveillance and bias

  • What it is: Use of algorithms and automated systems to make decisions (e.g., hiring, grading, security).
  • Main ethical problems: Biased training data, lack of transparency, surveillance of citizens and students.

Definition: Algorithmic bias occurs when an AI system produces systematically unfair outcomes for certain groups because of biased data or design choices.

Practical example: A recruitment AI trained on past hires at a company may learn to favour applicants similar to previous hires, perpetuating inequality.

💡 Did you know?Fun fact: Facial recognition systems have been shown in studies to make more errors identifying people of certain racial groups than others.

3. Academic dishonesty and youth behaviour

  • What it is: Misuse of AI tools and online resources to cheat, plus social media pressures.
  • Why it matters: Reduces genuine learning, damages integrity and mental wellbeing.

Definition: Academic integrity means completing and presenting work honestly and with proper acknowledgement of sources.

Practical example: Students using AI to generate essays without understanding the content miss developing critical thinking skills.

4. Influencer culture and manipulation

  • What it is: Influencers promote lifestyles and products to followers, sometimes using editing and filters.
  • Ethical issue: Misleading advertising and unrealistic standards affecting young people’s self-image.

Practical example: A beauty influencer promotes expensive cosmetics as "essential" while heavily editing photos to hide reality.

💡 Did you know?Did you know that many influencers edit images or use filters to change their appearance before promoting products to followers?

5. Positive uses of technology

  • Examples: AI-assisted medical diagnosis, online learning platforms, social media campaigns for social justice.
  • Key idea: Technology can be ethical when guided by responsibility, transparency and compassion.

Definition: Ethical technology is technology designed and used with consideration for fairness, privacy, and human dignity.

💡 Did you know?Fun fact: AI systems can help doctors detect certain diseases earlier than traditional screening in some cases, improving patient outcomes.

Ethical lenses (short guide)

  • Utilitarianism: Judge actions by their consequences — greatest good for the greatest number. Example: Demoting sensational posts if they reduce harm.
  • Rights-based ethics: Focus on protecting individual rights like dignity, privacy and equal treatment.
  • Care Ethics: Emphasises empathy, relationships and wellbeing — especially relevant in edu
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Ethics of Technology

Klíčové pojmy: Ethical accountability means responsibility, transparency and fairness in technology use, Misinformation spreads fast due to emotional content and engagement-driven algorithms, Algorithmic bias arises when AI learns unfair patterns from biased data, Surveillance in schools can protect safety but may harm privacy and trust, Care Ethics focuses on relationships, empathy and wellbeing over profits, Influencer editing can mislead followers and harm teenagers' self-esteem, Fast fashion often exploits workers and damages the environment for cheap prices, Balanced policies require transparency, audits and education to reduce tech harms, Utilitarianism weighs overall consequences; rights-based ethics protects individual rights, Schools should combine clear rules, limited data use and regular bias checks, Technology can be ethical when guided by responsibility and compassion

## Introduction Technology shapes how we learn, communicate and make decisions. While it brings many benefits — faster communication, better healthcare and new learning tools — it also raises serious ethical questions. This guide breaks down the main ethical issues linked to technology, offers clear definitions, real-world examples, and shows how different ethical lenses help us judge actions and policies. > **Definition:** Ethical accountability in technology means that people, companies and governments are responsible for the social effects of their technologies and must act transparently, fairly and accountably. ## Key concepts broken down ### 1. Misinformation and social media - What it is: False or misleading information shared online. - Why it spreads: Speed of sharing, emotional content, and engagement-driven algorithms. - Real-world effects: Political polarisation, public panic during crises, reduced trust in institutions. > **Definition:** Misinformation is information that is false or misleading regardless of intent; disinformation is deliberately false information spread to deceive. Practical example: During a pandemic, an unverified post claiming a fake cure can lead people to avoid proper treatment and endanger public health. Did you know that social media algorithms often prioritise content that gets more likes and shares, even if it is inaccurate? ### 2. AI, surveillance and bias - What it is: Use of algorithms and automated systems to make decisions (e.g., hiring, grading, security). - Main ethical problems: Biased training data, lack of transparency, surveillance of citizens and students. > **Definition:** Algorithmic bias occurs when an AI system produces systematically unfair outcomes for certain groups because of biased data or design choices. Practical example: A recruitment AI trained on past hires at a company may learn to favour applicants similar to previous hires, perpetuating inequality. Fun fact: Facial recognition systems have been shown in studies to make more errors identifying people of certain racial groups than others. ### 3. Academic dishonesty and youth behaviour - What it is: Misuse of AI tools and online resources to cheat, plus social media pressures. - Why it matters: Reduces genuine learning, damages integrity and mental wellbeing. > **Definition:** Academic integrity means completing and presenting work honestly and with proper acknowledgement of sources. Practical example: Students using AI to generate essays without understanding the content miss developing critical thinking skills. ### 4. Influencer culture and manipulation - What it is: Influencers promote lifestyles and products to followers, sometimes using editing and filters. - Ethical issue: Misleading advertising and unrealistic standards affecting young people’s self-image. Practical example: A beauty influencer promotes expensive cosmetics as "essential" while heavily editing photos to hide reality. Did you know that many influencers edit images or use filters to change their appearance before promoting products to followers? ### 5. Positive uses of technology - Examples: AI-assisted medical diagnosis, online learning platforms, social media campaigns for social justice. - Key idea: Technology can be ethical when guided by responsibility, transparency and compassion. > **Definition:** Ethical technology is technology designed and used with consideration for fairness, privacy, and human dignity. Fun fact: AI systems can help doctors detect certain diseases earlier than traditional screening in some cases, improving patient outcomes. ## Ethical lenses (short guide) - Utilitarianism: Judge actions by their consequences — greatest good for the greatest number. Example: Demoting sensational posts if they reduce harm. - Rights-based ethics: Focus on protecting individual rights like dignity, privacy and equal treatment. - Care Ethics: Emphasises empathy, relationships and wellbeing — especially relevant in edu