Philosophy · Class 12 · Ethics and the Moral Compass · Term 1

Ethics of Technology: AI and Autonomy

Exploring the ethical dilemmas posed by emerging technologies, such as artificial intelligence, privacy, and automation.

About This Topic

Ethics of Technology: AI and Autonomy guides Class 12 students through moral challenges of artificial intelligence, privacy, and automation. They predict issues like biased algorithms denying loans unfairly, analyse digital privacy amid India's vast Aadhaar-linked data ecosystem, and justify duties of developers to ensure transparency alongside users' responsibility to question tech reliance. Core concepts draw from Kantian imperatives on autonomy and Mill's utilitarianism in weighing societal benefits against harms.

This unit in the Ethics and Moral Compass anchors abstract philosophy to real-world scenarios, such as facial recognition in public spaces or chatbots replacing counsellors. Students build skills in ethical argumentation, vital for CBSE exams and life in a digital India where tech shapes governance and employment.

Active learning excels here: structured debates and role-plays let students simulate AI dilemmas, like prioritising passenger safety in autonomous vehicles. They argue positions, confront counterviews, and refine reasoning collaboratively. This approach makes ethics personal and dynamic, deepening empathy and critical analysis over rote memorisation.

Key Questions

1. Predict the ethical challenges posed by advanced artificial intelligence.
2. Analyze the concept of digital privacy in an increasingly connected world.
3. Justify the moral responsibilities of developers and users of new technologies.

Learning Objectives

• Critique the ethical implications of algorithmic bias in AI systems used for loan applications or hiring processes.
• Analyze the trade-offs between data collection for public safety and individual digital privacy in smart city initiatives.
• Justify the moral obligations of AI developers to ensure transparency and accountability in their creations.
• Evaluate the societal impact of automation on employment and the economy, considering principles of distributive justice.

Before You Start

Introduction to Ethics: Concepts and Theories

Why: Students need a foundational understanding of ethical principles like utilitarianism and deontology to analyze the moral dimensions of technology.

Logic and Argumentation

Why: The ability to construct coherent arguments and identify logical fallacies is essential for justifying moral responsibilities and critiquing technological applications.

Key Vocabulary

Algorithmic Bias	Systematic and repeatable errors in a computer system that create unfair outcomes, such as privileging one arbitrary group of users over others.
Digital Privacy	The right of an individual to control their personal information when it is collected, processed, and shared in the digital realm.
Automation	The use of technology to perform tasks with minimal human intervention, often involving machines or software.
AI Autonomy	The capacity of an artificial intelligence system to make decisions and act independently without direct human control or supervision.

Watch Out for These Misconceptions

Common Misconception

AI decisions are always neutral and unbiased.

What to Teach Instead

AI inherits biases from training data shaped by humans. Role-plays of biased loan approvals help students trace origins and test fixes, building nuanced views through peer challenges.

Common Misconception

Privacy issues concern only governments, not individuals.

What to Teach Instead

Personal data fuels surveillance capitalism affecting daily choices. Case analyses reveal user complicity; group mapping connects dots, fostering ownership via collaborative insights.

Common Misconception

Technology ethics applies only to experts, not ordinary users.

What to Teach Instead

Everyone shares moral responsibility in tech use. Debates position students as stakeholders, clarifying duties and sparking ethical agency through active defence of views.

Active Learning Ideas

Debate Pairs: AI Autonomy Limits

Pair students and assign one pro-AI full autonomy, the other pro-human oversight. Provide cases like medical diagnosis bots. Pairs debate for 10 minutes, then share key arguments with class. Conclude with vote and reflection on strongest points.

30 min·Pairs

Role-Play Stations: Privacy Scenarios

Set up three stations with roles: developer, user, regulator. Groups enact dilemmas like data sharing for UPI security. Rotate roles after 10 minutes, note ethical trade-offs. Debrief as whole class on resolutions.

45 min·Small Groups

Dilemma Cards: Group Analysis

Distribute cards with AI ethics prompts, such as biased hiring tools. Small groups discuss, apply philosophical lenses like deontology, and propose guidelines. Present to class for peer feedback.

40 min·Small Groups

Ethical Mapping: Whole Class Chart

Project a mind map on AI impacts. Students add sticky notes on privacy risks and autonomy threats from personal experiences. Discuss clusters, vote on priorities, and link to moral theories.

35 min·Whole Class

Real-World Connections

• The widespread use of Aadhaar-linked digital identity in India raises significant questions about data security and the potential for surveillance, impacting millions of citizens daily.
• Autonomous vehicle development, like that by companies such as Tata Motors or Mahindra, presents complex ethical dilemmas regarding accident liability and decision-making in critical situations.
• AI-powered chatbots are increasingly used by Indian banks like HDFC and ICICI for customer service, prompting discussions about job displacement and the quality of human interaction.

Assessment Ideas

Discussion Prompt

Pose the question: 'If an autonomous vehicle must choose between swerving to avoid a pedestrian and risking the lives of its passengers, what ethical framework should guide its decision?' Facilitate a class debate, encouraging students to cite specific ethical theories discussed in class.

Quick Check

Present students with a short case study of an AI algorithm exhibiting bias (e.g., facial recognition software performing poorly on darker skin tones). Ask them to identify the source of bias and propose two concrete steps developers could take to mitigate it.

Exit Ticket

On a slip of paper, ask students to write one potential ethical challenge posed by AI in the next decade and one personal responsibility they have as a user of technology to ensure its ethical deployment.

Frequently Asked Questions

What are key ethical challenges of AI autonomy?

Challenges include loss of human agency when AI makes life decisions, such as in self-driving cars or predictive policing, and risks of opaque 'black box' algorithms hiding biases. Students weigh autonomy erosion against efficiency gains, using philosophy to argue for accountable design in India's growing AI sector.

How does digital privacy link to moral philosophy?

Privacy upholds Kantian respect for persons as ends, not means for data harvesting. In connected India, breaches like app data leaks violate this; analysis activities help students apply rights-based ethics to demand consent and security from platforms.

What moral duties do AI developers and users have?

Developers must prioritise fairness and transparency per virtue ethics, auditing for biases. Users owe vigilance, questioning over-reliance. Justifications emerge in debates, preparing students for ethical tech citizenship amid automation's job shifts.

How can active learning help teach ethics of technology?

Active methods like role-plays and debates immerse students in dilemmas, such as defending privacy in surveillance scenarios. They negotiate trade-offs, refine arguments via peer feedback, and connect philosophy to life. This builds deeper retention and ethical intuition compared to lectures, suiting CBSE's skill focus.