Computer Science · 11th Grade · Artificial Intelligence and Ethics · Weeks 19-27

AI and the Future of Work

Predicting the impact of AI on the workforce, privacy, and human autonomy.

• Common Core State Standards
• CSTA: 3B-IC-26
• CSTA: 3B-IC-27

About This Topic

AI and automation are already reshaping the US labor market, and this topic asks students to think rigorously about where those changes are heading. Rather than treating AI job displacement as a future threat, students examine current evidence: the Bureau of Labor Statistics tracks occupational shifts in real time, and sectors from manufacturing to customer service to legal research show measurable automation effects right now. CSTA standards 3B-IC-26 and 3B-IC-27 ask students to predict broader societal effects of computing and to evaluate how communities respond.

This topic goes beyond predicting which jobs will disappear. It examines who bears the costs of automation most heavily, what skills create resilience in an AI-driven economy, and what policy tools societies use to manage transitions. US students can analyze responses like community college retraining grants, proposed universal basic income pilots, and workforce development programs tied to specific industries.

Active learning is essential here because this topic requires students to hold competing values simultaneously: the economic gains from automation alongside the disruption costs to specific workers and communities. Structured discussions and scenario-planning exercises give students practice making nuanced arguments rather than defaulting to simple optimism or pessimism about AI's effects on work.

Key Questions

1. Predict how AI and automation will transform various industries and job roles.
2. Analyze the ethical considerations surrounding job displacement due to AI.
3. Design educational and policy initiatives to prepare society for an AI-driven economy.

Learning Objectives

• Analyze current trends in automation across at least three distinct industries to predict future job role transformations.
• Evaluate the ethical implications of AI-driven job displacement on different socioeconomic groups.
• Design a policy proposal or educational initiative aimed at preparing a specific community for an AI-driven economy.
• Critique the potential impacts of AI on human autonomy in decision-making processes within the workplace.

Before You Start

Introduction to Artificial Intelligence Concepts

Why: Students need a foundational understanding of what AI is and its basic capabilities before analyzing its impact on work.

Societal Impacts of Computing

Why: This topic builds on students' prior exploration of how technology affects society, requiring them to apply these concepts specifically to AI and employment.

Key Vocabulary

Automation	The use of technology, including AI, to perform tasks previously done by humans.
Job displacement	The loss of employment due to technological change, such as automation or AI replacing human workers.
Reskilling	The process of learning new skills to adapt to changing job market demands, particularly those arising from AI and automation.
Human autonomy	The capacity of individuals to make their own informed, uncoerced decisions, which may be impacted by AI's influence on choices and actions.
Universal Basic Income (UBI)	A periodic cash payment unconditionally provided to all individuals, often discussed as a potential response to widespread job displacement.

Watch Out for These Misconceptions

Common Misconception

AI will create as many jobs as it destroys, so overall employment will be fine.

What to Teach Instead

Historical technological transitions did eventually create new jobs, but the timing, geography, and skill requirements of those new jobs rarely matched the workers who lost them. Students examining specific labor market data see that the transition costs are real and unevenly distributed.

Common Misconception

Only low-skill, repetitive jobs are at risk from automation.

What to Teach Instead

Automation increasingly affects knowledge work including legal research, medical imaging analysis, and financial reporting. Students who analyze automation risk scores across occupational categories see that vulnerability correlates more with task structure than with credential level.

Common Misconception

Individual workers just need to learn to code and they'll be protected from automation.

What to Teach Instead

Reskilling is valuable but not a complete solution; structural labor market changes require policy responses at scale. Scenario-planning activities help students see both personal agency and systemic constraints operating simultaneously.

Active Learning Ideas

Scenario Planning: Automation in 2035

Assign each group one sector (healthcare, transportation, retail, creative industries). Groups research current automation trends in that sector, project plausible outcomes for workers in 10 years, and present a 'spectrum of futures' ranging from best to worst case with the policy levers that determine which occurs.

50 min·Small Groups

Structured Academic Controversy: Universal Basic Income

Pairs argue that UBI is the right policy response to AI-driven job displacement, then switch and argue for reskilling and education investment instead. After both rounds, partners present a synthesized policy recommendation that draws from both perspectives.

35 min·Pairs

Think-Pair-Share: Job Vulnerability Analysis

Give students an abbreviated occupational database showing automation risk scores. Students individually predict which factors correlate with high risk, compare with a partner, then the class builds a shared model of what makes a job more or less automatable.

20 min·Pairs

Real-World Connections

• The trucking industry is exploring autonomous vehicle technology, which could significantly alter the roles and employment of millions of drivers across the United States.
• Customer service roles are increasingly augmented or replaced by AI chatbots and virtual assistants, impacting call center operations in cities like Omaha, Nebraska, a major hub for such employment.
• Legal research firms are using AI tools to analyze vast amounts of case law, changing the day-to-day tasks of paralegals and junior associates.

Assessment Ideas

Discussion Prompt

Pose the question: 'Imagine you are a city council member. Given the rise of automation in manufacturing, what are two concrete steps your city could take to support displaced workers?' Students should share their ideas and justify their choices based on feasibility and impact.

Quick Check

Provide students with a short news article about AI impacting a specific job sector. Ask them to identify: 1) The industry affected, 2) The specific AI technology mentioned, and 3) One potential ethical concern raised by this development.

Peer Assessment

Students draft a brief (1-paragraph) prediction about how AI will change a job role they are interested in. They then exchange drafts with a partner. The partner provides feedback on the clarity of the prediction and identifies one skill that might become more important for that role in the future.

Frequently Asked Questions

Which jobs are most at risk from AI automation?

Jobs with high proportions of routine, well-defined tasks are most vulnerable, regardless of whether they require physical or cognitive work. Data processing, predictive analysis, and pattern-matching tasks in fields like accounting, transportation, and customer service face the most near-term displacement risk.

What new jobs does AI create?

AI creates demand for roles that complement automated systems: AI trainers, model auditors, prompt engineers, and AI policy analysts. It also increases demand for work requiring empathy, complex judgment, and physical dexterity that automation handles poorly, such as counseling, trade work, and elder care.

What policy responses to AI-driven job displacement exist in the US?

Current US responses include trade adjustment assistance, community college retraining grants, apprenticeship expansion programs, and proposed automation taxes to fund workforce transition. At the state level, programs like California's EDD and Texas Workforce Commission provide sector-specific reskilling support.

Why does active learning matter for discussing AI and the future of work?

This topic requires students to reason about competing values, contested evidence, and uncertain futures. Active formats like scenario planning and structured controversy give students practice constructing arguments from data rather than restating talking points, which is exactly the skill an uncertain labor market demands.