IB DP Digital Society HL: 5.1 Global Well-Being (STAGE ONE): Key Theories, Digital Case Studies & Exam Prompts
- lukewatsonteach
- Sep 4
- 11 min read
Updated: Sep 18
Global well-being is fundamentally transformed by digital systems - from algorithmic healthcare decisions to AI-driven employment, technology doesn't just reflect inequality, it actively shapes it through embedded power structures and systemic biases.
5.1 Global well-being
5.1A Local and global inequalities
Economic inequality and stratification
Food insecurity and access to safe, nutritious and sufficient food
Access to health care and medicine
5.1B Changing populations
Population growth
Shifting demographics, for example, ageing and youth populations
Migration and the movement of people
5.1C The future of work
Automation and employment
Ensuring meaningful and secure employment
Addressing the collective needs of workers
5.1A Local & Global Inequalities: The Big Ideas
5.1A Topics
Economic inequality and stratification
Food insecurity and access to safe, nutritious food
Access to health care and medicine
5.1A Key Theories & Thinkers
Three-Level Digital Divide: (1) Access, (2) Skills, (3) Benefits.
Bourdieu's Digital Capital: Economic/cultural/social background influences your digital power.
Castells' Network Society: Life is increasingly organised around digital networks. Context: Geographic location shapes network access and quality
Amartya Sen's Entitlement Approach: Hunger stems from lack of access, not food shortage. Digital payment systems and food delivery platforms reshape food access
Inverse Care Law (Hart): Medical care flows to the wealthy, away from those most in need. Algorithmic healthcare reinforces existing geographic and social inequalities
5.1A Core Concepts
Power: Who controls access to digital resources and algorithmic decisions?
Access: Digital divides shape well-being through computing infrastructure
Identity: Who is included/excluded in digital systems and community networks?
Sustainability: Tech-driven food and health systems within environmental contexts
Key Concepts & Thinkers:
Digital Divide / Digital Inequality The gap in access, skills, and online participation - linked to well-being through subjective well-being theory and Internet use research (e.g., Hargittai’s internet skills research).
Network Society (Manuel Castells & Jan van Dijk): Castells coined the idea of a network society shaped by digital networks at all levels (individual to global); van Dijk echoes this as a communications-era society.
Digital Self-Determination & Digital Apartheid: Examines individuals’ ability to control their digital lives, issues of autonomy, inequality, and exclusion (e.g., Christian Fuchs on “digital apartheid” detailing access disparities across material, skills, and cultural dimensions).
Public Health Model for Tech Governance: Approaches tech policy through a public-health lens - preventing harm and building equitable systems, spotlighting systemic inequalities mirrored in digital governance.
5.1A Local and global inequalities (Food insecurity and access to safe, nutritious and sufficient food)
Platform-Based Food Systems:
Food Deserts Go Digital: Uber Eats/DoorDash maps show service gaps in low-income areas
Algorithmic Food Access: AI determines delivery zones, often excluding poorest neighbourhoods
Ghana's Jumia Food: Platform expansion creates new food access but requires smartphone/banking
AMARTYA SEN's Entitlement Approach Enhanced:
Digital Entitlements: Access now includes digital literacy, smartphone ownership, and internet connectivity
Platform Dependency: Food access is increasingly mediated by algorithmic systems beyond individual control
Food Sovereignty vs. Platform Control:
Via Campesina vs. Big Tech: Traditional food sovereignty movements now resist algorithmic control of food systems
Indian Farmer Apps: Government-supported platforms vs. corporate platforms create new power dynamics
CASE STUDIES Weaponised Hunger:
Gaza Strip: 160+ aid workers killed in 3 months (systematic targeting)
Sudan: Zamzam camp famine confirmed (July 2024) - 25.6 million affected
Ethiopia 1984: 1 million deaths despite being 3rd largest food producer
Yemen: 17 million (60% population) in crisis, 70% deaths are children under 5
5.1A Local and global inequalities (Access to health care and medicine)
Core Theories & Thinkers:
The Inverse Care Law (JULIAN TUDOR HART, 1971): "The availability of good medical care tends to vary inversely with the need for it in the population served" - healthcare flows like champagne: rich get lots, poor get none. (Digital Version: "AI-powered healthcare tends to flow toward those who need it least")
Social Determinants of Health (WHO Framework): Your health depends more on where you're born and live than your genes or medical care
Social Gradient in Health (MARMOT Model): Health inequality isn't just rich vs. poor - there's a step-by-step ladder from top to bottom of society
Algorithm Training Bias: AI trained on wealthy, white populations performs poorly for others
Digital Health Divide: Telemedicine requires devices, internet, digital literacy - excluding most vulnerable
Contemporary Issues:
COVID-19 Vaccine Apartheid: By January 2021: 39 million doses in rich countries vs. 25 doses in one poor country
Digital Health Divide: AI medicine and genomics could make health inequality worse if only the wealthy can access them
Health Data Colonialism: Who owns and profits from your medical data?
Telemedicine Revolution: COVID-19 accelerated digital healthcare, but who got left behind?
Global South Digital Health Innovation
Indian Telemedicine Revolution:
Apollo Telemedicine: Connects 300+ rural hospitals to specialist doctors in cities
Arogya Setu App: COVID contact tracing reached 230 million users, but raised privacy concerns
AI Diagnostics: Diabetic retinopathy screening using smartphone cameras in rural clinics
African Health Tech:
mHealth Ghana: SMS-based maternal health support reduces mortality 16%
South African HIV Apps: Digital adherence monitoring improves treatment outcomes
Algorithmic Healthcare Discrimination
Contemporary Digital Health Issues:
COVID-19 Vaccine Algorithms: AI allocation systems reinforced racial and geographic disparities
Insurance AI Bias: Algorithms deny coverage based on social media posts and shopping data
Diagnostic Algorithm Inequality: Skin cancer AI 98% accurate for white skin, 60% for dark skin
Mental Health Apps: Cultural bias in AI chatbots misunderstands non-Western emotional expression
Health Data Colonialism:
Big Tech Health Data: Google/Amazon extract health data value from communities without compensation
Genomic Inequality: Precision medicine based on white European genomes excludes 80% of world population
5.1B Changing Populations (Demographics, Ageing, Migration): The Big Ideas
5.1B Topics
Population growth
Shifting demographics (ageing and youth)
Migration and movement of people
5.1B Key Theories & Thinkers
Demographic Transition Theory: All societies move from high to low birth/death rates. Computing: Digital contraception apps and fertility tracking reshape reproductive choices
Digital Well-being Theory (DWBT): ICT use affects well-being, shaped by habitus. Community: Social media creates new forms of social capital and isolation
Positive Computing: Tech designed for human flourishing. Context: Cultural differences in what constitutes "positive" digital interaction
Ravenstein's Laws Enhanced: Push-pull migration now includes digital connectivity factors
5.1B Digital Case Studies
AI in elderly care in Japan: robots, monitoring systems, smart homes.
China’s digital generation gap: young vs. old in tech literacy.
Climate migration tracked through digital mapping.
5.1 B Core Concepts
Networks: Migration and smart city infrastructures.
Identity: Generational digital divides.
Culture: Habitus shaping tech use.
Access: Unequal digital engagement across age groups.
5.1B Changing populations (Population growth)
Foundational Theories:
MALTHUS vs. Reality (1798): Predicted population would outstrip food supply causing mass starvation. Wrong about timing, but resource limits still matter
Demographic Transition Theory (WARREN THOMPSON 1930, FRANK NOTESTEIN 1940s-50s): All societies move through 5 stages from high birth/death rates to low birth/death rates (with population explosion in between)
Current Global Picture:
Peak Population Coming: 8.2 billion now → 9.7 billion (2050) → 10.3 billion peak (2080s)
Digital Demographic Divide: Population growth concentrated in regions with weakest digital infrastructure
Digital Influences on Population Growth
Fertility and Digital Technology:
Dating Apps Impact: Tinder/Bumble in South Korea correlate with declining marriage/birth rates
Contraception Apps: Natural Cycles app used by 2 million women, FDA-approved birth control
China's Digital Family Planning: Apps track reproductive health, extending state population control
Digital Population Surveillance:
India's Digital Census: Aadhaar system enables real-time population tracking
China's Population Management: Social credit system influences reproductive decisions
Key Concepts for Exams:
Youth Bulge: Large young population can fuel economic growth OR cause instability if no jobs available
Population Momentum (JOHN BONGAARTS): Even when fertility drops, population keeps growing for decades due to young people reaching reproductive age
Brain Drain Crisis: Pakistan lost 800,000 skilled workers in 6 months (2023) - doctors, engineers, IT experts fleeing
Regional Hotspots:
Africa's Population Explosion: Will double by 2050, 50% of global births by 2100
India's Demographic Sweet Spot: 50% under 25, dividend phase peaks 2041 when 65% will be working age
5.1B Changing populations (Shifting demographics, for example, ageing and youth populations)
The Great Age Shift:
Global Ageing Tsunami: Population 60+ doubles to 2.1 billion by 2050
Digital Caregiving Crisis: Who cares for elders in digital society?
Generation Alpha vs. Silver Surfers
AI Elderly Care Innovation:
Japan's Robot Caregivers: PARO therapeutic robots reduce loneliness, 5,000+ facilities
Smart Home Monitoring: AI systems detect falls, medication compliance for aging-in-place
Digital Divide in Ageing: Rural elderly excluded from digital health solutions
China's Digital Generation Gap:
WeChat Pay Exclusion: Elderly unable to pay for basic services without smartphones
Digital Literacy Programs: Intergenerational teaching - grandchildren as tech tutors
Social Credit Age Bias: Algorithms favour younger users in social scoring
Social Media Demographics:
TikTok Generation: Generation Alpha (2010-2025) first fully algorithmic generation
LinkedIn Ageism: AI recruitment algorithms discriminate against older profiles
Dating App Demographics: Algorithmic matching reinforces age-based social stratification
Digital Generation Wars:
Generation Alpha (2010-2025) (McCRINDLE coined the term): First fully 21st-century generation, 2 billion by 2025, digital natives from birth
Generation Z (1995-2009): First truly global generation, shaped by social media and climate crisis
The Great Digital Divide: Gen Alpha spends 4 hours/day on social media vs. older generations struggling to keep up
Critical Regional Case:
East Asian Demographic Cliff: South Korea, China, Singapore are ageing fastest globally. Labor force shrinking 30-40% while elderly population doubles
Intergenerational Tensions:
COVID-19 as Bridge: Pandemic forced young people to teach grandparents digital skills, creating unexpected learning exchanges
Screen Time Explosion: Gen Alpha gaming time jumped 65% (2020-2024), and parents worry about attention spans
China's Digital Generation Gap (Study by Chinese researchers): Study of 3,790 households shows massive differences: young generation scored 16.82 vs. the elderly 11.68 on digital engagement
5.1B Changing populations (Migration and the movement of people)
The Global Movement Scale:
281 million international migrants globally (2022): tripled since 1970 (84 million)
123.2 million forcibly displaced (2024): equivalent to 1 in 67 people on Earth
40% are children under 18 years: largest youth displacement in history
RAVENSTEIN's Laws of Migration (1885):
Push-Pull Process: Unfavourable conditions "push," favourable conditions "pull"
Distance Decay Principle: Migration decreases as distance increases
Step Migration: Movement occurs in stages, not one long move
Economic Motivation: Primary cause is better economic opportunities
LEE's Theory of Migration (1966):
Four Factor Framework: (1) Origin factors, (2) Destination factors, (3) Intervening obstacles, (4) Personal factors
Selectivity Principle: Age, gender, education affect response to push-pull factors
Threshold Effect: Decision requires overcoming natural inertia + obstacles
New Digital Migration Patterns
Digital Nomadism:
Estonia's Digital Nomad Visa: Remote work visas create new migration category
Bali Digital Nomad Impact: Western remote workers gentrify local communities
African Digital Cities: Rwanda's Kigali positions as regional tech hub attracting talent
Climate Migration and Digital Mapping:
Pacific Climate Refugees: Digital mapping predicts sea-level displacement
Bangladesh Early Warning: AI flood prediction enables proactive migration planning
Climate Migration Apps: Digital platforms coordinate climate refugee resettlement
Digital Diaspora Networks:
WhatsApp Migration Groups: Real-time advice networks guide migration routes
Facebook Migration Misinformation: False information shapes dangerous migration choices
LinkedIn Skill Migration: Professional network data reveals global talent flows
CASE STUDIES:
Ukrainian Digital Refugees:
Telegram Coordination: Encrypted messaging coordinates refugee assistance
Digital Identity Preservation: Cloud storage maintains documents during displacement
Remote Work Continuity: Ukrainian IT workers maintain jobs while displaced
Syrian Digital Diaspora:
Refugee Integration Apps: Digital tools help navigate host country systems
Hawala Digital Remittances: Traditional money transfer goes digital for Syrian families
5.1C The Future of Work: The Big Ideas
5.1C Topics
Automation & employment
Ensuring meaningful and secure work
Addressing the collective needs of workers
5.1C Key Theories & Thinkers
Brynjolfsson & McAfee (Second Machine Age): Tech increases wealth ("bounty") but widens inequality ("spread"). Computing: AI capabilities vs. human skills create new winner-take-all dynamics
Platform Cooperativism (Trebor Scholz): Worker-owned digital platforms as alternatives. Community: Collective ownership models challenge platform capitalism
Algorithmic Management Theory: AI systems increasingly control worker behavior and outcomes. Context: Cultural differences in workplace surveillance acceptance
5.1C Digital Case Studies
Uber drivers under algorithmic management (gig economy precarity).
IBM AskHR chatbot replacing millions of HR interactions.
Finland’s UBI experiment — testing responses to automation.
5.1C Core Concepts
Power: Algorithms and platforms dominate labour relations.
Access: Who benefits from automation — and who is excluded?
Networks: Platform work as globalised labour.
Culture: Changing meanings of “work” in digital society.
5.1C The future of work (Automation and employment)
Hiring Algorithm Discrimination:
Amazon's Biased AI Recruiter: System downgraded resumes containing "women" (discontinued 2018)
HireVue Video Interviews: AI judges facial expressions, voice tone - cultural bias embedded
Criminal Background AI: Algorithms perpetuate racial bias in background check systems
Global South Employment Innovation:
Nigeria's Andela Model: Train African developers for global remote work
India's Gig Economy: Zomato, Swiggy create millions of delivery jobs via algorithmic management
Kenya's iHub: Tech innovation hub creates local platform cooperative alternatives
Digital Taylorism:
Amazon Warehouse AI: Algorithms set productivity targets, fire workers automatically
Uber Driver Control: Surge pricing algorithms manipulate driver behaviour without transparency
Microsoft Productivity Score: AI monitors employee computer activity, meetings, emails
Resistance and Innovation:
Turkopticon: Browser extension lets Amazon Mechanical Turk workers rate employers
Driver Coordination Apps: Uber drivers use WhatsApp groups to coordinate strike action
Fairwork Foundation: Rates platform employers on algorithmic transparency and worker rights
5.1C The future of work (Ensuring meaningful and secure employment)
ILO Decent Work Agenda (1999): "Productive work in conditions of freedom, equity, security and human dignity". Four pillars: Employment creation, Social protection, Rights at work, Social dialogue. Central to UN Sustainable Development Goals - employment as development strategy
The Nordic Solution - Danish Flexicurity Model: The Golden Triangle (1990s): Flexibility: Easy hiring/firing, 25% of private sector workers change jobs annually. Security: Up to 2 years unemployment benefits (67% wage replacement). Active Labor Market Policy: Retraining, job search support, "right and duty" principle
Gig Economy Realities: Digital platform workers = new working class with precarious conditions. 77% of platform earners have health insurance, but 10 points below national average. No workers' compensation if injured during gig work
Active Labour Market Policies (ALMPs): Denmark spends more on ALMPs than any OECD country. Compulsory participation for unemployment benefit recipients. Addresses moral hazard - prevents long-term benefit dependency
The Security-Flexibility Trade-off: Danish model proves high flexibility and high security can coexist - but requires strong institutions and social trust
The Precarity Paradox: Gig work offers flexibility but creates new forms of insecurity - workers want autonomy without vulnerability
The Collective Action Problem: Individual solutions (relational work, skill building) can't replace collective protections and worker power
The Platform Dilemma: Technology enables new work forms but concentrates wealth while distributing risk to workers
The Policy Innovation Need: Traditional employment law designed for standard jobs - requires creative solutions for new work arrangements
African Platform Cooperatives:
Green Taxi Cooperative (Denver): Worker-owned Uber alternative, 37% market share
Stocksy United (Global): Photographer-owned stock photo platform, profit-sharing model
South African Uber Alternative: Bolt driver cooperative experiment in Cape Town
Latin American Innovations:
Brazil's Autonomous Couriers: Delivery worker cooperatives challenge iFood/Uber Eats
Argentina's Platform Cooperatives: Government supports worker-owned platform development
5.1C The future of work (Addressing the collective needs of workers)
The Platform Cooperative Movement: Trebor Scholz's vision of worker-owned Uber alternatives like Green Taxi Cooperative (37% Denver market share)
Digital Organising Innovation: Google's 20,000-worker walkout used social media vs traditional union structures
Collective Action Theory: Suresh Naidu's analysis of why dense social networks are a prerequisite for modern organising
ITUC Global Strategy: International Trade Union Confederation's response to platform economy and informal work
Digital Labour Organising:
Google Walkout (2018): 20,000 workers coordinate via internal messaging systems
Deliveroo Strike Apps: Riders use encrypted messaging to coordinate strikes
Amazon Warehouse Organising: Workers use TikTok, Instagram to build solidarity
Algorithmic Collective Bargaining:
Uber Driver Data Rights: European drivers win right to see algorithmic decision-making
Platform Worker Protection Laws: EU Digital Services Act requires algorithmic transparency
AI Union Organising: Unions demand right to audit hiring/firing algorithms
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