IB Digital Society 1.1A Introduction to Digital Society Notes

1.1A Introduction to Digital Society

What the Course Is

1. Digital Society is an individuals and societies subject, alongside history, geography, and economics. It studies how digital systems affect people and communities.
2. It is a social-science course: you study a system like a recommendation feed or facial recognition closely enough to weigh its effect on people, without building it.
3. A computer scientist works out how a delivery app plans its routes. In Digital Society the question is different: what the app does to courier pay and to the restaurants it lists.

A Contested Subject

1. Digital society is a contested term: people disagree on what it includes and on whether its developments are good or bad.
2. Contested: does social media foster tolerance or entrench tribalism? It gives isolated groups a voice. It also rewards outrage and pulls people into hostile camps. Which effect dominates depends on the users and the case you look at.
3. Exam consequence: a strong answer weighs competing evidence and reaches a supported, qualified conclusion. Handing down a flat verdict scores poorly.

The Framework: Concepts, Content, Contexts

1. Every inquiry combines three sets of seven: concepts, content, contexts.
2. Concepts (7 lenses): change, expression, identity, power, space, systems, values and ethics.
3. Content (7 digital systems): data, algorithms, computers, networks and the internet, media, artificial intelligence, robots and autonomous technologies.
4. Contexts (7 settings): cultural, economic, environmental, health, human knowledge, political, social.
5. Combine, never study alone: a ride-hailing platform (algorithms + data) examined through power (platform vs driver) in the economic context is one inquiry. Swap the lens to space and the context to cultural and the same platform yields a separate inquiry.

Content: Just Enough to Judge It

1. Learn each system to the depth that lets you reason about impact, and no more.
2. Example: a machine learning hiring model. Skip the maths. What matters is that a model trained on past hiring data absorbs its bias and repeats it at scale, which lets you discuss fairness and accountability.
3. Target: social literacy, the level that supports judgement. Too little knowledge leaves your analysis vague. Straying into engineering detail wastes effort the course never assesses.

Concepts: One Example, Seven Lenses

1. Each concept is a question you put to any system; the same example answers differently under each.
2. Facial recognition in a public square: power (who watches whom, who can't opt out); space (public place becomes monitored place); identity (your face becomes a key to your records); values and ethics (consent, where the data goes).
3. Show the lens working: power = who gains the capacity to influence or control whom. Just dropping the word in is only a label.

Real-World Examples: The Evidence

1. Anchor every inquiry in a real-world example: a specific, existing instance. "Social media" is a category; the 2024 AI robocall faking President Biden's voice in the New Hampshire primary is a specific instance.
2. To earn marks: name the system and what it does; give who/where/when and what happened; separate impacts from implications; name the concepts. Stating an example without explaining it is the top way to lose marks.
3. Prefer examples that are current and local.

Impacts vs Implications, People and Communities

1. Impacts = effects that have already happened. Implications = opportunities and risks going forward. Keep them distinct.
2. Predictive policing test. Impacts: some neighbourhoods patrolled more, arrests followed, communities felt it. Implications: risk that biased policing data trains a tool that repeats the bias; opportunity that open data makes the bias auditable.
3. Every system touches several people and communities who rarely agree. Delivery app: customer (convenience), courier (steady income), restaurant (reach without high commission), platform (growth), city (traffic, labour law).
4. Name the competing groups: treating the user as the only stakeholder is thin, and the exam rewards the plural view.

Inquiry: How the Course Works

1. You run inquiries, not just memorise facts; the process is examined and structures the internal assessment (IA). Five stages:
   1. Focus: open question, link to concepts/content/context, pick a real-world example.
   2. Explore: find diverse sources, weigh claims and perspectives.
   3. Investigate: analyse and evaluate impacts and implications for people and communities.
   4. Reflect: draw further insight, consider emerging trends and future developments.
   5. Share: communicate findings clearly, backed by evidence.
2. The IA is one inquiry done alone: a research and analysis project. You weigh existing evidence rather than run an experiment or collect primary data.