Digital systems both reflect and construct identity. They reflect existing characteristics and preferences, but also influence self-presentation, how others perceive people, and how identities develop over time.
In IB Digital Society, identity helps define a person, group, social entity, or community. It is not static: it changes with context, time, and other people's perspectives. It is also intersectional, involving age, culture, nationality, gender, race, religion, and social class.
| Digital systems reflect identity | Digital systems construct identity |
|---|---|
| Users select content based on existing interests and values. | Recommendations expose users to ideas, communities, and behaviours that may change their interests. |
| Profiles communicate chosen characteristics and affiliations. | Platform features encourage curated self-presentation through filters and follower counts. |
| Activity data records existing preferences. | Algorithms classify users and repeatedly present content based on those classifications. |
Consider TikTok's For You feed. System: its recommendation system processes interaction data, including watch time, likes, shares, and searches, to select videos. Example specifics: TikTok adapts each user's feed to these behavioural signals. Existing interests shape recommendations, while repeated recommendations may strengthen an interest or connect users with a new community.
Impacts: users may discover communities supporting self-expression and belonging, while algorithmic classifications can narrow the people and ideas they encounter. Implications: personalization enables identity exploration but risks stereotyping users or reinforcing a limited version of them. This shows systems because behaviour and recommendations form a feedback loop, and power because the platform influences which identities gain visibility.
A common misconception is technological determinism, the belief that digital systems independently determine identity. Identity instead emerges through interaction among users, communities, institutions, platform design, and social context.
For SL and HL exams, avoid a one-sided answer. A strong discuss response balances both positions, explains a specific real-world example, and reaches a supported, context-specific conclusion.
