What counts as a real-world example in the IB Digital Society IA?

A real-world example is a specific, existing digital system operating in a defined social context. It might be a biometric payment system, recommendation feature, automated workplace tool, content-moderation process, or school AI policy. A broad technology such as artificial intelligence is not sufficiently specific by itself. You must explain how the example connects to your inquiry question, relevant course concepts, content, and context. The strongest examples also provide evidence of measurable or documented impacts on identifiable people and communities.

Can I use a case study from another country for my Digital Society IA?

Yes, the real-world example can be local or global, provided that it is specific and relevant to your inquiry. A foreign case may offer strong regulatory documents, academic research, and contrasting stakeholder perspectives. However, you still need a realistic route to first-hand research, which may be difficult if the affected community is inaccessible. You could interview a relevant expert or investigate how local users understand the same system, but you must explain how that evidence relates to the original case. A local example is often easier to investigate in depth, although it is not automatically better.

How recent should an IB Digital Society IA example be?

There is no simple rule that every example must come from the current year. The example should be sufficiently current to support analysis of an existing digital system and its continuing impacts or implications. An older deployment can remain useful when its consequences, regulation, or influence are still developing. Recent cases often make it easier to discuss emerging trends and future developments, but reliable evidence may be more limited. Choose the period that best supports a focused investigation rather than selecting a case only because it appeared in the latest news.

Can I investigate ChatGPT for my Digital Society IA?

You can investigate ChatGPT, but the platform name alone is much too broad for a successful inquiry. Narrow the example to a defined use, group, institution, and impact, such as the use of ChatGPT for formative feedback in one school department. Your question should allow you to evaluate benefits and risks involving learning, agency, privacy, bias, or academic integrity. Interviews with teachers and students can provide contrasting first-hand perspectives, while policies and research can support your analysis. Avoid asking participants to disclose academic misconduct or submit private conversations with an AI system.

Do I need both positive and negative impacts in my inquiry?

You are not required to divide the presentation mechanically into positive and negative sections. However, effective evaluation normally considers competing impacts, stakeholder interests, trade-offs, and limitations. A facial-recognition system, for example, may improve speed or security while creating concerns about consent, accuracy, and unequal treatment. The relative importance of those consequences may differ among users, administrators, companies, and regulators. Your conclusion should make a justified judgment rather than claiming that the technology is entirely beneficial or entirely harmful.

How many real-world examples should I use in the Digital Society IA?

Your inquiry should be anchored in one specific, relevant real-world example rather than several unrelated technologies. Maintaining one central case allows you to develop sustained analysis of its system, stakeholders, impacts, and implications. You may introduce a limited comparison when it clarifies a safeguard, alternative design, or different outcome. That comparison should support the main inquiry rather than becoming a second independent project. If you cannot explain the boundaries of your central system in one or two sentences, your scope probably needs further narrowing.

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Real-World IB Digital Society IA Examples

IB Digital Society Internal Assessment IB IA

• 30 Sept 2026•10

Real-World IB Digital Society IA Examples

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Real-World IB Digital Society IA Examples | RevisionDojo

Back to all posts

Real-World IB Digital Society IA Examples

IB Digital Society Internal Assessment IB IA

• 30 Sept 2026•10

The best IB Digital Society IA examples focus on one identifiable digital system, a defined context, and impacts that can be investigated through credible sources and first-hand research. Artificial intelligence, privacy, and social media are not sufficiently focused topics by themselves.

The official IB Digital Society subject brief describes the inquiry project as an investigation into the impacts and implications of a digital system for people and communities. It involves an inquiry process document, a recorded multimedia presentation, and references. The examples below are starting points that must be adapted to your access, interests, and evidence.

What makes a real-world example suitable?

A strong example gives you a manageable route from evidence to a justified conclusion. Look for:

A specific digital system, such as a biometric payment system
A bounded context, including a place, organization, community, and period
Identifiable stakeholders with different interests or levels of power
A genuine tension, such as convenience versus meaningful consent
Accessible evidence, including reliable secondary sources and feasible first-hand research

“How does AI affect society?” is too broad because neither the system nor the affected community is defined. A question about how a named school’s generative-AI policy affects student agency is more workable. The RevisionDojo guide to writing a focused Digital Society IA research question provides a practical narrowing process.

Six current IB Digital Society IA examples

Real-world example	Central tension	Possible first-hand research
Facial recognition in a school canteen	Convenience versus consent	Student survey or staff interview
TikTok Lite Rewards in the EU	Engagement versus well-being	User interviews or interface analysis
Rite Aid facial-recognition surveillance	Security versus fairness	Consumer survey
Clearview AI’s facial-image database	Security versus privacy	Interviews about online-image consent
AI and Kenyan content moderators	Automation versus worker welfare	Expert or digital-worker interview
Generative AI rules in your school	Learning support versus integrity	Student and teacher interviews

1. Facial recognition for school canteen payments

Chelmer Valley High School introduced facial recognition for canteen payments in 2023. In 2024, the UK Information Commissioner’s Office reprimanded the school because it had not completed the required risk assessment before deployment and initially relied on parental opt-out instead of explicit consent.

Possible question: To what extent can facial-recognition payments improve school-canteen efficiency without undermining privacy and meaningful consent?

A student survey and administrator interview could reveal contrasting views about convenience, choice, and institutional power. Do not collect biometric data yourself.

2. TikTok Lite’s discontinued EU rewards programme

TikTok Lite rewarded users in France and Spain for activities including watching videos and following creators. Following concerns about addictive effects and inadequate risk assessment, TikTok agreed to withdraw the rewards programme permanently from the EU in 2024.

Possible question: To what extent do reward-based engagement features reduce teenage users’ autonomy?

Interviews can explore how users respond to platform rewards. Distinguish self-reported habits from medical claims about addiction.

3. Rite Aid’s use of facial recognition

The US Federal Trade Commission alleged that Rite Aid deployed facial recognition without reasonable safeguards against consumer harm. The resulting order prohibited its use for surveillance for five years and introduced requirements concerning testing, complaints, deletion, notice, and oversight.

The FTC Rite Aid case connects technical limitations with false matches, unequal outcomes, and accountability.

Possible question: How effectively can regulation protect consumers from unfair facial-recognition surveillance in retail stores?

4. Clearview AI and scraped facial images

Clearview AI created a facial-recognition service using images gathered from publicly accessible online sources. In 2024, the Dutch data-protection authority imposed a €30.5 million fine after finding that the company lacked an appropriate legal basis for processing personal data, according to the European Data Protection Board summary.

Possible question: To what extent should people control publicly posted photographs when they are repurposed for biometric databases?

Use hypothetical consent scenarios rather than collecting identifiable photographs.

5. AI and Kenyan content moderators

Content moderation exposes the human labour behind apparently automated platforms. A 2025 International Labour Organization study considered social dialogue around AI and algorithmic management, including Kenyan content moderators working within technology supply chains.

Possible question: How does algorithmic management affect the power and well-being of outsourced content moderators in Kenya?

Direct access may be difficult. Confirm feasibility early, or interview a labour researcher, union representative, or worker in comparable digitally managed employment.

6. Generative AI policy in your school

A school’s rules for ChatGPT or similar tools can provide a strong local case when you identify the precise policy, use, and affected group. UNESCO guidance on generative AI in education highlights privacy, human agency, inclusion, bias, and institutional responsibility.

Possible question: To what extent does my school’s generative-AI policy balance student agency with academic integrity in Grade 11 assignments?

Interview students and teachers, then analyse the written policy. “ChatGPT in education” remains too broad without a specific subject, year group, or educational use.

How to choose your Digital Society case study

Begin with access rather than novelty. A global controversy may provide excellent documents but little opportunity for meaningful first-hand research, while a local policy can produce detailed stakeholder evidence.

Before requesting teacher approval, check that you can:

Name the system and context in one sentence.
Identify the affected people or community.
Find contrasting credible perspectives.
conduct ethical and manageable first-hand research.
Reach a judgment about impacts or implications.

Use course concepts only when they clarify relationships within the case. Simply listing identity, power, systems, change, and ethics does not create analysis. The RevisionDojo Digital Society IA guide and coursework exemplars can help you judge whether your scope is realistic.

Common mistakes when using IA examples

Do not copy a sample question unchanged. Your inquiry must reflect your own context, access, and evidence. Investigating several unrelated systems also produces shallow analysis, so keep one central case and use comparisons only when they clarify safeguards or outcomes.

First-hand research should contribute directly to the argument, not decorate the presentation. Acknowledge limitations such as small samples, self-selection, and inaccessible stakeholders. Regulatory criticism also does not prove that every use of a technology is unethical; evaluation requires documented harms, benefits, safeguards, stakeholder differences, and uncertainty. RevisionDojo’s guide to using Digital Society case studies explains how to move from evidence to judgment.

Conclusion

Strong IB Digital Society IA examples are specific, contested, researchable, and centred on consequences for people and communities. Choose a case for which you can obtain contrasting sources and ethical first-hand evidence, then narrow it to one system and context.

RevisionDojo’s Digital Society resources, IA guide, coursework exemplars, and Jojo AI can help you refine the question, organize evidence, and test whether your conclusion is justified.

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