Practice A4.4 Ethical considerations with authentic IB Computer Science (First Exam 2027) exam questions for both SL and HL students. This question bank mirrors Paper 1, 2, 3 structure, covering key topics like programming concepts, algorithms, and data structures. Get instant solutions, detailed explanations, and build exam confidence with questions in the style of IB examiners.
An educational technology platform uses AI to personalize learning experiences for students while addressing concerns about data privacy and algorithmic bias.
Discuss the ethical considerations of using AI to track student performance and predict academic outcomes.
A facial recognition system is deployed for security purposes in public spaces, raising concerns about privacy, surveillance, and civil liberties.
Examine the ethical challenges of facial recognition technology in public surveillance, considering privacy rights, consent, and potential for misuse.
Analyse how demographic bias in facial recognition systems disproportionately affects certain groups and discuss solutions to address these inequities.
A predictive policing system uses machine learning to forecast crime hotspots and allocate police resources, but critics argue it reinforces racial profiling and over-policing of minority communities.
Analyse the potential benefits and harms of predictive policing systems:
| Aspect | Potential Benefits | Potential Harms | Affected Communities | Mitigation Measures |
|---|---|---|---|---|
| Crime Prevention | - | - | - | - |
| Resource Allocation | Efficient deployment | - | General public | - |
| Community Relations | - | - | - | Community engagement |
| Justice System | - | Reinforced bias | - | - |
Evaluate strategies for developing more equitable predictive policing systems that balance public safety with civil rights.
A smart city traffic management system uses machine learning to optimize traffic flow, reduce emissions, and improve public safety across a metropolitan area.
Explain how data from multiple sources (traffic cameras, GPS, weather, events) must be integrated and pre-processed for effective traffic management.
Discuss the privacy and surveillance implications of comprehensive traffic monitoring systems in urban environments.
A financial fraud detection system processes millions of transactions daily using machine learning to identify suspicious activities while minimizing false positives that inconvenience customers.
Explain how ensemble methods and anomaly detection algorithms can be combined to improve fraud detection accuracy.
Analyse the ethical considerations of automated fraud detection including customer privacy, algorithmic bias, and the presumption of innocence.
An autonomous vehicle must make split-second decisions in emergency situations where harm to different groups of people is unavoidable.
Examine the ethical dilemmas posed by autonomous vehicle decision-making algorithms, including the trolley problem and value of life considerations.
Discuss how society should determine the ethical frameworks that guide autonomous vehicle programming.
A ride-sharing platform uses machine learning for dynamic pricing, driver matching, and route optimization while facing scrutiny over algorithmic fairness and labor practices. (c) Evaluate the ethical implications of surge pricing algorithms and their impact on transportation equity in different communities.
Evaluate the ethical implications of surge pricing algorithms and their impact on transportation equity in different communities.
A smart agriculture platform uses machine learning to optimize crop yields while addressing concerns about environmental impact and farmer autonomy.
Describe how reinforcement learning algorithms can optimize irrigation and fertilizer application while minimizing environmental impact.
A recommendation algorithm on a social media platform influences what content billions of users see, potentially affecting public opinion and democratic processes.
Analyse the ethical responsibilities of technology companies regarding algorithmic transparency and the impact of recommendation systems on society.
Evaluate different approaches to algorithmic accountability including auditing, regulation, and self-governance by technology companies.
A ride-sharing platform uses machine learning for dynamic pricing, driver matching, and route optimization while facing scrutiny over algorithmic fairness and labor practices.
Explain how online learning algorithms enable real-time adaptation to traffic patterns, demand fluctuations, and special events.