Practice 3.2 Algorithms with authentic IB Digital Society (DS) exam questions for both SL and HL students. This question bank mirrors Paper 1, 2, 3 structure, covering key topics like systems and structures, human behavior and interaction, and digital technologies in society. Get instant solutions, detailed explanations, and build exam confidence with questions in the style of IB examiners.
Paper
Level
Question 1
SLPaper 1
Sentencing criminals using artificial intelligence (AI)
In 10 states in the United States, artificial intelligence (AI) software is used for sentencing criminals. Once criminals are found guilty, judges need to determine the lengths of their prison sentences. One factor used by judges is the likelihood of the criminal re-offending*.
The AI software uses machine learning to determine how likely it is that a criminal will re-offend. This result is presented as a percentage; for example, the criminal has a 90 % chance of re-offending. Research has indicated that AI software is often, but not always, more reliable than human judges in predicting who is likely to re-offend.
There is general support for identifying people who are unlikely to re-offend, as they do not need to be sent to prisons that are already overcrowded.
Recently, Eric Loomis was sentenced by the state of Wisconsin using proprietary AI software. Eric had to answer over 100 questions to provide the AI software with enough information for it to decide the length of his sentence. When Eric was given a six-year sentence, he appealed and wanted to see the algorithms that led to this sentence. Eric lost the appeal.
On the other hand, the European Union (EU) has passed a law that allows citizens to challenge decisions made by algorithms in the criminal justice system.
* re-offending: committing another crime in the future
1.[2]
Identify two characteristics of artificial intelligence (AI) systems.
2.[2]
Outline one problem that may arise if proprietary software rather than open-source software is used to develop algorithms.
3.[2]
The developers of the AI software decided to use supervised machine learning to develop the algorithms in the sentencing software.
Identify two advantages of using supervised learning.
4.[2]
The developers of the AI software used visualizations as part of the development process.
Explain one reason why visualizations would be used as part of the development process.
5.[4]
Explain two problems the developers of the AI system could encounter when gathering the data that will be input into the AI system.
6.[8]
To what extent should the decisions of judges be based on algorithms rather than their knowledge and experience?
Question 2
SL & HLPaper 1
1.[2]
Define the term “finite” in the context of algorithms.
2.[2]
Identify two reasons why an algorithm should have well-defined inputs and outputs.
3.[4]
Explain why an algorithm must be unambiguous to function correctly.
4.[4]
Describe one example where the feasibility of an algorithm impacts its use in a real-world application.
Question 3
SLPaper 1
The role of portable digital devices in health
Jaime is an athlete and uses his sports watch to monitor his training sessions. He also uses it to keep a record of his health and well-being. The sports watch can monitor Jaime’s vital signs. It is also global positioning systems (GPS) enabled, so it can track his location (see Figure 4).
Figure 4: Data collected by a sports watch
The information that is recorded by Jaime’s sports watch is synchronized with a mobile application (app) installed on his cellphone/mobile phone.
1.[2]
Identify two vital signs that can be recorded by Jaime’s sports watch.
2.[4]
Identify the steps that the GPS receiver in Jaime’s sports watch uses to show the routes of his training runs.
3.[6]
Jaime has decided to share his personal health information with researchers at the University of Sierra Nevada.
Analyse Jaime’s decision to share his personal health information with the University of Sierra Nevada.
4.[8]
The development of mobile health apps has changed the way citizens manage their own health and well-being.
Discuss whether citizens like Jaime should rely only on the advice of a health app to manage their own health and well-being.
Question 4
SLPaper 1
Wildfire modelling
The fire control centre in the Kinakora National Park in New Zealand often has to cope with the natural phenomenon of wildfires. Staff have been collecting data about wildfires since 1970.
The size of each wildfire is measured, and the vegetation types affected are recorded. Data on the weather conditions is collected from sensors in the park. The staff at the fire control centre use this information to fight the wildfire.
A new computer modelling system is being developed using data collected from previous wildfires. This new system will improve the quality of the information available when fighting future wildfires.
The new system will also enable staff at Kinakora National Park to send information to tourists in the park to warn them when they are in danger from a wildfire.
1.[2]
Identify two measurements that could be taken by the weather sensors in Kinakora National Park.
2.[2]
Identify two methods that could be used to train the staff to use the new computer modelling system.
3.[2]
Identify two methods of visualization that could be used to present information from the new computer modelling system.
4.[6]
Two methods for informing tourists about wildfires in Kinakora National Park are:
- short message service (SMS) texting/text messaging
- posting information on the Kinakora National Park website.
Analyse these two methods.
5.[8]
Evaluate Kinakora National Park’s decision to use computer modelling to develop strategies for dealing with wildfires.
Question 5
HLPaper 1
The Role of Machine Learning in Predictive Policing
Machine learning algorithms are increasingly used in predictive policing to identify potential crime hotspots and allocate resources. While these tools may improve efficiency, concerns exist about bias in crime data, which can lead to unjust targeting of certain communities.
1.[12]
Evaluate the ethical implications of using machine learning in predictive policing, considering both benefits in resource allocation and the risks of reinforcing bias.
Question 6
HLPaper 1
1.[12]
Cameras in school
The principal at Flynn School has received requests from parents saying that they would like to monitor their children’s performance in school more closely. He is considering extending the school’s IT system by installing cameras linked to facial recognition software that can record student behaviour in lessons.
The facial recognition software can determine a student’s attention level and behaviour, such as identifying if they are listening, answering questions, talking with other students, or sleeping. The software uses machine learning to analyse each student’s behaviour and gives them a weekly score that is automatically emailed to their parents.
The principal claims that monitoring students’ behaviour more closely will improve the teaching and learning that takes place.
Discuss whether Flynn School should introduce a facial recognition system that uses machine learning to analyse each student’s behaviour and give them a score that is automatically emailed to their parents.
Question 7
HLPaper 1
In criminal justice, "black box" algorithms are increasingly used to make decisions about bail, parole, and sentencing. However, the lack of transparency and potential for bias raise serious ethical concerns about fairness and accountability.
1.[12]
Evaluate the challenges of implementing algorithmic transparency and accountability in criminal justice, particularly with “black box” algorithms.
Question 8
SLPaper 1
Airport luggage control
Large airports need to handle thousands of pieces of luggage (including suitcases and other types of baggage) from the moment passengers check them in at the counter until the moment they arrive at their final destination. Sometimes a passenger will change airplanes during their journey, so their bags will need to be transferred by conveyor belt from one plane to another.
When the passenger checks in at the airline counter, a tag is printed and attached to each piece of luggage (see Figure 2). This tag has information about the passenger and their journey printed on it and also shows both a barcode and a ten-digit number that are unique to each piece of luggage.
Figure 2: A luggage tag
The luggage then goes on to a number of conveyor belts that take each bag to where it needs to go. Conveyor belts connect to other conveyor belts that direct luggage from the airport building to the correct airplane, from one airplane to the next if the passenger changes airplanes during the journey, or to the baggage reclaim area at the end of the journey. The airport luggage control system will know when to push the bag from one conveyor belt to another to ensure it gets to the correct destination.
The barcode allows the airport’s luggage control system to access a database containing information about each piece of luggage.
1.[2]
Identify two pieces of information about the luggage that may be obtained from this database.
2.[4]
Identify the steps taken by the luggage control system to decide which conveyor belt to choose when a bag reaches a junction between two conveyor belts.
3.[6]
Analyse the decision by some airports to attach radio frequency identification (RFID) tags to luggage when it is checked in by the passenger, instead of barcode paper printed tags.
4.[8]
Airlines have databases that contain data about passengers when tickets are booked. This data includes travel dates, itineraries, contact details, passport details and passengers’ home addresses. When passengers purchase a ticket online from an airline company, they have to accept the airline’s terms and conditions by clicking “Agree” (see Figure 3).
Figure 3: Acceptance of airline terms and conditions
Within these terms and conditions, it states that the airline may receive a request to share this data with the government of the country to which the passenger is flying.
Discuss whether airlines should share passengers’ data with the governments of the countries to which they are flying.
Question 9
HLPaper 1
In healthcare, algorithms are employed for predictive diagnostics by analyzing patient data to predict diseases or suggest treatments. While these algorithms can increase efficiency, a lack of transparency and accountability in cases of misdiagnosis or bias raises ethical concerns.
1.[12]
Evaluate the ethical implications of relying on algorithms for health diagnoses, particularly in terms of transparency and accountability for patient outcomes.
Question 10
SL & HLPaper 1
Facial recognition algorithms, used for security in airports, rely on large datasets and are sometimes criticized for algorithmic bias. For instance, these algorithms have been known to misidentify individuals of certain racial backgrounds, raising fairness and transparency issues.
1.[2]
Identify two issues related to algorithmic bias in facial recognition software.
2.[4]
Explain why transparency is essential for accountability in facial recognition algorithms used in security.
3.[4]
Discuss one risk associated with “black box” algorithms in facial recognition systems.
4.[8]
Evaluate the impact of algorithmic bias on fairness in facial recognition, particularly concerning racial and ethnic disparities.