Author: Cigdem Sengul, Ph.D. FHEA (Computer Science, Brunel University). 

Topic: Embedding SDGs into undergraduate computing projects using problem-based learning and teamwork. 

Tool type: Guidance. 

Relevant disciplines: Computing; Computer science; Information technology; Software engineering.  

Keywords: Sustainable Development Goals; Problem-based learning; Teamwork; Design thinking; Sustainability; AHEP; Pedagogy; Higher education; Communication; Course design; Assessment; STEM; Curriculum design. 
 
Sustainability competency: Collaboration; Integrated problem-solving.

AHEP mapping: This resource addresses two of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4): The Engineer and Society (acknowledging that engineering activity can have a significant societal impact) and Engineering Practice (the practical application of engineering concepts, tools and professional skills). To map this resource to AHEP outcomes specific to a programme under these themes, access AHEP 4 here and navigate to pages 30-31 and 35-37.  

Related SDGs: All 17; see specific examples below for SDG 2 (Zero Hunger); SDG 13 (Climate Action). 
 
Reimagined Degree Map Intervention: Adapt and repurpose learning outcomes; Active pedagogies and mindset development; Authentic assessment.

Who is this article for? This article should be read by educators at all levels in Higher Education who wish to embed sustainable development goals into computing projects. 

Supporting resources:  

 

Premise:  

Education for Sustainable Development (ESD) is defined by UNESCO (2021) as:  “the process of equipping students with the knowledge and understanding, skills and attributes needed to work and live in a way that safeguards environmental, social and economic wellbeing, in the present and for future generations.” All disciplines have something to offer ESD, and all can contribute to a sustainable future. This guide presents how to embed the Sustainable Development Goals (SDGs) into undergraduate computing projects, using problem-based learning and teamwork as the main pedagogical tools (Mishra & Mishra, 2020).  

 

Embedding Sustainable Development Goals (SDGs) into computing group projects: 

Typically, the aim of the undergraduate Computing Group Project is to: 

This type of project provides students with an opportunity to integrate various skills, including design, software development, project management, and effective communication.  

 

In this project setting, the students can be asked to select a project theme based on the SDGs. The module team then can support student learning in three key ways: 

1. Lectures, labs, and regular formative assessments can build on lab activities to walk the project groups through a sustainability journey that starts from a project pitch, continues with design, implementation, and project progress reporting, and ends with delivering a final demo.

2. Blending large classroom teaching with small group teaching, where each group is assigned a tutor, to ensure timely support and feedback on formative assessments.

3. A summative assessment based on a well-structured project portfolio template, guiding students to present and reflect on their individual contribution to the group effort. This portfolio may form the only graded element of their work, giving the students the opportunity to learn from their mistakes in formative assessments and present their best work at the end of the module.  

 

Mapping the learning outcomes to the eight UNESCO key competencies for sustainability (Advance HE, 2021), the students will have the opportunity to experience the following: 

 

More specifically, sustainable development can be embedded following a lecture-lab-formative assessment-summative assessment path: 

1. Introduction lecture: Introduce the SDGs and give real-life examples of software that contribute to SDGs (examples include: for SDG 2 – Zero Hunger, the World Food Programme’s Hunger Map; SDG 13 – Climate Action, Climate Mind ). The students then can be instructed to do their own research on SDGs. 

2. Apply design thinking to project ideation: In a lecture, students are introduced to design thinking and the double-diamond of design to use a diverge-converge strategy to first “design the right thing” and second “design things right.” In a practical session, with teaching team support, the students can meet their groups for a brainstorming activity. It is essential to inform students about setting ground rules for discussion, ensuring all voices are heard. Encourage students to apply design thinking to decide which SDG-based problem they would like to work on to develop a software solution. Here, giving students an example of this process based on a selected SDG will be useful. 

3. Formative assessment – project pitch deliverable: The next step is to channel students’ output of the design thinking practical to a formative assessment. Students can mould their discussion into a project pitch for their tutors. Their presentation should explain how their project works towards one or more of the 17 SDGs. 

4. Summative assessment – a dedicated section in project portfolio: Finally, dedicating a section in a project portfolio template on ideation ensures students reflect further on the SDGs. In the portfolio, students can be asked to reflect on how individual ideas were discussed and feedback from different group members was captured. They should also reflect on how they ensured the chosen problem fits one or more SDGs, describe the selection process of the final software solution, and what alternative solutions for the chosen SDG they have discussed, elaborating on the reasons for the final choice. 

 

Conclusion: 

Computing projects provide an excellent opportunity to align teaching, learning, and assessment activities to meet key Sustainable Development competencies and learning outcomes. The projects can provide transformational experiences for students to hear alternative viewpoints, reflect on experiences, and address real-world challenges. 

 

References: 

Advance HE. (2021) Education for sustainable development guidance. (Accessed: 02 January 2024). 

Lewrick, M., Link, P., Leifer, L.J. & Langensand, N. (2018). The design thinking playbook: mindful digital transformation of teams, products, services, businesses, and ecosystems. New Jersey: John Wiley & Sons, Inc, Hoboken. 

Mishra, D. and Mishra, A. (2020) ‘Sustainability Inclusion in Informatics Curriculum Development’, Sustainability, 12(14), p. 5769.  

 

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.  

Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters. 

 
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Authors: Cortney Holles (Colorado School of Mines); Ekaterina Rzyankina (University of Cape Town).

Topic: Critical digital literacy.

Engineering disciplines: Computer Science; Information Systems; Biomedical engineering.

Ethical issues: Cultural context; Social responsibility; Privacy.

Professional situations: Public health and safety; Working in area of competence; Informed consent.

Educational level: Intermediate.

Educational aim: Engaging in ethical judgement: reaching moral decisions and providing the rationale for those decisions.

 

Learning and teaching notes:

The case involves an engineering student whose personal choices may affect her future professional experience. It highlights both micro- and macro-ethical issues, dealing with the ways that individual actions and decisions can scale to create systemic challenges.

An ethical and responsible engineer should know how to work with and use digital information responsibly. Not all materials available online are free to use or disperse. To be digitally literate, a person must know how to access, evaluate, utilise, manage, analyse, create, and interact using digital resources (Martin, 2008). It is important to guide engineering students in understanding the media landscape and the influence of misleading information on our learning, our political choices, and our careers. A large part of critical digital literacy is evaluating information found on the web. For students working on a research project or an experiment, accessing accurate information is imperative. This case study offers several approaches to engaging students in the critique and improvement of their critical digital literacy skills. The foundations of this lesson can be applied in multiple settings and can be expanded to cover several class periods or simplified to be inserted into a single class.

This case study addresses two of AHEP 4’s themes: The Engineer and Society (acknowledging that engineering activity can have a significant societal impact) and Engineering Practice (the practical application of engineering concepts, tools and professional skills). To map this case study to AHEP outcomes specific to a programme under these themes, access AHEP 4 here and navigate to pages 30-31 and 35-37.

The dilemma in this case is presented in two parts. If desired, a teacher can use the Summary and Part one in isolation, but Part two develops and complicates the concepts presented in the Summary and Part one to provide for additional learning. The case allows teachers the option to stop at multiple points for questions and / or activities as desired.

Learners have the opportunity to:

Teachers have the opportunity to:

 

Learning and teaching resources:

News articles:

Educational institutions:

Legal regulations:

Non-profit organisations:

Business:

 

Summary:

Katherine is a biomedical engineering student in her 3rd year in 2022, and will have a placement in a community hospital during her last term at university. She plans to pursue a career in public health after seeing what her country went through during the Covid-19 pandemic. She wants to contribute to the systems that can prevent and track public health risks from growing too large to manage, as happened with Covid-19. She is motivated by improving systems of research and treatment for emerging diseases and knows that communication between a variety of stakeholders is of the utmost importance.

 

Optional STOP for questions and activities:

1. Discussion: What can you determine about Katherine’s values and motivation for her studies and her choice of career?

2. Discussion: How do you connect with her mission to improve diagnostic and treatment systems for public health threats?

3. Discussion: Who should be responsible for the messaging and processes for public health decisions? How are engineers connected to this system?

4. Activity: Research the Covid-19 vaccine rollout in the United Kingdom versus other countries – how did power, privilege, and politics influence the response?

5. Activity: Research current public health concerns and how they are being communicated to the public. In what ways might engineers affect how and what is communicated?

 

Dilemma – Part one:

As Katherine approaches the winter holiday season, she makes plans to visit her grandmother across the country. She hasn’t seen her since before the Covid-19 pandemic and is excited to be around her extended family for the holidays once again. However, she receives an email from her cousin informing everyone that he and his family are not vaccinated against Covid-19 because the whole vaccination operation was forced upon citizens and they refused to participate. Katherine is immediately worried for her grandmother – at 85 years old, she is at a higher risk than most – and for her brother, who suffers from Addison’s disease, an autoimmune disorder. Additionally, if Katherine comes into contact with Covid-19 while celebrating the holidays with her family, she could suffer repercussions at both her university and the hospital where she will work for her placement.

 

Optional STOP for questions and activities:

1. Discussion: How can Katherine communicate with her cousin about her concerns for her brother and grandmother? How might she use her expertise as a biomedical engineer in this conversation?

2. Discussion: What kind of information will be most convincing to support her decision? What sources would provide the evidence she is looking for, and which ones would provide counter arguments?

3. Discussion: What impacts might the decision have on Katherine’s position as a student or in the hospital?

4. Discussion: Do engineers, scientists, and medical professionals have more of an obligation to promote and adhere to public health guidance? Why or why not?

5. Activity: Talk to people in your life about their experience of navigating the Covid-19 vaccine. Did they choose to get it as soon as it was available? Did they avoid getting the vaccine for particular reasons? Were there impacts on their personal relationships or work because of their choices about the vaccine?

6. Activity: Research some of the impacts on individuals with health concerns and comorbidities in regard to Covid-19 and other viruses or public health concerns. How do these experiences match with or differ from your own?

7. Activity: Investigate the different ways that engineers were involved in vaccination development and response.    

 

Dilemma – Part two:

Katherine went back to university after a lengthy break for the holidays and immediately registered for an account on Facebook as a brand-new user. She was in such a hurry to have her profile up that she did not take the time to configure any privacy settings. She stayed up late reading an article about Covid-19  that had been posted on the website of one of the online newspapers. Before she posted this report on her own Facebook page, she did not verify the accuracy of the information or the source of the information.

 

Optional STOP for questions and activities:

1. Discussion: What kind of impact might this social media activity have on Katherine’s position as a student or in the company/organisation/hospital she is working for as an intern? What should Katherine be worried or concerned about after posting information?

2. Discussion: Do social media companies collect or ask for any other non-essential information from you? Why does the website claim that they are collecting or asking for your information? Does the website share/sell/trade the information that they collect from you? With whom does the website share your collected information? How long does the website keep your collected information? Does the website delete your information, or simply de-personalise it?

3. Discussion: Regarding question 2, how are engineers involved with products, processes, or services that enable those choices and actions?

4. Discussion: What is real and fake news? How do you know? What do you look for to know if it is real or fake news (share guidelines)? Do you expect it to be easy to spot fake news? Why should we care if people distribute and believe fake news?

Students are particularly susceptible to being duped by propaganda, misleading information, and fake news due to the significant role that information and communication technology which is problematic to verify plays in their everyday life. Students devote a significant portion of their time to participating in various forms of online activity, including watching television, playing online games, chatting, blogging, listening to music, posting photos of themselves on social networking sites, and searching for other individuals with whom they can engage in online conversation. Students owe a significant portion of what they know about the world and how they perceive reality to the content that they read online. While many people share reliable and positive information online, others may engage in negative impact information sharing:

5. Discussion: What are some other examples of how engineering might fall prey to negative impact information sharing?

6. Discussion: How might engineers help address the problem of fake news and negative impact information sharing?

 

References:

Martin, A. (2008). ‘Digital Literacy and the “Digital Society”’, in Lankshear C. and Knobel M. (eds.), Digital Literacies: Concepts, Policies, and Practices. New York: Peter Lang,  (pp. 151-176).

 

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.

Case enhancement: Facial recognition for access and monitoring

Activity: Prompts to facilitate discussion activities. 

Author: Sarah Jayne Hitt, Ph.D. SFHEA (NMITE, Edinburgh Napier University).

 

Overview:

There are several points in this case during which an educator can facilitate a class discussion about relevant issues. Below are prompts for discussion questions and activities that can be used. These correspond with the stopping points outlined in the case. Each prompt could take up as little or as much time as the educator wishes, depending on where they want the focus of the discussion to be. The discussion prompts for Dilemma Part three are already well developed in the case study, so this enhancement focuses on expanding the prompts in Parts one and two.

 

Dilemma Part one – Discussion prompts:

1. Legal Issues. Give students ten minutes to individually or in groups do some online research on GDPR and the Data Protection Act (2018). In either small groups or as a large class, discuss the following prompts. You can explain that even if a person is not an expert in the law, it is important to try to understand the legal context. Indeed, an engineer is likely to have to interpret law and policy in their work. These questions invite critical thinking and informed consideration, but they do not necessarily have “right” answers and are suggestions that can help get a conversation started.

a. Are legal policies clear about how images of living persons should be managed when they are collected by technology of this kind?

b. What aspects of these laws might an engineer designing or deploying this system need to be aware of?

c. Do you think these laws are relevant when almost everyone walking around has a digital camera connected to the internet?

d. How could engineers help address legal or policy gaps through design choices?

2. Sharing Data. Before entering into a verbal discussion, either pass out the suggested questions listed in the case study on a worksheet or project on a screen. Have students spend five or ten minutes jotting down their personal responses. To understand the complexity of the issue, students could even create a quick mind map to show how different entities (police, security company, university, research group, etc.) interact on this issue. After the students spend some time in this personal reflection, educators could ask them to pair/share—turn to the person next to them and share what they wrote down. After about five minutes of this, each pair could amalgamate with another pair, with the educator giving them the prompt to report back to the full class on where they agree or disagree about the issues and why.

3. GDPR Consent. Before discussing this case particularly, ask students to describe a situation in which they had to give GDPR consent. Did they understand what they were doing, what the implications of consent are, and why? How did they feel about the process? Do they think it’s an appropriate system? This could be done as a large group, small group, or through individual reflection. Then turn the attention to this case and describe the change of perspective required here. Now instead of being the person who is asked for consent, you are the person requiring consent. Engineers are not lawyers, but engineers often are responsible for delivering legally compliant systems. If you were the engineer in charge in this case, what steps might you take to ensure consent is handled appropriately? This question could be answered in small groups, and then each group could report back to the larger class and a discussion could follow the report-backs.

4. Institutional Complexity. The questions listed in the case study relate to the fact that the building in which the facial recognition system will be used accommodates many different stakeholders. To help students with these questions, educators could divide the class into small groups, with each group representing one of the institutions or stakeholder groups (college, hospital, MTU, students, patients, public, etc.). Have each group investigate whether regulations related to captured images are different for their stakeholders, and debate if they should be different. What considerations will the engineer in the case have to account for related to that group? The findings can then be discussed as a large class.

 

Dilemma Part two – Discussion prompts:

The following questions relate to macroethical concerns, which means that the focus is on wider ethical contexts such as fairness, equality, responsibility, and implications.

1. Benefits and Burdens. To prepare to discuss the questions listed in the case study, students could make a chart of potential harms and potential benefits of the facial recognition system. They could do this individually, in pairs or small groups, or as a large class. Educators should encourage them to think deeply and broadly on this topic, and not just focus on the immediate, short-term implications. Once this chart is made, the questions listed in the case study could be discussed as a group, and students asked to weigh up these burdens and benefits. How did they make the choices as to when a burden should outweigh a benefit or vice versa?

2. Equality and Utility. To address the questions listed in the case study, students could do some preliminary individual or small group research on the accuracy of facial recognition systems for various population groups. The questions could then be discussed in pairs, small groups, or as a large class.

3. Engineer Responsibility. Engineers are experts that have much more specific technical knowledge and understanding than the general public. Indeed, the vast majority of people have no idea how a facial recognition system works and what the legal requirements are related to it, even if they are asked to give their consent. Does an engineer therefore have more of a responsibility to make people aware and reassure them? Or is an engineer just fulfilling their duty by doing what their boss says and making the system work? What could be problematic about taking either of those approaches?

 

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.

Case enhancement: Developing a school chatbot for student support services

Activity: Stakeholder mapping to elicit value assumptions and motivations.

Author: Karin Rudolph (Collective Intelligence).

 

Overview:

This enhancement is for an activity found in point 5 of the Summary section of the case study.

What is stakeholder mapping?

What is a stakeholder?

Mapping out stakeholders will help you to:

  1. Identify the stakeholders you need to collaborate with to ensure the success of the project.
  2. Understand the different perspectives and points of view people have and how these experiences can have an impact on your project or product.
  3. Map out a wide range of people, groups or individuals that can affect and be affected by the project.

 

Stakeholder mapping:

The stakeholder mapping activity is a group exercise that provides students with the opportunity to discuss ethical and societal issues related to the School Chatbot case study. We recommend doing this activity in small groups of 6-8 students per table.

 

Resources:

 

Materials:

To carry out this activity, you will need the following resources:

1. Sticky notes (or digital notes if online).

2. A big piece of paper or digital board (Jamboard, Miro if online) divided into four categories:

3. Markers and pencils.

 

The activity:

 

Board One

List of stakeholders:

Below is a list of the stakeholders involved in the Chatbot project. Put each stakeholder on a sticky note and add them to the stakeholders map, according to their level of influence and interest in the projects.

Top tip: use a different colour for each set of stakeholders.

School Chatbot – List of Stakeholders:

 

Placement:

 

Guidance:

Each quadrant represents the following:

Board One

Motivations, assumptions, ethical and societal risks:

Materials:

1. A big piece of paper or digital board (Jamboard, Miro if online) divided into four categories:

2. Sticky notes (or digital notes if online).

3. Markers and pencils.

The activity:

 

Board Two

The Board Two activity can be done in two different ways:

Option 1:

You can use some guiding questions to direct the discussion. For example:

Option 2:

We have already written some assumptions, motivations and ethical/societal risks and you can add these as notes on a table and ask students to place according to each category: stakeholders, motivations, assumptions, and ethical and societal risks.

Motivations:

Assumptions:

Potential ethical and societal risks:

Move and match: 

 

 

 

Reflection:

Ask students to choose 2- 4 sticky notes and explain why they think these are important ethical/societal risks.

 

Potential future activity:

A more advanced activity could involve a group discussion where students are asked to think about some mitigation strategies to minimise these risks.

 

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.

Authors: Dr Nicola Whitehead (University of Wales Trinity Saint David); Professor Sarah Hitt (NMITE); Emma Crichton (Engineers Without Borders UK); Dr Sarah Junaid (Aston University); Professor Mike Sutcliffe (TEDI-London), Isobel Grimley (Engineering Professors’ Council).

Topic: Development and use of a facial recognition system. 

Engineering disciplines: Data, Electronics, Computer science, AI.

Ethical issues: Diversity, Bias, Privacy, Transparency.

Professional situations: Rigour, Informed consent, Misuse of data, Conflicts with leadership / management.

Educational level: Advanced. 

Educational aim: To encourage ethical motivation. Ethical motivation occurs when a person is moved by a moral judgement, or when a moral judgement is a spur to a course of action. 

 

Learning and teaching notes: 

This case involves an engineer hired to manage the development and installation of a facial recognition project at a building used by university students, businesses and the public. It incorporates a variety of components including law and policy, stakeholder and risk analysis, and both macro- and micro-ethical elements. This example is UK-based: however, the instructor can adapt the content to better fit the laws and regulations surrounding facial recognition technology in other countries, if this would be beneficial.

This case study addresses two of AHEP 4’s themes: The Engineer and Society (acknowledging that engineering activity can have a significant societal impact) and Engineering Practice (the practical application of engineering concepts, tools and professional skills). To map this study to AHEP outcomes specific to a programme under these themes, access AHEP4 here and navigate to pages 30-31 and 35-37.

This case is presented in three parts. If desired, a teacher can use Part one in isolation, but Part two (focusing on the wider ethical context of the case) and Part three (focusing on the potential actions the engineer could take)develop and complicate the concepts presented in Part one to provide for additional learning. The case study allows teachers the option to stop at multiple points for questions and / or activities as desired.

Learners have the opportunity to:

Teachers have the opportunity to: 

 

Learning and teaching resources:

 

Summary: 

Metropolitan Technical University (MTU), based in the UK, has an urban campus and many of its buildings are located in the city centre. A new student housing development in this area will be shared by MTU, a local college, and medical residents doing short rotations at the local hospital. The building has a public café on the ground floor and a couple of classrooms used by the university. 

The housing development sits alongside a common route for parades and protests. In the wake of demonstrations by Extinction Rebellion and Black Lives Matter, students have raised concerns to the property manager about safety. Despite an existing system of CCTV cameras and swipe cards, the university decides to install an enhanced security system, built around facial recognition technology that would enable access to the building and cross-reference with crime databases. To comply with GDPR, building residents will be required to give explicit consent before the system is implemented. Visitors without a student ID (such as café customers) will be buzzed in, but their image will be captured and cross-referenced before entry. A side benefit of the system is that MTU’s department of Artificial Intelligence Research will help with the installation and maintenance, as well as studying how it works, in order to make improvements. 

 

Dilemma – Part one:

You are an engineer who has been hired by MTU to take charge of the facial recognition system installation project, including setting policies and getting the system operational. With your background in AI engineering, you are expected to act as a technical advisor to MTU and liaise with the Facilities, Security and Computing departments to ensure a smooth deployment. This is the first time you have worked on a project that involves image capture. So as part of your preparation for the project, you need to do some preliminary research as to what best practices, guidance, and regulations apply.

 

Optional STOP for questions and activities: 

1. Discussion: What are the legal issues relating to image capture? Images allow for the identification of living persons and are therefore considered as personal data under GDPR and the Data Protection Act (2018).

2. Discussion: Sharing data is a legally and ethically complex field. Is it appropriate to share images captured with the police? If not the police, then whose crime database will you use? Is it acceptable to share the data with the Artificial Intelligence Research group? Why, or why not?

3. Discussion: Under GDPR, individuals must normally consent to their personal data being processed. How should consent be handled in this case?

4. Discussion: Does the fact that the building will accommodate students from three different institutions (MTU, the local college, and the hospital) complicate these issues? Are regulations related to students’ captured images different than those related to public image capture?

5. Activity: Undertake a technical activity that relates to how facial recognition systems are engineered.

 

Dilemma – Part two:

The project has kicked off, and one of its deliverables is to establish the policies and safeguards that will govern the system. You convened a meeting of project stakeholders to determine what rules need to be built into the system’s software and presented a list of questions to help you make technical decisions. The questions you asked were:

What you had thought would be a quick meeting to agree basic principles turned out to be very lengthy and complex. You were surprised at the variety of perspectives and how heated the discussions became. The discussions raised some questions in your own mind as to the risks of the facial recognition system.

 

Optional STOP for questions and activities:

The following activities focus on macro-ethics. This seeks to understand the wider ethical contexts of projects like the facial recognition system.

1. Activity: Stakeholder mapping – Who are all the stakeholders and what might their positions and perspectives be? Is there a difference between the priorities of the different stakeholders?

2. Activity: There are many different values competing for priority here. Identify these values, discuss and debate how they should be weighed in the context of the project.

3. Activity: Risks can be understood as objective and / or subjective. Research the difference between these two types of risk, and identify which type(s) of risks exist related to the project.

4. Discussion: Which groups or individuals are potentially harmed by the technology and which potentially benefit? How should we go about setting priorities when there are competing harms and benefits?

5. Discussion: Does the technology used treat everyone from your stakeholders’ list equally? Should the needs of society as a whole outweigh the needs of the individual?

6. Activity: Make and defend an argument as to the appropriateness of installing and using the system.

7. Discussion: What responsibilities do engineers have in developing these technologies?

 

Dilemma – Part three:

A few days later, you were forwarded a screenshot of a social media post that heavily criticised the proposed facial recognition system. It was unclear where the post had originated, but it had clearly been shared and promoted among both students and the public raising concerns about privacy and transparency. Your boss believes this outcry endangers the project and has requested that you make a public statement on behalf of MTU, reaffirming its commitment to installing the system.

You share the concerns, but have been employed to complete the project. You understand that suggesting it should be abandoned, would most likely risk your job. What will you tell your boss? How will you prepare your public statement?

 

Optional STOP for questions and activities:

Micro-ethics concerns individuals and their responses to specific situations. The following steps are intended to help students develop their ability to practise moral analysis by considering the problem in a structured way and work towards possible solutions that they can analyse critically.

 1. Discussion: What are the problems here? 

2. Discussion: What are the possible courses of action you can take as an employee?

 Students can be prompted to consider what different approaches they might adopt, such as the following, but can also develop their own possible responses. 

3. Discussion: Which is the best approach and why? – Interrogate the pros and cons of each possible course of action including the ethical, practical, cost, local relationship and the reputational damage implications. Students should decide on their own preferred course of action and explain why the balance of pros and cons is preferable to other options. The students may wish to consider this from other perspectives, such as: 

4. Activity: Public Communication – Students can practise writing a press release, giving an interview, or making a public statement about the case and the decision that they make.

5. Activity: Reflection – Students can reflect on how this case study has enabled them to see the situation from different angles. Has it motivated them to understand the ethical concerns and to come to an acceptable conclusion.

 

Enhancements:

An enhancement for this case study can be found here.

 

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.

Authors: Professor Sarah Hitt SFHEA (NMITE); Professor Raffaella Ocone OBE FREng FRSE (Heriot Watt University); Professor Thomas Lennerfors (Uppsala University); Claire Donovan (Royal Academy of Engineering); Isobel Grimley (Engineering Professors’ Council).

Topic:  Developing customised algorithms for student support.

Engineering disciplines: Computing, AI, Data.

Ethical issues: Bias, Social responsibility, Risk, Privacy.

Professional situations: Informed consent, Public health and safety, Conflicts with leadership / management, Legal implications.

Educational level: Beginner.

Educational aim: Develop ethical sensitivity. Ethical sensitivity is the broad cognisance of ethical issues and the ability to see how these might affect others.

 

Learning and teaching notes:

This case study involves the employees of a small software start-up that is creating a customised student support chatbot for a Sixth Form college. The employees come from different backgrounds and have different perspectives on the motivations behind their work, which leads to some interpersonal conflict. The team must also identify the ethical issues and competing values that arise in the course of developing their algorithm.

This case study addresses two of AHEP 4’s themes: The Engineer and Society (acknowledging that engineering activity can have a significant societal impact) and Engineering Practice (the practical application of engineering concepts, tools and professional skills). To map this case study to AHEP outcomes specific to a programme under these themes, access AHEP 4 here and navigate to pages 30-31 and 35-37.

The dilemma in this case is presented in two parts which build in complexity and navigate between personal, professional, and societal contexts. If desired, a teacher can use Part one in isolation, but Part two develops and complicates the concepts presented in Part one to provide for additional learning. Pre-reading ‘Ethics of Care and Justice’ is recommended, though not required, for engaging with Part two. The case allows teachers the option to stop at multiple points for questions and / or activities as desired.

Learners have the opportunity to:

Teachers have the opportunity to:

 

Learning and teaching resources:

 

Summary:

Exaba is a small, three-person software startup. Like all small businesses, it has been struggling with finances during the pandemic. The company began selling its services across a variety of industry sectors but is now trying to expand by developing software solutions for the growing education technology sector.

Ivan, Exaba’s founder and CEO, was thrilled to be contracted by a growing local Sixth Form College in North West England, NorthStar Academy, to create a chatbot that will optimise student support services. These services include ensuring student safety and wellbeing, study skills advice, careers guidance, counselling, and the identification for the need and implementation of extra learning support. It is such a large project that Ivan has been able to bring in Yusuf, a university student on placement from a computer systems programme, to help Nadja, Exaba’s only full-time software engineer. Ivan views the chatbot contract as not only a financial windfall that can help get the company back on track, but as the first project in a new product-development revenue stream.

Nadja and Yusuf have been working closely with the NorthStar Academy’s Principal, Nicola, to create ‘Alice’: the custom student-support chatbot to ensure that she is designed appropriately and is fit for purpose. Nicola has seen growing evidence that chatbots can identify when students are struggling with a range of issues from attendance to anxiety. She has also seen that they can be useful in helping administrators understand what students need, how to help them more quickly, and where to invest more resources to make support most effective.

 

Optional STOP for questions and activities:

1. Discussion: What moral or ethical issues might be at stake or arise in the course of this project?

2. Discussion: What professional or legal standards might apply to the development of Alice?

3. Discussion: What design choices might Nadja and Yusuf have to consider as they build the chatbot software in order for it to conform to those standards?

4. Discussion: is there anything risky about giving cognitive chatbots human names in general, or a female name specifically?

5. Activity: Undertake stakeholder mapping to elicit value assumptions and motivations.

6. Activity: Research any codes of ethics that might apply to AI in education, or policies / laws that apply to controlling and processing student data.

7. Activity: View the following TED talk and have a discussion on gender in digital assistants: Siri and Alexa are AI Built for the Past by Emily Liu.

 

Dilemma – Part one:

After undertaking work to ensure GDPR compliance through transparency, consent, and anonymisation of the data harvested by interactions with Alice, Nadja and Yusuf are now working on building the initial data set that the chatbot will call upon to provide student support. The chatbot’s information to students can only be as good as the existing data it has available to draw from. To enable this, Nicola has agreed to provide Exaba with NorthStar Academy’s existing student databases that span many years and cover both past and present students. While this data – including demographics, academic performances, and interactions with support services – is anonymised, Yusuf has begun to feel uncomfortable. One day, when the entire team was together discussing technical challenges, Yusuf said “I wonder what previous students would think if they found out that we were using all this information about them, without their permission?”

Ivan pointed out, “Nicola told us it was okay to use. They’re the data controllers, so it’s their responsibility to resolve that concern, not ours. We can’t tell them what to do with their own data. All we need to be worried about is making sure the data processing is done appropriately.”

Nadja added, “Plus, if we don’t use an existing data set, Alice will have to learn from scratch, meaning she won’t be as effective at the start. Wouldn’t it be better for our chatbot to be as intelligent and helpful as possible right away? Otherwise, she could put existing students at a disadvantage.”

Yusuf fell silent, figuring that he didn’t know as much as Ivan and Nadja. Since he was just on a placement, he felt that it wasn’t his place to push the issue any further with full-time staff.

 

Optional STOP for questions and activities:

1. Discussion: Expand upon Yusuf’s feelings of discomfort. What values or principles is this emotion drawing on?

2. Discussion: Do you agree with Yusuf’s perspective, or with Ivan’s and Nadja’s? Why?

3. Discussion: Does / should Yusuf have the right to voice any concerns or objections to his employer?

4. Discussion: Do / should previous NorthStar students have the right to control what the academy does with their data? To what extent, and for how long?

5. Discussion: Is there / should there be a difference between how data about children is used and that of adults? Why?

6. Discussion: Should a business, like Exaba, ever challenge its client, like NorthStar Academy, about taking potentially unethical actions?

7. Technical activity: Undertake a technical activity such as creating a process flow diagram, pieces of code and UI / UX design that either obscure or reinforce consent.

8. Activity: Undertake argument mapping to diagram and expand on the reasoning and evidence used by Yusuf, Nadja, and Ivan in their arguments.

9. Activity: Apply ethical theories to those arguments.  

10. Discussion: What ethical principles are at stake? Are there potentially any conflicts or contradictions arising from those principles?

 

Dilemma – Part two:

Nicola, too, was under pressure. The academy’s Board had hired her as Principal to improve NorthStar’s rankings in the school performance table, to get the college’s finances back on track, and support the government efforts at ‘levelling up’ This is why one of Nicola’s main specifications for Alice is that she be able to flag students at risk of not completing their qualifications. Exaba will have to develop an algorithm that can determine what those risk factors are.

In a brainstorming session Nadja began listing some ideas on the whiteboard. “Ethnic background, family income, low marks, students who fit that profile from the past and ultimately dropped out, students who engaged with support services a lot, students with health conditions . . .”

“Wait, wait, wait,” Yusuf said. “This feels a little bit like profiling to me. You know, like we think kids from certain neighbourhoods are unlikely to succeed so we’re building this thing to almost reinforce that they don’t.”

“The opposite is true!” Ivan exclaimed. “This algorithm will HELP exactly those students.”

“I can see how that’s the intention,” Yusuf acknowledged. “But I’ve had so many friends and neighbours experience well-intentioned but not appropriate advice from mentors and counsellors who think the only solution is for everyone to complete qualifications and go to university. This is not the best path for everybody!”

Nadja had been listening carefully. “There is something to what Yusuf is saying: Is it right to nudge students to stay in a programme that’s actually not a best fit for them? Could Alice potentially give guidance that is contrary to what a personal tutor, who knows the student personally, might advise? I don’t know if that’s the sort of algorithm we should develop.”

At this point Ivan got really frustrated with his employees: “This is the proprietary algorithm that’s going to save this company!” he shouted. “Never mind the rights and wrongs of it. Think of the business potential, not to mention all the schools and students this is going to help. The last thing I need is a mutiny from my team. We have the client’s needs to think about, and that’s it.”

 

Optional STOP for questions and activities:

1. Activity: compare an approach to this case through the ethics of care versus the ethics of justice. What different factors come into play? How should these be weighed? Might one approach lead to a better course of action than another? Why?

2. Discussion: what technical solutions, if any, could help mitigate Yusuf and Nadja’s concerns?

3. Activity: imagine that Ivan agrees that this is a serious enough concern that they need to address it with Nicola. Role play a conversation between Ivan and Nicola.

4. Activity: undertake a classroom debate on whether or not Alice has the potential to reinforce negative stereotypes. Variations include alley debate, stand where you stand, adopt and support opposite instinct.

 

Enhancements:

An enhancement for this case study can be found here.

 

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