In November 2025 the EPC, with support from Quanser, launched a new Complex Systems Toolkit, aimed at providing accessible, practical resources for embedding complex systems concepts into engineering education.
The Toolkit launched with an abundance of resources, allowing educators and industry professionals to dive into the ‘what’ and ‘how’ of complex systems with knowledge and guidance articles, discover ready-to-use teaching resources including case studies and other classroom activities, and hear directly from the creators and partners who helped shape the Toolkit with a well-attended launch webinar (now available to watch on demand).
These resources have been well used in their first six months, but we’re not stopping there. We want to add further resources, on topics that are emerging as being of vital importance to students as they graduate and seek work. The first of the topics that we want to cover is intelligent robotics.
What and why?
Intelligent robotics, and the more recent applications to physical AI, generally refers to artificial intelligence systems that are embedded in and interact directly with the physical world, rather than operating purely in digital environments. This includes technologies like robots, autonomous vehicles, and drones that can perceive their surroundings through sensors, process that information using AI models, and take real-world actions. Unlike traditional software-based AI, intelligent robotics applications deal with real-time constraints, uncertainty, and complex environments, requiring tight integration between hardware (like sensors and actuators) and decision-making algorithms.
For engineering students, learning about intelligent robotics and physical AI workflows matters because it sits at the intersection of software, hardware, and real-world problem solving. It forces students to grapple with uncertainty, noisy sensor data, timing constraints, and safety considerations, which are unavoidable in real systems like robots or autonomous vehicles. That experience builds practical intuition about how algorithms behave outside ideal conditions. Engineers who understand this are better equipped to design systems that are robust, adaptive, and resilient. Industries are moving rapidly toward automation, robotics, and intelligent infrastructure, so familiarity with intelligent robotics and physical AI workflows opens doors in fields like manufacturing, healthcare technology, and transportation. It helps engineers think holistically: not just “does the code work?” but “does the system behave safely and effectively in the real world?”.
Contributors sought to develop resources on Intelligent Robotics for inclusion in the toolkit
We are seeking experts in intelligent robotics, from academia, industry, and engineering organisations, to develop resources on this topic for publication in the Complex Systems Toolkit. These resources will inform, guide and aid educators to embed teaching on intelligent robotics into their engineering lessons, modules or courses.
We invite contributors to develop resources in three areas:
Knowledge articles: These are resources that users can access to improve their knowledge or find more information. These are intended to provide theoretical and practical background on intelligent robotics concepts and tools such as modelling or decision-making approaches. While guidance articles focus on “how”, knowledge articles focus on “what”.
Guidance articles: These are resources that users can access to learn how to do something. These are intended to provide practical advice on subjects such as how to explain intelligent robotics to students, or how to assess for skills and competencies in this area. While knowledge articles focus on “what”, guidance articles should focus on “how”.
Teaching activities: These are resources that users can access to help them know what to integrate and implement. These include use cases/case studies which provide examples of intelligent robotics which can be directly utilised in teaching with the suggested tools, as well as other classroom activities such as coursework, project briefs, lesson plans, demonstration simulations, or other exercises.
We’re also looking for experts in intelligent robotics and physical AI to join us as reviewers and working group members.
We are seeking content on the following topics
Resources should reference the topic’s relationship to complex systems and engineering education/graduate skills. We are particularly interested in resources that help engineering educators teach these topics effectively.
Robotics and autonomous systems
Human-robot interaction
Swarm systems and distributed intelligence
Edge AI and embedded intelligence
Cyber-physical systems
Simulation and digital twins
Safety, resilience, and uncertainty
Systems thinking for Intelligent Robotics or Physical AI
Teaching approaches and assessment methods
Read more about the specific content we are looking for (click on the arrows to expand the sections)
Submit a knowledge article
Submit a knowledge article
As well as choosing a topic, you will need to choose an angle for your resource.
For knowledge articles. contributors might consider one of the following:
What it is: explaining the topic and its relation to complex systems.
Why educators should teach it / students should learn it.
Why it should be integrated into engineering education.
An angle of your own choosing.
These articles should connect the why (why must teaching about the topic be present in engineering education?) to the how (how can this be done efficiently and effectively?). Through these tools, we aim to help upskill UK engineering educators so that they feel capable of and confident in integrating complex systems concepts and intelligent robotics topics into their engineering teaching.
Step 1: Read the guidance for submitting a knowledge article
Research:
Knowledge articles are resources that users can access to improve their knowledge or find more information. These are intended to provide theoretical and practical background on complex systems concepts and tools such as modelling or decision-making approaches. While guidance articles focus on “how”, knowledge articles focus on “what”.
Knowledge articles are meant to be overviews that a reader with no prior knowledge of the topic could refer to in order to develop a baseline understanding and learn where to look for additional information (they can reference other sources). They should be understandable to students as well: imagine that an educator might excerpt content from the article to provide their students context on a project or learning activity.
They should be approximately 500-1000 words (although they can be more in depth if necessary) and reference relevant online open-source resources.
Overview:
The articles are meant to be able to stand on their own as a piece of knowledge on a topic; they are also meant to work alongside other articles so that taken together they form a sort of complex systems in engineering handbook.
Purpose:
Each article should inform, explain, and provide knowledge on the topic. Put yourself in the perspective of an engineering educator who is new to the topic.
Content:
The content of the article should be organised and well developed. That is, it should be presented in a logical way and thoroughly explained.
References and resources:
Where additional explanation could be given, it might point to other resources, and where information is presented from another source, it needs to be properly referenced using Harvard referencing.
Format:
Knowledge articles should follow this format:
Premise;
Body of article, divided up into headed sections as necessary;
Knowledge articles should be submitted in Word file format (.doc or .docx).
Also submit any additional resources such as spreadsheets, handouts etc., and ensure that they are in an editable format. Please clarify where in the resource these should be embedded or linked.
Any corresponding images should be submitted in either .jpeg, .jpg or .png format. We need these to be uploaded separately from the Word file, as we will be embedding them in a web page. Please ensure that they are of high resolution and adequate size (we suggest a minimum of 800 pixels wide); that you have the right or permission to use them (bearing in mind they will be published under a Creative Commons license); and that you have added any permissions, sources, credits or other details for them in the body of the document that you are submitting.
To ensure that everyone can use and adapt the Toolkit resources in a way that best fits their teaching or purpose, this work will be licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Under this licence users are free to share and adapt this material, under terms that they must give appropriate credit and attribution to the original material and indicate if any changes are made.
These articles should also connect the why (why must teaching about this topic be present in engineering education?) to the how (how can this be done efficiently and effectively?). Through these tools, we aim to help upskill UK engineering educators so that they feel capable of and confident in integrating complex systems concepts and intelligent robotics topics into their engineering teaching.
Step 1: Read the guidance for submitting a guidance article
Research:
Guidance articles are resources that users can access to learn how to do something. These are intended to provide practical advice on subjects such as how to explain complex systems to students, or how to assess for skills and competencies in complex systems. While knowledge articles focus on “what”, guidance articles should focus on “how.”
Guidance articles aim to help situate our teaching resources in an educational context and to signpost to additional research and resources on complex systems theory and tools.
They should be approximately 500-1000 words (although they can be more in depth if necessary) and reference relevant online open-source resources.
Overview:
Guidance articles are meant to be able to stand on their own as a piece of guidance on a topic; they are also meant to work alongside other articles so that taken together they form a sort of complex systems in engineering handbook.
Purpose:
Each article should inform, explain, and provide guidance on the topic. Put yourself in the perspective of an engineering educator who is new to the topic.
Content:
The content of the article should be organised and well developed. That is, it should be presented in a logical way and thoroughly explained.
References and resources:
Where additional explanation could be given, it might point to other resources, and where information is presented from another source, it needs to be properly referenced using Harvard referencing.
Format:
Guidance articles should follow this format:
Premise;
Body of article, divided up into headed sections as necessary;
Guidance articles should be submitted in Word file format (.doc or .docx).
Also submit any additional resources such as spreadsheets, handouts etc., and ensure that they are in an editable format. Please clarify where in the resource these should be embedded or linked.
Any corresponding images should be submitted in either .jpeg, .jpg or .png format. We need these to be uploaded separately from the Word file, as we will be embedding them in a web page. Please ensure that they are of high resolution and adequate size (we suggest a minimum of 800 pixels wide); that you have the right or permission to use them (bearing in mind they will be published under a Creative Commons license); and that you have added any permissions, sources, credits or other details for them in the body of the document that you are submitting.
To ensure that everyone can use and adapt the Toolkit resources in a way that best fits their teaching or purpose, this work will be licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Under this licence users are free to share and adapt this material, under terms that they must give appropriate credit and attribution to the original material and indicate if any changes are made.
As well as choosing a topic, you will need to choose an angle for your resource.
For activities, contributors might consider one of the following:
Case studies that, through a real-world situation, illustrate the topic and its relation to complex systems, use cases for the tools that can be used to model / simulate this, techniques that promote development and use of systems architecture, and effects such as trade-offs, emergent properties, impacts, or unintended consequences. Case studies could also reference the implications for risk, security, ethics, sustainability, teamwork, and communication.
Demonstrator simulations that provide examples of how systems can be modelled.
This could include:
Examples of how the topic relates complex systems
Interactive examples showing how well-intentioned action can lead to failure
Interactive examples showing the best approaches to handling complexity
Teaching/learning activities, coursework, project briefs, lesson plans, modelling or simulation exercise/activities, technical content related to complex systems, worksheets, slides, robotics labs, swarm behaviour activities, system mapping exercises, hardware-in-the-loop demonstrations, digital twin exercises, or other teaching materials.
An angle of your own choosing.
These resources should promote active learning pedagogies and real-world teaching methods by showing how complex systems teaching can be embedded within technical problems and engineering practice. Through these resources, we aim to help upskill UK engineering educators so that they feel capable of and confident in integrating complex systems into their engineering teaching.
Step 1: Read the guidance for submitting a teaching activity/resource
Research:
Teaching activities are resources that users can access to help them know what to integrate and implement. These include use cases/case studies which provide examples of complex systems topics which can be directly utilised in teaching with the suggested tools, as well as other classroom activities such as coursework, project briefs, lesson plans, simulation exercises, robotics labs, swarm behaviour activities, system mapping exercises, hardware-in-the-loop demonstrations, digital twin exercises, or other exercises.
Before you begin, you should review existing Complex Systems Toolkit teaching resources, since we hope that contributions will be fairly consistent in length, style, tone, format and approach. Remember that the audience for these resources is educators seeking to embed complex systems topics within their engineering teaching.
Step 1a: Guidance for submitting a case study
Case studies present real-world scenarios that can be used in teaching about complex systems topics in engineering. They provide students with opportunities to explore complex systems tools, and trade-offs, in authentic contexts, and reflect on decisions made about them.
They are usually based on a real example, although fictionalised cases are acceptable when they are grounded in realistic detail. Case studies should enable students to identify or interpret key features of complex systems topics (feedback loops, interdependence or emergent behaviour) and apply relevant tools or frameworks to make sense of the situation.
Case studies will vary in length depending on scope and resource, but many are around 1500-2000 words. They should reference relevant online open-source resources.
The case study should be presented as a narrative about a complex systems issue in engineering.
Narrative strength: the case should be clearly structured with a compelling and coherent story.
System complexity: it should explore interdependencies, multiple stakeholders and/or competing goals.
Tool integration: systems tools should be mentioned or incorporated (e.g. soft systems methodology, SysML, Agent-based modelling etc).
Activities and Resources: there should be questions, prompts or teaching activities to guide discussion or classroom use.
Authenticity:
Case studies are most effective when they feel like they are realistic, with characters that you can identify or empathise with, and with situations that do not feel fake or staged. Giving characters names and backgrounds, including emotional responses, and referencing real-life experiences help to increase authenticity.
Complexity of issue:
Many cases are either overly complicated so that they become overwhelming, or so straightforward that they can be “solved” quickly. A good strategy is to try to develop multiple dimensions of a case, but not too many that it becomes unwieldy. Additionally, complexity can be added through different parts of the case so that instructors can choose a simpler or more complicated version depending on what they need in their educational context.
Activities and resources:
You should provide a variety of suggestions for discussion points and activities to engage learners, as well as a list of reliable, authoritative open-source online resources, to both help educators prepare and to enhance students’ learning. Where information is presented from another source, it needs to be properly referenced using Harvard referencing.
Educational level and assessment:
Educational level: When writing your case study, you should consider which level it is aimed at. A Beginner level case is aimed at learners who have not had much experience in engaging with this complex systems topic or problem, and usually focuses on only one or two dimensions of a challenge. An Advanced-level case is aimed at learners who have had previous practice in engaging with this complex systems topic or problem, and often addresses multiple challenges. An Intermediate case is somewhere in between.
Assessment: If possible, suggest assessment opportunities for activities within the case, such as marking rubrics or example answers.
Format:
The case study should follow the following format:
Teaching notes (with learning objectives, time needed, materials): This is an overview of the case and its dilemma, and how it relates to AHEP4 and INCOSE competencies.
Learning and teaching resources: A list of reliable, authoritative, open-source online resources that relate to the case and its dilemma. These can be from a variety of sources, such as academic institutions, journals, news websites, business, and so on. We suggest a minimum of five sources that help to provide context to the case and its dilemmas.
Summary of system or context.
Narrative of the case (presenting the complexity).
Questions and activities. This is where you provide suggestions for discussions and activities related to the case and the dilemma.
Further discussion or challenge (optional). Some case studies are sufficiently complex at one dilemma, but if the case requires it you can provide further parts (up to a maximum of three).
Step 1b: Read the guidance for submitting a different teaching activity
Purpose & outcomes:
Teaching activities/tools are intended to support educators’ ability to apply and embed complex systems concepts and topics within their engineering teaching.
Educators need to quickly and easily find help with:
Adapting and integrating existing complex systems resources to their disciplinary context.
Implementing new and different pedagogies that support complex systems learning.
Structuring lessons, modules, and programmes so that complex systems skills and outcomes are central themes.
Thus, these teaching activities/tools will provide crucial guidance for those who may be teaching complex systems related material for the first time, or who are looking for new and different ways to integrate complex systems concepts or topics into their teaching.
Teaching activities/tools may take the form of learning activities, coursework, project briefs, lesson plans, modelling or simulation exercise/activities, technical content related to complex systems, worksheets, slides, robotics labs, swarm behaviour activities, system mapping exercises, hardware-in-the-loop demonstrations, digital twin exercises, or other similar teaching materials.
Imagine that you are an engineering educator who is new to teaching complex systems concepts or topics. You turn to this teaching tool to help you apply and embed these in your module.
Does this resource help introduce or develop concepts related to complex systems or systems thinking so that learners can engage with these topics in the context of engineering?
If not, what is needed to make this possible?
Presentation and clarity:
Depending on the resource, you may choose to provide worksheets, slides, problem sets, narrative prompts, etc.
Is the resource explained in such a way that someone new to teaching complex systems could understand how to use it?
Is the material clearly introduced and described?
Resources and guidance:
Depending on the topic, educators may need additional resources or guidance to support their use of the material. For instance, background information may be required or a technical topic explained.
Have you provided sufficient material so that educators can easily employ the resource?
The teaching activity/tool should follow this format:
Overview:
Short description of what the resource is and what it aims to do.
States how it is related to complex systems or systems thinking topic(s), referring to external content such as INCOSE Competencies and AHEP 4.
Provides an overview of the activity, suggesting how it might be implemented and in what contexts, how long it might take, and any other relevant delivery information.
Details any specific materials or software required for the activity, as well as any modelling or simulation tools to be used.
Lists any learning and teaching resources recommended in order to undertake the activity, including suggested pre-reading or other references.
Explains the activity in as much detail as is required (this will vary depending on the type of material the resource addresses.)
If relevant, provides assessment guidance–marking rubrics, sample answers, etc.
Step 2b: Before you submit, review this checklist:
Does this resource help introduce or develop concepts/topics related to complex systems or systems thinking so that learners can engage with these topics in the context of engineering?
Is the resource explained in such a way that someone new to teaching complex systems could understand how to use it?
Is the material clearly introduced and described?
Have you provided sufficient material so that educators can easily employ the resource?
Step 3: Submitting your teaching activity/resource
Teaching resources should be submitted in Word file format (.doc or .docx).
Also submit any additional resources such as spreadsheets, handouts etc., and ensure that they are in an editable format. Please clarify where in the resource these should be embedded or linked.
Any corresponding images should be submitted in either .jpeg, .jpg or .png format. We need these to be uploaded separately from the Word file, as we will be embedding them in a web page. Please ensure that they are of high resolution and adequate size (we suggest a minimum of 800 pixels wide); that you have the right or permission to use them (bearing in mind they will be published under a Creative Commons license); and that you have added any permissions, sources, credits or other details for them in the body of the document that you are submitting.
To ensure that everyone can use and adapt the Toolkit resources in a way that best fits their teaching or purpose, this work will be licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Under this licence users are free to share and adapt this material, under terms that they must give appropriate credit and attribution to the original material and indicate if any changes are made.
We are also seeking experts on intelligent robotics/physical AIto join the Complex Systems Toolkit Working Group. Please apply here.
We are also seeking experts on intelligent robotics/physical AI to review resources for the toolkit. Please apply here.
If you would like to suggest links to pages or online resources that we can add to our database of engineering education resources for complex systems teaching, please email Wendy Attwell.
Additional information
In undertaking this work, contributors will become part of the growing community of educators who are helping to ensure that tomorrow’s engineering professionals have the complex systems skills, knowledge, and attributes that they need to provide a better future for us all. Contributors will be fully credited for their work on any relevant Toolkit materials and will be acknowledged as authors should the resources be published in any form. Developing these resources will provide the chance to work with a dynamic, diverse and passionate group of people leading the way in expanding engineering teaching resources, and may help in professional development, such as preparing for promotion or fellowship.
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.
Peter Martin, Director of Research & Development at Quanser, and co-chair of the Complex Systems Toolkit Working Group, reflects on the importance of engineers understanding complex systems when working in the field of intelligent robotics.
“In late 2024 I had the opportunity to join the EPC Complex Systems Toolkit team as co-chair of the working group. At the time I felt a little fraudulent, as the intricacies of complex systems thinking was new to me. I had brushed up against complex systems numerous times over the years as I had studied and worked in the world of robotics for over 20 years. However, I had never discovered the world of formal complex systems analysis. Looking back, this is a perfect validation for the need to create a toolkit to better prepare students for careers like mine. As I have learned more over the last 18 months about the tools and techniques that systems engineers employ to model and manage complexity, the critical value that these techniques offer engineers in the world of intelligent robotics has become obvious. As we hear often in the field of engineering lab equipment for the academic space, “I wish I’d had this when I was at university”.
The other reassuring aspect of my experience, for me, is that I’m not alone. A growing need for better approaches to managing complexity has emerged in industry over the last couple of decades as robotics and their governing systems have become increasingly integrated into society. This transition of robotics out of the structured environment of the factory floor and into direct contact with both the dynamic and unstructured world and the public, has introduced a high degree of non-linear predictability, complex interactions with multiple robotic agents, and emergent behaviours as the decision-making algorithms that dictate robotic behaviour adapt. All of these elements are central to the world of complex systems analysis.
At a high level, modern robotics systems no longer represent technical engineering challenges in the narrow, discipline-specific sense that engineers would traditionally have seen in higher education. They are complex adaptive systems that routinely demonstrate behaviours that emerge from interactions with their environment rather than being fully specified in advance. A robot navigating a hospital corridor, a swarm coordinating warehouse logistics, or a surgical assistant adjusting in real time to tissue variability represent challenges in undefined, non-linear, and largely unpredictable spaces. Students, and later robotics engineers who lack a complex systems vocabulary are essentially tasked with trying to understand emergence without the tools to describe it.
An example that I like to use is one that we encountered a couple of years ago: a team of mobile robots transporting parts around a manufacturing space. In many cases, the agents (ground robots, arms, etc.) in this scenario are programmed with independent control and decision-making code to govern their behaviour, with some overarching supervisory code to manage tasks and assignments. The ground robots would have algorithms to localise, path plan, navigate, and avoid obstacles while communicating with other complementary agents and central task management. However, as I have learned, complexity lies in the emergence of unexpected interactions between the agents and their environment. How they avoid each other and the environment while achieving their tasks is largely a complex non-linear system where conflicts can routinely delay or disrupt their operation. Introducing more sources of disruption such as humans, unstructured environments, weather conditions etc. only makes dealing with unpredictable scenarios more and more complicated using traditional techniques.
Luckily, many of the tools and techniques that are highlighted in the toolkit have direct applications to the challenges faced by engineers in the world of robotics. Causal Loop Diagrams (CLDs) are an excellent way to model the feedback dynamics that are at play in adaptive control systems. When a robot’s perception system updates its world model based on changes in what the sensors can perceive, that leads to changes in its action policy that when executed create a feedback loop. These diagrams are a great way to visualise and analyse these loops. Agent-Based Modelling (ABM) is directly relevant to the scenario I described above where swarms of robot must be coordinated or manage human-robot interaction scenarios. Using these simulation tools, engineers can test and manage emergent fleet behaviour without hardware. If things do go sideways, Fault Tree Analysis is a common approach to mapping causes and evaluating data to help develop robots that work in safety-critical applications. Finally, for long-term operations such as field robotics missions, Systems Dynamics Modelling can be a useful tool for predicting and managing a robot’s resource consumption (battery, compute, bandwidth) depending on the required task performance over time.
In addition to these considerations, there is a whole world of network modelling and the management of behaviour stemming from machine learning and applied AI algorithms that also overlaps quite closely with complex systems. Engineers that understand emergence, feedback loops, and attractors are far better equipped to reason about why a robot does something unexpected, than students who only have a component-driven technical understanding of the behaviour of an intelligent robot. Beyond the decisions, at an actual component level there are critical decisions that need to be made for efficient deployment of physical and edge AI algorithms. What data is processed locally and what goes to the cloud, when models are updated and how decision making is distributed across a robot swarm are exactly the kind of questions that systems thinking trains engineers to answer. Systems tools are ready to help, including influence diagrams to manage information exchange and action planning.
Overall, the field of complex systems introduces a set of tools, techniques, and mental models that are increasingly essential to robotics engineers that seek to prepare their agents to be effective in performing complicated tasks in increasingly complex systems.”
Intelligent robotics, and the more recent applications to physical AI, generally refers to artificial intelligence systems that are embedded in and interact directly with the physical world, rather than operating purely in digital environments. For engineering students, learning about intelligent robotics and physical AI workflows matters because it sits at the intersection of software, hardware, and real-world problem solving. It helps engineers think holistically: not just “does the code work?” but “does the system behave safely and effectively in the real world?”.
We are seeking experts in intelligent robotics, from academia, industry, and engineering organisations, to develop resources on this topic for publication in the Toolkit. These resources will inform, guide and aid educators to embed teaching on intelligent robotics into their engineering lessons, modules or courses.
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.
Author: Aditya Johri (George Mason University).
Topic: Sustainability implications in mobility and technology development.
Sustainability competency: Normative; Self-awareness; Strategic; Critical thinking.UNESCO has developed eight key competencies for sustainability that are aimed at learners of all ages worldwide. Many versions of these exist, as are linked here*. In the UK, these have been adapted within higher education by AdvanceHE and the QAA with appropriate learning outcomes. The full list of competencies and learning outcome alignment can be found in the Education for Sustainable Development Guidance*. *Click the pink ''Sustainability competency'' text to learn more.
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: SDG 4 (Quality education); SDG 9 (Industry, innovation, and infrastructure), SDG 12 (Responsible consumption and production); SDG 13 (Climate action).
Reimagined Degree Map Intervention: Active pedagogies and mindset development. The Reimagined Degree Map is a guide to help engineering departments navigate the decisions that are urgently required to ensure degrees prepare students for 21st century challenges. Click the pink ''Reimagined Degree Map Intervention'' text to learn more.
Educational aim: The objective of this activity is to provide students with an understanding of the complexity of technology development and different considerations that need to be made by stakeholders in the design and implementation of a technology. The activity is set up as a role-play where students are assigned different roles as members of an expert panel providing feedback on the use of E-Scooters on a college campus.
Educational level: Beginner.
Learning and teaching notes:
Learners have the opportunity to:
Consider sustainability issues related to the design and use of devices and technology.
Discuss concerns related to safety and accessibility, that can be overlooked or not attended to when technology is developed under time pressure and when developers lack resources – human and material.
Practice a variety of communication modes.
Engage in research and reflection.
Teachers have the opportunity to:
Highlight issues revealing the intricate links between digital technology and the environment.
Demonstrate the value of perspective-taking and stakeholder engagement in technology development.
Reveal the ethical and accessibility aspects of technology development.
Informally evaluate critical thinking and communication skills.
Supporting resources:
Several different ethical frameworks, codes, or guidelines can be provided to students to prepare for the discussion or to reflect upon during their discussion depending on the students’ disciplinary composition. Here are a few examples:
One of the goals of this exercise is to motivate students to undertake their own research on the topic to prepare for the activity. But it is important to provide them with preliminary material to start their own research. Here are a few useful resources for this case:
Each student is assigned a role a week before the discussion.
Students assigned to the role of Eva Walker serve as the moderator and lead the conversation based on the script below.
The script provided below is there to guide the discussion, but you should leave room for the conversation to flow naturally and allow everyone to contribute.
One way to ensure students are prepared for the discussion is to assign a few questions from the script as a pre-discussion assignment (short answers). Similarly, to ensure students reflect on the discussion, they can be assigned the last question from the script as a post-discussion exercise. They can also be asked specifically about frameworks and concepts related to sustainability.
Role-play scenario narrative and description of roles:
Eva Walker recently started reporting about on-campus traffic issues for the student newspaper. She would have preferred to do more human-interest stories, but as a new member of the staff who had just moved from intern to full-time, she was happy to get whatever opportunity she could. Eva was studying both journalism and creative writing, and this was her dream on-campus job. She also realised that, even though many stories at first didn’t appear to her as though she would be interested in them, as she dug deeper she eventually found an angle with which she could strongly relate.
One weekday morning, Eva was working on yet another story on parking woes when Amina Ali, one of the editorial staff members, texted her to say that there had been an accident on campus; she just passed it at the intersection of the library and the recreation building, and it might be worth covering. Eva was at the library, and within no time, reached the spot of the accident.
When Eva arrived, a police vehicle, an ambulance, and a fire engine were all present at the scene, and near the accident site, an e-scooter lay smashed into a tree. It looked like the rider was sitting in the ambulance and was being treated by the medical staff. A little further away, Eva noticed the police speaking to a young woman in a wheelchair. Although Eva’s first instinct was to try to talk to the police or the medical staff to ascertain what had happened, she realised this probably wasn’t the best moment and she would have to wait until later for the official version of the event.
She looked around and saw a group of four students leaning against a wall with drinks in their hands. A couple of them were vaping. Eva thought that they looked like they had been here for a while, and she walked over to ask them what had happened. From the account they gave her, it appeared as if the e-scooter rider was coming around the bend at some speed, saw the woman in the wheelchair a little too late to ride past her, and, to avoid hitting her, leapt off his e-scooter and let the vehicle hit the tree. Things happened very quickly and no one was exactly sure about the sequence of events, but this was the rough story she got.
Later, she called the police department on campus and was able to speak with one of the officers to get an official account. The story was very similar to what she already knew. She did find out that nobody was seriously hurt and that the only injuries were to the e-scooter rider and were taken care of at the scene by the medical staff. When she asked about who was to blame or if any legal action was expected, she was told that there were no laws around the use of helmets or speeding for e-scooters yet and that she should reach out later for more information. Eva wrote up what she had so far, sent it over to the editorial staff, and considered her work done.
But as she was walking back to her halls of residence that evening, her attention was drawn to the large number of e-scooters parked near the library. As she crossed the central campus, she noticed even more e-scooters lying about the intersections, and there was a litter of them around the residence hall. She wondered why she hadn’t noticed them before. Her attention was drawn today, she thought, because of the accident and also because she saw a good Samaritan remove an e-scooter from the sidewalk, as it was blocking the path of one of the self-driving food delivery robots. It’s a sign, Eva thought, this is what she needs to look for more in her next article, the use of e-scooters on campus.
Eva recognised that, to write a balanced and informative article, as she had been taught to do, she would have to look at many different aspects of the use of e-scooters as well as look broadly at mobility on campus and the use of battery powered vehicles. She had also recently seen e-bikes on campus and, in addition to the food delivery robots, service robots in one of the buildings that she assumed was either delivering paperwork or mail. The accident had also made her realise that, when it came to mobility, accessibility was something that never crossed her mind but that she now understood was an important consideration. She hoped to learn more about it as her research progressed.
As background research for the article, Eva started reading up on articles and studies published about e-scooters, e-bikes, and urban mobility and came across a range of concerns that had been raised beyond accessibility. First, there were reports that e-scooters are not as environmentally friendly as many service providers had made them out to be. This is related to the production of the battery as well as the short lifespan of the vehicles, and as of yet, there has been no procedure implemented to reuse them(Pyzyk, 2019). Second, there were reports of littering, where e-scooters are often left on sidewalks and other places where they restrict movement of other vehicles, pedestrians, and in particular, those in wheelchairs (Iannelli, 2021). Finally, it was also clear from the reports that accidents and injuries have increased due to e-scooters, especially since many riders do not wear safety gear and are often careless, even inebriated, as there were little to no regulations (2021). When she approached her editor with an outline for an article, she was advised to do some more reporting by talking with people who could shed more light on the issue.
After some research, Eva shortlisted the following experts across fields related to e-scooters for an interview, and once she spoke with them, she realised that it would help her if she could get them to have a dialogue and respond to some of the questions that were raised by other experts. Therefore, she decided to conduct a focus group with them so that she achieved her goal of a balanced article and did not misrepresent any expert’s point of view.
Experts/roles for discussion:
1. Bryan Avery is co-founder and chief technology officer (CTO) of RideBy, an e-scooter company. RideBy is one of the options available on campus. Born in a small town, Bryan used to ride his bicycle everywhere while growing up, and for him, founding and leading an e-scooter company provided a chance to merge his interests in personal transportation and new forms of energy. He was a chemical engineer by training, and at a time when most of his friends ended up working for big oil companies, Bryan decided to work on alternative fuels and found himself developing expertise and experience with batteries. For most of the software- and mobile device-related development, RideBy outsourced the work and utilised ready-to-configure systems that were available. By only keeping the core device and battery functionality in-house, they could focus on delivering a much stronger product. Overall, he is quite happy with the success of RideBy so far and can’t help but extol the difference it can make for the environment.
2. Abiola Abrams is a professor of transportation engineering and an expert on mobility systems. Her work combines systems engineering, computer science, and data analytics. Her recent research is on urban mobility and micro-mobility services, particularly e-bikes. In her research, Dr. Abrams has looked at a host of topics related to e-bikes, many of which are also applicable to e-scooters, including the optimisation of hubs for availability, common path patterns of users, subscription use models, and the e-waste and end of lifecycle for these vehicles. Increasingly, she has become concerned about the abuse of some of these services, especially in cities that attract a lot of tourists, and about the rough use of the vehicles, so much so that many do not even last for a month. In a new project, she is investigating the effect of e-vehicles on the environment and has found that there is mixed evidence for how much difference battery-operated vehicles will actually make for climate change compared to vehicles that use fossil fuels.
3. Marco Rodrigues works as transportation director for the local county government where the university is based. As part of a recent bilateral international exchange, he got the opportunity to spend time in different cities in Germany to learn about local transportation. He realised very quickly that local transportation was very different in Germany; residents had a range of public, shared options that were missing in the United States. However, he also realised that e-mobility services were being considered across both countries. He investigated this further and found that Germany waited until it could pass some regulations before allowing e-mobility operators to offer services; helmets were mandatory on e-scooters and e-bikes, and riders had to purchase a nominal insurance policy. He also learned that there were strict rules around the sharing of data generated by the vehicles as well as the apps used by riders.
4. Judy Whitehouse is director of infrastructure and sustainability on campus and responsible for planning the long-term development of the campus from a space perspective, but also increasingly from a sustainability dimension. As the number of students has increased, so has the need for more infrastructure, including classrooms and halls of residence. This has also resulted in greater distances to be traveled on campus. Judy regards e-mobility options as a necessary component of campus life and has been a strong supporter for them. Lately, she has been called into meetings with safety and emergency management people discussing the issue of increased accidents on campus and the littering of e-vehicles across the campus. Not only is it bad for living on campus, but it is also bad for optics. A recent photo featured in the campus newspaper was a stark reminder of just how bad it can look. She is further divided on the use of e-scooters due to misgivings about the sustainability of battery use, as new research suggests that manufacturing batteries and disposing them are extremely harmful for the environment.
5. Aaron Schneider heads Campus Mobility, a student interest group focused on autonomous vehicles development and use. The group members come from different degree programmes and are interested in both the technical dimensions of mobile solutions and the policy issues surrounding their implementation. Aaron himself is a computer science student with interests in data science, and with some of his fellow members from the policy school, he has been analysing a range of mobility-related datasets that are publicly available online. Of these, the data on accidents is quite glaring, as the number of accidents in which e-scooters are involved has gone up significantly. Aaron and his friends were intrigued by their findings and approached some of the companies to see if they would share data, but they were disappointed when they could not get access. Although the companies said it was due to privacy reasons, Aaron was not too convinced by that argument. He was also denied access to any internal reports about usage patterns of accidents. Ideally, he would have liked to know what algorithms were used for optimising delivery and access, but he knew he was not going to get that information.
6. Sarah Johnson is the head of accessibility services on campus and is responsible for both technology- and infrastructure-related support for students, faculty, and staff. The growth of the physical campus and the range of technological offerings has significantly increased the workload for her office, and they are really strained in terms of people and expertise. The emphasis from the university leadership is largely on web and IT accessibility, as teaching and other services are shifting quickly online, but Sarah realises that there is still an acute need to provide physical and mobility support to many members of the community. Although all the new buildings are up to code in terms of accessibility, there is still work to be done both for the older buildings and especially for mobility. Campus beautification does not always go along with access. She is also worried about access to devices, as taking part in any campus activity requires not just a computer, but also access to mobile devices that are out of reach economically for many and not easy to use.
Role-play script:
To help get the dialogues started and based on her prior conversation with the group, Eva has prepared some initial questions:
What role are you playing and, from your perspective, what do you see as the biggest pros of using e-vehicles, especially e-scooters on campus?
From your perspective, what do you see as the biggest downside of using e-vehicles, especially e-scooters on campus?
Can you confidently say that e-scooters are an environmentally friendly option?
What current accessibility accommodations would be impacted by the use of e-vehicles, and what new, potential accessibility accommodations might arise from increased use of e-vehicles?
Would we be better off waiting for more regulations to come before deploying these vehicles on campus and, if so, what should those regulations look like?
Should we use automatic regulation of speed on the vehicle based on where it is and/or inform authorities if it is violated?
Can we control where it can go or penalise if not put back?
What guidelines do you recommend for e-scooter usage on campus?
Authorship and project information and acknowledgements: The scenarios and roles were conceptualised and written by Aditya Johri. Feedback was provided by Ashish Hingle, Huzefa Rangwala, and Alex Monea, who also collaborated on initial implementation and empirical research. This work is partly supported by U.S. National Science Foundation Awards# 1937950, 2335636, 1954556; USDA/NIFA Award# 2021-67021-35329. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding agencies. The research study associated with the project was approved by the Institutional Review Board at George Mason University.
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.
Keywords: SDGs; AHEP; Sustainability; Design; Life cycle; Local community; Environment; Circular economy; Recycling or recycled materials; Student support; Higher education; Learning outcomes.
Sustainability competency: Systems thinking; Anticipatory; Critical thinking.UNESCO has developed eight key competencies for sustainability that are aimed at learners of all ages worldwide. Many versions of these exist, as are linked here*. In the UK, these have been adapted within higher education by AdvanceHE and the QAA with appropriate learning outcomes. The full list of competencies and learning outcome alignment can be found in the Education for Sustainable Development Guidance*. *Click the pink ''Sustainability competency'' text to learn more.
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: SDG 9 (Industry, innovation, and infrastructure); SDG 12 (Responsible consumption and production).
Reimagined Degree Map Intervention: Adapt and repurpose learning outcomes; More real-world complexity.The Reimagined Degree Map is a guide to help engineering departments navigate the decisions that are urgently required to ensure degrees prepare students for 21st century challenges. Click the pink ''Reimagined Degree Map Intervention'' text to learn more.
Who is this article for? This article is for educators working at all levels of higher education who wish to integrate Sustainability into their robotics engineering and design curriculum or module design. It is also for students and professionals who want to seek practical guidance on how to integrate Sustainability considerations into their robotics engineering.
Part of the strategy to ensure that engineers incorporate sustainability into their solution development is to ensure that engineering students are educated on these topics and taught how to incorporate considerations at all stages in the engineering process (Eidenskog et al., 2022). For instance, students need not only to have a broad awareness of topics such as the SDGs, but they also need lessons on how to ensure their engineering incorporates sustainable practice. Despite the increased effort that has been demonstrated in engineering generally, there are some challenges when the sustainability paradigm needs to be integrated into robotics study programs or modules (Leifler and Dahlin, 2020). This article details one approach to incorporate considerations of the SDGs at all stages of new robot creation: including considerations prior to design, during creation and manufacturing and post-deployment.
1. During research and problem definition:
Sustainability considerations should start from the beginning of the engineering cycle for robotic systems. During this phase it is important to consider what the problem statement is for the new system, and whether the proposed solution satisfies this in a sustainable way, using Key Performance Indicators (KPIs) linked to the SDGs (United Nations, 2018), such as carbon emissions, energy efficiency and social equity (Hristov and Chirico, 2019). For instance, will the energy expended to create the robot solution be offset by the robot once it is in use? Are there long-term consequences of using a robot as a solution? It is important to begin engagement with stakeholders, such as end-users, local communities, and subject matter experts to gain insight into these types of questions and any initial concerns. Educators can provide students with opportunities to engage in the research and development of robotics technology that can solve locally relevant problems and benefit the local community. These types of research projects allow students to gain valuable research experience and explore robotics innovations through solving problems that are relatable to the students. There are some successful examples across the globe as discussed in Dias et al., 2005.
2. At design and conceptualisation:
Once it is decided that a robot works as an appropriate solution, Sustainability should be integrated into the robot system’s concept and design. Considerations can include incorporating eco-design principles that prioritise resource efficiency, waste reduction, and using low-impact materials. The design should use materials with relatively low environmental footprints, assessing their complete life cycles, including extraction, production, transportation, and disposal. Powered systems should prioritise energy-efficient designs and technologies to reduce operational energy consumption, fostering sustainability from the outset.
3.During creation and manufacturing:
The robotic system should be manufactured to prioritise methods that minimise, mitigate or offset waste, energy consumption, and emissions. Lean manufacturing practices can be used to optimise resource utilisation where possible. Engineers should be aware of the importance of considering sustainability in supply chain management to select suppliers with consideration of their sustainability practices, including ethical labour standards and environmentally responsible sourcing. Robotic systems should be designed in a way that is easy to assemble and disassemble, thus enabling robots to be easily recycled, or repurposed at the end of their life cycle, promoting circularity and resource conservation.
4. Deployment:
Many robotic systems are designed to run constantly day and night in working environments such as manufacturing plants and warehouses. Thus energy-efficient operation is crucial to ensure users operate the product or system efficiently, utilising energy-saving features to reduce operational impacts. Guidance and resources should be provided to users to encourage sustainable practices during the operational phase. System designers should also implement systems for continuous monitoring of performance and data collection to identify opportunities for improvement throughout the operational life.
5.Disposal:
Industrial robots have an average service life of 6-7 years. It is important to consider their end-of-life and plan for responsible disposal or recycling of product components. Designs should be prioritised that facilitate disassembly and recycling (Karastoyanov and Karastanev, 2018). Engineers should identify and safely manage hazardous materials to comply with regulations and prevent environmental harm. Designers can also explore options for product take-back and recycling as part of a circular economy strategy. There are various ways of achieving that. Designers can adopt modular design methodologies to enable upgrades and repairs, extending their useful life. Robot system manufacturers should be encouraged to develop strategies for refurbishing and reselling products, promoting reuse over disposal.
Conclusion:
Sustainability is not just an option but an imperative within the realm of engineering. Engineers must find solutions that not only meet technical and economic requirements but also align with environmental, social, and economic sustainability goals. As well as educating students on the broader topics and issues relating to Sustainability, there is a need for teaching considerations at different stages in the robot development lifecycle. Understanding the multifaceted connections between sustainability and engineering disciplines, as well as their impact across various stages of the engineering process, is essential for engineers to meet the challenges of the 21st century responsibly.
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.
Professional situations: Rigour; Informed consent; Misuse of data.
Educational level: Intermediate.
Educational aim: Gaining ethical knowledge. Knowing the sets of rules, theories, concepts, frameworks, and statements of duty, rights, or obligations that inform ethical attitudes, behaviours, and practices.
Learning and teaching notes:
This case study involves an engineer hired to develop and install an Industrial Internet of Things (IIoT) online machine monitoring system for a manufacturing company. The developments include designing the infrastructure of hardware and software, writing the operation manuals and setting policies. The project incorporates a variety of ethical components including law and policy, stakeholders, and risk analysis.
This case study addresses three of the themes from the Accreditation of Higher Education Programmes fourth edition (AHEP4): Design and Innovation (significant technical and intellectual challenges commensurate the level of study), 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 hereand navigate to pages 30-31 and 35-37.
The dilemma in this case is presented in three parts. If desired, a teacher can use Part one in isolation, but Part two and Part three 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:
apply their ethical judgement relating to privacy and consent on the use of machine data;
determine the societal impact of a technical solution to a complex problem;
analyse risks associated with ethical concerns and justify their ethical decisions;
communicate these risks and judgements to both technical and non-technical audiences.
Teachers have the opportunity to:
highlight a range of ethical considerations within the scope of a complex engineering project;
introduce methods for risk analysis and ethical decision-making;
link Engineering Council statements of ethical principles with real world situations;
IIoT is a new technology that can provide accurate condition monitoring and predict component wear rates to optimise machine performance, thereby improving the machining precision of the workpiece and reducing the production cost.
Oxconn is a company that produces auto parts. The robotic manipulators and other automation machines on the production line have been developed at considerable cost and investment, and regular production line maintenance is essential to ensure its effective operation. The current maintenance scheme is based on routine check tests which are not reliable and efficient. Therefore Oxconn has decided to install an IIoT-based machine condition monitoring system. To achieve fast responses to any machine operation issues, the machine condition data collected in real time will be transferred to a cloud server for analysis, decision making, and predictive maintenance in the future.
Dilemma – Part one – Data protection on customers’ machines:
You are a leading engineer who has been hired by Oxconn to take charge of the project on the IIoT-based machine monitoring system, including designing the infrastructure of hardware and software, writing the operation manuals, setting policies, and getting the system up and running. With your background in robotic engineering and automation, you are expected to act as a technical advisor to Oxconn and liaise with the Facilities, Security, Operation, and Maintenance departments to ensure a smooth deployment. This is the first time you have worked on a project that involves real time data collection. 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 machine condition monitoring? Machines’ real-time data allows for the identification of production status in a factory and is therefore considered as commercial data under GDPR and the Data Protection Act (2018). Are there rules specifically for IIoT, or are they the same no matter what technology is being used? Should IIoT regulations differ in any way? Why?
2. Discussion: Sharing data is a legally and ethically complex field. Are there any stakeholders with which the data could be shared? For instance, is it acceptable to share the data with an artificial intelligence research group or with the public? Why, or why not?
3. Discussion: Under GDPR, individuals must normally consent to their personal data being processed. For machine condition data, how should consent be handled in this case?
4. Discussion: What ethical codes relate to data security and privacy in an IIoT scenario?
5. Activity: Undertake a technical activity that relates to how IIoT-based machine monitoring systems are engineered.
6. Discussion: Based on your understanding of how IIoT-based machine monitoring systems are engineered, consider what additional risks, and what kind of risks (such as financial or operational), Oxconn might incur if depending on an entirely cloud-based system. How might these risks be mitigated from a technical and non-technical perspective?
Dilemma – Part two – Computer networks security issue brought by online monitoring systems:
The project has kicked off and a senior manager requests that a user interface (UI) be established specifically for the senior management team (SMT). Through this UI, the SMT members can have access to all the real-time data via their computers or mobiles and obtain the analysis result provided by artificial intelligence technology. You realise this has implications on the risk of accessing internal operating systems via the external information interface and networks. So as part of your preparation for the project, you need to investigate what platforms can be used and what risk analysis must be taken in implementation.
Optional STOP for questions and activities:
The following activities focus on macro-ethics. They address the wider ethical contexts of projects like the industrial data acquisition system.
1. Activity: Explore different manufacturers and their approaches to safety for both machines and operators.
2. Activity: Technical integration – Undertake a technical activity related to automation engineering and information engineering.
3. Activity: Research what happens with the data collected by IIoT. Who can access this data and how can the data analysis module manipulate the data?
4. Activity: Develop a risk management register, taking considerations of the findings from Activity 3 as well as the aspect of putting in place data security protocols and relevant training for SMT.
5. Discussion/activity: Use information in the Ethical Risk Assessment guide to help students consider how ethical issues are related to the risks they have just identified.
6. Discussion: In addition to cost-benefit analysis, how can the ethical factors be considered in designing the data analysis module?
7. Activity: Debate the appropriateness of installing and using the system for the SMT.
8. Discussion: What responsibilities do engineers have in developing these technologies?
Dilemma – Part three – Security breach and legal responsibility:
At the beginning of operation, the IIoT system with AI algorithms improved the efficiency of production lines by updating the parameters in robot operation and product recipes automatically. Recently, however, the efficiency degradation was observed, and after investigation, there were suspicions that the rules/data in AI algorithms have been subtly changed. Developers, contractors, operators, technicians and managers were all brought in to find out what’s going on.
Optional STOP for questions and activities:
1. Discussion: If there has been an illegal hack of the system, what might be the motive of cyber criminals?
2. Discussion: What are the impacts on company business? How could the impact of cyber-attacks on businesses be minimised?
3. Discussion: How could threats that come from internal employees, vendors, contractors or partners be prevented?
4. Discussion: When a security breach happens, what are the legal responsibilities for developers, contractors, operators, technicians and managers?
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); Johnny Rich (Engineering Professors’ Council); Dr Matthew Studley (University of the West of England, Bristol); Dr Nik Whitehead (University of Wales Trinity Saint David); Dr Darian Meacham (Maastricht University); Professor Mike Bramhall (TEDI-London); Isobel Grimley (Engineering Professors’ Council).
Professional situations: Communication, Honesty, Transparency, Informed consent.
Educational level: Intermediate.
Educational aim: Practise ethical analysis. Ethical analysis is a process whereby ethical issues are defined and affected parties and consequences are identified so that relevant moral principles can be applied to a situation in order to determine possible courses of action.
Learning and teaching notes:
This case involves a software engineer who has discovered a potential data breach in a smart home community. The engineer must decide whether or not to report the breach, and then whether to alert and advise the residents. In doing so, considerations of the relevant legal, ethical, and professional responsibilities need to be weighed. The case also addresses communication in cases of uncertainty as well as macro-ethical concerns related to ubiquitous and interconnected digital technology.
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 hereand navigate to pages 30-31 and 35-37.
The dilemma in this case is presented in two parts. 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. The case allows teachers the option to stop at multiple points for questions and/or activities as desired
Learners will have the opportunity to:
analyse the ethical dimensions of an engineering situation;
identify professional responsibilities of engineers in an ethical dilemma;
determine and defend a course of action in response to an ethical dilemma;
practise professional communication;
debate possible solutions to an ethical dilemma.
Teachers will have the opportunity to:
highlight professional codes of ethics and their relevance to engineering situations;
address approaches to resolve interpersonal and/or professional conflict;
integrate technical content on software and/or cybersecurity;
informally evaluate students’ critical thinking and communication skills.
Smart homes have been called “the road to independent living”. They have the potential to increase the autonomy and safety of older people and people with disabilities. In a smart home, the internet of things (IoT) is coupled with advanced sensors, chatbots and digital assistants. This combination enables residents to be connected with both family members and health and local services, so that if there there are problems, there can be a quick response.
Ferndale is a community of smart homes. It has been developed at considerable cost and investment as a pilot project to demonstrate the potential for better and more affordable care of older people and people with disabilities. The residents have a range of capabilities and all are over the age of 70. Most live alone in their home. Some residents are supported to live independently through: reminders to take their medication; prompts to complete health and fitness exercises; help completing online shopping orders and by detecting falls and trips throughout the house. The continuous assessment of habits, diet and routines allows the technology to build models that may help to predict any future negative health outcomes. These include detecting the onset of dementia or issues related to dietary deficiencies. The functionality of many smart home features depends on a reliable and secure internet connection.
Dilemma – Part one:
You are the software engineer responsible for the integrity of Ferndale’s system. During a routine inspection you discover several indicators suggesting a data breach may have occurred via some of the smart appliances, many of which have cameras and are voice-activated. Through the IoT, these appliances are also connected to Amazon Ring home security products – these ultimately link to Amazon, including supplying financial information and details about purchases.
Optional STOP for questions and activities:
1. Activity: Technical analysis – Before the ethical questions can be considered, the students might consider a number of immediate technical questions that will help inform the discussion on ethical issues. A sample data set or similar technical problem could be used for this analysis.For example:
Is it possible to ascertain whether a breach has actually happened and data has been accessed?
What data may have been compromised?
Is a breach of this kind preventable, and could it be better prevented in the future?
Has the security been subject to a hack or is the data not secure?
Has the problem now been rectified, and all data secured?
2. Activity: Identify legal and ethical issues. The students should reflect on what might be the immediate ethical concerns of this situation. This could be done in small groups or a larger classroom discussion.
Possible prompts:
Is there a risk that the breach comprised the residents’ personal details, financial information or even allowed remote and secret control of cameras? What else could have been compromised and what are the risks of these compromises? Are certain types of data more risky when breached than others? Why?
What are the legal implications if there has been a breach? Do you, as a software engineer, have any duty to the residents at this point?
At the stage where the breach and its potential implications are unknown, should you tell the community and, if so, what should you say? Some residents aren’t always able to understand the technology or how it works, so they may be unlikely to recognise the implications of situations like this. Should you worry that it might cause them distress or create distrust in the integrity of the whole system if the possible data breach is revealed?
At the stage where the breach and its potential implications are unknown, is there anyone else you should inform? What should you tell them? Are there any risks you may be able to mitigate immediately? How?
Who owns the data collected on a person living in a smart home? What should happen to it after that person dies?
3. Activity: Determine the wider ethical context. Students should consider what wider moral issues are raised by this situation. This could be done in small groups or a larger classroom discussion.
Possible prompts:
When engineered products or systems go wrong, what is our responsibility to tell the people affected?
What is our right to privacy? Can, or should, it be traded away or sacrificed for another good? Who gets to decide?
Are smart homes a good thing if their technology is always going to present privacy risks? Should the technology be limited in some way?
The homes in this case are inhabited by senior citizens with disabilities. Do we owe a different level of care to these people than others? Why? Should engineers working on software for these homes employ a duty of care in a different way than they would in software for homes for young able-bodied professionals? Why? Should a duty of care be delivered by people who have the capacity to care in the emotional sense?
Should individuals have the ability to determine their own level of risk and choose what functionality to accept based on this risk? Should technology enable these kinds of choices?
Should engineers be held responsible for unsafe systems? If not, who is responsible?
Dilemma – Part two:
You send an email to Ferndale’s manager about the potential breach, emphasising that the implications are possibly quite serious. She replies immediately, asking that you do not reveal anything to anyone until you are absolutely certain about what has happened. You email back that it may take some time to determine if the software security has been compromised and if so, what the extent of the breach has been. She replies explaining that she doesn’t want to cause a panic if there is nothing to actually worry about and says “What you don’t know won’t hurt you.” How do you respond?
Optional STOP for questions and activities:
1. Discussion: Professional values – What guidance is given by codes of ethics such as the Royal Academy of Engineering/Engineering Council’s Statement of Ethical Principles or the Association for Computing Machinery Code of Ethics?
2. Activity: Map possible courses of action. The students should think about the possible actions they might take. They can be prompted to articulate different approaches that could be adopted, such as the following, but also develop their own alternative responses.
Do nothing. Tell no one. Try to improve the security to avoid future breaches.
Shut down the smart home technology until any, and all, risks can be mitigated.
Explain the situation fully to the residents, detailing subsequent risks for the future and steps they should take to mitigate the risks themselves.
Offer a partial explanation of the situation, the solutions proposed (or carried out) and reassure them that everything is in order.
3. Activity: Hold a debate on which is the best approach and why. The students should interrogate the pros and cons of each possible course of action including the ethical, technical, and financial implications. They should decide on their own preferred course of action and explain why the balance of pros and cons is preferable to other options.
4. Activity: Role-play a conversation between the engineer and the manager, or a conversation between the engineer and a resident.
5. Discussion: consider the following questions:
What is the role of robotics and artificial intelligence in caring for people in the future?
Is there a limit to what data should be shared and is it justified to use other people’s data for profit?
Could people like Ferndale’s residents be exploited through access to their data? How?
What more could be achieved through the use of data and connectivity to care for older or ill people, in their homes or hospitals, and what additional safeguards should be put in place?
6. Activity: Change perspectives. Imagine that you are the child of one of Ferndale’s residents and that you get word of the potential data security breach. What would you hope the managers and engineers would do?
7. Activity: Write a proposal on how the system might be improved to stop this happening in the future or to mitigate unavoidable risks. To inform the proposal, the students should also explore the guidance of what might be best practice in this area. For example, in this instance, they may decide on a series of steps.
Use human care providers to inform and explain to residents (or their families) about digital security.
Deploy a more rigorous security protocol as well as a programme of regular testing and updates to minimise the risk of the situation occurring again.
Shut down systems where the risks outweigh the potential benefits.
Instigate a reporting procedure and a chain of command for decision-making in the future.
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.
We are seeking further contributions for the Complex Systems Toolkit. Please register your interest in developing a resource by 12th July 2026. You can also join our forthcoming CPD-certificated webinar on ACE-Box and agentic engineering workflows, where we will tell you more about this call for content.
We are seeking further contributions for the Complex Systems Toolkit. Please 
Authors: