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My summer school experience: Inquiry through making and playing with objects, spaces and situations

post by Daniel Swann (2021 cohort)

In early June 2022, I attended a PhD summer school entitled ‘Inquiry through making and playing with objects, spaces and situations.’ The summer school lasted for three days and was organised by Design School Kolding, although was hosted by Aalborg University at their Copenhagen campus. I was looking forward to attending the summer school: I had identified play as an important theme to my research and was also engaging with theoretical approaches to design, particularly in the way that it can inform interaction. The summer school was not specifically focused on children and young people, but I felt this would be a positive as it may allow me to reengage with my research from a different perspective—which I understood as one of the main benefits of attending a summer school as a PhD student.

On the way to Copenhagen, I went over the provided list of reading resources which were curiously broad in scope. It included seminal texts from design theory, research papers from the field of Human-Computer Interaction, experimental autoethnography, and examples of futures studies (an area which was almost entirely new to me). As well as providing the reading list in advance, the organisers asked that each participant brought an object or image that somehow embodied the focus of our research. This provided the basis for introductory conversations with the group on day one of the summer school.

After we had done our introductions, the organisers each made a short presentation that established some of the key themes and ideas of the summer school. This included the many ways we can think about play, especially in the context of making, and a broad overview of design anthropology. These presentations were important as they allowed the group to share their initial interests, doubts, or queries in relation to the central themes of the summer school. Furthermore, it provided us all with a common vocabulary with which to identify the synergies and tensions between the theoretical framework(s) and the practical activities that took place over the following days.

The first day ended with a visit to the Play Lab at the National Museum of Denmark. This innovative laboratory at the heart of the museum is home to a small team that work on reimagining the relationship between the historical assets and the public in an inherently playful way. This was highly relevant to my own research, and I found their presentation and the subsequent discussion to be highly rewarding, as the Play Lab team were engaged in academic debates around playful experiences in cultural institutions as well as the practicalities of running events and exhibitions on a day-to-day basis.

Day two of the summer school represented a deeper dive into the themes as we explored how play can be thought of conceptually and applied to a variety of practical activities. The first topic was ‘Atmospheres and Ambiances.’ Two of the organisers had transformed the seminar room that we were using entirely by changing the layout of the furniture and introducing interactive artefacts, with different lighting and ambient music added also. We were invited to explore the space in silence as a group and then discussed how these changes had altered our perceptions of the atmosphere both individually and collectively. After this, we split up into small groups and explored the campus through our senses: one member of the group would provide prompts and the other would respond through a constant stream-of-consciousness.

After playing with spaces, we then played with empirical data by writing down our experiences and then editing them in a collaborative, creative, and chaotic way. For example:

I remember becoming intrigued, inspired, interested in the elemental world, the spaces we inhabit, use, appropriate, play with
Jeg husker smagen af min farmors saftevand
Jeg husker følelsen af cykelshorts
​​I remember discussing new methods, new ways of thinking
I remember being told that I was going to have a sister.

 

This activity vividly brought to life many of the ideas discussed on the first day. In the following discussion, there was a general feeling that this playful approach to poetry had enabled an entirely different engagement with our memories than was otherwise possible. I found day two of the summer school to be sometimes challenging, and often I felt outside of my comfort zone, but it certainly provided me with many ways of thinking about the central themes of my doctoral research.

On the final day, we focused mainly on making and tinkering. This was particularly rewarding as it began as quite a simple creative task but evolved into an engaging activity that questioned how we can think about both space and time in playful ways. We ended by presenting back to the group as a whole and then discussing some of the emergent themes of the summer school in a round circle debate. It was interesting how the different backgrounds of the participants had influenced the discussions and produced original thoughts and ideas that were thoroughly interdisciplinary.

As I cycled back from the campus to central Copenhagen, I quite literally bumped into another participant who was going the same way. We decided to grab a drink and reflect on the summer school as a learning experience. Without a doubt, we enjoyed our time, particularly the fact that the PhD students came from a variety of backgrounds which ensured that our debates remained dynamic and multidisciplinary throughout. During our conversation, however, we noted that sometimes these debates produced interesting ideas that could not be fully explored due to the time pressures of the summer school.

On further reflection, I felt this was somewhat unfair as it seems to me that this is the very purpose of attending a summer school as a PhD student: to be challenged and leave with fresh ideas that one’s research can attempt to resolve. My time in Denmark not only provided me with a new network of like-minded researchers, but also allowed me to reengage with my studies from a new playful perspective.

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Robot dancer interacting with children – Feng’s internship

post by Feng Zhou (2017 cohort)

The robot dancer was one of four exhibits of “Thingamabobas,” a playful, sensory experience where participants meet and interact with a circus troupe of performative hybrid mechanized sculptures crafted from sustainable and recycled materials. The installation space is a place of wonder. It draws on the absurdities of British artists Heath Robinson and Rowland Emett’s contraptions, Calder’s Circus (1930’s), automata, object theatre, puppetry, and circus acts.

The robot dancer was shown in Lakeside Arts at the University of Nottingham. It attracted many families with children to attend.

We chose the low-cost robot arm – Ned as our dancer. It is also safe working with humans. The Intel RealSense Depth Camera was used as “dancer”‘s eyes to conduct facial recognization.

The fan-shaped zone is the range of the camera. It is also the zone in which children interact with the “robot dancer.” When the camera “sees” the face of the nearest child in the green area, it will dance following the child’s face. Since the “robot dancer” has a bad eye condition, it will be hard to tell whether there is anyone around when the nearest child shows in the purple zone. Thus the “robot dancer” will try to look around and search for children. And then, when children stand farther than the purple area, the distance will be over the range of the camera’s detection. So the “robot dancer” will fall asleep. During the same time when children go through “interacting,” ” searching,” and “sleeping” areas, there will be corresponding music being played.

There are still many points that could be improved such as increasing the interacting zone by increasing amount of cameras, switching professional robotic arms to achieve more sufficient movements, and decreasing the delay of interaction.

It was an amazing experience to work with artists and children.

My job was primarily on developing the robotic interacting system base on ROS, including developing the robotic interacting mode based on distance from the users, music playing etc. From this internship, I extended my skill set by learning the ROS system, which enables high flexibility in combining multiple devices into an integrated system. This enabled me to extend my six-axis 3D printing system, which is significant for my PhD research. During the process of developing the interaction mode of the robotic arm, I had a chance to work with dancers, who interacted with the system with dancing motion, through which, I got valuable experience working with dancers who are also aimed users for my PhD research.

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Paper reflection – Articulating Soma Experiences using Trajectories

post by Feng Zhou (2017 cohort)

Somaesthetics combines the term ‘soma’ with ‘aesthetics’. The concept of ‘soma’ is predicated on the interconnectedness of mind, body, emotion and social engagement, considering all to be inseparable aspects that together form an embodied, holistic subjectivity. Aesthetics here refers to the ways in which we perceive and interact with the world around us. Somaesthetics is a widely used methodology for user study, which plays a significant role in my PhD research. Researchers who have focused on the research of Somaesthetics for many years and have published a number of prominent papers from the Royal Institute of Technology Stockholm visited the Mixed Reality Lab (MRL) of the University of Nottingham (where I am based) and collaborated with researchers here to run workshops on Somaesthetics. It was an excellent chance for me to learn Somaesthetics deeply through the workshop and explore the application of this methodology to my research.

Researchers were split into four groups to explore different applications. The group I was involved in was to explore the boundaries between humans and technology. The skin is traditionally seen as being a critical boundary of the body and one way of defining the bodily self. We can see, i.e. perceive with our eyes, our “external”, fleshy body – our moving limbs and parts, and our skin as the boundary between our “external” and “internal” body –our organs, cells, muscles etc., – which we cannot see, but instead feel or imagine. However, the boundary may be considered malleable. Take the example of a prosthesis – is this a part of our body or a separate piece of technology?

We attached cloth straps to the dancer’s calf and thigh so other members of the team could control them. Participants had to imagine a limb that had a ‘mind of its own’ – an exploration of dance where a part of one’s body was separated from control. The dance experience became one of negotiating control with one’s own body. This could serve as a conceptual stand-in for novice kinaesthetic skills where one’s body is unable to do what is asked – perhaps lacking the range of motion needed. But this was beyond being simply unable to perform the controlled limb; it actually became a separate performer in its own right, creating an intriguing partnership with a part of one’s own body, and encouraging the dancer to question the boundaries of their body and soma.

As we began to dance, our bodies behaved as we expected and we were unfettered. As our group began to take control of our limbs, we lost some agency over our bodies. The external influence started to exert itself in such a way that it restrained us, or actively pulled us. We were no longer ‘at one’ with our own bodies – rather those who controlled our limbs shared control with us. Over time as we learned how to work together, that action could even be considered a part of us (at least as far as the experience goes). It should be noted that the group members pulling on the straps were a stand-in for a ‘disobedient’ prosthesis – so the notion of it becoming part of us, or perhaps beginning as part of us, separating from us and returning might be more tightly aligned to our own body than the group experience – nevertheless the group does have access and licence to control our limbs.

This workshop was one of the user studies to support our final paper. Questioning the boundaries between humans and technology also invites reflection on the boundary between ‘inside’ and ‘outside’: separated by the skin, breathing in and out, ingesting and excreting. Thinking through these boundaries allows designers to redefine them, and thus challenge not only where the soma begins and where it ends, but also where the boundaries of experience lie. This turned out to significantly support my user workshop with disabled dancers to personalise their prostheses.

My job for the final paper was mainly to describe the activity I was involved in during the workshop. This was a precious experience to learn to write a paper collaboratively with many authors. Our final paper has 14 authors from the Royal Institute of Technology Stockholm and Mixed Reality Lab. Each of us wrote a specific part of the paper on Overleaf. We also have regular meetings to discuss writing up issues. This was also the time l started to learn Latex, which helped a lot in my left writing up on papers and thesis.

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Paper Accepted in the Machine Learning, Optimization and Data Science Conference

post by Jimiama Mafeni Mase (2018 cohort)

EFI: A Toolbox for Feature Importance Fusion and Interpretation in Python

Divish Rengasamy (a PhD candidate with the Institute for Aerospace Technology at the University of Nottingham, who recently passed his viva) and Dr. Grazziela Figueredo (my supervisor) published a manuscript to Applied Sciences. Their manuscript proposed a solution to address the lack of agreement among feature importance techniques regarding how they quantify the importance of features to machine learning predictions.  Their solution combined the results from multiple feature importance quantifiers to reduce the variance in estimates and to improve the quality of explanations using crisp information fusion techniques, such as mean and majority vote. A few months later, Grazziela scheduled a meeting to discuss opportunities to improve their solution using a fuzzy logic system (FLS), which is one of the main approaches in my PhD due to its capability to capture and model uncertainties and ambiguity in information.  Divish, Dr. Mercedes Torres Torres (who was my second supervisor at that time, but now works for B-Hive Innovations at Lincoln) and I attended the meeting. In the meeting, Divish went through their proposed solution and together we identified some limitations i.e., significant loss of information as their approach reduced several quantifiers to crisp outputs and difficulty to understand the representation of `importance’ as continuous values (also known as importance coefficients). Next, I described the potential benefits of FLSs, such as using human-understandable linguistic terms to define concepts and using fuzzy sets and rules to handle ambiguous information. They loved the idea and provided synthetic data for experiments.

After obtaining the results from the experiments, we observed that FLSs outperformed the previous solution proposed by Divish in capturing increased variation of feature importance caused by increased data dimensionality, complexity and noise. However, the previous solution still showed remarkable performance in situations with less noise and less variability in the importance of features produced by the multiple machine learning models and feature importance techniques.  It was at this point that we decided to develop an open-source Python toolbox called Ensemble Feature Importance (EFI) consisting of the two solutions i.e., crisp information fusion and FLS.  However, we needed an expert in software modularity and testing to handle the development of the toolbox. Fortunately, Aayush Kumar (a software data scientist), who was doing a master’s in data science at the University of Nottingham, agreed to come on board as the developer of the toolbox. Aayush implemented the toolbox in Python programming language as his master’s dissertation. The toolbox consists of packages to automatically optimise ML algorithms, calculate and visualise the importance of features using various feature importance techniques, aggregate the importance of features from multiple ensemble methods, and create fuzzy logic systems for capturing uncertainties and interpreting importance. The audience for the toolbox is machine learning researchers, end-users of machine learning systems, and decision-makers. After developing and testing the toolbox, we approached Professor David Winkler (a Professor of Biochemistry & Chemistry at La Trobe University, Professor of Pharmacy at the University of Nottingham, and Professor of Medicinal Chemistry at Monash University) to assist in the theoretical motivation of the solutions and as a  second pair of eyes in reviewing the paper.

The paper was written in two weeks and the team was divided into two groups. The first group was made up of Divish, Grazziella and I, who developed the paper structure and decided on the content.  We used `Overleaf’, an open-source online collaborative platform for writing and editing documents, to write the paper. The second group was made up of Mercedes, Benjamin Rothwell (Divish’s supervisor) and David, who reviewed and proofread the paper. Comments were made in ‘Overleaf’ using color-coding and the platform’s chat functionality. After several iterations, we all agreed the paper was ready for submission. A month after submission, we received an email titled ‘Final Decision: Notification of Paper’ with delightful content that our paper had been accepted for presentation at the conference. It was indeed a pleasant message because we were aware of the importance of our toolbox to the machine-learning community. There were a few comments from the reviewers. We were required to address all the comments before uploading a camera-ready version of the paper with a maximum of 15 pages including references. I quickly created a google word document for addressing the comments and shared the link with the other authors. We dedicated a week to addressing the comments, as they were minor. Divish and I did a majority of the revision, as we were more familiar with the methodologies. The most recent version of the toolbox is limited to classification tasks; however, we plan to extend the toolbox to deal with regression tasks. In addition, the toolbox is open-source (i.e., accessible to the public for review, modification and extension)  and we encourage other researchers and ML engineers to contribute to its growth, such as improving the structure of the toolbox, implementing additional state-of-the-art ML algorithms and implementing other feature importance techniques.

Finally, I will like to mention the role of this paper in my PhD. To recap, my PhD aims to develop a reliable, comprehensive and interpretable intelligent driving risk assessment system that considers the simultaneous occurrence of driving behaviours and external conditions. The fuzzy approach implemented in the toolbox for aggregating importance coefficients from multiple machine learning models and feature importance techniques, and to make the importance of features easily understandable has also been explored in my thesis. In my thesis, we explore FLSs for capturing uncertainties in driving data and providing meaningful representations of driving behaviours as linguistic terms using fuzzy sets. In addition, we explore human-understandable fuzzy rules to combine the impact of driving behaviours and external conditions on road safety and incorporate expert knowledge into the system.

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Gaining another perspective – a reflection on my internship with Derbyshire County Council (DCC)

post by Kathryn Baguley (2020 Cohort)

My internship opportunity arose from my ongoing work with DCC. Whilst working on another project in early January 2022, I was excited to hear the news that DCC was looking to initiate two large data projects. Hearing this made me wonder whether there might be an opportunity for me to experience some different work within DCC and complete my internship. Upon enquiring, I was delighted to hear that DCC and the CDT thought this would be a good match, and I was given the go-ahead to continue.

As you might expect, DCC, like many large organisations, holds vast amounts of data across many systems. The projects I worked on aim to enable more meaningful use of data for DCC, its employees, and service users. The work looks at aspects such as the accuracy of data, data migration, and the interoperability of new systems moving forward. At the end of the project, DCC hopes that having data in a better place can drive key performance indicators (KPIs). KPIs will assist with better planning, which it hopes will result in a better outcome for service users and generate much-needed savings for the public purse.

I completed my internship over three months on a full-time basis in the Information Technology team. I was excited to be a part of a new team, but it was reassuring that I had worked with some colleagues on previous projects. Overall, my role was part of a larger multidisciplinary team to assist DCC in achieving better management of its data, and enable more agile working.

Going into my internship I hoped for further insights into how a large organisation makes system changes, mainly around automated decision-making. I was also looking to dive deeper into understanding Microsoft systems and work more closely with my new colleagues in Information Technology (IT).

My internship plan was to liaise with IT, the project team and internal clients (various departments) to understand both the technology and the intended context for use. However, we quickly discovered that the scope was too broad, so I concentrated on the technology side and laid foundations to assist the context later. I prepared documents showing the work carried out for accountability of which also acted as a living document moving forward. I also gave ongoing feedback to the project and senior management teams. I recorded my work through a data protection impact assessment (DPIA). The document quickly grew to some 100 pages just to lay down the foundations. I feel the learning acquired here is something that I will definitely carry forward and use in my PhD writing. I am also reflecting on how the Council is carrying out these projects. I am thinking about how risks were assessed relating to automated decision-making and how I can expand my Peer Review Module output to integrate into my PhD writing.

My internship was fully remote, but I do not feel this negated my experience in any way. I felt fully integrated into the organisation and into the project teams from the very beginning. I accept that I may feel this way simply because of my pre-existing relationship with the organisation and colleagues within. It was helpful to me that I had some knowledge of the wider Council and basic knowledge of the IT systems. The experience did build my research skills in both a practical and academic way, since I had to use a combination of speaking with skilled colleagues and online research. It also underlined to me that I find research is much more satisfying if it can be done in a collaborative way with others, as it brings the topic to life. Moving forwards, I am now wondering how I might bring in the practical and collaborative approach to my work, so as to limit the usual loneliness a PhD can bring.

I thoroughly enjoyed the internship, and it is always a pleasure to work on projects where the people in the organisation are passionate about what they do and about doing the right thing. At the end of the internship, I was recognised for doing a good job, and this has helped me to build confidence in an area to which was technically unfamiliar.

On reflection of the module, I feel the biggest challenge was obtaining the right internship in the first place. I envisaged that the process might be more accessible in my case being a qualified and practising solicitor with several years of professional practice experience. In reality I found opportunities scarce, and maybe this appeared to be the case, owing to increased remote working in 2020 with the pandemic and less collaboration in general. I also had my doubts about the module and how I might make it useful for me. As someone with a professional career before starting my PhD, I was keen to ensure the internship gave me more than ‘work experience’ and provided insights that I could use in my PhD.

A further reflection I have is that while there is an emphasis on doing the internship early, I think it is more important to conduct it when the right opportunity comes along with the right organisation. I began to feel pressure to find and do the placement module from the start. For me, I did not feel I had enough detail to understand what I wanted from the experience in the first year. By my second year I did know more about what I wanted from the internship and I am very glad I did wait; the experience has definitely benefited me.

In conclusion, while the internship is complete, I am happy that DCC have provided me with more opportunity to continue working with them to progress these projects. The work carried out over the placement underlines for me the need for industry and academia to work together and how it can produce much better results for all. In particular, I am currently liaising with the IT team about building on the systems work, and risk assessments carried out in the internship.

 

 

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Summer placement with Campden BRI

post by Melissa Clover (2021 cohort)

This summer (2022) I undertook a 3-month placement with my partner company, Campden BRI. They specialise in food and drink science and innovation in the UK, based largely out of their site at Chipping Campden in the Cotswolds. Deciding to complete this at the end of my first year was a deliberate decision despite being aware that my skills and research are in the very early stages; the hope was that being able to familiarise myself with the company and the different areas in which it works, as well as doing considerable networking, would provide a sound foundation on which to build our working relationship as the PhD progresses. I am pleased to say that this hope was realised and that whilst I did not complete a set project for Campden during the placement, the time spent with them over the summer has greatly developed my understanding of the company, as well as providing my first exposure to Consumer & Sensory Science in industry.

Right from the outset, my partner supervisor and I were determined to create a varied schedule for the duration of the placement. I was eager to express interest in a diverse range of departments and activities, knowing that even where not directly related to my studies, the experience would be useful in some way. My partner supervisor was highly engaged and helpful in facilitating this, producing a 12-week schedule and contacting all of the different people on my behalf to set up initial meetings so that I could then make arrangements independently. This was a highly useful activity and I would recommend it to anyone undertaking a placement of this nature where your activities and duties vary week on week; it created a sense of structure and helped me remain focussed on initial objectives and activities – something that as we all know can be difficult from time to time. The objectives outlined at this early stage were as follows:

      • To better understand Campden BRI as a business, getting to know how different departments are run and interact, what kind of data/databases are available as resources for the PhD research and how the member companies can be involved in the producer side of the research
      • To be exposed to consumer and sensory science in practice
      • To learn new methods of data collection and analysis within sensory and consumer
      • To undertake a mini project that can be shared, potentially with the members in the next Member Interest Group (MIG)

Despite a positive Covid test the day before I was due to begin, the schedule kicked off (2 weeks later than expected) with a visit to the Packaging Pilot Plant on-site in Chipping Campden. On the whole I was working remotely, with an average of 3 visits a month, but where possible (as was the case with this first day), I tried to have initial meetings with people in person and take any opportunities for in-person activities, such as lab tours and consumer testing days. This helped form part of the working activities that enabled the objectives to be achieved; these were as follows:

      • Shadowing/working with both the consumer & sensory team and packaging team
      • Designing a survey to understand trade-offs for consumers when considering certain categories of food products that they buy
      • Receiving training on Compusense and MaxDiff/Conjoint Analysis
      • Being given time within the placement to read and analyse existing work already done by Campden BRI e.g., relevant reports
      • Combining online work with visits to Campden and test centre in Leamington Spa depending on the nature of the work
      • Delivering short presentations on my findings within the next Packaging and Sensory MIGS (tbc)

The experience gained from these placement activities stems further than the networking opportunities gained and professional skills developed (e.g., communication, problem solving, collating and writing up information, teamwork), as much of it will be useful within the context of my PhD research. From designing a survey to learning new statistical skills and acting as notetaker within focus groups, I was fortunate in being able to engage in practical activities that have added to the skillset I will require going forward. I felt that I was able to achieve a sound balance of academic and industry-related skills development; the former came from learning new statistical methods and how to use consumer-specific software and the latter largely from shadowing within different departments. Additionally, I was able to gain useful insights into the production and industrial side of food systems, being reminded of the constant need to think about application of research and ensure that the context within which a certain system functions is carefully considered.

Regarding my take-home messages and/or lessons learnt, one of my most prominent observations was that of the differing pace between academia and industry. In reality, the initial objectives from an academic perspective were highly ambitious, due to the logistics surrounding ethical approval for a survey to be undertaken. This was not an issue as such, rather required adaptations to the schedule which ended up being advantageous (being exposed to another department that is highly related to my area of work – regulatory). It simply highlighted that once again the context of applied research must be considered. This is of course not unique to industry, as similar discrepancies exist between policy and academia relating to pace, funding and overall objectives. It was however useful to be reminded that throughout the duration of the PhD, I need to be mindful of deadlines, pace and expectations when collaborating with Campden.

I am thrilled to be starting my second year with the foundation this placement provided and feel confident that the connections made will be useful as I continue researching. My hope is that as I get more research experience under my belt, I will have more to offer Campden by means of a potential second placement and/or via their bi-annual Member Interest Groups.

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Summer Placement with Nottingham City Council (NCC)

post by Torran Semple (2021 cohort)

During summer 2022, I was on placement with my industry partner, Nottingham City Council (NCC). My main responsibility was to draft NCC’s annual Domestic Energy Efficiency Fuel Poverty report, which combines statistics on fuel poverty, energy efficiency, housing quality and energy prices, as well as information about fuel poverty grants (e.g., financial assistance for Nottingham residents). The report was aimed at various groups, including the public, third-sector organisations and local businesses, therefore there was a particular focus on how to effectively communicate information to all audiences.  Given the report’s potentially varied readership, I was determined to use data visualisation techniques to communicate information in a way that was attractive to any reader. Rather strikingly, none of the council’s previous fuel poverty reports included any graphics and were instead populated with (objectively) cumbersome tables.

Fuel poverty is caused by a combination of factors, including housing quality and household income. Given that there is a geographical aspect to housing and income deprivation, intuitively you would expect the same for fuel poverty trends. Figure 1 shows a bivariate (fuel poverty and index of multiple deprivation) map of Nottingham’s Lower Super Output Areas (LSOAs) that I created to illustrate this point. This graphic is similar in nature to the map I generated for NCC’s fuel poverty report and, pending approval from council staffers, it will also be included in the final release. Nevertheless, this was the perfect excuse to hone my GIS skills – something that had lingered on my to-do list for too long.

Figure 1. Bivariate choropleth map of Nottingham, showing fuel poverty (LILEE metric) and Index of Multiple Deprivation (IMD) per LSOA

Academic and Political Collaboration

Since my undergraduate degree, I have been involved in research projects at the interface of academia and politics. These included analysing public perceptions towards pedestrianisation in Edinburgh city centre and exploring mobility patterns during the COVID-19 pandemic in Scotland. In both projects, Edinburgh City Council and Transport Scotland engaged with our research and in the case of the latter provided invaluable data to aid our analysis. Given the vast reach of governmental bodies, the data that can be captured are inevitably more extensive and representative than what would be achievable otherwise. The same applies to my current working relationship with NCC, and the summer placement provided an opportunity to become familiar with the council’s approach to collecting, storing and sharing data. I did, however, begin to realise that some data are so closely guarded, such as household income and employment data, that some aspects of my research questions would need to be tweaked accordingly.

Although my experience working with NCC was overwhelmingly positive, some differences in working style became apparent. For example, one of my research questions explores issues with the current Low-Income Low Energy Efficiency (LILEE) fuel poverty metric. The metric is controversial as it focuses on household efficiency, rather than the ability of occupants to afford energy, and omits ~40% of homes in Nottingham on the basis that they are too efficient (EPC ratings A–C). From a statistical perspective, this is an obvious oversight and is something that should be discussed and corrected where possible. However, the dominant opinion at NCC seemed to be that this issue was best left untouched, as fuel poverty metrics are imposed at a national level. Eventually, we were able to compromise, and I was permitted to add a short discussion to the report regarding the potential for the current metric to underestimate fuel poverty.

I may be wrong, but I suspect that one unresolvable difference between academic and governmental work is that the latter is subject to a greater level of public and media scrutiny. This likely perpetuates the need for councillors or any other elected officials to present things in a positive light and improve their chances of re-election. As a result, a metric that undeniably underestimates poverty may not be politically disadvantageous, whereas, from an academic perspective, this simply looks like inaccuracy. I still consider this to have been a very valuable experience for myself, as I became more acutely aware of the differences in priorities in an academic and political context.

Final Thoughts

In summary, my placement with NCC provided some excellent opportunities to network and become familiar with local policymaking processes, two experiences that will undoubtedly aid my PhD research. Perhaps most saliently, I now feel more comfortable working in the space that bridges academia and politics, which is of course key to ensuring that my research has real-world impact. I think that I was able to bring a fresh perspective to NCC and generally my ideas were well-received by colleagues. I was particularly pleased that I was entrusted to write the first draft of the fuel poverty report and that some of my ideas, such as including visualisations as communication tools, were adopted and will hopefully continue to be used in the future.

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Reflections of my placement with Ipsos

post by Dan Heaton (2020 cohort)

Background

My PhD examines how discourses concerning the agency of decision-making algorithms can be understood using a hybrid language analysis framework. This framework consists of a multi-disciplinary methodological approach, involving NLP-based computational linguistic tools, corpus linguistics and critical discourse analysis, all underpinned by social actor representation. At the beginning of my doctoral studies in September 2020, my chosen partner for my PhD was the Trustworthy Autonomous Systems (TAS) Hub. TAS is a group of three universities collaborating on the ‘development of socially beneficial autonomous systems that are both trustworthy in principle and trusted in practice by the public, government, and industry’ – a very suitable partner, given my PhD focus!

However, as TAS is still very much within the ‘academia bubble’, my supervision team and I decided that it would be best to undertake my placement with an external industry-based company. After what seemed like an endless search, we found what we thought might be the right fit: Ipsos, the market research and public opinion business. Their Behavioural Science team, led by Colin Strong, were keen to collaborate on different social and commercial analytical projects, especially ones where I could see how their automated analysis worked and others that were concerned with improving and innovating existing approaches through using different qualitative lenses. As a result, I undertook my placement with Ipsos between July and September 2022.

Disinformation Radar

The main project I was involved with was the Ipsos disinformation radar. This involved two main parts: detecting disinformation using linguistic markers and the exploration of social media users respond to and discuss disinformation online. This was in direct response to a client brief that had been received regarding the detection of disinformation and preventing its online reach.

In the first part, involving disinformation detection, I surveyed many pieces of literature regarding disinformation detection. Beginning with literature felt like a familiar starting point, which was very welcome, but I was very excited to see how this would play out when we applied these detection ideas on pieces of suspected disinformation. Although we anticipated that many pieces of disinformation that were shared would be text based, we found that the vast majority were external video links – something we hadn’t accounted for at all in the application of our proposed detection framework! Nevertheless, an exciting challenge was to see whether this applied to the transcripts of these videos, only proving the difficulty of the task at hand and how fulfilling the original brief would have been bordering on the impossible.

After this, I focused on the second part of the project, which involved using ideas stemming from Linguistic Inquiry and Word Count dictionaries, as suggested in Colin’s favourite academic paper by Humphreys and Wang (2017). We had a great behavioural focus and ended up devising a system that detected the intuitive and reflective processes present in tweets, indicating how a tweet author might have responded to disinformation.

I was delighted to be able to bring corpus linguistics into the picture here in order to analyse collocates (frequently occurring adjacent or near-adjacent words) in discourses. Showing Ipsos staff how corpus linguistics tools work was a real highlight and cemented a feeling that I wasn’t just there to learn, but I was also there to teach. As a former primary school teacher and leader, this was very satisfying!

However, the most exciting part of working on the disinformation radar project was the idea that we were doing something that went against norms. I think I went into this placement with a strange mindset: the translation into industry might end the creative freedoms of academia and impose restrictions on what we can and can’t do due to an increased focus on outputs. I am happy to say that this was not the case at all. The innovative way that we worked on this project was not only refreshing,

Though there is something to be said about people’s ‘readiness for change’ – something that frequently appeared as an item of discussion in our meetings. With social media analytics (including the detection of disinformation) having a heavy focus on what automated detection can do, we anticipate some resistance to our ‘pick-and-mix’ approach. This is a challenge that resonates with my PhD too. Although we didn’t quite find the ultimate answer to tackling this, I now feel well-equipped with strategies to get people on board with a multi-disciplinary approach when arguing the relevance of my doctoral project.

Social Analytics for Clients in Action

I also gained experience of working directly with the social analytics team, supporting on client and company briefs. The brief I worked on was investigating sustainability across social media platforms – what does ‘sustainability’ means in social spaces? What do online authors associate with sustainability? This was a good opportunity to use Ipsos’ social intelligence analytics platform, Synthesio, and delve into their sentiment and topic modelling tools.

Undertaking this work brief helped me realise the needs of clients in Ipsos’ daily routines. It also allowed me to reflect on how NLP-based computational linguistic tools were being used and interpreted. It was interesting to use different software to what I have engaged with so far during my doctoral studies. For example, the topic modelling was a little more sophisticated and even attempted to name the topics for you! Naturally, this often ended with some errors, but the topic groupings seemed reasonable and helped narrow down a data focus. That being said, the outputs from Synthesio weren’t necessarily revolutionary when comparing them to the ‘off-the-shelf’ NLP-based tools I’ve used prior. Obviously, this isn’t a problem unique to Ipsos, but it’s a good reminder of why my PhD is important in tipping that scale and showing that a combination of approaches is beneficial.

Final Reflections

Overall, this placement helped me realise how research like mine translates out of academia. Combining quantitative and qualitative linguistic analytics is one thing, but making sure you’ve got a strong ‘philosophical stance’ (as Colin aptly named it) is another. I was imagining I might see a few things being done for the sake of it at Ipsos; however, when it came to it, it was refreshing to see that the desire for underpinning choices with a strong theoretical rationale was very much there with the disinformation radar project. It was also brilliant to see how things really worked in applied social analytics and a great reminder of the necessity of my PhD work so that the reliance on automated outputs isn’t skewed one way or another. Through undertaking this project, I believe it helped refine my analytical skills in an adjacent area of study: cognitive linguistics. This will, ultimately, be beneficial to my doctoral studies as a potential theoretical or methodological underpinning to my work.

I would like to thank Colin for his time, effort, enthusiasm and guidance during this placement. Duncan Fergusson and Danielle Latreche were also great advisors, too, and I couldn’t have done it without them. As the placement ends, I’m very much looking forward to continuing our working relationship together for the remainder of the PhD and beyond.