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A Reflection on The Connected Everything and Smart Products Beacon Summer School 2020

post by Cecily Pepper (2019 cohort)

My first summer school started with an invite via email. Despite my interest in the topic, my first thought was that robotics was not my area of expertise (coming from a social science background), so maybe I shouldn’t bother applying as I’d be out-of-my-depth. Although after some consideration, I thought it would create some great opportunities to meet new people from diverse backgrounds. So, I stopped worrying about my lack of knowledge in the area and just went for it; and I got a place!

The summer school was held digitally due to COVID-19 restrictions, which had both its benefits and pitfalls. On the first day, we were welcomed by Debra Fearnshaw and Professor Steve Benford, and were then given the opportunity to introduce ourselves. From this it was apparent that there was a wide variety of delegates from several universities, with a range of disciplines including social sciences, robotics, engineering and manufacturing. The first day mostly consisted of talks from experts about the challenges we face in connecting technology and the potential of co-robotics within the fields of agrirobotics, home and healthcare. The main task of the summer school was to create a cobot (collaborative robot) that could overcome some of the issues that COVID-19 has created or exacerbated. The issue that the group chose to address had to fall into one of the categories introduced on the first day: food production (agrirobotics), healthcare or home. Along with this challenge, more details were needed on function, technological components, and four key areas of the cobot design: ethics, communication, learning and safety. These aspects were introduced on the second day. After being split into groups at the end of the first day, I felt happy as my group had a range of experience and expertise between us, which I felt would bode well for the challenge as well as being beneficial for myself as I could learn something from everyone.

Similarly, the second day consisted mostly of talks, this time based on the four themes mentioned previously. The ethics discussion was interesting and included in-depth explanations around aspects to consider when reflecting upon the ethical consequences of our designs, such as privacy, law, security and personal ethics. An online activity followed the ethics talk but was soon interrupted by a technical glitch. Despite this, we were able to engage with alternative resources provided in order to reflect upon the ethics of our cobot design. This was useful both for our eventual design, as well as applying this to our own PhD research.

The other themes then followed, including a discussion around interaction and communication in technology. This was an insightful introduction to voice user interfaces and alike, and what the current research is focusing on in this field. While fascinating on its own, it was also useful in thinking about how to apply this to our cobot design, and which features may be useful or necessary for our cobot’s functionality. A talk on the third theme of learning was then delivered, including details about facial recognition and machine learning, and the applications of these in the field of robotics. Likewise, this was useful in reflecting upon how these features may be applicable in our design. Finally, the theme of safety was considered. This talk provided us with the knowledge and ability to consider safety aspects of our cobot, which was particularly apt when considering COVID safety implications too. Overall, the first two days were quite lengthy in terms of screen time (despite some breaks), and I found myself wilting slightly towards the end. However, I think we could all understand and sympathise in the difficulty of minimising screen time when there is a short space of time to complete all of the summer school activities.

On the final day, we split into our teams to create our cobot. This day was personally my favourite part of the summer school, as it was fantastic to work with such a variety of people who all brought different skills to the group. Together, we developed a cobot design and went through the themes from the previous day, ensuring we met the design brief and covered all bases. Probably the biggest challenge was keeping it simple, as we had so many ideas between us. Despite our abundance of ideas, we were strict with ourselves as a group to focus and keep the design simplistic. Additionally, the five-minute presentation time meant that we had to keep our design simple yet effective. We then presented our home assistant cobot, Squishy. Squishy was an inflatable, soft cobot designed to assist carers in lifting patients who were bed-bound (as occupational injuries are a significant problem within the care industry). Squishy’s soft design enabled comfort for the patient being lifted, while the modular design provided a cost-effective solution and the possibility of added-extras if necessary. Along with this, Squishy was beneficial in that it consisted of wipe-clean surfaces to enable effective cleaning in light of COVID-19, as well as aiding social distancing by reducing the need for carer-patient contact. Other features of Squishy included machine-learned skeletal tracking and thermal cameras to aid safe functionality, and minimal personal data collection to maintain ethical standards. After the presentations and following questions, the judges deliberated. Results were in…my team were the winners! While I was happy to have won with my team, the most fruitful part of the experience for me was meeting and learning from others who had different backgrounds, perceptions and ideas.

Overall, I felt the summer school was well-organised and a fantastic opportunity to work with new people from diverse backgrounds, and I was very glad to be a part of it. I’m also pleased I overcame the ‘Imposter Syndrome’ feeling of not believing I would know enough or have enough experience to be a valuable delegate in the summer school. So, my advice to all students would be: don’t underestimate what you can contribute, don’t overthink it, and just go for it; you might end up winning!

The Summer School was funded by EPSRC through the Connected Everything II network plus (EP/S036113/1)

 

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HOLDING AUDIENCES TO ACCOUNT

Nick Tandavanitj has recently begun his PhD journey as part of the Horizon CDT 2023 cohort.

Nick is a leading member of the artist group Blast Theory, which is one of the CDT’s supporting industry partners and whose work combines interactive media, digital broadcasting, and live performance.

Nick’s research will explore the meaning of asking for audience involvement. You can read more about this on Nick’s original post on the Blast Theory Blog.

Holding audiences to account

 

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My Internship at Capital One

post by Edwina Borteley Abam (2019 cohort)

My internship at Capital One started mid-November 2021 and ended mid-May 2022.  Capital One is a credit card company originally situated in the US with two branches located within the UK in Nottingham and London specifically. I interned at the Nottingham branch over a period of 6 months, on a part-time basis.

The company has several departments and units. I was placed within the Data Science team which forms part of the wider Data group within the organisation. There are three main sections within the Data Science team namely Acquisition, Customer Management and the Bureau team. The Acquisition team concentrates on building models to score new credit card applicants. The Customer Management team focuses on managing and monitoring the behaviour of all existing credit card customers and credit line extensions and the Bureau team manages all data and information exchanged between credit bureaus and Capital One.  For my daily work, I was placed within the Customer Management team and collaborated on two related projects- (Onescore2 and Challenger Model).

The internship:

Onescore2 project involved creating machine learning models to manage the behaviour of existing credit card customers. I worked together with my manager to build models to predict customers likely to default on their cards over a defined period of time.  We used R (a statistical programming software) as the main tool for the project. The specific activities assigned to me on the project involved creating the R program files for executing the models, monitoring the progress of the models’ execution, collecting and interpreting model results, and updating the GitHub repository with project outputs. The previous knowledge and skills acquired from the Data Modelling and Analysis course in year two of my PhD helped me understand the technical details involved in the analysis and to carry out my assigned duties effectively on the project.

The second part of this project is the Challenger Model project and it involved building different models in Python to compare their performance with Onescore2.  The project was an exploratory study of different conventional models in predicting the likelihood of default. The Challenger Model project serves as a baseline to compare with results from my PhD work, which potentially could form part of my PhD thesis. As this phase of the project is linked to my PhD work, I benefitted from the guidance and input of my supervisor.  While working on the Challenger Models, I held periodic meetings with my manager, supervisors and other members of the Data Science team where I presented on progress and discussed possible directions for the project.  I also took part in weekly stand-up sessions where all associates within the Data Science team shared updates on ongoing projects.

My reflections:

Looking back on my internship, overall the experience has been insightful, an exciting journey and a time of personal development.  I have grown and evolved in several areas in terms of interpersonal and professional skills.

Upon arrival in the first week of the internship, my manager was deliberate to arrange informal meetings and chat sessions with other members of the Data science team.  These introductions and chats exposed me to a range of people in various roles and at different levels of leadership in the team. It helped to quickly integrate into the team to create new connections and meet new people. Despite being naturally reserved, I enjoyed the conversations much as everyone was friendly. I was encouraged to step out of my shell to interact with more people. During my interactions, I seized the opportunity to ask all the lingering questions I had on the topic of credit scoring which is also at the heart of my PhD research. Each person was friendly and particularly eager to answer all my questions and chat about the work they do.

Apart from the Data Science team, I had the chance to speak with other associates in other departments of the company and that experience was reassuring and enhanced my confidence at the workplace. I got first-hand experience in mixing with different people from different backgrounds in an office setting and learning to blend with them.   The conversations in the first couple of weeks opened up my understanding more on the details of credit scoring and credit cards. I got more understanding of how the different teams work together to make credit cards available to people and how customers are managed and credit lines extended. I had the opportunity to join major meetings and to hear updates on projects being worked on within the different departments of the organisation. This also gave me a wider view of other aspects of the business.    I was able to connect how the theory of credit scoring I had read in books and research articles played out practically in the real world through this experience.

During my internship, I worked both from home and the office.  Every week during the first few months, I worked three days at home and two days in the office.  I found commuting to work on time a discipline to develop as this was my very first time working outside of industry. Although challenging initially but got easier with time.  The regular catch-ups and progress updates with managers and my supervisor were sometimes strenuous and nerve-wracking, however, it trained my communication and presentation skills.

The work culture in Capital One challenges associates to give their best on the job but at the same time encourages relaxation and places such high priority on wellbeing.  Unlike other work environments, I was surprised to find several fitness and relaxation points like the gym, tennis and pool table strategically placed in the Capital One building to support associates. In addition, during my internship, the company observed a day of fun activities for its associates every quarter of the year just to have a break from work.  This shaped my perceptions about the working environment.

Capital One is the industry partner for my PhD and I was privileged to have access to their data for my PhD work. Through my connections with the team members, I was able to easily recruit participants for my first PhD study which I believe would have been difficult otherwise without the internship.  Overall, I enjoyed the internship and the experience has been beneficial not only for my PhD but for my personal development.

 

 

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My experience at the Mindtrek Doctoral Consortium in Finland

post by Emma Gentry (2021 cohort)

In November 2022 I was accepted to present my PhD plans at Mindtrek’s Doctoral Consortium in Tampere, Finland. With the exception of one prior conference, until this point, I had only presented to academics and peers within the CDT, so I was delighted to be given this opportunity. Mindtrek is an international technology conference held every year in collaboration with Tampere University. With its strong focus on human-computer interaction and future technology, I was eager to immerse myself in all that the conference had to offer during this stage of my development as an early career researcher. In what follows I reflect on my experience of attending a doctoral consortium for the first time, offering key takeaways for PhD students looking to attend similar events in the future.

The event was brought to my awareness when I came across a post in the CDT impact group written by one of our Horizon alumni, Velvet Spors. Velvet offered a great deal of insight about the benefits of attending such an event. Reflecting on this moment I feel grateful to be part of the CDT community with access to an abundant network of researchers and alumni. I would strongly advise talking to PhD students/alumni in similar areas to see what kinds of events and conferences they recommend. I’m very glad to have established a connection with Velvet before attending Mindtrek.

The conference lasted a total of three days and was set up as a hybrid event, though I was fortunate enough to attend in person. For the doctoral consortium itself, we were asked to deliver a 10-minute presentation followed by a 10-minute discussion with four panel experts. Trying to explain your PhD in 10 minutes or less is always a challenge (especially when it’s a 2-minute flash presentation on Industry Day), but it is a skill that is so important to develop for effectively communicating and ‘selling’ your research to others. Reflecting on this experience I realised the importance of prioritising what you talk about, placing emphasis on why the contribution is important, and illustrating what other people might gain from your work.

The depth of the feedback I received from the doctoral consortium exceeded my expectations and each panel expert had a different angle of the PhD to comment on. I ultimately learned the importance of saying what’s out of scope for the PhD and being ok with not knowing the answer to a question, especially in the very early stages when you are still ironing out the specifics of your project. The doctoral consortium panel provided extensive suggestions for where I could take my research based on their expertise. I think the exposure you have to go through in the early stages can be quite daunting but also necessary for your development as a researcher. It’s helpful to think that everyone on the panel started somewhere and probably had a similar experience at their first doctoral consortium/conference.

The following days comprised the main part of Mindtrek’s academic conference where I came across many exciting tracks relevant to my PhD topic. The tracks I found particularly interesting were “Understanding and Designing for the Socio-Technical” and “Fictional, Speculative, and Critical Futures”. The focus of my PhD was still very much open at this point, and I felt inspired by many of the talks in these tracks. As part of the Horizon CDT program, we are encouraged to take awareness of upcoming, novel, and creative methods given the interdisciplinary nature of the training centre. The Mindtrek conference was ultimately a perfect opportunity to expose myself to a range of creative methods and to broaden my horizons in this way. Networking events were held in the evenings after conference hours which provided a more relaxed environment to speak with researchers and panellists. I always find it helpful to ask PhD students in the later stages of their doctorate, and even those with many years of experience after their PhD, what they wish they’d done earlier on.

The event enriched my career as a researcher in a multitude of ways. As well as developing my presentation skills further, I learned how to effectively communicate my project to an audience outside of the CDT. I was encouraged to think about the impact my PhD might have afterwards, and how I might engage with key stakeholders. For example, how might I disseminate my recommendations in a way that would make the most impact? It’s easy to get caught up in the theory of a PhD but recognising the real-world impact you can achieve is essential.

To sum up, I would highly recommend attending a doctoral consortium to anyone in the early stages of their PhD. I ultimately learned the importance of keeping an open mind in the early days and accepting that your project may change a lot from your original plan. You also need to have the exposure to be guided in the right direction. It may feel challenging to take this step but expanding your comfort zone is necessary for growth.

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Neurodiversity Challenges

post by Jenn Layton Annable (2020 cohort)

Working as an autistic autism researcher can sometimes be a lonely and distressing experience. Daily contact with academic literature that consolidates pathologising or stigmatising beliefs and constructs can be traumatising. Luckily there is a growing community of autistic autism researchers who, although widely dispersed geographically, come together through digital technology and virtual spaces to offer peer support and collaborate in academic writing and work that counter such narratives with alternatives, grounded in our self-knowledge and awareness. This digital network of neurodivergent researchers, activists and thinkers has also crystalised into the academic disciplines of neurodiversity studies and critical autism studies, containing both scholarship and activism in equal measures.

My first published peer-reviewed paper emerged from this need to counter potentially harmful, clinically situated perspectives. An autistic autism researcher acquaintance Nick Chown raised the matter of the paper Neurodevelopmental disorders and neurodiversity: definition of terms from Scotland’s National Autism Implementation Team within an autistic autism research group asking for collaborators to respond to the publication, specifically dealing with a number of flawed assertions contained the text.

These included:

    • An attempt to formalise the concept of neurodivergence within a typology in which those who are neurodivergent fall outside of societal norms and those who did not are neurotypical, when societal norms are fluid and ambiguous at the best of times.
    • The reduction of all other types of neurodivergence (such as different learning abilities and styles, tourettes or other atypical mental and neurological experiences) beyond those of autism or ADHD within the category of “other”, essentially disregarding the original principle of neurodiversity as encompassing the entirety of human experience; a very standard reductionist psychiatric/diagnostic approach to this vast diversity.
    • Crediting of the term ‘neurodiversity’ to Judy Singer (an academic who was the first to use this in scholarship), when it had in fact been used online by autistic activists up to five years previously in the early nineteen-nineties.

The collaborative writing process within a neurodivergent research group can be complex, with much consideration given to the different sensory or communication needs of each individual as well as the ongoing stress they may be experiencing at any time. Often there are occurrences that would be considered rude or inappropriate, such as abruptly leaving a meeting with no explanation, were they to occur in an equivalent neurotypical workspace. Our team of writers and advisors included those who had a range of neurodivergent differences; autism, ADHD, dyslexia and mental health challenges, so as much time went into managing these with compassion and understanding toward one another as the actual writing itself. Although conflicting needs can cause frustration and difficulty, the shared experience of stigma and ignorance from others that neurodivergent people hold together is a strong foundation to work from to overcome them.

Additionally, the neurodivergent status of several contributors is not known publically outside of our research community (individuals holding prominent or senior academic positions would still experience discrimination were they to publically disclose). Others who worked on the response are publically known as autistic clinicians who have to be seen to not be challenging their professional status quo too much. This risk is such, that meeting recordings that included such individuals were transcribed and then deleted to avoid exposure of them to harm, professionally or personally.

We worked virtually using email, and shared documents for writing, commenting and editing, together with the occasional face-to-face video call. These styles of working have of course become much more prevalent since the Covid pandemic, however, their benefits to neurodiverse writing groups extend beyond the convenience of meeting without travel.

Neurodivergent communication preferences span many media and dimensions beyond that of written language. One of our group creates TikTok content incorporating signing for the deaf ADHD/autistic community, opening up lived experiences such as these to others who might be excluded because of intersectional disabilities. There was much lively debate about the inclusion of graphically based examples of neurodiversity and how far we would be able to challenge the publication boundaries of a very traditional medical journal such as the British Journal of Psychiatry and still be considered credible. On this occasion, an alternative format such as this was deemed to be too far to be included. Our work shows how different social and communication styles implicit in neurodiverse/neurodivergent groups demonstrate the value they can add to the democratisation of academic knowledge through variable dissemination, both from within the academy to the outside and from the outside in, via the insider/outsider perspective we hold and express through our output, whatever form it takes.

Overall, the process of containing the very different perspectives and styles within even a small neurodivergent group such as ours can be a challenge in and of itself, ensuring that they are all included in enough substance whilst still creating a coherent narrative. Nick and I worked on this refinement and translation process, with the agreement and ‘member checking’ of the wider team. This is how I came to receive the second author attribution in the writing process.

The first challenge we faced was the rejection of the paper’s original format as that of analysis, instead being considered as a commentary, with a word count and citation limit of half of what we had submitted. We decided as a group to reformat the original writing, to ensure a timely response to the original article with a commitment to submitting an expanded version at a later date. Upon resubmission, we received thoughtful reviewer feedback which improved the overall quality and style of the paper. These included challenges to “better capture the nuance and undoubted controversy in the field of biomedical vs social paradigms of neurodiversity and disability” which we managed successfully, whilst remaining within the wordcount and inclusive of the many different frames of neurodivergent reference included in our authorial group.

The final submission was well received by the BJP, whose editors and reviewers thanked us for our thoughtful and considerate responses both to their comments and the original paper. Although we were disappointed to have to shorten our original writing there was a commitment between a smaller group of those who contributed to further our thinking in a later piece, alongside others who produce and curate digital content for social media to adapt what we had created to make it suitable for audiences in these different contexts. We felt that this would be the best approach overall. In coming together we were able to express and explore a range of different ways of thinking, expressing and depicting our ideas. All are valid and worthy of use, however, the delineated nature of certain specialities like academic publishing means that, unfortunately, certain ways of being and communicating are still valued above others. We hope our work, as neurodivergent academics, will champion a breaking down of these barriers of in/validation between different styles and types of communication, along with greater acceptance of neurodivergent ways of being and knowing.

If you would like to read the full response written by me, Nick Chown, Luke Beardon and Nik Howard, please click here.

 

 

 

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Safe and Trusted AI: Insights from the Summer School Attendance

post by Farid Vayani (2020 cohort)

Introduction:
The “Safe and Trustworthy AI” (STAI) summer school, which Imperial College held in July over three days, brought together renowned academics, industry experts and students, providing a platform to learn the cutting-edge research and developments in artificial intelligence (AI). It fostered critical thinking about the ethical issues of AI and its influence on society. The event included discussions on the ethical challenges, advances in Explainable AI (XAI), deep reinforcement learning, AI-driven cybersecurity risks, and the importance of integrating ethical considerations and interdisciplinary collaboration for the development of safe and trustworthy AI systems. The event also provided an opportunity to reflect on the methodologies and constraints of the research paper titled “BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning”.

AI’s Ethical Challenges:
The talks and subsequent discussions focused on the effects of AI on job displacement and workers’ rights, where we discussed the delicate balance between artificial intelligence automation and its influence on the work market. Concerns over pervasive surveillance, as well as the necessity for transparent AI governance, were debated. The ethical implications of AI’s inclusion into the legal system were of participants’ interest because of the potential bias and discrimination of AI-driven decision-making.

Data ethics diagram
Figure 1: AI Landscape

The speaker used real-world examples that raised serious ethical problems, such as the highly criticised algorithm COMPAS (CorrecEonal Offender Management Profiling for AlternaEve SancEons) which is used in the US criminal justice system allegedly perpetuating systemic racial bias. The Cambridge Analytica scandal where data from 87 million Facebook users was exposed via a quiz app, which took advantage of a flaw in Facebook’s API, leading to security and privacy problems which was exacerbated by its use for political purposes. The event surfaced the complexity of the AI landscape and equally the significance of translating legal provisions into efficient business practices.

Explainable AI (XAI):
The event also drew attention to XAI, a key aspect of AI research aimed at improving transparency and interpretability of AI systems. Speakers showed various techniques for interpreting AI models and understanding their decision-making processes, ensuring trustworthiness and accountability in AI applications. XAI has emerged as a significant field of study, addressing the black-box (see Figure 2) nature of complex AI algorithms, and striving to make AI more understandable and explainable to end-users and stakeholders.

diagram of AI Interpretable vs Black box model
Figure 2: Type of AI Interpretable vs Black box model

Deep Reinforcement Learning:
Speakers discussed the progressions in deep reinforcement learning (DRL), which has garnered significant attention for its notable capabilities in enabling AI systems to learn complex tasks through trial and error. DRL combines deep learning and reinforcement learning, allowing AI agents to learn from experience and decide in dynamic environments. Discussions revolved around the potential of DRL to revolutionise various domains, such as robotics, gaming and more. However, ethical considerations were highlighted as DRL presents challenges in ensuring safety, fairness, and accountability.

Review of “BabyAI” Research Paper:
The student-led activity involved reviewing the research paper titled “BabyAI: A PlaBorm to Study the Sample Efficiency of Grounded Language Learning.” The paper introduced the BabyAI research platform, designed to facilitate human-AI collaboration in grounded language learning. The platform offered an extensible suite of levels, gradually leading the AI agent to acquire a rich synthetic language, similar to a subset of English. The research presented in the paper highlighted the challenges of training AI agents to comprehend human language instructions effectively. The platform could serve as an important tool for researchers to test methods for DRL, it would suffer from scaling and the opacity of the algorithm which raises the question of whether AI agents learnt the language for human machine interaction or did they just learn to solve the test presented. It calls for further research to improve sample efficiency in grounded language learning to interact with and understand natural language instructions more proficiently.

AI-Driven Cybersecurity:
Speaker from the industry devoted to AI-driven cybersecurity. They showed novel ways that adversaries could exploit AI-generated attacks for automatic discovery of zero-day attacks, methods of malware propagation, and adversarial attacks on defensive systems. The event underscored the necessity for vigilance and collaborative efforts to safeguard digital infrastructures from the evolving AI-based threats. While AI has shown potential to enhance cybersecurity measures, it clearly has introduced new challenges, that demand sophisticated countermeasures.

Ethics and Interdisciplinary Collaboration for Safe AI:
Throughout the event, the importance of integrating ethical considerations into AI development and deployment was emphasised. Ethical AI frameworks are essential to ensure that AI technologies align with societal values and protect individuals’ rights and privacy. Moreover, interdisciplinary collaboration between scientists, engineers, ethicists, policymakers, and other stakeholders is vital for a consistent approach to AI development that prioritises human well-being and safety.

The Way Forward:
The various talks and discussions during the event revealed that regulation and policy alone cannot fully address the complex challenges in managing AI risks such as the European Union’s AI regulation is an important step in the right direction, however, the speakers and participants underscored that more comprehensive approaches are needed to ensure that AI systems function ethically and responsibly. These approaches include integrating solid safety engineering principles into AI development and embedding ethical considerations in the impact assessment, design, validation, and testing.

In conclusion, the STAI event shed light on the ethical challenges and advancements in AI research, emphasising the significance of integrating ethics into AI development, considering distributive fairness, privacy protection, and responsible practices. The quest for ethical AI remains an ongoing journey, where interdisciplinary collaboration, solid safety engineering processes, and thoughtful regulation play pivotal roles in shaping the future of responsible AI technology, one that benefits people.

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An enrichment event with care-experienced young people

post by Cecily Pepper (2019 cohort)

My research surrounds the exploration of how social media can impact the mental wellbeing of care-experienced young people. In June 2023, I ran an enrichment event for young people in care with the help of my supervisor, Elvira Perez Vallejos. As my doctorate journeys into its final stages, it was important to me to consider how I can maximise the impact of my work. Along with public engagements and presentations, Nottingham City Council and I decided that a broadening horizons event at the university would be the most impactful for the young people. With the help of Mark Ball, who has kindly offered advice and support throughout my research regarding safeguarding, Elvira and I set to work on the organisation of an event that would be both enjoyable and offer the opportunity to discuss higher education and research.

Along with Nottingham City Council, we decided to reach out to the Cobot Maker Space: an innovative space that explores human-robotic interaction at the University of Nottingham (https://cobotmakerspace.org/). While this space is not directly linked to my research, it was thought to be an ideal choice for the visitors as it’s an interactive and fun space that would be enjoyable and inspiring. The Cobot Maker Space kindly agreed to hosting the event and providing fun demonstrations, whilst also generously gifting the young people with a robotics kit.

After liaising with the stakeholders, the enrichment event was organised for June 2023. The event consisted of a tour of the Jubilee campus, interactive demonstrations led by the Cobot Maker Space team, and (crucially) pizza and snacks. The young people were encouraged to ask any questions they had regarding university or higher education, which they did indeed take the opportunity to do so. All of the young people asked questions about college or university, asking about different courses and paths into higher education. It was a pleasure to have these discussions with them and we spoke about how care experience might impact this. I spoke about my research with care-experienced young people who have been to university, showing that it is possible for anyone to go to university if they want to, despite the challenges they face and how unlikely it may seem for them.

The young people and their residential carers thoroughly enjoyed the event, with the cobot demonstrations being incredibly well-received. Feedback received from social workers showed how excited the young people were, with them talking about research and robotics with the other young people and staff when they got home. This feedback was greatly appreciated, and we were very pleased that the event had been impactful for the young people. In addition to this, the event also had an impact on the university staff and researchers, as it triggered discussions surrounding further outreach events such as after-school clubs for care-experienced young people and people from other minority groups.

Overall, the enrichment event was successful, and I’m pleased to say it made a positive impact on the young people. I’d like to extend my thanks to everybody involved, but especially the researchers at the Cobot Maker Space who went the extra mile to ensure the event was fun, interactive and inspiring.

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Participatory methods for digital inclusion

post by Oliver Miles (2018 cohort)

Reflections on values orientated ideation as an outreach activity

I previously reflected on my research internship with digital accessibility and mobility start-up ‘CityMaaS’, focussing on the resulting ‘drivers and barriers to digital inclusion’ report and my own experiences of working in the world of start-ups. In this post I’ll focus instead on the leadership and methods I brought to the work – a participatory ideation workshop drawing on principals of values-sensitive design (VSD) [1] – positioning this as a form of outreach to two key stakeholders: CityMaaS as the host organization and corporate professionals as participants.

As an independent researcher embedded with CityMaaS I was asked to critically uncover the drivers and barriers to digital inclusion services across three diverse B2B organizations from financial, healthcare, and higher education sectors that were current or potential clients.

Figure 1 – Speculative use case ideation

This first entailed understanding the host organization’s perspective on digital inclusion priorities, by listening to CityMaaS software and digital inclusion subject matter experts and building a detailed inventory of their solutions in terms of core features and functions.  These would later serve as card-based options and provocations in a collaborative workshop.

Considering participant organizations, I then spoke to heads of web and digital, interviewing them regarding their journeys and priorities regarding digital inclusion, with a view to uncovering core themes which could be positioned as corporate ‘practical values’ [2]. These were presented alongside software features and functions in later ideation workshops for wider web and digital teams to participate in, with a view to articulating speculative use cases.

In the example above, participants reason that the accessibility questionnaire feature of the web-page personalization tool ‘Assist Me’, considering its user data dashboard functionality, might be applied to the everyday internal practice of raising support tickets for the end-users. Conceivably, this might fulfil the chosen practical value of ‘deriving knowledge of end-users through their interaction data’ (Figure 1).

This process was repeated for three practical values chosen as priority issues across three existing software solutions using a card-based framework inspired by VSD, presented in Miro[1] (Figure 2). This resulted in a final ‘wildcard’ digital inclusion software solution being incrementally articulated, tailored to the needs of the participant. Aside from these research output, I would outline the following two benefits of the approach I took as relevant to outreach objectives.

Sharing a replicable, inclusive methodology: The VSD ideation workshop is inclusive as a practice, and in terms of the method, and can easily be reappropriated in future projects requiring participatory or deliberative approaches.

Advocating for an important equality, diversity, and inclusion issue: I was able to participate in CityMaaS’ broad stated agenda of improving ‘…the way the disabled community consumes accessibility data and services’ by contributing to raising corporate awareness of the challenges of web-accessibility, digital mapping and real-world navigation, and alignment to global web-accessibility standards [3]. As participatory methods emphasise the importance of all stakeholders working toward a shared objective, which in this case was ‘journeys to digital inclusion’, I felt this enabled constructive interactions that did not conflict with my ability to critically reflect on strengths and weaknesses in either the participant’s responses, or CityMaaS’ offering more broadly.

References

[1]        T. Winkler and S. Spiekermann, “Twenty years of value sensitive design: a review of methodological practices in VSD projects,” Ethics Inf Technol, vol. 23, no. 1, 2021, doi: 10.1007/s10676-018-9476-2.

[2]        T. Nilsson, J. E. Fischer, A. Crabtree, M. Goulden, J. Spence, and E. Costanza, “Visions, Values, and Videos: Revisiting Envisionings in Service of UbiComp Design for the Home,” 2020, doi: 10.1145/3357236.3395476.

[3]        CityMaaS, “Homepage,” https://www.citymaas.io/, Jun. 03, 2022.

 

 

 

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Call for Participants – Biometric Recognition of the Hand in Uncontrolled Images

post by Gabrielle Hornshaw (2021 cohort)

Hello

My name is Gabrielle and I am a second-year PhD candidate at the Horizon Centre for Doctoral Training (CDT). I am looking for participants to contribute data to a new hand image dataset and earn a £10 Amazon voucher in return (first 50 respondents).

We are aiming to collect a wide variety of images of each participant’s hands, under different lighting conditions and performing different poses and gestures. To do this, we will be asking for 8 short videos (like these: https://youtu.be/Z5OPjIjQwi4) to be self-recorded and uploaded by participants. These recordings should take no more than 5 minutes in total but be done across a period of at least 1 day.

This data will be used to develop techniques for hand matching (deciding whether two hands are the same or not) with the aim to improve investigative processes in cases of abuse with perpetrator-recorded images, where hands can feature more often than faces. Automation of this analysis can improve the efficiency of investigations and reduce some of the human burden of viewing harmful material.

For more information on the project please see the information sheet below. For more detailed recording instructions, and to confirm your participation and submit your videos, please visit this survey:

https://forms.office.com/e/TnRStTT97z

If you do not have a University of Nottingham email address to complete the survey and would still like to participate, please email me directly at gabrielle.hornshaw@nottingham.ac.uk.

Please feel free to contact me with any further questions.

Best regards,
Gabrielle Hornshaw

Information Sheet

Posted on

Reflecting on my placement with RSSB

post by Sam Smith (2021 cohort)

In Autumn 2022, I spent 3 months completing a placement in the Human Factors team at RSSB (Rail Safety and Standards Board). The placement was remote, but I was invited to come and see the office before I started. The office is in London and has a very modern but welcoming atmosphere. I enjoyed a morning being shown around the office and meeting new colleagues, followed by a couple of briefings to chat about the project and what my contributions would be.

The project that I was working on was looking at the Safety Management Intelligence System (SMIS). SMIS is a system that is designed to be a central data hub for reporting safety incidents within the rail industry. Specifically, we were interested in encouraging Train Operating Companies (TOCs) to engage more actively with SMIS. Initially, given my background in mathematics, I was tasked with delving into the data and uncovering insights that would encourage TOCs to invest more time into inputting all their incidents.

Despite finding some surface-level insights, it was clear that without some guidance from the TOCs themselves, I was searching blindly through the data. I made the decision that it was crucial to speak to TOCs to understand why they weren’t already engaging with SMIS and what their expectations were. I communicated with my team at RSSB, and we set up some meetings with TOCs. Over the next period, I conducted a series of interviews which were useful in understanding the perspectives of the different companies.

Each week my team and I had a catch-up meeting to discuss the work we had done and plan the next steps. It was useful to discuss the findings of my meetings and what other parts of the team had found so that I could improve for the upcoming interviews. Over a period of a month or so, I completed several meetings and made copious notes about the different perspectives. I then collated my findings and created a final presentation I shared with my team at RSSB.

During my placement, I used several different skills that will be useful during my PhD. I conducted some basic data analysis before identifying a fundamental problem with the task briefing. After identifying the problem, I communicated it with my team and proposed a solution that was feasible and sensible. In order to do this, I had to present the problem in a digestible and comprehensive way. I found that this was a daunting task to start with because I hadn’t been involved in an industry project before and I was unsure whether it was my place to suggest changes. Of course, the team was hugely receptive to my suggestions and that gave me confidence moving forward.

Another challenge was conducting interviews with industry professionals because it was my first time doing anything like that. Judging the tone of the interviews was difficult but I improved over the course of the placement. In the end, I felt more confident communicating with stakeholders, which is something that will be immensely helpful in my PhD. Something that I learned during this process was that each stakeholder had very contrasting views, despite their similar standpoint, so it is important to not assume any perspectives.

Overall, the placement was incredibly useful for me to see how industry works and to be exposed to new challenges. While the content of the work wasn’t directly comparable to my PhD, the skills I developed and the challenges I faced will help me complete the PhD. I am very grateful to the Human Factors team at RSSB for their support and guidance throughout the PhD. I would recommend anyone to get involved in projects where they have a good amount of creative license and responsibility as it can really help develop you as a researcher.