Lost in translation? How language defines trust in AI tools

Last month, the Department for Science, Innovation and Technology released the report Assuring a Responsible Future for AI. This important piece of work highlights the challenge of businesses and public sector organisations adopting AI tools without sufficient safeguards in place. For our latest blog, our Research & Insights Director, Ed Houghton looks at the importance of choosing the right words for assurance, and takes an in-depth look at some of the trust issues our research discovered.

Humans are hard-wired to consider trust, whether we’re buying a new car, meeting a stranger, or even understanding when to cross the street. We’re constantly assessing the world around us and deciding whether or not, through a decision we or someone else makes, we’re likely to benefit or come to harm. The problem is that humans aren’t always great at knowing what should and shouldn’t be trusted.

Trust, or more specifically trustworthiness, is a central element in the field of AI acceptance.

Trustworthiness, defined as displaying the characteristics that demonstrate you can be trusted, is gold dust to those looking to make use of AI in their tools and services. Tech designers go out of their way to make sure you trust their tools, because without trust, you’re very unlikely to come back. UX designers might choose voices that convey warmth, or use colloquialisms and local language to help ease interactions and build rapport. In text-based interactions too there’s a need for trust – some tools might use emojis to appear more authentic or friendly, others might seek to reassure you by providing references for the answer it generated. These are all methods to help you trust what AI is doing.

The issue, however, is that trust in AI is currently being fostered by the tools seeking your engagement. This obvious conflict here means that people using AI, whether employees or consumers, may be placing their trust in a risky product or tool – and in an emerging market that is evolving at pace, that creates real risk.

Understanding the risk AI presents, and the language used by business to assure products, was the topic of our most recent study for government. The DG Cities team undertook research for the Responsible Technology Adoption Unit and Department for Science, Innovation and Technology exploring AI trust from the perspective of those buying and using new products in the field today to understand what AI assurance means to them – and to understand their needs in order to assure new tools coming to the market. Our approach explored how AI tools are currently understood, and key to people’s understanding was the concept of fairness.

Understanding fairness of AI tools

For AI tools to be used safely, there’s a need to ensure their training is based on real world data that represents the reality in which the tool is likely to operate, but which also protects it from making decisions that are biased or limit outcomes. We found an example of the reality of “good bias” vs “bad bias” when exploring the use of AI in recruitment technology – here, bias from both objective and subjective measures is considered to drive a hiring decision – but for those using the tool, there is a need to ensure there is no bias related to protected characteristics. This challenge is an area where fairness comes to the fore:

“Fairness is the key one. And that intersects with unwanted bias. And the reason I try and say ‘unwanted bias’ is that you naturally need some (bias). Any AI tool or any kind of decision making tool needs some kind of bias, otherwise it doesn't produce anything. And so, I think front and centre is how does it work, does it work in the same way for all users?”

- private sector procurer

You can imagine a similar scenario playing out in a local authority setting in which resident information is used to asses housing allocation, or drive retrofit and improvement works to social housing stock. Here, bias must be understood to ensure the tool is delivering value to all groups – but with the introduction of certain criteria, an equitable approach may be created, whereby certain characteristics (e.g. low income, disabilities) are weighted differently. Fairness here is critical – and is a major reason why assurance processes, including bias assessments, and impact evaluations, are key practices for local authorities to build their capabilities in.

Making AI assurance more accessible

UK public sector bodies and businesses of all sizes are going to need to ensure the AI tools they are using are fit for purpose – without steps in place to make the checks needed, there is real risk of AI being used incorrectly and potentially creating harm.

Defining terms is important for several reasons, not least because without clarity and consistency, it is likely that those involved in the development, implementation, and regulation of AI technologies may find themselves speaking at cross purposes. Clear terms, used in agreed ways, help prevent misunderstandings and misinterpretations that could lead to errors or inefficiencies.

Well-defined terminology is also crucial for establishing ethical guidelines and legal standards. It allows policymakers to create regulations that address specific aspects of AI, such as privacy, bias, and accountability, ensuring that AI technologies are developed and used responsibly. Terminology related to AI assurance practice must convey requirements for legal standards, but as we’ve found from our engagement with industry for DSIT, this issue of terminology prevents business of all sizes from understanding what they need.

“Is the language of AI assurance clear? I don't know whether it's the language per se, I think there's probably a lack of vocabulary… to me it's a question of ‘what are you assuring? What are you trying to show that you've achieved?’ And that all stems from: ‘what does the public want from the technology, what do they not want, what do regulators expect to see, how much evidence is enough evidence?”

- private sector procurer

Assurance language that is clear and well understood is also a pillar of effective risk management.

By precisely defining terms like "bias," "transparency," and "explainability," businesses and their stakeholders are far more likely to understand potential risks and take action to limit their potential impact. Shared meaning between leaders, teams, suppliers and clients is important if issues with AI are to be tackled in an appropriate way.

Finally, and perhaps most importantly, without clear AI assurance terminology, it’s unlikely that AI technologies are to be widely accepted and trusted. Assurance is one of the key mechanisms through which public bodies and businesses convey the trustworthiness of AI to the public. This is where clear terminology can be most powerful – it helps to demystify complex concepts, making AI more accessible to non-experts and increasing public trust. It’s also important in demonstrating the trustworthiness of brands – not only private sector businesses, but also local government.

Being a trusted source of information

As our research highlights, there’s a lot to be done in business and public sector to share and learn about AI tools and services in reality. At DG Cities, this is the kind of role we’re playing with authorities today to make sense of a complex and changing field. If you’re keen to learn more about what AI tools are in the field, and the types of assurance steps you should take to make better decisions on AI, get in touch.

---

Read the full report, Assuring a Responsible Future for AI.

Welcome Gabriela!

As is customary, we invite our newest team members to say hello and share an introduction to their work at DG Cities, some of their previous experience and how they are finding their first few weeks. We’re delighted to welcome our new Graduate Evaluation & Data Analyst, Gabriela Mihaylova…

After just over a month as a Graduate Evaluation and Data Analyst at DG Cities, I can already say that this is a dynamic environment where the missions and projects are as inspiring as the team behind them.

With a background in BA Geography with Quantitative Methods, I value sustainable urban development and the innovative solutions that can have a positive impact people and businesses, and help them achieve their potential. The team at DG Cities aims to do exactly that by putting people first, with a collaborative approach and by exploring the capabilities of data and technology to create better cities for everyone.

My first few weeks were packed with a variety of engagements, some expected - think introductory meetings and admin - and some very exciting, - like joining an NHS-led session about local connection, meeting the Royal Borough of Greenwich council leader Anthony Okereke, and even getting involved in a rebranding exercise. These experiences showed me the behind the scenes of where and how we bring value to the public sector, organisations and people - and built my excitement for what is to come. 

My academic background centres around GIS (Geographic Information System) mapping, data analysis and visualisation, with a focus on population health and accessibility to city services. My expertise in geocomputation was applied in a specialised quantitative dissertation, developing a framework to measure the effect of proximity to amenities on personal happiness, reliant on concepts like the 15-minute city. 

I’m experienced in tools like R, QGIS and Excel, and had the opportunity to do placements at QStep and Rail Safety and Standards Board (RSSB) where I enhanced my understanding of research applications and real-world data analysis.

I’m now excited to contribute to innovative projects here at DG Cities, by using evaluation-based methods including Theory of Change (ToC) development, data analysis and report writing. I am thrilled to be part of this interdisciplinary and passionate team aiming to address urgent environmental, social and economic challenges!

Understanding how we describe trustworthy, responsible and ethical AI

Less than half (44%) of UK businesses using AI are confident in their ability to demonstrate compliance with government regulations, according to a new report released by the Department for Science, Innovation and Technology. DG Cities contributed to this research, published under the Responsible Technology Adoption Unit, which highlights the challenge of businesses and public sector organisations adopting AI tools without sufficient safeguards in place. For our latest blog, our Research & Insights Director, Ed Houghton, who led the research, explains why the words we use to define emerging tech matter.

Max Gruber / Better Images of AI / Ceci n'est pas une banane / CC-BY 4.0

In a world already full of jargon and buzzwords comes AI to generate its own. Almost overnight (although those in the field will no doubt argue otherwise) business has had to run to keep up, as new terms, such as gen-AI have entered the lexicon. Of course, the day-to-day use of jargon might be irritating, but beneath it lies a critical challenge: within the AI space there is no clear language that people believe, understand and trust.

Nowhere in the AI field is language more important than in the space of AI assurance. Put simply, assurance is the practice of checking something does as it is designed and intended. For businesses using AI, assurance is critical in assessing and validating the way AI uses business or consumer data. In regulated industries like banking, AI assurance is becoming a key requirement of responsible practice.

At DG Cities, we were recently commissioned by DSIT to explore assurance language as part of the UK government’s push to create the UK’s AI assurance ecosystem. Our aim was to engage with UK industry to understand the barriers to using assurance language, and the importance of standardised terms to helping businesses communicate with their customers and stakeholders. We surveyed over 1,000 business leaders and interviewed 30 in greater depth to explore their views.

What we found gives an interesting picture of this emerging space. We found excitement and interest in making use of AI, but concerns over doing the right thing. For example, almost half (44%) didn't feel confident they were meeting assurance requirements from regulation. The reasons for this were numerous, but consistent themes were: lack of clear terms, and lack of UK and international standards.

We also spoke to the public sector about assuring AI when working on public services, including in local government. Here similar issues came up: lack of knowledge in how to assure AI, and terms that were inconsistent. We believe this a barrier to the safe adoption of AI in sectors where it could have major value.

It's great to see our work for DSIT now shared. We think this is a massive opportunity for the UK to lead globally, to create AI assurance businesses and tools that are designed to ensure AI remains safe and trustworthy, and that ensure the public is always protected when AI is used.

---

If you’re interested in finding out more about our work in AI, you can read about how we help local authorities navigate the challenges of ethical and effective use of new tools here, browse our reports here, or get in touch. 

Have you factored independent evaluation into your retrofit funding bid?

As councils and organisations get ready to apply for Wave 3 of the Warm Homes: Social Housing Decarbonisation Fund, it’s useful to examine the critical role of behaviour in both intervention success and M&E design. Our research for the Department for Energy Security & Net Zero has shown that effective retrofitting goes beyond physical upgrades. It requires understanding of the behavioural and socio-economic factors that influence residents’ engagement and satisfaction.

For the first of two blogs, our Behavioural Economist, Leanne Kelly shares her tips to improve retrofit outcomes; by gathering household insights early, tailoring engagement strategies, and designing projects with co-benefits in mind. This kind of robust, behaviour-informed M&E is key to better outcomes, and scaling retrofit efforts much more efficiently across social housing.

As an innovation company owned by a local authority, and with the trials, engagement and monitoring and evaluation (M&E) work we do in communities, we understand the place-based, practical, and behavioural elements to schemes like the Warm Homes: Social Housing Fund, which is open for Wave 3 applications.

Our Complex-to-Decarbonise (CTD) work with UCL for the Department for Energy Security & Net Zero, for example, helped surface and evidence challenges and solutions for retrofit work. It gave a holistic picture of the complex challenge. The output of the work was an identification framework that integrated the physical, locational, occupant demographic, behavioural, and system-level attributes.

The Warm Homes fund has been an important vehicle for social housing retrofit, and laying critical foundations for energy system change – it has also provided the opportunity to demonstrate success and value to the wider sector and to private housing. There are of course challenges to its implementation, which M&E should capture, to reflect back lessons and best practices – and M&E should itself be designed to overcome challenges.

Here, I want to focus on the role of behaviour – in retrofit work, and in M&E design and delivery more generally – and share some of DG Cities’ tips to improve intervention delivery and evaluation in this space.

Behaviour matters

Behavioural attitudes, intentions and changes are critical to decarbonisation at scale. In terms of how aware and informed people and organisations are, how able and motivated they are to participate and respond to interventions, and how lived outcomes change. These outcomes often include subjective wellbeing considerations, like financial stress, place and housing satisfaction.

Behavioural attributes should be understood across a household’s whole user journey of retrofit: the design process, engagement and buy-in, work delivery, and post-work use and maintenance. These stages often require significant care and time and/or cost, whilst the decanting of residents for work and the disruption to their daily lives are critical factors to retrofit uptake and effectiveness. Therefore, understanding and shaping interventions through this user journey and project cycle can help to reduce drop-off, delay and disappointment.

Behaviour is only mentioned once in the DESNZ M&E Framework, with just a few mentions of satisfaction (2) and attitudes (2), with no inclusion of the term wellbeing. Our CTD work also found there were limited datasets for considering socio-economic barriers, impacts, distributional aspects beyond household characteristics and income data, and limited evidence on social and behavioural barriers. Nevertheless, our CTD research raised the need to include social, economic and behavioural attributes as they exacerbate the complexity and challenges to retrofit homes. Our interviews and case studies identified many useful examples.

“Many people don’t understand what it means to them, other people understand it as a cost, other people understand it as a comfort, so it needs a very different communication tool that you need to use to understand the urgency to improve their building... to use different tools depending on the group of people that you need to work with.” (Interviewee)

Low willingness to have one’s own home retrofitted needs to be recognised as a barrier, which has wider elements, both intrinsic (attitudes, knowledge, ability, disruption concern) and extrinsic (incentives, benefits framing) motivation. Ability, or perceived ability, matters too. Vulnerable households, those with health-related issues or potential push-back may or may not be initially known, but they can be identified (other services may know these householders better), empathised with (is home safe, familiar, under their control?), and planned with (why those times or that approach may not work with your family).

Councils can spend a great deal of time and money trying to reach, engage, inform, engage again, and understand a wide range of residents on decarbonisation, and there is a risk that some of these efforts don’t keep households in the programme or provide valuable final outcomes. This has ramifications for further council decarbonisation and place-based ambitions for that neighbourhood. It also matters in understanding and delivering a just transition, with any households being left behind.

Further, there may have been missed opportunities to utilise the retrofit and its engagement to meet other needs of households – opportunities to collaboratively share wider information or invite residents to local health, community or service activities/events - or to support the development of more neighbourhood connection and cohesion – a chance for people to interact positively with their neighbours.

Trying to mitigate risks has been reflected in some of our tips below for enhanced outputs and outcomes. For example, there is quite a gap between the basic M&E KPIs of Number of tenants engaged and signed up to works and Number of properties completed and various risks. These reflect some of what we have learnt through our monitoring and evaluation work.

DG Cities’ top three tips to aid better outcomes through design and delivery:

1. Undertake housing and household information gathering and profiles earlier on, identifying where ability or willingness for programme inclusion may be low and interaction more complex.

   The CTD identification framework can be followed to consider a range of attributes, including physical and behavioural barriers and opportunities, recognising that varying levels of challenges exist across a stock of housing rather than the challenging and non-challenging ones. A range of methods can be used here.

   As well as required in-house surveys, integrating wider service teams’ knowledge and behavioural frameworks like COM-B can be really useful. Build in understanding of resident attitudes, home behaviours and motivations to design and deliver the work, and tailor or disaggregate approaches as needed.

2. Tailor the outreach and engagement design in response to these barriers and enablers.

   A range of routes and methods could be used, considering current communication and community channels, trusted local messengers, and collaborating with more embedded service teams.

3. Design with co-benefits – there may be clear ways for co-benefits to be delivered via the retrofit and energy works, such as street quality, home comfort and others that matter for the specific residents.

   Creating a sense of shared neighbourhood aims and social connection and an individual sense of agency (having areas of choice, even if small, within the programme) have been found to work elsewhere. These may need to be better framed, explored with and presented to residents.

   There may also be an opportunity or need to create a more beneficial offer, raising interest and motivation – could the retrofit journey be combined with other service delivery? Could residents jointly be informed on and access retrofit and other activities? Could the group of residents be brought together earlier, developing a sense of connection and familiarity before the improvement work?

   Here, we have been exploring the concept of local activity matching in neighbourhoods as an efficient delivery model.

Of course, such approaches themselves need to be tested. M&E has a critical role in enabling design and delivery teams to learn what works. There is an important role for pilots here – trying, for example the profiling, tailoring and co-benefits designs above in relation to a wider cohort to assess if they worked better – and, if so, where. Doing so now, and continuing to learn with the monitoring of any different approaches and innovations, can help councils take forward the future scale of retrofit and heating works more efficiently. This is something our DG Cities team love to help with.

---

Stay tuned for part two of Leanne’s blog, which looks at how to design an M&E approach in this context, with some useful tips. You can learn more about our evaluation practice, our experts and read our introductory whitepapers here, or get in touch to discuss how this strand of our work can support your decarbonisation and funding aims.

How can councils meet their housing decarbonisation aims

Every country is working to mitigate the impacts of climate change. While the global direction is guided by COP summits and diplomacy, and national policy might set the budget and priorities, it is down to local government to deliver on targets, whether that’s upgrading housing stock or rolling out EV charging infrastructure. Great work is being done at this local level, but councils face significant barriers to working at pace and scale to realise some of their ambitions. Here, we’re taking a look at some of the main issues, and possible strategies to address them, drawing insights from some of our research and practical experience supporting local authorities in their decarbonisation efforts.

Can we afford it?

The first and most obvious barrier to any initiative is cost. With enormous pressure on budgets, local authorities can face impossible decisions between cuts or investment in different services. In many cases, the capacity to invest in new infrastructure simply isn’t there, despite the recognition that in the long-term, financing renewable tech will deliver benefits. Another issue in terms of financing is the absence of a structured approach to funding at the right scale to tackle decarbonisation.

A 2021 report by the National Audit Office highlighted the extent to which funding shortages were identified as a barrier to achieving carbon reduction targets: “17 local authority areas received £20 million or more each, while 37 received less than £2 million each.” While the situation has evolved since, it is still the case that some councils have been more successful in grant funding than others. Much of the funding is allocated through competition, which naturally favours councils with existing resources. Matched funding is required, and delivery timescales are linked to government budget timelines, rather than what is actually feasible on the ground, and often reward caution rather than ambition and innovation.

Do we have the expertise?

Decarbonisation initiatives can require specialist knowledge and expertise, which may be limited within some councils. Within existing teams, with responsibilities and budgets stretched, the lack of available capacity to plan, implement, and monitor decarbonisation projects can also hinder progress.

“In some areas, officers might have to be placed in jobs that don’t match their expertise because that’s where the funding is now allocated – there’s often a skills challenge that councils have to address, whether through hiring, training or reallocation of resources.”

- Balazs Csuvar, Director of Innovation & Net Zero, DG Cities

How can we predict and invest on the basis of future policy?

Shifting regulatory frameworks and national policies can create uncertainty for councils, making it difficult to develop coherent decarbonisation strategies. Ambiguity surrounding government incentives and targets may have deterred councils from committing to long-term sustainability goals pre-election. Following July’s result, as the new government establishes itself, it’s natural to be cautious of investing in areas where there may be significant policy change.

What if there is resistance locally?

Decarbonisation initiatives can face resistance from various stakeholders, not least residents, businesses, and local interest groups. Concerns about cost implications, disruption, change to the appearance of a place, as well as any perceived inconveniences may hinder community support for sustainability measures. Some policies can be particularly divisive, such as LTNs and restrictions around parking.

---

How do we start to break down some of these barriers to meeting national and local targets?

First, by tackling the financial argument and helping councils identify, meet the criteria and apply for funding.

There are grants, private partnerships, and sustainable finance mechanisms to support decarbonisation efforts. Underpinning all these investment models is the principle that prioritising low-carbon infrastructure and energy-efficient technologies can yield long-term cost savings and environmental benefits. Our data-led approach can often help councils evidence this.

The government’s Warm Homes Social Housing Funding is an important source of financing for housing retrofit. The third and latest wave opened for applications at the end of September and will close on 25 November. A key step in submitting is identifying priorities, and DG Cities has developed a tool to support this – find out more about our ‘home-by-home’ plan here.

Second, by upskilling and building capacity within councils.

There’s clearly a need for investment in training and knowledge-sharing initiatives to build internal capacity for decarbonisation, potentially in collaboration with academic institutions, industry experts, and peer councils. This is a long-term priority. However, we understand the realities of council budgets and know that this isn’t always feasible – that’s why we exist. DG Cities was set up as an independent company by the Royal Borough of Greenwich to advance innovation in the area, but also to act as a strategic innovation partner for other councils to benefit from this expertise and experience of Greenwich as a testbed.

Third, we need continuity and stability in policy-making from government.

The public sector needs supportive regulatory frameworks that incentivise decarbonisation. Proactive participation in policy consultations and lobbying efforts can influence national decision-making processes and ensure alignment with local priorities. Projects must be coordinated beyond a local level – as our government-funded work to support the rollout of electric vehicle charging in rural areas showed, there is no use putting infrastructure where there is no grid capacity to support it. This sentiment was echoed in the LGA’s report, Green heat: Achieving heat and buildings decarbonisation by 2050, which highlighted the gap between national policy and local delivery for heating, as currently, there is “no mechanism and limited ability for councils to influence or shape investments in developing the electricity grid infrastructure in line with local plans for decarbonising heat.”

Finally, bring the public into the process.

This is vital. Effective communication and engagement are essential in building support for even the most contentious decarbonisation initiatives – ideally, turning apprehension into advocacy. Councils need to ensure transparent and inclusive approaches, involving residents and businesses in decision-making and addressing any concerns through meaningful dialogue and education. Our work in public engagement around new technologies has demonstrated the value of engagement in building trust and shifting attitudes – and meaningful is the key here, as the process must be open, inclusive and impactful, and not guided by pre-determined outcomes.

If the UK is to achieve its decarbonisation targets, national and local government must work together and in partnership with communities. Where internal capacity and skills are an issue, councils should look to bring in staff with relevant expertise and knowledge, or selectively look to external consultancies for support. We say selectively, as the aim should be to create in-house expertise and build capacity. By identifying and addressing barriers such as financial constraints, lack of capacity and expertise, regulatory uncertainty, and stakeholder resistance, local councils can drive the transition towards a more sustainable, equitable and resilient future.

---

Read more about our home-by-home plan and some of our work delivering council electrification strategies - and get in touch, we’d be happy to discuss our experience working with local authorities on strategies to meet decarbonisation targets across housing and transport.

Increasing cycling rates: from the Dutch seaside to Stevenage, the value of examining what works in practice

Our Head of Communications, Sarah Simpkin spent her holidays enjoying the impressive cycling infrastructure of the Netherlands. For our latest blog, she takes the opportunity to talk about it endlessly… sorry, to take a look at how Dutch best practice is being shared with other cities, the value of working with specific groups to encourage uptake, evaluating what works (or not) and why, and some great feedback from DG Cities recent work in Stevenage.

Knoopunt ‘point to point’ cycle route sign in Haarlem, the Netherlands

One of the first things I did when I got back from our summer holiday was read the Dutch Cycling Embassy’s best practice guidelines. Not a sentence I might have expected to write.

We had been cycling around the Netherlands. Everyone knows the country is a leader when it comes to cycling’s modal share (in some areas, more than half of all journeys are made by bike). Still, we were so taken by the comfort of universal cycle lanes, the network of signposted ‘fietsknooppunten’ (point-to-point number sequences that our 9-year-old was able to remember and direct us between), the easy connections between towns and cities that didn’t involve the mortal danger of joining an A-road or our national speed limit on narrow country lanes; then the underground bike parks, drop kerbs, and oh my, those magical Dutch roundabouts... Equally wonderful was seeing the range of people (and pets) using them, from weekend racers to cargo carriers, and the freedom designing for wheels also gave mobility scooter users and parents with pushchairs. 

The Dutch Cycling Embassy’s best practice guide is a great example of a document of its type: clear, engaging and well sourced, with so many potential lessons for spending the money the UK government has promised to invest in safe infrastructure for active travel. It demonstrates the usefulness of knowledge sharing initiatives, like Sharing Cities, which London and Greenwich, with DG Cities, were part of – an EU-funded platform for international collaboration to help commercialise, advance and deliver new smart city solutions. A chance to learn from Milan’s expertise in retrofit, for instance, or the roll out of e-bikes on the hills of Lisbon.

Cycling in London

It would be easy to come back from the Netherlands to anywhere feeling as deflated a flat tyre on a touring bike, but it’s important to remember that they are decades ahead in terms of policy and investment. While London hasn’t gone fully Dutch quite yet, things have improved significantly since I started tentatively commuting along Brixton’s bus lanes more than twenty years ago.

For a start, there are many more people out on bikes – 24% of Londoners say they have ridden a bike in the past year – supported by positive changes implemented by some councils, as well as major improvements driven by walking and cycling commissioner Will Norman and his team. We have more segregated routes, more choice, there are many more cyclists, all wonderful to see, but we’re still far from normalising the bike as a viable alternative for everyone – and clearly it has as much to do with culture and perception as infrastructure.

It's also about having access to a bike. It’s a catch-22 that many people who might be open to taking more journeys by bike won’t do so without safe infrastructure, but safe infrastructure won’t always be prioritised unless more people demand it. How might policy induce demand? In London, this kind of stimulation is helped by hire cycles and e-bike services – Lime bikes’ survey claims their usage has increased by more than 10% per month, so demand is increasing. Still, hiring any bike can be expensive for some longer journeys. When it comes to ownership, there are Ride to Work schemes and great initiatives aimed at specific groups, such as bike donation schemes for refugees, but I’m interested to see how else can we address affordability – to give people the means as well as the routes.

Understanding what works

Alongside innovation in urban design, policy and public engagement, there’s a need to commit to diagnosis and evaluation; to look at what works in terms of space, facilities and behaviours, and be prepared to adjust for change where necessary. Earlier this year, DG Cities was commissioned by Hertfordshire County Council and Stevenage Borough Council to do just that with a project looking at cycling uptake in the town.

Ed, Emily and Leanne of DG Cities in Stevenage

Stevenage, as a new town, is built to accommodate cycling and they have invested in paths and infrastructure, but rates remain stubbornly low, particularly across some demographics. This focus on increasing uptake among particular groups was one of the most interesting and useful aspects of the project – its focus was families with children under 18, staff at the Lister Hospital, and students attending North Hertfordshire College.

This kind of targeted strategy has benefits when it comes to supporting any behaviour change initiative, as Ed, our Director of Insights, who led the project explains:

“The right way to do behaviour change is to focus on cohorts, rather than any generic approach. This makes it much more effective. Here, we were able to look at behaviours within the underrepresented groups where there is an opportunity to make a difference.”

Following an intensive phase of evidence analysis and discussion, the team spent time out and about in Stevenage, talking to all kinds of road users, hospital staff, students and residents, to understand the unique circumstances of the place and people’s barriers to cycling. From this came a co-design process, to explore potential solutions and put together a practical intervention plan, which included some great ideas to trial that respond directly to people’s concerns. Bicycles libraries for people to hire rather than buy, for example, an inventive ‘cycle miles’ scheme, refresher opportunities for those at different life stages, and measures to support and grow local networks and create events centred around cycling. Great ideas that came through a more iterative process of continual improvement, and really highlighted the importance of evaluation in any programme with behaviour change as its aim.

And it’s not just us saying that. The DG Cities team was delighted to receive some very positive feedback from our client, who commented on how Ed, Leanne and Emily “demonstrated a thorough understanding of our objectives and tailored their approach to meet our specific needs. They employed rigorous behavioural science methodologies and delivered comprehensive insights that have been invaluable to our understanding of barriers and facilitators to cycling behaviours in the target area and target demographics.” They also found the final report clear, useful and told us it “provided actionable recommendations that we are confident will drive positive change to our cycling offer in Hertfordshire.” 

Part of the ease and enjoyment of cycling in the Netherlands is the lack of friction between different road users. To work towards this, it’s vital to fully understand people’s concerns and work collaboratively to find solutions – not everyone can or would want to hop on a bike, and not all vulnerabilities are obvious. So it’s great to see a project like this give the DG Cities team the chance to examine the data, talk to people and look at what really works, why and for whom – and bringing fresh ideas to the challenge of increasing cycling and walking rates in different areas.

To find out more about our evaluation service, read our introduction to assessing impact or get in touch!

Computer says yes: can AI help to streamline a council’s complaints process? Imperial College London students explore the challenge.

DG Cities has collaborated with Imperial College London for several years, from forming industry-academic partnerships for research projects to sharing real-world case studies for student learning. For the latest of these, we have been working with students on a key issue facing councils - the complaints process - and looking at how AI might help to streamline responses. For the next in his series on AI in local government, Graduate Consultant (and Imperial MEng alumnus), Nima Karshenas explains…

AI-generated image of customer service terminal

Capacity and deficit in a skilled workforce is often quoted as one of the main reasons for the shortfall in the ability of some councils to drive and implement innovation. DG Cities has been helping to address this by forging a unique collaboration with the EEE (Electrical and Electronic Engineering) course at Imperial College London, drawing on some of the very brightest minds in the country. This has been a resounding success over the years, and this year we tasked our students with reimagining the complaints processing system within councils, harnessing AI tools to ensure the robust, informative, and consistent collection and presentation of complaints data. 

We believe that every organisation providing social housing in the UK can benefit from this use case. The use of new technologies will improve the quality of service delivery, tenant satisfaction and reduce costs. Based on our analysis, this use case can be delivered with the current readiness of AI techniques.

Following two months of hard work, the students have provided us with an impressive proof-of-concept, leaving us with clear next steps to think about how to turn these systems into a reality. The potential is clear, and these are the beginnings of a long road towards making our public services smarter and more efficient; providing more value to the taxpayer, and most importantly freeing up the time and resources to allow a more proactive approach to governance. 

What were the outputs?

The students made use of a large language model (LLM) to process and categorise complaints, providing summaries, attributing them to their relevant department, and assigning them an urgency level to facilitate quicker resolutions. 

Dynamic Dashboard: The dashboard offers real-time analytics, enabling council members to identify trends and address issues proactively. The tile system allows for customisable insights based on the council’s priorities.

Interactive Map Interface: Complaints are displayed on an interactive map with markers that provide summary popups. This feature allows for easy visualisation of complaint locations and the status of each. 

Automated Data Handling: Complaints submitted via online forms are automatically processed and stored in a secure, online database. The integration of AI ensures that each complaint is categorised and summarised, reducing manual workload. 

Importantly, the data collected by the system can feed into more robust and detailed data analysis systems that can pool in other sources of data (IoT environment sensors, energy monitors, cameras etc.) enabling the council to develop evidence-informed response strategies to complaints, ensuring a prioritisation that matches internal policy and fairness goals. 

Complaints portal - dashboard view (example data synthesised)

Complaints portal - map view (data and locations synthesised)

How does this system help?

Improved efficiency: The new system has the potential to significantly reduce the time required to handle complaints. By automating data entry and providing actionable insights through AI, the council can address issues more promptly. This shift from manual to automated processes helps eliminate backlogs and ensures that resident concerns are addressed in a timely manner.

Enhanced decision-making: The AI-powered insights and real-time analytics provided by the dashboard enable council members to make more informed decisions. Identifying patterns and trends early allows for proactive measures, potentially preventing issues from escalating and improving overall community satisfaction. The map-level UI enables the council to build a location-aware understanding of the issues faced by residents, allowing them to take appropriate engagement measures and problem resolution strategies. This ultimately means for more effective public services.

Greater resident satisfaction: With the ability to address complaints more efficiently, resident satisfaction is expected to improve. The system not only speeds up response times but also ensures that residents are kept informed through automated updates when their complaints are being addressed. This crucially brings the council closer to the community and ensures everyone can feel heard. Such a system has the potential to be extended to resident engagement in different contexts, such as digital inclusion.

Lower costs: Assuming an average of 50 daily complaints, the students have estimated the cost of using this model amounts to just around £4 per year. It’s important to note that even if this number is higher, model costs scale linearly.

Building organisational knowledge: Perhaps most crucially, developing  a system like this is hugely impactful to organisational knowledge and memory. Building out the data pipelines, codebases and organisational processes to maintain such a system will be crucial to massively accelerating the timelines of future AI projects within the council. Fundamentally, this is a resident engagement project, it has constructed an automatic means of collecting and sorting communications from residents. As such, it can be very easily adapted to other applications grounded in resident communications and engagement. Furthermore, building out these digital systems offers automated and robust collection of clean data (complete, correct and error-free), which will be crucial moving into the future. 

Next Steps

Address reliability of AI outputs: One of the primary barriers to making the system production-ready is ensuring the reliability of the AI-generated summaries and urgency levels. As these outputs directly impact how complaints are prioritised and addressed, they must be accurate and consistent. More extensive testing is required to validate the AI’s performance under real-world conditions. If performance is deemed insufficient, we must look towards a more sophisticated model, leading me onto my next point…

Fine-tune with council data:  The current model leverages general-purpose LLMs with Few-Shot Learning and Prompt Engineering to categorise, summarise and label (urgency level) complaints. This means that there is an inherent reliance on the general purpose data that is not visible to the council. Due to a lack of a clean available dataset, students had to resort to AI generated complaints to test their system, this needs to be addressed for obvious reasons. The council should look to build their own database of complaints categorisation, labelling and summarisation, such that the LLMs can be fine-tuned to match desired outcomes, and ultimately lead to more reliable and explainable behaviour from the AI model.

Scale and test: The system needs to be tested with the actual volume of complaints that the council receives to ensure it can handle the load effectively. This step is crucial for identifying any potential bottlenecks or performance issues. Can the system be effectively scaled to meet every council’s needs and prevent individual developmet?

Enhance features & integrate with other data sources: The students have identified some additional features that can be developed in the future to enhance the product, such as an expanded dashboard with more customisable tiles, a task-tracking login system for better complaint management, and automated updates for residents. Furthermore, there is an opportunity to integrate other databases such as ward boundaries, relevant stakeholders to location and type of issue. This will allow for even more sophisticated features, for example, if there are numerous complaints from a particular area and issue type relevant to a council member then they can be automatically and be able to respond immediately. This can be especially powerful in the case of disaster.

Implement data security: Implement advanced data encryption methods to enhance the security of resident data, ensuring compliance with data protection regulations.

Look at integration with council workflows: Ensure that the system integrates seamlessly with the existing workflows of the council. This involves training council staff to use the new system effectively and making any necessary adjustments based on their feedback.

Increase cost effectiveness: Work with the council to assess the affordability of implementing the system on a larger, and production scale. This includes exploring funding opportunities, potential collaborations with the private sector.

---

The students said…

Mathew Stevenson:

I thoroughly enjoyed working on this project for DG Cities - it was a new experience for me, thinking about how technology could help local government. My role in the project was building the user interface, and this gave me the opportunity to explore how best to present the information to council, which added an additional challenge beyond the technical challenge of building a web app; trying to build a clear interface that would be useful to all council members, regardless of previous experience with technology, was a challenge to balance with providing plenty of information – but a challenge I found very interesting, and I am happy with our solution!

I hope the web app we developed can help as a proof of concept for the council, broadly showing that technology can help make managing complaints easier and more automated! Beyond this, I particularly hope our solution highlights three key things:

(1) Getting automatic insights into the data (quantitatively via the dashboard and visually via the map) could be very helpful in identifying both problem areas, as well as areas where solutions are succeeding; action can be taken and lessons learned from this, much quicker than trying to spot these patterns manually from a spreadsheet.

(2) AI doesn’t have to be made the ‘front and centre’ feature of a tool when it doesn't need to be – you can leverage some great utility from it, as I hope we have, but it needn’t be shoehorned in everywhere.

(3) These solutions can be simple and flexible; our dashboard tile system makes it very easy for a client council to request specific insights, and these would be very easy to add in! This customisability means the council could get even deeper and more specific insights as they desire them, which is useful again for identifying problems earlier, which in turn means dealing with them quicker and happier residents.

The primary barrier to making our system production ready is the reliability of the AI summary and urgency; because this could have a real impact on people's lives and the responsiveness to their concerns, it needs to be reliable, consistent and accurate. It needs further in depth testing, which we didn’t have the time to do – however the performance from our small-scale subjective tests is promising. In the meantime, to help with this problem of reliability, we made sure to make the full original complaint easily accessible from the summary popup, so council members could still cross-reference with the original complaint.

Junyu Meng:

I thoroughly enjoyed working with DG Cities on this project and seeing our vision come to life. I mainly worked on the database in the backend, making sure all the relevant information is stored correctly to allow for our desired functionalities. Clearly displayed complaints, actionable insights and resident satisfaction were our top priority and I am pleased to see that evident in our end-to-end solution. Councils will no longer have to suffer from large backlogs caused by the current manual handling process, as efficiency would be massively improved. Resident issues can thus be addressed more timely, amending resident satisfaction.

Our proposed solution still requires a few more steps before it would be ready for production, including testing and ensuring the system functions well under the actual amount of complaint data that the council receives. However, we believe that both councils and residents would greatly benefit from a smarter complaint management system, should councils deem it affordable enough to implement it into their workflow.

---

A huge thank you to the team at Imperial - it was an impressive piece of work, with great potential benefits. Thanks to Bhavya Sharma, Matthew Stevenson, Junyu Meng, Ben Marconi, Alex Dhayaa and Sasha Afanasyeva.

We at DG Cities are working with councils on the many potential useful and ethical applications of AI and we’re committed to carrying this momentum forward into integration planning and initial testing and trials, so feel free to reach out if you are keen to collaborate or discuss further.

AI: how can councils put it to work?

Beyond the hype, how can AI really help councils day-to-day? For example, how can users write more effective prompts, or incorporate new tools in existing processes? For our latest blog, and the first in a series, our Graduate Consultant and AI expert, Nima Karshenas gives a practical guide to some of the ways local government can use these new systems to improve efficiency, streamline tasks and turn them into helpful tools.

AI-generated image showing a woman at a desktop computer wearing headphones

With the unprecedented growth of AI (artificial intelligence) and LLM (large language model) industries, unlocked by advances in hardware, we are increasingly seeing these tools incorporated into different aspects of our lives. The buzz around the potential of AI and the amount of information out there can be overwhelming – particularly when new services suggest it can be essentially ‘thrown’ at tasks to instantly transform and improve existing processes. However, as with all previous transformative technologies, it takes time, due diligence and a fundamental understanding of the technology to see beyond the haze of extreme narratives.

Here at DG Cities, we will be taking a closer look in the coming months at how AI can be used in specific contexts to transform processes in local authorities, ensuring local government can deliver its services more robustly and efficiently in the face of immense resource pressures. But we want it to be as useful as possible. So before we dive into future plans, this blog will explore how LLMs such as ChatGPT and Claude 3.5 can be immediately incorporated into individuals’ workflows, with a particular focus on tasks undertaken at the council.

How do LLMs work and where should we trust them?

At their core, and especially in earlier iterations like GPT 3.5, which many people still use after exceeding their GPT-4o daily limit, LLMs are master imitators. They regurgitate text in the same manner as the data on which they have been trained. These datasets comprise a vast portion of the internet, which LLMs first learn to imitate and are then fine-tuned to answer both general and task-specific questions. 

Despite their immense power, LLMs are not reasoners. They do not follow a strict model or process to ensure the accuracy of information. This means that they can suffer from what is referred to in the industry as ‘hallucinations’, where quotes and figures are made up, and have no basis in any kind of official source. Furthermore, being frozen to the data on which they are trained means they often do not use the most up-to-date information. 

Although LLMs are beginning to incorporate more sophisticated ‘helper’ models that utilise external tools, such as documents, web browsing, and calculators to support LLM responses, reduce hallucinatory behaviour, and provide the latest information, accuracy is still not guaranteed. Therefore, human oversight is essential, and LLMs should be seen as the starting point, not the final step, of any task they are used for.

Where are LLMs most useful for councils?

Considering all this, which specific tasks do we see current LLMs having the most positive impact on everyday work?

• Research: LLM web search tools such as Perplexity.ai serve as an excellent starting point for research. They scan the internet and provide sources for statements, but still sometimes suffer from hallucinations. To truly understand a topic, use the information as a starting point and delve deeper by conducting your own searches or asking Perplexity more specific questions – and always remember to verify information that you have drawn.

• Translation: DeepL is a state-of-the-art translation tool that can be particularly useful for understanding research in other languages, corresponding with foreign stakeholders, or reducing the effort required by council employees for whom English is a second language.

• Text summarisation: This feature helps you understand long documents by extracting key information. However, hallucinations still apply. If you are not specific about the information you want to extract, key segments might be missed, and the likelihood of hallucinations increases. Use it to get a high-level understanding of a document, not a final comprehension. If the understanding is critical, further checks will still be necessary.

• Create slide decks from reports: LLMs can help set up a skeleton of a slide deck by taking information from a document. This saves significant time in the initial stages of collecting key information and structuring it.

• Writing Support: LLMs can help rewrite text to match a certain tone or target audience, useful for emails, blogs, and reports. Let LLMs be the cure for writer’s block, but do not rely on them for the final version. If everyone used LLMs to write, text would lose personality and become monotonous, and would not provide or at least imply the absence of a bespoke response that service users expect. Keep things interesting by incorporating your personal touch!

• Data Analysis: With the sheer volume, complexity and variety of data that flows through a council, it has been previously arduous to find the answers to questions we have of our own data. With LLMs, data analysis becomes more intuitive and accessible. By simply asking questions in plain English, users can quickly retrieve key insights from their datasets in an instant. These insights can then be visualised through graphs and charts, helping provide our decision makers with a complete, evidence-informed picture of their area of interest.

There are also benefits more specific to a local authority’s IT and Data Analysis departments:

• Unlocking the power of programming: LLMs write and run code based on natural language prompts, making it easier to develop and test applications that can automate and streamline council processes. Through description of a task, LLMs such as ChatGPT can instantly provide code to tackle the problem. This allows users, even with limited programming knowledge, to develop and test applications rapidly, and to eliminate repetitive and routine coding tasks, freeing up time for true innovation. 

• Data Cleaning & Preparation: LLMs, including ChatGPT, can automate data cleaning tasks, such as joining datasets, fixing incomplete data, removing duplicates, and adding new information. This ensures the data used in analysis is accurate and reliable. By improving data quality, we open up the possibility of more sophisticated tools to come in and make use of that data in the future, easing the transition to smarter council communication and decision-making.

Guide: how to write better prompts

Hold your LLM’s hands! The key to maintaining robustness and accuracy in LLMs is maximising the guidance provided in prompts. Chain of Thought is an effective technique for maximising guidance, and ensuring you are getting the quality of results you are looking for.

Step 1: Define the Objective Clearly state what you want the LLM to achieve. This sets the context for the prompt and helps the model understand your end goal.

Step 2: Break Down the Task Break the task into smaller, more manageable steps. This approach makes sure the model can follow the logical progression of the task.

Step 3: Provide Context and Examples: Give the LLM context and examples relevant to the task. This helps the model understand how to handle each step.

Remember to use clear and specific language. Craft prompts using precise language to minimise ambiguity. 

Tips for teams using LLMs

Create a repository for prompts for commonly-used tasks: Having a well-organised repository of effective prompts for different tasks can save time and ensure consistency in the output. Prompts are hard to get right off the bat, so having a collaborative repository enables teams to iterate, and improve their prompts to suit their desired team outputs over time.

And finally…

While LLMs offer incredible capabilities that can transform how local authorities operate, it is crucial to use them wisely. They should be seen as powerful tools that augment our efforts, not replace them. With careful application, ethical use and human oversight, LLMs can significantly enhance efficiency and effectiveness in our daily operations.

Local authorities need guidelines, which they may have introduced – people need to proceed with caution when they are using LLM's to draft letters or other forms of communication with, as it isn't infallible and communications need to go through a filter of sorts to ensure managers are comfortable with the language and responses being made. Follow us for more practical and forward-looking guidance on the specific applications, risks and opportunities for AI in local government over the next few months.

---

Nima Karshenas is a Graduate Consultant at DG Cities working across a range of technology-led projects. He has a Masters in Electrical and Electronic Engineering from Imperial College London, with a particular research interest and in-depth technical knowledge of AI, Statistics, and Signal Processing in projects that promote social impact and sustainability.

Predictive policy: how does the government decide which emerging innovations to back?

In the run up to the election, commentary naturally focused on manifesto commitments, and trying to predict which policies would change. Now, different sectors are restating their hopes for the new government – arts bodies lobbying for funding, the UK’s Mayors setting out their own priorities and vision for a closer relationship. The Prime Minister and new cabinet have an endless list of issues across the UK, from prison capacity, economic growth and investment in new infrastructure and house building, to climate change and energy security to tackle. How do they begin to prioritise? We can help…

In a rapidly changing landscape, there can be a similar degree of prediction, analysis and judgement when it comes to technology strategy – which renewables to invest in, how to plan for a population’s needs and lifestyles fifty years from now, or how to put the right guardrails in place to ensure AI is used ethically. Then there’s the interconnectedness of systems and the knock-on effects of different decisions: how to make sure the grid capacity and connectivity is there to support EV charging in a neighbourhood, for instance.

We believe in bold, forward-thinking policy around emerging technologies – as an innovation consultancy, we would say that. But taking a lead in a global tech marketplace is significant in terms of the domestic and foreign agenda; positioning the UK as a global leader in innovation, boosting economic growth, and making sure society benefits from any investment from the public purse. As a company used to acting as the glue between the public and private sector, we’re here to support growth at a local and national scale.

How we support government

Tensions can run high and an election can polarise opinions, but when it comes to predicting future tech, it pays to be agnostic. We are passionate advocates for the value of innovations in improving places and people’s lives, but impartial and rigorous when it comes to deciding which solution works best, led by data, experience and our own in-house independent evaluation service. We maintain strong links with both industry and academia, and work with a network of consortium partners to explore use cases, conduct research and offer advice. In that way, we help to bridge the gap between public and private sector expertise.

This is why independent strategic consultancies like DG Cities play such a valuable role in supporting government at a local as well as a national level. We can help policymakers understand how the public feels about particular tech, whether that’s self-driving cars or heat pumps – and here are five ways why and how we do it. We can help harness the potential of data and community engagement to inform better, quicker decision-making.

1. We help to inform and shape policy

Whether through funded projects as part of a consortium or our independent Research Community, we produce a range of in-depth reports that help government understand the current landscape, define priorities and deployment strategies for particular tech. We can offer insights into global best practice through our work with initiatives such as Sharing Cities, assess the feasibility of proposed initiatives, and help design regulatory frameworks that balance innovation with public interest.

2. We’re a link between public and private sector enterprises

By fostering partnerships between public institutions and private enterprises, we can ground initiatives in reality and help align commercial strategies with public policy goals. This aspect of our work spans a range of fields, from smart city tech to establishing the commercial framework that can allow a council to deliver ultra-fast connectivity to local residents and businesses.

3. We can turn an idea into a workable solution – then test it

We work across the lifecycle of technologies and their deployment, from research into emerging, as yet untested ideas, to the implementation of new services and finally, independent evaluation of their impact. The focus is always on delivering benefits for people and communities, and value for investors, whether that is local government or a service provider. Ensuring that policy ambitions translate into tangible outcomes requires effective project management. In projects such as electrifying a council’s vehicle fleet, for example, we ensure strategies meet deadlines, stay within budget, and achieve desired objectives.

4. We use behavioural innovation to maximise investment in innovation

DG Cities has grown a behavioural science service within our team, which gives us a strategic advantage when it comes to understanding why one solution is accepted over another, or how a behaviour change programme can support new tech to deliver a greater return on investment for a local authority. Ultimately, any innovation that isn’t rooted in need, doesn’t respond to people’s motivations, preferences or engage with the people it is intended to benefit, will likely fail.

5. We bring a focus on ethics and values

Navigating the ethical landscape of emerging technologies is a critical aspect of our work. We put communities first - we help clients develop policy around ethical norms, mitigating the risks associated with issues like data privacy, trust, and AI ethics. Questions we examine might be the decision-making process of a self-driving car, or people’s understanding of bias in AI language models – all themes that come back to people, their relationship with technology and how well any innovation meets human needs and aligns with our shared values.

Already, in these early days, we have seen decisive moves on onshore wind power and North Sea oil. When it comes to technology, the early decisions of the new government will define the future of many emerging solutions – some may be relegated to history, others given greater focus and even a funding boost, depending on priorities. Consultancies like ours play a useful and important role in helping government turn manifestos into action and harness the potential of technology to deliver on their promises – and keep the UK’s tech innovation landscape internationally competitive and aligned with society’s goals.

Read more from Cllr Lolavar on the value of delivery approaches to innovation in her piece in Homes for London published by Concilio & Fabian Members.

The Digital Exclusion Data Gap

For our latest short read on digital inclusion – or exclusion – our Behavioural Scientist, Emily King explains why understanding people’s barriers to accessing online services is vital to delivering inclusive public engagement, whether that is around council services or what happens in their neighbourhood. Highlighting our work with the Royal Borough of Greenwich, she explains the need for councils to get specific: to understand the area-wide picture, but also behaviours at an individual and community level.

Image: Unsplasg/Centre for Ageing Better

To ensure that design is inclusive and human-centred, local government and other public sector organisations need to closely involve the public in shaping services and innovations. At DG Cities, we work on projects doing just that – engaging the public with new innovations, services, and initiatives in their local area, to ensure these are always designed with their needs in mind.

However, in a world that is increasingly moving online, from ordering a prescription to commenting on a planning application, it is important to consider the methods used to engage the public, to ensure that those who do not regularly use the internet are not excluded from having their voices heard.

““There is no one-size-fits-all approach to tackling digital exclusion. It’s a complex issue that demands a clear focus and good data if decision-makers are going to create the positive change that will improve the lives of those most at risk of being left behind.””

— Ed Houghton, Director of Research & Insights, DG Cities

Who won’t see your online survey?

According to Lloyds’ 2023 Digital Consumer Index, 2.1 million people in the UK are offline, and c.4.7 million people cannot connect to WiFi. These individuals are unlikely to answer an online survey or attend a virtual interview, both increasingly common methods for conducting public-facing research since the Covid-19 pandemic and the popularisation of online collaboration tools. Inclusive research design involves applying varied methodologies that can capture the views of people that don’t have the skills or resources to access the internet.

It is also difficult to identify digitally excluded individuals in the first place, for organisations to be aware that they may need to receive information in a non-digital format, or to recruit them to take part in research. Recent work by LOTI has sought to map the extent of digital exclusion across London, which provides useful information about key areas of exclusion and types of digitally excluded groups. However, more work is necessary to understand digital exclusion on a more granular level; to uncover which individuals or areas in local communities may require further support and options for engagement, and what these options might look like for different individuals. 

Tackling digital exclusion with local government

DG Cities is currently working with the Royal Borough of Greenwich to map digital exclusion on two Greenwich estates, to better understand which residents are digitally excluded and why.

There are many different aspects to tackling digital exclusion, from connectivity, access and education to behaviours and respecting personal preferences. Despite being an increasingly connected society, only 27% of UK households can access modern, gigabit-capable broadband. As the rollout of new connectivity technology is fragmented and delivered by multiple providers, there is a risk that some get left behind and can’t take advantage of new opportunities. Early last year saw the launch of Digital Greenwich Connect, a joint venture enabled by DG Cities between the Royal Borough of Greenwich and tech provider, ITS to bring ultrafast broadband to housing estates in the borough. Our research into the behaviours and factors influencing people’s ability to access online services is key to tackling the issue holistically and helping communities make the most of this infrastructure investment.

This work will help Greenwich to understand where there might be gaps in their ability to communicate with residents via online channels. As well as ensuring these residents are receiving adequate support in their daily lives more broadly, the work will help to ensure that digitally excluded residents are not left out of opportunities for engagement and consultation.

---

We know that great initiatives are underway in this area, and we think it is hugely important that more local authorities and organisations work to involve the voices of digitally excluded residents. As a multidisciplinary team, we’re able to look at the technical aspects of the issue - the availability of infrastructure and role of data in identifying groups - as well as behavioural science and engagement. If you would like to talk to us about how we might support you in addressing the issue of digital exclusion in your area, get in touch.

Technological innovation with human values

How do we ensure innovations in transport, for example, or public services, are not only easy to use but also meet real human needs? Can they reflect fundamental societal principles like safety, fairness, and community? Following up on some great discussions at Tech Week in London last week, our Behavioural Scientist, Emily King explores the science behind value-led development at a local as well as a global scale, and how an understanding of these drivers can ensure that innovations like self-driving cars are responsibly designed and deployed.

Ethical Roads workshop at SMLL

One of the last bills to make it through parliament before the election was the UK’s Automated Vehicles Bill – a world-first piece of legislation designed to ensure AI innovations on our roads are safe and deployed responsibly by industry. The AV Act has established the legal framework, but for self-driving to be accepted, legal foundations aren’t enough. New AI-based technologies need sound ethical foundations too.

At DG Cities, we spend a lot of time thinking about how to develop technologies that work for individuals and communities. We use principles and approaches from the fields of human-centred design and behavioural science to understand how to develop and deploy technologies that meet real human needs.

In this respect, self-driving is an interesting area of innovation, as it is one challenging industry to put people first. Our work often centres on the concepts of trust and acceptance of technology in different forms. Our ongoing DeepSafe work, for example, with a commercial and academic consortium in the self-driving industry, seeks to better understand the factors driving acceptance of self-driving vehicles, and what is important to build trust in them.

The technology acceptance model highlights two important factors that drive acceptance, commodity and ease:

• Is it useful? Does the technology help to meet specific needs?

• Is it easy to use?  

Human-centred design focuses largely on the second of these factors – how easy or attractive they are to use – by developing technologies which take as their starting point the user experience. However, what seems to be less at the heart of discussions around human-centred design of technological innovations is their actual usefulness ­– how much they will meet real human needs, and particularly how they align with broader societal values.  

How do we start to bring values into the design of self-driving services?

One way to make the process of ensuring acceptance of technological innovations more seamless would be for those working in technological innovation to root the process in societal values. The human-centred design process begins with empathy for the potential user of a product – this should include an empathetic understanding of what users value the most.

But first, how to define values – essentially, they are our internal standards of what is important. Our values inform our attitudes, beliefs and behaviours. Whilst individuals hold different values, cross-cultural analysis[1] suggests that some types of values are consistent across most individuals and societies.

According to this research, the most strongly held values worldwide include:

• Benevolence: ‘preserving and enhancing the welfare of those with whom one is in frequent personal contact’

• Universalism: ‘understanding, appreciation, tolerance, and protection for the welfare of all people and for nature’

• Self-direction: ‘independent thought and action-choosing, creating, exploring’.

Technological innovations may align with some widely-held values more than others. For example, self-driving vehicles are a solution to improving societal needs such as improved safety on the roads, and increased ease of travel by reducing congestion. These benefits largely come from the greater connectedness of vehicles providing additional information to enable safer driving decisions.

However, the autonomous element of the vehicles also threatens ‘human welfare’, for example by reducing the job security of bus and taxi drivers, or reducing connectedness and community by removing any opportunity for human interaction between passengers taking a taxi journey. Thus, this innovation is not fully aligned with the core values of benevolence and universalism.

Our Ethical Roads project, delivered in collaboration with Reed Mobility, identified several ‘ethical red lines’ for self-driving vehicles, which align with the values of benevolence and universalism, such as ensuring that vehicles improve road safety and that all road users are protected equally. This highlights how values underpin requirements for technologies to be accepted.

For technological innovations to be truly human-centred, it is crucial to develop a coherent sense of which values are most important to communities, and use these as a basis for innovation, to ensure that technologies reflect the true needs and values of society.

What could this look like in practice?

At DG Cities, we look at technological innovation at a range of different scales, from very local issues facing a particular community (e.g. the best method for using sensors to reduce damp and mould on specific estates) through to issues at a national or global scale (e.g. AI assurance).  

On a local community scale: values-centred design could involve identifying the specific priority needs and values communities hold before embarking on a project or introducing a new technological innovation. Research into attitudes and priorities is important here – what is it that matters most to people, and what innovations might be possible to truly improve their lives?

Innovation should also be based on the values of a specific community. Measures such as the Schwartz Value Survey or the Portrait Values Questionnaire could be used in research instruments to identify which values are of greatest importance to individuals and communities, and technological innovations should be aligned with these.

Starting a project with a problem or goal which has been identified or defined by communities helps to bring a sense of ownership to new innovations, and involves communities throughout the whole process, rather than seeking feedback on a pre-determined idea.

At a global level, technological innovation that is truly human-centred should be aligned with the values of the global majority. This means that innovations in AI should not only reflect the values of demographics like tech bros or white wealthy westerners, but those from around the world. According to Schwarz, this means ensuring innovations improve or at the very least do not reduce the overall welfare of the global population and nature; and that they enhance rather than undermine independent thought and creativity.

It is important for innovation to begin with research about people, communities, and their values. For innovations in AI which have a global reach and impact, there is a need for behavioural and design research to ensure innovations reflect the priorities of the rest of the world.

Meanwhile, local organisations should focus on establishing the values and priorities of local communities as a method for identifying where to innovate. Methodologies such as citizens assemblies or deliberative dialogue research, which asks communities across the globe to design their ideal futures, could be vital in taking the next step toward technological design centred on human values.

If you’d like to learn more about our behavioural innovation approach, you can read more here - or get in touch!

---

[1] Schwartz (2012)

The home-by-home plan using data to support decarbonisation

For the Building Centre’s Retrofit exhibition and seminar series, Director of Innovation & Net Zero, Balazs Csuvar took part in a discussion on the role of data in delivering decarbonisation at scale. In it, he introduced DG Cities’ home-by-home plan, designed to help local authorities use and consolidate data to streamline and better target and prioritise buildings. Here, he gives a little more detail on how the plan works and the benefits of a neighbourhood-level approach.

The net zero journey for housing providers is likely one of the most complex technical, organisational and financial challenges many of them have ever faced. Especially as it comes on top of their existing pressures to provide safe and comfortable homes for all their residents, navigating a time of rapid inflation of costs and shrinking budgets.

What net zero really means for councils also presents its own challenge, especially when it comes to defining what a housing provider can influence. For most, it would include direct and indirect emissions (due to heating, hot water, electricity use) and embodied emissions (carbon emitted through the production of materials, their transport and works associated with them). But there are many stages in this process and influences over which the local authority has no control.

There is, however, something we can agree on – there needs to be a plan. DG Cities has been working closely with a London council to develop a process that provides a housing provider with a detailed, practical, actionable plan that considers not only net zero, but also all the other requirements faced by a provider. We call it a home-by-home plan.

The objective of the home-by-home plan is to define which improvement works have to happen for each home, when, and how much they might cost. This is a simple sounding goal, but something that most providers with stocks of tens of thousands of homes do not currently come close to. We believe that part of the solution lies in the effective application and harnessing of data.

Data

Like most projects, putting this plan together starts with data collection. There is a need to develop a deep understanding of the housing stock to help with the prioritisation and selection of work at a home-by-home level.

We focus on using all the existing data held by housing providers. These datasets usually consist of stock condition data, housing repair data, EPC data, rent data, compliance data, tenant satisfaction data, and any other datasets that a provider collects. A level of data cleaning is then required to correct any anomalies and identify which datasets can be used reliably.

Once the data is cleaned, we work to set a number of key work types that will be required to improve the housing stock. This list includes interventions like window replacement, roof repair, or installing insulation. We then use the datasets that describe the stock to determine which properties need which works by establishing a number of rules. An example might be that a property that has had ‘X’ roof leaks over a period, has a poor EPC rating and has a poor stock condition rating, so gets classified as a property due for urgent roof repair. Meanwhile, one where none or only one of these conditions applies would be scheduled for repair across a longer timescale. Provider priorities can be used to adjust the rules using sensitivity analysis.

These rules allow us to prioritise works across the housing stock using a traffic-light system, highlighting the urgency of specific repair works.

Plan

Once priorities for individual works are set, it becomes possible to determine which projects (a project being defined as one or more works at a single property) need to happen at each home. This can be done by combining certain works that provide efficiencies when completed together, minimising both disruption to residents and mobilisation costs for the housing provider. This step allows us to determine year-by-year projects per home.

Further coordination is involved when determining programmes at the scale of a large building or estate. Some works cannot be completed at a home-by-home level (say external insulation of blocks, lateral main replacements, lift upgrade, etc.). In these instances, works to an individual home need to be aligned with other works required at the block level, to create a coordinated programme for the building or overall estate.

Finally, to ensure full alignment with wider council priorities, it is possible to package a number of work programmes together to provide further community benefits. Larger programmes of work delivered in a single neighbourhood can significantly improve the quality of the built environment, therefore raising living standards not only through home improvement, but through additional works in the area as well. Working with local businesses, stakeholders, contractor social value contributions and the communities themselves can give a boost to an area, as a great side-benefit of retrofit programmes.

All of these have to be aligned to available budgets and resource availability, and balanced against current costs spent on repairs and expected rent revenues from tenants. Where the cost benefit analysis becomes really unequal, a consideration can be made to estate regeneration.

Delivery

The last phase of the project is to manage a data flow during delivery and beyond. It’s an iterative, long-term process and it’s essential to have up-to-date data on the progress of retrofit works. This can help to capture progress towards net zero and other goals, keep the analysis live and overall targets on track. If the analysis is built correctly, any changes that happen across the stock (upgrades or deterioration) can be picked up, and changes to the home-by-home plan can then be made.

Monitoring needs to be put in place to oversee any such changes at the portfolio level, but ongoing monitoring can also be considered at a micro level, as part of the upgrade works. IoT sensors can be installed to collect condition information from homes, either to understand damp and mould risk or to assess energy use from shared heating systems. Real-time data can be used to inform the analysis, and work towards replacing more static data gathering, like patchy and outdated stock condition surveys.

Based on new data, emerging priorities or changing financial situations, the home-by-home plan is highly flexible. It can be reprioritised to help to plan short-term contractor mobilisation, medium-term budget requests and long-term strategic decisions related to housing stock.

---

DG Cities is leading the way in supporting housing providers and local authorities through strategies aligned to their specific needs and available datasets. The model described above is inherently flexible and takes into account the realities on the ground, while still providing an approach and methodology that is reliable and can deliver real, practical results. To discuss this approach and our work in more detail, get in touch.