The Daniel Armanios interview: sustainability, innovation, place and technology

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14 minute read
Jo Morrison

Jo Morrison

Director of Digital Innovation & Research

Digital Placemaking

Digital Insights

Aerial view of people walking down a street with long shadows

In order to reach net zero emissions by the mid-century and achieve the UN’s Sustainable Development Goals by 2030, society needs radical new models, mindsets and practices. We need to make wise economic, social and political choices today, so that digital innovations work in the service of us all, tomorrow. And, we must do so at speed. 

With this in mind, I have been speaking with leading figures who work at the intersection of people, place and sustainability, to share their ideas about what can be done to achieve sustainable urban futures. 

Daniel Armanios is BT Professor and Chair of Major Programme Management at Said Business School, and Professorial Fellow at St Anne’s College, University of Oxford.  Daniel’s research integrates civil engineering and organisational sociology to better understand how organisations coordinate to build, manage and maintain infrastructure amidst complexity. His findings inform efforts to advance sustainable development and innovation, while also alleviating systemic and persistent inequalities within such systems.

Read on to learn about the importance of listening to indigenous people’s voices and co-designing with communities, some practical ideas for innovating at speed and with care, and ways to design out inequalities from our towns and cities.

Photos and job titles of Daniel Armanios and Jo Morrison

What motivated you to develop a career that intersects strategic management, organisational management and public sector management?

I’m a pretty non-traditional academic. I publish in organisational sociology journals as well as engineering journals. Now, I work in a business school, but for a long time I was in the College of Engineering at Carnegie Mellon in Pittsburgh, Pennsylvania, USA. I was in the Department of Engineering and Public Policy and focussed on policy issues concerning large scale infrastructure, such as bridge, water, broadband, high voltage transmission, and innovation systems, to name a few.  My approach was to understand the technical issues in our large-scale engineering systems, so I could identify where focus on the system’s social and organisational characteristics may present solutions.

Fundamentally, I’m really fascinated by the ways that different communities think about the large systems they contribute to or even intersect with, and how to translate that thinking, in their own terms, towards developing solutions that enhance productivity and do so more sustainably and inclusively.

Two key moments in my earlier life influenced what I do today and the approaches that I take to figure out complex systems and ways to impact them positively – so that there’s a more even distribution of prosperity across a town or city.

The first was before I started my Master’s Degree. A friend asked me to help teach maths and science education in rural South Africa, on the border with Mozambique. During my first week, my lessons went completely over everyone’s head, however many times I tried to explain and push my ideas. Why? Because I had followed the typical technologist approach when creating the lesson plans – came up with an idea, assumed something about the community, developed something and then started deploying. 

So, despite months of preparation, in week two we completely scrapped everything and said, okay, let’s talk to the students and the local community – let’s better ground ourselves in their worldview and ways of thinking and doing. I started realising they have an amazing intuitive sense of technology without necessarily the apparatus or objects typically used in the Global North.

Once we completely inverted the process and started studying what’s in their local environment and building science and technology lessons through their daily observations, such as the animals around them, and natural hands-on practices, they were flying – comprehending and retaining the lessons much better.

When I started getting this more indigenous Global South perspective, it became very apparent to me that there are ways to be innovative through their deep technical understanding that doesn’t need to be linked to preconceived notions of high-tech apparatuses available in the Global North. You just have to spend time discovering what those technical process are in their language and context, not yours.

This leads to my second key moment. My parents are Christian Egyptian immigrants to the US, so I am first generation American. In Egypt there is a community known as the Zabbaleen, which means literally ‘garbage people’, who make their entire living out of trash. The community is structured around the trash recycling process – some will go pick up the trash, some sort it in their homes  and then sorted items are then turned into usable outputs or back into primary inputs for reuse. There’s even a trash school, where they learn how to process materials such as aluminium, plastics etc. It’s very labour intensive but their recycling rates are better than anywhere in the world; as an example, plastics are recycled at the rate of 85%.

Buckets containing sorted waste for recycling
Photo: Jas Min

To give an example of things they do, they’ll take old medical x-rays, use hydrosulfuric acid to clear them, stretch them, and sell the material as lamination for books. Most of their money is generated by what they sell, so the Zabaleen have a fundamentally different view of waste. A completely inverted view to many of us in the Global North in fact, where waste is seen as something that should be “out of sight out of mind”. The Zabbaleen think waste is gold, to the point that they will pay hotels and others to have access to their trash, because for them waste is prized based on what can be created from it. What they create, not what they landfill, is what generates value for them.

From that model, you can see how this indigenous understanding can scale based on how the fundamental meaning shifts, in this case meanings around waste. Moreover instead of seeing technology as only around the novel, the Zabaleen see technology around the old, even around supposedly “useless” waste. That influences how I think of technologies. I often start with the use cases developed from indigenous community learning and then it becomes much clearer what the technology can do. Unfortunately, my experience is we focus on how technology will be implemented and simply assume how the community is going to use it – as opposed to co-designing with the community. This is a lost opportunity for leveraging truly path breaking indigenous sources of innovation to make significant impact.

Both of your examples demonstrate the need to spend time learning about a community and its context. How can place professionals do this and, for those resistant organisations, what arguments can be used to convince them?

Many organisations, corporates, and local governments worry that all this community learning and canvassing slows down the process, but funny enough, there are studies saying that more data speeds up your decision making.

So, a first argument is that with more data, you build your intuition and that intuition then speeds up your thinking in future. So, the more perspectives, viewpoints, case studies and so forth that you have at hand, the more informed and richer your thinking.

The second is that if you do things by comparison, it’s often faster to make decisions than if you think of everything sequentially. If you work with communities, you’re benefiting from a different comparative approach to place alongside a corporate approach, an academic approach and so on. If you’re trying to see each one separately, it actually slows decision making because you don’t know what else could be the alternative. Think about when you go shopping for clothes, it’s often easier to do so if you have something to compare it with. I like this shirt, but I only know that because I’ve seen other shirts. 

If you think of this as just different perspectives and approaches, and you’re building both your intuition to understand those possibilities and you get to compare them, in the long run decisions can speed up. It may be slower in the beginning, but once you build that capability, things become very fast because you can develop a process to implement that approach across the board. 

My third point is that place-based community engagement need not be a slow process. Perhaps by looking at the community network to identify the individuals who are trusted figures in neighbourhoods, you can create an engagement map and see where a certain set of nodes percolate. That’s where discussions start, with those nodes or individuals, because they’re each often bridging a bunch of information together in the community and actioning it. This helps  you more quickly ensure you’re getting pretty representative and diverse voices from the community, via those individuals. In talking with these key individuals, you also signal that you are serious about working with the community in an inclusive and collaborative manner. In this way you can balance speed with diverse and accurate representation to generate more timely and socially sustainable and inclusive solutions.

Two people hugging a welcome in a community hall
Photo: Erika Giraud

We have heard for decades that regulation, ethics and community engagement all get in the way of digital innovation – they are obstacles to first mover advantage in the market as they slow things down. With increasing deployment of digital technologies in our towns and cities, how can we innovate at speed and with care?

I think that Google’s Sidewalk Labs case in Toronto is a really interesting example. Google saw an opportunity to create a smart futuristic city on Toronto’s waterfront that would be imbued with digital technology, often untested. The foundation of their vision was technology, and they spoke of a community “built from the internet up”. Their big problem was that the Torontonian community didn’t share the vision, ultimately rejecting the tech-led approach. This is a cautionary tale of how not to innovate; this was speed without adequate indigenous voice and understanding. 

They really didn’t do enough community engagement to understand how people felt about their data being collected, shared and used.  The community were concerned with privacy issues and lack of clarity around  data governance, as well as concerns about accountability and the scope of the project, only further exacerbated these concerns. It ran for two and a half years, with nothing at the end.

What can we learn from this case? Engage communities early and throughout the project to understand their needs, concerns and ideas. Seek to more deeply understand the social and cultural context of the locale for which you seek to support. Prioritise data governance and privacy concerns. Take an inclusive approach to the way that infrastructure is designed and built. Collaborate and co-develop your approach with both the communities and the governments and regulators who will need to enforce the resulting consensus. This requires a long-term commitment to the locations that you choose to invest, so choose wisely for this is the approach that is most likely to result in meaningful progress.

We are living now with the results of what has been well documented as the biased nature of city design. For example, urban planning decisions that have prioritised the design and construction of roads and transportation systems that mainly benefit male workers, effectively neglecting the needs of women who have different commuting patterns and safety concerns. Similarly, we have developed digital systems that have inherent bias. Now that our physical and digital environments are increasingly enmeshed, how can we design-out inequality and bias in our connected places and future smart cities? 

I have a couple of practical ideas that I’ll set-up with some context. 

What’s not widely recognised is that in the U.S., infrastructure is unevenly distributed. What that means is that a truck may not be entering an area because it physically cannot, not because the driver doesn’t want to. Why? There’s a bridge that’s restricting its path or the road is really badly torn up, and often such obstructions and disrepair are associated with marginalised communities. What people assume is that everyone can access everything evenly, when the reality of infrastructure is that access is not equitable. So, if we just take the digital data that can be seen on the road and use that to make decisions, such as the spatial movements of trucks as we have been discussing here, then we have a problem. Because, potentially, by using this truck data we’re going to optimise and even exacerbate bias! We are not paying attention to the data about the physicality of our environment, such as bridges that are too small for the size of the trucks. So, if we just look at digital data without the physical, then we’re not going in directions that are useful. 

Old box bridge with grass growing through road surface
Photo: Martin Castro

At the moment, as part of my research, I’m looking at operational models to address this situation by trying to build models that address this root cause through addressing the inequity of physical infrastructure through prioritising maintenance based on both condition and equity (i.e., minimising the difference in infrastructure condition between advantaged and disadvantaged communities). Until we can build and scale such models, perhaps we should weight our traffic  models to account for such infrastructure inequities, or even penalise such algorithms to overfit on data that does not account for skews in the built environment landscape. That’s one potential way to better design-out bias.

A second way is to look at policy. On one hand, you want to try new digital systems out in places, and on the other hand, you don’t want to rely solely on the high-tech companies often at the vanguard of such innovations without constraints. After all, the composition of these companies is much more technically driven – computer scientists, mathematicians, those who develop the algorithms, and so forth.  They may be very well intentioned, but they often don’t have the sociological or anthropological skillsets (amongst others) to understand the societal implications for what they are creating, and therefore better identify and mitigate bias.

There are two policy options which I’ve seen implemented to try to address such challenges. One offers a spatial constraint through sandboxing and the other a temporal constraint through sunrise and sunset clauses. 

If we set up a sandbox, we take a slice of a physical area and say that’s where we’re going to experiment but it can only be done there. In this way, everyone knows what’s going on and things can be monitored before scaling.

The temporal constraint enables experimentation within an agreed time window, because you don’t want to just let things be released without scrutiny, especially if it has the potential for wider social consequences. At the same time, you don’t want to hinder potentially promising innovations. Generative AI was unleashed without such careful balancing, and just took on a life of its own and now we are on the backfoot on how to properly regulate it. We don’t want the same to happen within the smart cities space. So, I think it is important to find policy mechanisms that balance public policy interests with technology interests. It’s a balance of acknowledging the need for the capabilities of these technologies and enabling them, while also managing their blind spots and their unintended consequences. .

Thank you Daniel for sharing your time and providing such a wealth of ideas, reasoning and evidence that will certainly inspire as well as inform readers. Urban digital technologies are increasingly pervasive and will continue to make fortunes for a few tech entrepreneurs and their investors, causing skyrocketing inequalities – unless we make the right choices. Your research and willingness to share your insights in this Expert Interviews Series will help to inform those choices. It has been a pleasure to speak with you and thanks again.

 

Calvium is a member of the SME Climate Hub.

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Hear from other expert practitioners, bringing their lived experience into delivering positive innovation:

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  • Ceren Clulow, Programme Director, Connecting Cambridgeshire
  • Daisy Narayanan MBE, Public Realm Director, The Crown Estate
  • Dan Cook, Assessor, Cambridge Institute for Sustainability Leadership
  • Joel Mills, Senior Director, Communities by Design
  • Ludo Pittie, Head of Landscape, WSP
  • Marc Cairns, Managing Director, New Practice
  • Mark Hallett, Regeneration Associate, The Good Economy
  • Prof Peter Madden, Professor of Practice in Future Cities, Cardiff University
  • Steve Sayers, Chief Executive, Windmill Hill City Farm

 

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