Daniel Armanios - Inaugural Lecture

Key Takeaways

please rise follow them in okay thank you is where you'll be please be seated welcome to today's inaugural lecture to be delivered by Professor Daniel armanios BD professor in major program management at the side business school and fellow of sentence College thank you for joining us on this very special occasion it is customary their statutory professor beyond the research leadership the demonstrator of the department and wider University have the opportunity to share the research with a wider audience and we're very pleased to have distinguished guests and colleagues from across the university here to share in this event I'm also delighted to welcome Daniel's family his wife Lee his beautiful daughter Fame area and the parents mahera and Aryan welcome Daniel joined the school in January this year but he has been part of the Oxford Community much longer than that a former Rhodes Scholar he obtained two MSC degrees from Oxford one in management research another in water science policy and management as a road scholar he holds a PhD in Stanford University in management science and engineering which is interdisciplinary approach Daniel embodies the best of Oxford where we are all enriched by the opportunity to work with colleagues beyond our own departments and to benefit from the extraordinary breadth of knowledge across this University his work in engineering was recently recognized when Daniel was made a fellow of the American Society of mechanical engineers and we offer him congratulations for this honor Daniel's entersmith research integrates civil engineering organizing Theory to understand how organizations coordinate to build manage and maintain infrastructure amidst complexity in today's lecture Daniel proposed a working framework to tackle the grandest challenges whether concerning climate change or health and well-being to Equitable access to food energy education I hope you enjoy the lecture and now invite Daniel to take the flow [Applause] um thank you Dean symmetra Duda for your kind words and thank you also to Pro Vice Chancellor Professor sir Rick Traynor Vidal Carolyn Barnes senior Proctor Professor Jane mellor and Junior Proctor Dr Linda Flores principal Helen King as well as the senior leadership team and fellow faculty outside business school for leading and participating in this procession I also want to take a moment to thank Arthur Gregory Tiffany Franklin asked me barwood Tom Madden David and Robin and so many others that have worked behind the scenes to make this lecture possible I also want to thank you distinguished guests at Syed Oxford and beyond for coming to this lecture on building major programs for tomorrow as I was reflecting on what would discuss in this inaugural lecture I naturally look back at other lectures here at Syed and elsewhere and I found them ambitious and bold in their attempt to strive not to be a final word but an initial word on a new vision hence the notion of inaugural and I will do my best to strive for that here today however as I thought about it further my mind went to this famous Taoist phrase which I'll tell you in Chinese [Music] which roughly translates a leader is best when people barely know he exists when his work is done his aim fulfilled they will all say we did it ourselves then it dawned on me this is not even my inaugural lecture but a lecture written across many generations and with the hands of many the next few slides are those who I want to honor who have helped me have this platform today my lecture in many respects was written by my grandmother in 1953. that year my grandmother became convinced that my father and his brother my uncle would not have as much opportunity in their hometown of Abu Diablo in Egypt it's a small town just outside of Anna near La sor so she sold her best gold earrings to pay for the overnight train to Cairo and called their husband my grandfather and said I'm staying in Cairo and you can come but I'm not going back if she did not write those words through her actions this lecture clearly likely would have never been delivered it's written by my parents who came to the United States from Egypt and sacrificed so much for me to be born and educated in the United States if they did not write their words to their heroic sacrifices this lecture clearly would have never been delivered this is written by my wife who sacrificed so much as I worked through the toes of being a junior faculty in Engineering in the United States and delivering our daughter our precious Jewel to the world if she did not write those words with her many years of toil and sweat this lecture would have never been delivered this is written by so many students and collaborators in management studies sociology psychology civil engineering systems engineering and computer engineering from whom I've learned so much and whose gifts and talents I've benefited tremendously from if it was not for them this inaugural lecture would have never been delivered it's written by so many colleagues mentors and Scholars in the social engineering Sciences all of which I could not find all the pictures I tried my best both before and since I have arrived here who have given me so much intellectual insight and guidance even Beyond those here on these pages if it was not for them this lecture would not have been delivered this then is a lecture that reflects the hands and actions of many across generations and across communities who have helped give me this platform to speak today this is not just my inaugural lecture but a continuing lecture of many My Hope Is that these words and actions give inspiration to the Next Generation like my daughter that if someone like me could be fortunate enough to be given this platform then they too can speak and be heard to begin the scholarly basis of my talk I want to share who I am as a researcher and why that has led me down the route of major programs I'm a researcher at the intersection of engineering Sciences namely civil engineering and social sciences namely organizational Theory and sociology whereby I publish regularly across these two domains what unites my work together is what I call institutional infrastructure simply put it's defined as the coordination between organizations that underpin the Norms regulations and shared understandings that underlie undergird that system I focus on two kinds of systems in engineering Sciences I focus on infrastructure systems and have focus on how organizations coordinate and manage and deploy Water Systems remote sensing systems mainly Satellite Systems Bridge systems energy and broadband in the social sciences I focus on how organizations coordinate to manage and facilitate entrepreneurship and Innovation systems here I have focused on Innovation systems in China the United States Tunisia Egypt and Thailand what excites me about major programs is that this is an opportunity to really integrate and feedback across these two domains that will serve as the basis for the core of my talk there's a line of work in construction engineering around the operations projects and delivery as well as the organizational governance mechanisms and the social management and Behavioral Sciences The Arc of my talk will come predominantly for my work in China that runs through much of my early career with my more recent and current work that helps generalize from this Arc in the United States on broadband systems as we begin this journey together I want to ground the reader as to what the prevailing thinking of major programs is in my scholarly opinion and a few examples that led me to re-envision major programs in a way that will guide my core conceptual framework that will serve the majority of this talk whether we are tackling climate change economic inequality energy access digital literacy health and well-being and so many of our other Grand challenges we usually Define major programs as a large-scale programs that entail complex stakeholders and organizations and ambiguous inputs planning time skills and outputs that affect diverse peoples in other words what goes in what comes out and all the time in between are all unclear to provide a sense of the scales that we're usually discussing we're talking about projects usually over a billion pounds that affect millions of people and take over five plus years to build and the reality is given those time scales often none of the original managers are present by the time of completion which necessitates institutional systems to manage trade-offs and handoffs throughout the program's life from this vantage point the usual view is major programs as Mega projects though multi-organizational in nature Mega projects rely on centralized convening sites and current models likewise seek to theorize and therefore consolidate programs into a single governing structure that typifies such Mega projects such projects include but not limited to what you see here such as stadia such as the one you see here from the 2012 London Games Bridge infrastructure Highway infrastructure and other such large-scale energy and transportation projects I will now present some examples that I think reflect a new trend that runs counter to these prevailing archetypes of major programs as we look at these next set of examples ask yourself what are the features of these programs and how do they compare or contrast with our prevailing thinking what Newfound challenges and opportunities do they provide to Major program managers the first example is icon the company that 3D prints housing and other constructions the company was founded in 2017 and built their first 3D permitted house in Austin in 2018. they use their proprietary machine called the Vulcan and their proprietary substrate called lavacrete that can be fed into the machine to print one layer at a time they then printed their first ever 3D community in Tabasco Mexico NASA has been interested because of their ability to tailor construction to a much wider set of designs that could adapt to potential lunar and Martian climates and the Armed Forces has been interested due to the ability to rapidly construct and deploy infrastructure for forward operations and missions the valuation of this company is approaching 2 billion according to TechCrunch now you may think this is a far-fetched dream but right now there's a 3D printed bridge in use in Amsterdam and the Chinese of proposed 3D printing an entire Dam an entire 180 meter High Dam and they plan to do it in two years called the Yang Chu Dam as you can see from the pictures here on icon the developments in their technology have been rapid the first home in 2018 took two days of print time to build 350 square feet at about ten thousand dollars one should know by 3D printed we mean the TR the foundation of the walls the fittings the windows are all traditional build fast forward to 2019 icon is building 500 square feet homes at 24 hours per house and this was for a community by the way that makes three dollars a day or about sixty dollars a month and the mortgage is offered were for those houses were for about twenty dollars a month for seven years so it's actually remarkably within their price point our next example is zipline a point-to-point drone based system this is a U.S company that was founded in 2014 but largely operates in Western East Africa namely gone and Rwanda and they've expanded their operations in Tanzania the company distributes agricultural medical supplies across these areas and they each also have an equally staggering evaluation evaluation of 2.8 billion you in 2021. so how does this work imagine someone has an injury that needs medical retention in a remote part of Rwanda where physical infrastructure is poor zipline will send a drone to the location where the medical supplies needed now for those of you may know drones there's usually two modes of takeoff one is launcher based or one is vertical takeoff and Landing or VTOL similar to how helicopters operate zipline launches their drone using a launcher with the medical payload and then delivers that payload out location and comes back yes our final set of examples is the movement in portable Renewables so shine is a Canadian company that developed a wind turbine that is under three pounds and fits in your backpack it can charge four devices at once and automatically spins towards the direction of wind usually about 8 to 28 miles per hour takes only two minutes for setup and takedown and has a power output of 40 Watts if you need even more power you can go to power blocks this is a Swiss company that built a standalone grit solar grid system in a box which can be stacked up like Legos and develop develop delivers up to 200 watts of power for even bigger needs can go to uprise energy a us-based company that can supply a 10 kilowatt power through a portable wind turbine that they set up via trailer and there have plans right now to build a 50 kilowatt Mobile Generation system while these systems bring unprecedented mobility and distribution to historically difficult Last Mile problems the communities that rely on such systems almost by definition are understandably quite remote and this presents a very different set of problems that are encountered by such distributed major programs to explore this further I wanted to look for the harshest conditions for which to understand distribution at its most extreme this led me to explore Water Systems in the rural Arctic of Alaska for which we are currently conducting field work as an extreme case to better theorize on distributed major programs Alaska has about 200 plus towns scattered throughout the state often with a thousand people or less and many are only accessible via flights that make milk and Supply runs to these remote locations which are truly locations in the extreme for those of you are not familiar with Alaska it is the largest U.S state by area and the text you see here which I don't expect you to read is just simply every single Native Alaskan community over 50 percent of all nationally recognized tribes in the United States are in Alaska so you have diverse indigenous and socio-cultural knowledge also in the extreme and of course the climate is Extreme in fact so extreme that you literally have to heat the water lines to continue water flowing with such extreme remoteness socio-cultural diversity and climate problems inevitably arise for instance here is one picture from Villages from our field work the permafrost has melted to such an extent that the soil in much of the village is unstable to the point that the water tank you're seeing here that carries most of their water supply is dangerously unstable and you can see that from the tilt the wooden planks you see here is where the villagers can only walk because anywhere else they're in risk of severe injury due to sinkholes from the permafrost and this has only happened in last two years the last two years it is personally the most Stark and Rapid climate change that I've ever seen in all my field work today and sadly for this state it's not unique this has become so bad that for decades the state has been dealing has been helping Villages decide on what they call manage retreat whereby they help Villages consider whether they can actually reinforce the village in its current location or have to literally relocate the entire Village to a more climate resilient location hence managed retreats given the Deep spiritual ties of these communities to the land the mere thought of leaving for many is akin to losing their ancestral or familial bonds that is how deep the trauma is for many amid such circumstances so what is different about these major programs on the one hand they are hyper distributed and they may not even be in the ground but actually literally through the air take cloud computing for example very little of it is actually physical other than the computers the servers and the fiber the literal transmission and interdependence is what's distributed and that's through the data these systems allocate data processing either to a cloud or two edges depending on computing power and process time needed such allocations must also be resilient to what is known as adversarial attack think spam fishing any kind of intrusion because if any attack even hits one node it can propagate throughout the entire system on the other hand they're also hyper hyper localized and situated strewn across many diverse contexts take this micro grid system in Zambia for example for small energy needs this microgrid may suffice but if the community begins to want greater energy needs and Ambitions they need to find ways to connect to other such grid systems how to create and govern such transmission is not trivial across a series of such remote communities literally connecting a bunch of Last Mile communities as you would have probably guessed we are moving rapidly from Mega projects along a centralized convening site to a major program portfolio distributed and governed across many locations the notion of scaling one project to cover demand is now making way to a portfolio of projects each calibrated to their size of local demand this is a process of right sizing as opposed to just scaling instead of replicating this same Bridge Project the same output in many other locations under the assumption that what works in one place is good for everywhere we are now in a world that's trying to replicate not the result but the method with the understanding that what may result in one community may differ for another overall then standardization and replication is making way to situated context-sensitive Construction the clear outcome of this is that we need tools not for managing a centralized Mega project but a distributed major program that is usually a portfolio of differently situated projects do not take my word for it in today's Financial Times there was an article entitled UK urged to lay out clear plan on new infrastructure projects in it an Institutional Investor with significant infrastructure interest in the UK set of Energy Efficiency programs which is one form of major programs this will take a partnership between government and Pension funds and other forms of institutional Capital to deliver across 28 million homes on Energy Efficiency to me this is a Clarion call for distributed major program thinking I see this challenge before us as akin to the provocation prose To Us by Pablo Picasso in his work entitled The Bull how do we approximate this a complex reality in major programs the bull in all its parts and glory and distill it into its most fundamental Essence the bull in its Bare Bones in other words can we find some common features across major programs that give us a typology that can serve as the analytical backbone for any major program with the understanding that the programs that our results are clearly likely to vary much Beyond such analytical simplifications our attempts to arrive at this fundamental essence of these new distributed major programs is the S cubed framework which has collaborators across several Departments of Oxford the aim is to integrate social and Engineering Sciences to begin to evaluate and stress test the future of major programs the QR code on these Pages directly lead you to the website where you can learn more this platform has three parts scoping scaffolding and sensing which we will now discuss Each of which as you expect from my work integrates a strand of Social and Engineering Sciences together as I noted previously I will use my work in China as the arc that weaves across these three parts with selected examples in the US and on broadband to be to show the generalizability obviously Beyond China to be clear this is not intended to make any normative claims that the country's organizations using these tools are somehow quote unquote good or bad these are tools and tools can enact benefits and they can enact Harms we are merely trying to characterize the key contracts that can help us better understand the operations and value sought from distributed major programs to summarize up front and to preview where we're going I pause it tomorrow's major programs are more distributed and situated rather than centralized and standardized they necessitate replicating a method means rather than the output ends and they require right-sizing projects in different ways across a major program portfolio rather than simply scaling a single Mega project the s-cube framework is a conceptual framework that we hope provides the tools and infrastructure that can help better address tomorrow's major programs this has three parts the first is scoping the where the idea here is to map major programs as a system of components with flows of various resources in between and then identify precisely which parts are vulnerable to disruption and how to motivate and coordinate learning and Innovation amongst the organizations that proximate such disruptions the second is scaffolding the how the idea here is given that major programs are distributed different organizational and digital Technologies are likely needed to coordinate across this wide spread across an entire program to identify expertise who knows what roles who will do what and specifications who requires what the third and final is sensing The Who in our focus on major program delivery we often ignore communities who are not on the delivery path but nonetheless intersect such programs however if we are to increase resilience resilience to disruptions of tomorrow we need to increase the strength of our most vulnerable which means for us to enhance overall ability to navigate disruption we must identify those communities who have been historically marginalized by such major programs to co-design and code a govern with co-govern with them tomorrow's programs I will now go through each s in turn we'll begin with scoping the key Insight from scoping is that mapping industry chains onto major programs can help better Target and identify experimental opportunities amidst disruption the intuition behind this is an integration of robust control theory and Engineering with performance feedback in the social sciences in robots control the view is that the system is so complex that its interdependencies and their consequences are so unknowable that the focus is simply around setting thresholds that bound the system to any disruption that would destabilize it so in this instance this is the system bounded the Red Arrows would be those that have been protected from the system and the green ones are the ones that are considered allowable disruption while this protects the system from harm that prevents us from knowing how we could possibly learn our way through such problems and thereby enhance resilience of the system to take on even more of these disruptions in performance feedback The View as one can learn through seeing whether a response or action meet goals and then change the action when they don't however if A disruption hits the system at the same time it becomes difficult to ascertain whether the response is due to the action or the disruption these two views in my opinion are synergistic in that robust control can bound the system to the manageable disruptions such that performance feedback can learn from a more reliable and mitigated set of disruptions once feedback helps improve our practices this in turn potentially could increase system resilience thereby changing the thresholds and allowing us to do with more disruptions perhaps then if we could Target such activities precisely to where the system is most anticipated to experience such disruptions this can present an opportunity to learn and innovate in ways that mitigate such disruption to understand this let's look at how the Chinese Innovation System handled the technological disruption in the form of drone technology which has been led by my doctoral student dnu to do this we overlay China's Innovation System of academic institutions science Parks academies of Sciences and various levels of government with the value train of drone technology focusing on Upstream components such as Motors gimbals cameras sensors and GPS and downstream end products namely the Assembly of the Drone platform for various Market applications ranging from pesticides spraying material photography what we see is different organizations in China's Innovation System proximate different parts of the technological disruption that drones in themselves present for those around components what we call Market inputs National universities National Labs are crucial for the experimentation in terms of advancing fundamental Aeronautics and avionics that update the componentry for those around the end products what we call Market outputs science Parks Tech licensing offices become crucial to experiment on different Market applications for that can be done from the Drone platform and this is has some interesting spatial manifestation so how this spatially targeting manifests is that componentary firms usually are around clustered patterns what we know from typical tech-based development so in the case here the big larger black dots around Beijing chandu Shion Wuhan they're actually proximate where a lot of the top aeronautical universities are so that's where the clustering happens in the system and then if we look at the market output side you see that the spread happens which is quite unique for a tech-based industry usually it's quite clustered only in the cities and we think that the tech-based spread is happening because Agricultural Science Parks allow different firms and organizations to experiment on their platforms in fact we interviewed Founders and they said that science Parks they go to them because they provide an airspace for actually testing out their products so as you can see then the spread of firm foundings again the black dots in the left picture seem to correlate with the spread of Agricultural Science parks in the country on the red dots on the right diagram it is no wonder then that the largest market application for drones in China are agricultural applications namely pesticide spray but we can think of this not just along one chain we could think of it along multiple and we've done that in the United States for instance tech-based development is the chain along which Technologies are developed and translated into economic value this can be Upstream such as education programs all the way to Downstream commercialization of breakthroughs we can think of institutional context such as the different parts of organizational life along which this occurs such as private sector non-profit and public secondary education narrow here just simply means you're experimenting on fewer channels along the chain and broader means wider so from this we developed four typologies one is Hub Specialists experimentation that's concentrated very much Downstream in a single industry and interesting example is the state of Montana they have a photonics cluster that's quite successful public entrepreneurs that spread across the entire tech-based development but usually is public sector driven such as Oregon where they have the public sector has been driving the science Parks as well as equipment manufacturing to share and build deploy Technologies industry Architects where you see much more focus on the on the Upstream in terms of infrastructure and human capital but wide uh orchestration starting from the private sector such as Michigan or Pennsylvania which runs the uh network of Ben Franklin Partners Innovation Works as well as Michigan life sciences now for ecosystem designers that spread across both you can typically think of Silicon Valley in California but to me the more interesting example is the state of Maine they actually have a director of innovation and infrastructure that tries to curate this across their entire state the EU also has a smart specialization strategy that looks at not just two but multiple different chains to figure out how to experiment in ways that match different cities competitive advantages and comparative advantages and we've tried to broaden this Beyond a wide range we're looking at socio-political disruptions in terms of turmoil we've been looking at how r d and Entrepreneurship happens amidst the Arab Spring as well as the Thai military coups with my colleague Omar oddly at AUC and cam Mogul seniors at Carnegie Mellon one of my PhD students and environmental disruptions with uh Malcolm McCulloch who's in the audience as well as Casey Faust in civil engineering at UT Austin to understand how this affects environmental change at rapid pace so let's look at scaffolding now the key Insight of scaffolding is that it can improve the relevance and integration across systems Parts this becomes really important if everything is distributed across many different organizations something has to coordinate all of this action the intuition again is yet again a Synergy between engineering and social sciences I focus on the work around construction engineering historically they focus on physical scaffolding but recently they've drive very much further into digital scaffolding and their view is it can help reimagine the possible and such need for reimagination is most acute in major programs that have to build today for an increasingly unpredictable future tomorrow for instance how do we understand this portfolio of projects and how they'll work if they're entirely built by machines or even how to handle climactic change so 2030 we have to have emissions 2050 you have to hit Net Zero major programs Take 5 10 15 years to build that means literally the projects that are developed now have to not have emissions when they come out yet we also know with warming the environment is also more unpredictable uncertain so a one in 100 year flood happens every year now so the question is how do you understand what that does when it doesn't meet your prediction and this opens up the possibility for what we're trying to do around augmented reality augmented reality and digital twins namely the theory that is brought here is perhaps if we can help managers visualize what that would be like at the time of development they can build better heuristics to guide their decision making to anticipate those problems in the social sciences particularly around organizational search and Scaffolding the need there is not that it has to be digital and doesn't even have to be high-tech it's mainly organizational so Arab for instance who built the 2008 water Cube on budget on time use something as simple as collaborative platforms like Slack so that everybody knew on the project what the roles and responsibilities were at all times this can even be just simply a model Farm project that can help demonstrate how you can use current practices or even experiment on new ones take for instance this model farm that was done in Nicaragua the idea there was there were subsistence farmers who had really high quality dairy products and they were trying to figure out how they could export it well you need to understand Global standards of control you need to understand how to get supply chains Etc so they literally built a model farm for Farmers to walk through and understand what that could look like from this we see yet another possible feedback loop whereby engineering Sciences helps you re-envision what's possible and the social sciences help execute or Implement that Vision within existing social and organizational understandings again we'll go look at China in this case as the Arca we've discussed one of the key reforms in China that they undertook in the late 1990s reformed the Chinese Academy of Sciences so that it could better demonstrate the market relevance of its scientific breakthroughs and two examples will show how they've demonstrated created these demonstration projects to help provide scaffolding that improved the ability of entrepreneurs to translate scientific knowledge into commercial value so this is the case of the Shenyang Chinese Academy of Sciences new fertilizer company in 1998 the research of Dr Shirley Ren young within the CIS Institute of Applied ecology led to the development of a slow release fertilizer which significantly reduced runoff improved efficiency and reduce nitrix oxide emissions with strong support from the local government they created a new company that was spun off from The Institute it was founded in 2001. as of 2007 just six years after the company's Revenue had totaled over 2.6 billion Renminbi which approximately is 370 million British pounds it's not bad for fertilizer here the market relevance of CAS science was demonstrated directly through a spin-off and the revenues went back to the Institute another interesting example is that Cas tendu Institute of organic chemistry when we interviewed their director their belief was that scientists are good at science but not necessarily have the capabilities to make firms so they're great at the scientific capabilities not so much on the market and management management capabilities so they said okay we'll spin off a business unit and that business unit went around to local companies to see who could benefit from their applications their technology and then arrange IP licensing and transfer agreements and then the revenues fed back into this into the Institute the National Institute of physics in Beijing also does this as of 2015 the annual operating income of this business unit was about 23.5 million pounds Market relevant knowledge generated by CS science was distributed through a separate organizational unit now this is great in terms of identifying breakthroughs along all parts of China but how do you then integrate those back in and it turns out that science Parks also provide a role here science Parks helped integrate science with the local firms who could commercialize that science and local governments who ascertain how to regulate such Newfound flows to do this science Park officials facilitated numerous joint meetings between government officials and CS researchers so to give context here this reform happened in 1998 and literally the first year they had 19 joint meetings with 80 different institutes across a thousand researchers to identify common areas of strategic interests and common kind of agreement of how they would regulate this kind of work we're expanding this out to others we're looking at this U.S local government to see if the certification they developed could help scaffold marginalized ventures in particular and I'm currently actually looking at technological Scaffolding in fact we ran a beta test this past Friday with colleagues in the I.T Department looking at how to use this to facilitate our understanding of marginalized communities so we're looking at augmented reality as well and this is work with Lauren Lanahan a mole Joshua Medi dnu my student David linderbar at Carnegie Mellon finally let's look at sensing here we're going to use prior infrastructure networks to see if we can help extract more of a program's kind of extract gaps in the program's onset and where to alleviate it in terms of marginalized communities as you probably guessed at this point the reiterating phase rearing phase this again combines approaches from engineering and social sciences in engineering Sciences they've converged on what they call the human as sensors approach which uses much more localized sensors to detect motion and behavior and this provides unprecedented resolution so think about advances in motion sensing for example detecting motion raising alarms in a room while advances are being made to more parsimoniously derive optimization to kind of make the data constraints less problematic these are highly still computationally intensive and so to do so at scale is really costly and time prohibitive imagine if you wanted to create a smart City platform for the whole city trying to integrate every single room in the entire city would be a Monumental effort in terms of computation in the social sciences there's been a long tradition of sociological and urban studies of infrastructure this work has long shown that infrastructure is not evenly distributed but skewed it's biased this work has shown that um a key piece excuse me a key piece in this stream is the work of Rick Grannis and T communities he finds that trivial streets t for trivial streets which are the streets that pedestrians walk on which are the non-bold lines in the diagram are crucial for social interaction you meet people on the sidewalk you strike up conversations and the like he finds that non-trivial streets which are the Bold lines that usually just have automobiles bound to two communities that restrict they restrict segregate communities together so essentially what's happening is any community that doesn't have any pedestrian streets walking across them don't interact even if they're right next to each other however these studies are often retrospective studies almost poor post-mortem studies of the bias and they can't adequately guide future action so our thinking is what if we take these configurations and see if we can find them across an entire city and perhaps you can then detect at scale where bias is happening and marginalization is most acute so that future policy can Target precisely those areas this could then allow us to use a human as sensors-based approach to identify these issues at greater granularity in this way while social sciences can detect infrastructure gaps engineering sensing approaches can more granularly Target them enhance the resolution if you will where such bias critically impacts community activities to better allocate limited resources to then localize and Target precisely the community activities that have these issues now clearly there are deep privacy and other individual rights that must be considered here notwithstanding these very important concerns the idea is merely to explain the ways these tools can work synergistically to see who has been historically excluded in major programs the inspiration for this approach came back on my work in China where I noticed the places that had more high-tech founding from the aforementioned Chinese Academy of Science reforms wherein those places that historically did not have such development for instance the cas organic chemistry Institute in Sichuan which experienced significant findings from these reforms Sichuan did not have much founding prior to this as well as in Liao ning which was where the Shenyang CS new fertilizer company was also experienced rapid growth and so we're trying to understand how did this help those that were formerly marginalized so we decided to try to apply this to broadband data amidst the covet pandemic the reason is that one of the key things that happened during covet as we all know was stay-at-home mandates to prevent the spread of the pandemic thus employment depended on your access to broadband and many had to make extremely tough decisions such as this Cambridge study saying whether they had to pay for the Wi-Fi or Feed the Children especially in marginalized communities whereby in the UK prior to the pandemic 38 percent of British adults could not pay a 500 pound emergency expense almost 40 percent of the population and this was prior to the pandemic and this experience was prevalent throughout many parts of the world such as in the states and other parts globally and our idea was then to see could we use Broadband to sense these gaps more in the moment to see if we can help governments know precisely where it's happening to Target Broadband vouchers and other short-term policy measures to allow vulnerable communities to get more immediate help to get through these very perilous times our aim then was to see where Broadband worked as a social sensor and where it didn't to do this this is with my doctoral student Nikki Reese we collected a whole range of broadband data everything from Advertiser reported speeds from the United States Federal Communications Commission survey responses of access from the American Community survey all the way to actual Broadband tests from Microsoft Google and app lab that all measured in different ways what we find in the base case when all else is equal is after the shock of the stay-at-home orders associated with covid-19 counties with more than 50 percent adequate Broadband access 50 of their population and by adequate here we mean 25 megabits download three megabits upload speed that's the convention in the states which is the Orange Line in this figure experience higher unemployment rates over similar counties that have less than 50 access which is the blue line now that seems quite odd how is broadband increasing unemployment the reason is that Broadband when we do these kind of studies is measured spatially and assumed to be evenly distributed let's say one location reports 80 percent having Broadband the assumption is that access is spatially distributed across the entire location but what we just discussed from social sciences of infrastructure is that marginalization is often heavily concentrated and skewed and we can actually see that here so what we did next is we got even more detailed speed data at the level of what is known in the US as a census tract for those unfamiliar a census tracks about 4 000 people it's equivalent to roughly 1 6 the size of the average population of a UK postcode District so your three first digits what we find is that for these counties with 50 of their population having Broadband access but have very very few neighborhoods that don't have access that's where you see the spike in unemployment so what this means is is that concentrated in Access seems to be driving unemployment rates this suggests pockets of marginalization who are likely not having Broadband access are especially getting harmed from a lack of it and we tested that further with demographics and other groups that would expect to have this issue so for instance the gap between counties with adequate Broadband access again the orange line and inadequate the Blue Line those gaps widen for counties with more uh percentage of Hispanic and latinx populations which is a group in the US that is known to have significantly less Broadband access and we see the same for African-American black populations and other socio-demographics however this is not a Panacea for everything we also see where this sensor is not precise for instance counties with more service sector workers these sectors should not be should not be affected by Broadband as a lack of unemployment is due to business closures okay you can't do laundry serve meals and perform other such services online however what the problem is here is broadband misdiagnosis this and shows a wider gap for these counties in the high service and in these high service sector areas this is perhaps because if you're working in high-tech sectors you also need these services and those services co-locate with high-tech industry and so Broadband can't differentiate between the two so why does sensing exclusion matter for major programs to understand the human toll for marginalization we can take no look further look no further than one of the most mundane Technologies Crash Test Dummies in 2019 the height and weight of a female crash test dummy was five foot 110 pounds even though the average female build was five foot four and 170 and a half pounds moreover a female crash test dummy wasn't even widely used until 2003. and the consequences of this was extremely severe in a study in 2019 women were found to be 73 percent more likely to die or get seriously injured in a car accident while not directly tested one must conjecture whether the unsuitability of a crash test dummy to the biomechanical properties of females has something to do with such findings even if merely correlation such potential consequences are too severe for us to not take a sobering look at who we are excluding in major programs in this case automobile programs and this is probably far Upstream this is due to the lack of female engineers in the company who would have recognized us on the offset so this is a really structural issue foreign so we've tried to also now broaden the kind of things we use as social sensors we have a long-standing set of work on bridge and road infrastructure with Nikki that I've mentioned as well as Carrie Gandy Casa samras and Maria roach and soon as Sir Duda and because these are also very computationally intense they require a lot of regression I'm working with agnews here to try to automate these sensing Technologies to see if we can do it more parsimoniously to conclude yep sorry slides okay to conclude we are now entering a new world where tomorrow's ability to achieve Grand challenges at scale are increasingly Reliant not on centralized Mega projects but distributed major programs in this talk I've presented a conceptual framework that we label as s-cube that we hope can re-envision the tools and infrastructure needed to better address these major programs of tomorrow this has three parts as we discussed the first is scoping the where again the idea here is to map major programs and systems of components with flows of various resources in between to help us identify precisely which parts are vulnerable to disruption and how to motivate and coordinate learning and Innovation amongst the organizations that proximate such disruptions the second is scaffolding the how the idea here is if it's distributed we need to coordinate across a much wider set of organizations in very different parts and those require different organizational and technological tools that are likely needed to do that to identify expertise who knows what roles who will do what and specifications and standards who requires what and the third and final is sensing in our focus on major program delivery we often ignore communities who are not on the delivery path but nonetheless intersect such programs however if we are to increase our resilience to the disruptions of tomorrow we need to increase the strength of our most vulnerable which means for us to enhance our overall ability to navigate disruption we must identify those communities who have not been historically included in the process and co-design and code of govern tomorrow's major programs to do that in conclusion thank you for attending today and especially thank you for those who have made this platform possible for me to speak I hope this lecture is truly inaugural and that it incites subsequent and future discussions around how we adequately built tomorrow's major programs to handle the grand challenges of our time thank you for your attention and have a good evening foreign [Applause] foreign