SUSTAIN: Sustainable Urban Systems Through Automated Infrastructure Networks Workshop Summary 29-30 July 2019 Carnegie Mellon University Pittsburgh, PA

Constantine Samaras1,2,3, Karen Lightman4, Christine Ogilvie Hendren5, Mario Bergés1,6, Greg

Lowry1, Sean Qian1,2, 1Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA 2Heinz College of Information Systems and Public Policy, Carnegie Mellon University, Pittsburgh, PA 3Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA 4Metro21: Smart Cities Institute, Carnegie Mellon University, Pittsburgh, PA 5Team Helium LLC, Durham, NC 6Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA

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Acknowledgements The workshop was supported by NSF Award Number 1929937, under the Division of Computer and Network Systems. We are tremendously grateful to Chelsea Cavlovic and Rachael Chambers for their time and assistance in making the workshop a success. We are grateful to the NSF Program Manager, Dr. Jonathan Sprinkle, for constructive feedback and advice regarding the workshop, and to the participants who graciously provided their time and energy participating in the event. The views expressed here do not represent the views of any organization. Any errors or omissions are the sole responsibility of the authors.

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1 Executive Summary Automation—in buildings, transportation, and infrastructure systems—is coming to urban environments. These sectors have a large impact on urban sustainability outcomes and hence how technology advances in automation affect urban sustainability are critically important to understand. New crosscutting knowledge is needed at the intersection of many fields across engineering, physical and social sciences, economics, humanities, public policy, and others. On July 29-30, 2019, we convened a diverse group of participants from academia, industry, the non-profit sector, and the public sector for workshop at Carnegie Mellon University in Pittsburgh, PA. The workshop was called: SUSTAIN: Sustainable Urban Systems Through Automated Infrastructure Networks. We conducted the workshop using the pseudo-nominal group technique (pseudo-NGT), which ensures that all workshop participants are given the opportunity for intellectual input, facilitates interaction between participants from different disciplines, and enables the participants to generate a prioritized list of opportunities. This report is a summary of the workshop outputs, and highlights research opportunities where automation can provide the greatest sustainability benefits and synergies. The overarching goal of the workshop was to stimulate discussion, visioning, and convergence across urban sustainability research in the energy, water, buildings, transportation, sensors, data integration, agrofood, and automation research communities, and to advance the frontiers of imagination of the synergies in these communities. We aimed to identify the scientific, engineering and data challenges, economic and societal barriers that will limit the benefits of urban automation, technologies and research required to maximize the benefits of urban automation. Day one of the workshop generated 14 broad topic areas, and from these the participants consolidated and voted on priority research topics on the second day. The 5 priority research topics developed by the workshop participants were:

• Applications for Transportation Automation • Infrastructure Services Transition and the Design of Adaptive Autonomous Sustainable Urban

Systems • Tradeoffs at the Systems of Systems Level • Governance - Community, Social, Economic, Equity, and Justice Issues • Building and the Built Environment, Land Use, & Resilience

There is a need to better measure and model general human factors that affect the integration automation into sustainable urban systems. The dynamic interplay of autonomy--human agency, self-rule, self-decision making--within autonomous systems was an important point of tension that workshop attendees discussed in earnest. The related key research question is: “how do we promote governance of autonomous technologies in an urban environment to ensure sustainability, including equity, justice, and maximum positive social and economic impact, and how can technology aid such governance while preserving and respecting human autonomy?” Through “autonomous automated autonomy” the goal is to have human and machine learning decision makers together, working towards the ultimate goal of a sustainable urban system with a resilient, equitable, and flexible governance process that evolves alongside the technology.

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2 Introduction Urbanization is a global megatrend in the 21st century. More than 55 percent of the world’s population currently live in urban areas, and this will likely increase to nearly 70 percent by 20501. Rapidly growing urban areas bring new challenges in providing transportation, food, water, energy, infrastructure, education, safety, waste handling, pollution reduction, and emergency response, among many other services. Cities currently generation more than 75 percent of energy-related greenhouse gas (GHG) emissions worldwide2, and extreme heat, severe storms, sea-level rise and other impacts from global climate change will require new efforts from urbanized areas to remain resilient in the face of these threats. At the same time, increases in social inequality may erode efforts to increase sustainability3,4. Along with urbanization and sustainability trends, digital and automated technologies have proliferated into daily life, quickly becoming part of critical infrastructure systems. Billions of sensors and actuators that comprise the Internet of Things (IoT) have been deployed around the world’s urban areas5. Advances in sensing, automation, IT, computer vision, and edge computing are enabling new data collection and processing capabilities that can automate decisions and responses in buildings, transportation, and infrastructure. These devices can provide real-time information at very high resolutions across interdependent infrastructure networks, which will change the ways residents experience and interact with cities, and how city managers make decisions. The deployment of automated devices can transform communities and introduce new opportunities, but can also introduce threats regarding economic, social, security, privacy, and sustainability outcomes. We need new knowledge to ensure that the transition to automation in urban systems improves sustainability, equity, and quality of life. The potential benefits of integrating automation in cities will not be realized without the willing support and trust of city residents, which must see tangible and equitable benefits. Rapid deployment of automated devices without testing, systems analyses, and cybersecurity protections could lead to unintended consequences that would increase risks and costs6. In addition, automated equipment and services in urban environments are often deployed by private actors, but since these solutions affect the public, ensuring and maintaining accountability remains a challenge. There are societal costs of integrating automation into urban systems that need to be considered and mitigated. Automation—in buildings, transportation, and infrastructure systems—is coming to urban environments. These sectors have a large impact on urban sustainability outcomes and hence how technology advances in automation affect urban sustainability are critically important to understand. New crosscutting knowledge is needed at the intersection of many fields across engineering, physical and social sciences, economics, humanities, public policy, and others. On July 29-30, 2019, we convened a diverse group of participants from academia, industry, the non-profit sector, and the public sector for workshop at Carnegie Mellon University in Pittsburgh, PA. The workshop was called: SUSTAIN: Sustainable Urban Systems Through Automated Infrastructure Networks. This report is a summary of the workshop outputs, and highlights focused research opportunities where automation can provide the greatest sustainability benefits and synergies between sectors.

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2.1 Workshop Goals and Key Questions The overarching goal of the workshop was to stimulate discussion, visioning, and convergence across urban sustainability research communities in the energy, water, buildings, transportation, sensors, data integration, agrofood, and automation research communities, and to advance the frontiers of imagination of the synergies in these communities. We aimed to identify the scientific, engineering and data challenges, economic and societal barriers that will limit the benefits of urban automation, technologies and research required to maximize the benefits of urban automation. Identifying the challenges will inform research organization decisions and future solicitations for research for sustainable urban systems.

Specific sub-goals of the workshop were to:

• Bring together leading researchers in engineering, data analysis, humanities, public policy, and social and decision sciences to identify the opportunities at the urban systems level for automation to increase sustainability.

• Determine what breakthroughs are needed in sensing, edge computing, machine learning, and technologies to enable broad sustainability benefits from automation.

• Brainstorm and facilitate new ideas on automation synergies across buildings, transportation, and infrastructure for urban sustainability and identify urban systems research priorities.

Among the key questions addressed at the workshop were:

1. What are the enabling pathways for reductions in energy use, greenhouse gases, air pollution, water use, and other sustainability indicators that can be achieved at the urban scale with automation?

2. What advances in sensors, data collection and management, IT infrastructure, and edge computing will be required to realize these benefits?

3. What are potential negative consequences of automation for urban sustainability and what technical and social and decision science advances are required to mitigate these challenges?

4. What are the economic benefits of enacting more equitable and sustainable urban systems? 5. What are the potential sustainability synergies of automation across transportation systems,

buildings, agrofood systems, and infrastructure and the required scientific and engineering advances to enable these synergies?

6. What are new methods to measure, benchmark, and evaluate the economic and social costs and benefits of automation for urban sustainability?

7. What are the technical and social barriers to realizing the sustainability benefits of automation and the advances needed to overcome these barriers? How can automation for urban sustainability increase sustainability for suburban and rural areas?

2.2 Workshop Process We convened the workshop over a 2-day period, and the full agenda and participant list is provided in the Appendix. We conducted the workshop using the pseudo-nominal group technique (pseudo-NGT)7, led by a trained pseudo-NGT facilitator, Dr. Christine Hendren. The pseudo-NGT serves several key

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purposes. First, it ensures that all workshop participants are given the opportunity for intellectual input into the workshop. Second, it facilitates interaction between participants from the different disciplines. Finally, it enables the participants to generate a prioritized list of opportunities for increasing sustainability through automation, as well as the scientific and engineering challenges associated with achieving breakthroughs in this area. In this technique, participants are provided a set of pre-determined questions related to the role of automation in improving sustainability in urban systems. Discussion begins with each participant providing an answer to the proposed question. This continues until all participants “pass”, suggesting that all ideas have been captured. The pseudo-NGT technique is optimal for groups of 15-20. Therefore, we divided attendees into 2 groups, each group having equal representation of research interests and backgrounds. We collated the responses from both groups, then divided the responses into categories for further refinement in day 2. On the second day of the workshop each group refined and prioritized their lists of opportunities, and then identified a list of scientific and engineering challenges that must be overcome to realize the sustainability benefits from automation in urban systems. Finally, each group presented the findings from their analysis to the workshop participants. Additional detail about the pseudo NGT technique and process used is provided in the Appendix.

Through guided questions and respectful and inclusive dialogue, the workshop identified where automation can best be employed to improve urban sustainability. Workshop participants determined where automation can lead to breakthrough technologies, and identified fundamental impediments to achieving those breakthroughs.

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3 Initial Research Areas Identified At the beginning of the workshop, two balanced groups of approximately 20 participants were formed, and the facilitator provided a guiding question to each group: “What is the most important research question to ask to understand how automation can improve sustainable urban systems? Using the pseudo-NGT process, each participant had the opportunity to offer a response to the guiding question, and their response was written on a poster board on the wall. After each person in a group responded, the process was repeated. The groups then each collectively clustered the research questions into broad topic areas. The breakout groups came together and their broad topic areas were then presented to the entire workshop, and collectively clustered into research idea topics. The group voted on the most important ideas, and clustered the results into 5 critical research opportunities. In this section, we list the 14 research ideas developed by the workshop, and list the summary text developed about these ideas. Additional detail on the process and on the responses for each of these 14 ideas are presented in the Appendix. In Section 4, we discuss the 5 critical research opportunities the workshop decided to highlight. • Mobility, Automated Vehicles, and Transportation

o What are the technologies and policies to maximize the benefits and minimize the damages from automated vehicles?

o How do we ensure synergies across mobility modes? o What is the feasibility and benefit of providing universal basic mobility?

• Buildings and Built Environment, Land Use, Resilience

o How can automated systems improve the productivity of urban living in shared environments?

o Can automated building systems minimize people’s exposures to environmental contaminants and minimize building energy use?

o How do we promote the diversification equity and equality in these urban centers?

• Infrastructure and Services Transition o What do we do with pre-existing infrastructure as we transition to new automated systems,

and how to manage equity, environmental, resilience, privacy, and economic impacts? o What is the optimal capital allocation of infrastructure under uncertainty?

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• Human Factors o Quantifying human factors that affect the development of human in the loop systems, and

how do we quantify human action with respect to physical, natural, and cyber systems? o How can automation improve quality of life? o How do we build trust and maintain and improve privacy?

• Social and Economic Impact

o What are measurement and evaluation methods for social ROI, equity, health assessment?

• Information, Privacy, and Sensors o In order to measure automated systems, we need sensor technology; this creates enormous

data and information opportunities to create resiliency and sustainability. What are ethical and privacy considerations that require thoughtful design with safety in mind?

• Adoption of Automation

o How does heterogeneity of adoption affect equity? o How to address adoption of automation technology? o What will the roll-out look like, temporally and spatially?

• Design of Adaptive, Autonomous, Sustainable Urban Systems

o How do you design safeguards against automation for the sake of it? o How do we design systems that allow opt-out? o How do we bake in the flexibility to continually update goals and definitions? o How do we incorporate and bake in, employment/education/training issues?

• Tradeoffs at the Systems of Systems Level o How can we use automation to understand links between sectors? o What is the role of automation in achieving sustainable urban systems, since tech alone will

not be a solution? o How to ensure that short-term efficiencies are not wiped out by unintended effects of

automation? o Can we develop a science for how to foster sustainable innovation within systems-of-

systems? • Governance

o How can automation worsen sustainability and how do we prevent that through governance? o How do we ensure private profit-seeking interests don’t encroach on the systems? o How do we ensure transparency and accountability (maybe leveraging automation for it)?

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• Automated Applications o How can automation reinvent transportation? o What are the possibilities in urban agriculture/food delivery? o Can reimagine lighting and its effects?

• Equity, Justice, and Automation

o How are the benefits/burdens of automation distributed? o How to engage communities? o What are the right metrics to use? o What biases do we have and help to persist with automation? o How do we do data analysis while assessing tradeoffs in burdens/benefits?

• Methods for Evaluating Impact

o How can automation worsen or lead to sustainability? o What framework can be used to evaluate autonomous urban systems throughout their life-

cycle and assess aging, maintenance strategies? • Scalability and Flexibility

o How do these questions relate to & serve megacities? o What does the roll-out of automation look like? o How do we consider automation, integration and interaction sustainability across scales? o Can we elucidate flexibility as sustainability (as a concept) changes?

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4 Critical Research Opportunities In the morning of Day 2 of the workshop, the facilitator presented the consolidated 14 ideas from the Day 1 process, along with the charge for Day 2. The clusters of flip charts were posted on the wall in groupings so that each of the 14 groupings were around the walls of a large room. Each participant was given 6 sticker dots to place on their 6 favorite options, and given 10 minutes to vote by placing a sticker on the title sheet of the cluster. With the participants from both brainstorming groups having had the opportunity to review all of the top 14 ideas in slightly more detail during the voting process, the facilitator led a rapid and organic process of combining some of the like areas, soliciting input and verification of the appropriateness of these groupings from the plenary group. This resulted in 5 consolidated winning ideas, which were then addressed by breakout groups. The 5 priority research question groupings were:

1. Applications for Transportation Automation

2. Infrastructure Services Transition and the Design of Adaptive Autonomous Sustainable Urban Systems

3. Tradeoffs at the Systems of Systems Level

4. Governance - Community, Social, Economic, Equity, and Justice Issues

5. Buildings and the Built Environment, Land Use, & Resilience

For each of the 5 prioritized areas, a smaller dedicated break-out group of between 4-6 people was asked to carry out a self-facilitated process to explore their idea further, guided by a minimally structured template. The groups self-selected based on interest and knowledge base, and the remainder of this section summarizes these explorations.

4.1 Applications for Transportation Automation Automation in vehicles has the potential to fundamentally shift the trajectory of change in the transportation sector and urban sustainability. Crashes, traffic congestion, air pollution, greenhouse gas emissions, energy consumption, and other negative externalities associated with driving may significantly diminish or shift to new areas as Autonomous Vehicles (AVs) are introduced8. Commuting times, vehicle designs, and the viability of vehicle electrification could potentially be improved in a future with connected autonomous vehicles, especially self-driving passenger vehicles. Public transit and freight transportation could have significantly lower costs. However, there are potential unintended societal consequences. For example, vehicle travel, energy use, and greenhouse gas emissions may increase with automated vehicles, as driving becomes less onerous, parking locations are decoupled from destinations,

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and individuals without driver licenses have more opportunities for travel9–14. Economic opportunities, valuations, and community needs will shift. Communities, businesses and regulators have begun to face policy, technical, and infrastructure dilemmas as automated vehicles are introduced. There is a pressing need for objective, peer-reviewed technical policy analysis to inform public and private sector stakeholders of how to maximize the benefits of vehicle automation while limiting the risks.

The transition to new vehicle technologies will also be shaped in large part by changes in performance of roadway infrastructure. In some communities, where the city roads are being utilized as a testbed for AVs, the transportation infrastructure is attempting to adapt to and accommodate the revolutionary changes required for the deployment of AVs. These infrastructure accommodations are often ill-informed and inconsistent as there are few standards in place to guide their design and construction. While the timing and adoption of AVs is uncertain, these vehicles will also have to navigate a traffic ecosystem with human-driven vehicles for the foreseeable future. For nearly a century, traffic flow in roadway networks has been operated purely by humans. Human reactions to other vehicles on the road dominate driving behavior, but as we can see with increasing frequency and intensity, this behavior is being replaced by vehicle automation and communication15,16. While AVs are cars that can be partially or fully controlled by computers, connected vehicles receive data from other vehicles, or a central system, that then instructs them how to operate safely. Generally, there is a considerable developmental overlap between the two systems, with future Connected Autonomous Vehicles (CAVs) able to receive data from itself, other cars and systems, and capable of driving themselves or accepting control from external systems. With an assigned time and travel path, these vehicles could proceed steadily through crowded infrastructure without the stop-and-go operations that cause congestion and reduce fuel efficiency. Many of the enabling technologies, such as adaptive cruise control and lane departure warning systems, already exist.

While there is already existing research on improving road capacities and speeds using AVs, two of the ideas that promise the greatest improvements are autonomous platoons and managed non-stop intersections. In autonomous platoons, or Cooperative Adaptive Cruise Control groups, vehicles communicate with each other to enable them to travel closer together and, possibly, at higher speeds than would otherwise be safe. In managed intersections the vehicles communicate their locations and planned paths with each other or a central system to allow themselves to pass through an intersection without the traditional stop-go light cycle. However, both of the ideas lack modeling support on how they would influence roadway flow capacity and thus time-of-day traffic flow evolutions. Therefore, in order to utilize such concepts to improve the performance of existing road networks, explicit modeling of traffic flow mixed with both conventional vehicles and AVs is required.

Communities will start to see more automated mobile infrastructure such as passenger cars, trucks, air drones and ground delivery robots, as well as more automated fixed infrastructure such as streetlights, traffic signals, energy and water systems, and other services. Automated mobility and infrastructure applications can enable a “system of systems” approach to smart and connected communities. While some communities will benefit from these advancements, others may be left behind. At this interface will be a connected and progressively automated infrastructure system that will manage the flow of people, goods, services, and resources. How will advancement of these infrastructure services affect communities differently and what technologies and modeling approaches can enhance the likelihood of more equitable

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access to these services across communities? Researchers must consider the following aspects of automated applications : 1) the inputs that allow them to operate (energy systems, physical infrastructure, etc.); 2) the outputs they now make possible (improved flows of goods and services), but also 3) do these new infrastructure systems bias towards one set of communities over another in how they are constructed and operated, and how can this be alleviated?

Research Question What are the most promising opportunities for automation to help the movement of people and goods into/out of/through urban and suburban areas while enhancing sustainability? What New Knowledge is Needed

For automated transportation, new knowledge is needed to understand how vehicle automation affects interactions across the urban environment at the systems level. The research community needs to develop advances on how to measure and model systemwide behaviors, responses, and impacts in both projections and near-real time. This is complex because it includes mobility of people as well as goods and services. New knowledge is also needed to enable prescriptive actions to optimize transport in real time and for decisions about long-term infrastructure investments. What Opportunities Will This New Knowledge Create

This knowledge will create new opportunities for research, and novel adaptation of existing research to enhance U.S. competitiveness in automated mobility. It will enable the U.S. to integrate multi-modal transportation services and incentivize behaviors to lower the sustainability triple bottom line of environmental, equity, and economic concerns. It will also allow the U.S. to seamlessly add new modes of transport into the mobility portfolio and guide both public and private investment into the mobility ecosystem. It will also make our systems more resilient and adaptable and increase access and mobility for people with disabilities and underserved populations.

4.2 Infrastructure & Services Transition and the Design of Adaptive Autonomous Sustainable Urban Systems

Infrastructure and services are essential to designing adaptive urban systems for society, and must be integrated into emerging autonomous urban systems. The management of infrastructure and services in a transition to automation covers many aspects, such as planning, maintenance, operation and re-sizing of pre-existing infrastructure and services. Examples include manufacturing and industrial facilities, parking and transportation infrastructure, utilities, warehouse and logistics networks, food value chains, and other systems. The way these systems are used, designed and operated will be substantially affected by automated systems. Services refer to not only those that are provided to directly improve individuals’ quality of life (e.g. mobility, health care, food, water), but also civic services that would be needed for citizens to adapt to autonomous urban systems, such as employment, education, and workforce training. Research is needed on how to maximize social equity, environment, resilience, privacy and economic prosperity regarding both infrastructure and services during the transition to automation.

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Research Question How to effectively manage pre-existing infrastructure and urban system services during the transition to automation? What New Knowledge is Needed

Cities need to understand what parts of the physical infrastructure and urban services needs to be retained, extended, transformed, or retired during the transition to automation.

What Opportunities Will This New Knowledge Create:

This will create the knowledge around the design, planning, and operation of pre-existing infrastructure during the transition to automation. This includes novel theories, methods, and algorithms to assess each component of the infrastructure based on its respective roles in an transitioning autonomous urban system, and how those roles are likely to evolve over time at different stages of the transition. When assessing those respective roles, it is crucial to develop theories and models to predict and quantify the social benefits and costs to enable system-level analysis and decision making. Urban systems automation is likely to link all urban systems more closely together and increase urban system interdependency. For instance, vehicle automation reduces the costs of both passenger and freight transportation, which would in turn encourage more personal trips and deliveries. We need to understand how infrastructure and services are linked among buildings, transportation, food, health care, manufacturing and water, particularly how these interdependencies change over time as we adapt to the incremental deployment of autonomous urban systems. The key is to develop theories and models to understand human behavior, since human beings are the ones who essentially uses and thus link all urban systems. The individual daily activities of people using urban systems that have strong spatial and temporal correlations. When one or several urban systems are deployed with automation at various levels, they could change the human behavior with respect to the way individuals use those urban systems. As the level of automation progresses, human behavior is likely to adapt to those changes, resulting in potentially substantial system impacts. Thus, the design, planning and operation of pre-existing infrastructure and services should be studied in regards to urban system interdependencies related to the scope of and the level of automation. The fundamental knowledge regarding societal impacts of automation and adaptation of infrastructure and services would then enable the policies and strategies that could enhance sustainability. For instance, for people living in low socioeconomic status communities or segregated minority communities, lack of access to reliable transportation is part of a system of interrelated issues which inhibits upward mobility. Not being able to physically travel prevents people from utilizing services, goods, educational opportunities, healthcare, and professional opportunities. A successful sustainable autonomous urban transportation system could improve the mobility and accessibility for these communities in general, but could also initially start from economically prosperous areas during the transition. This would lead to negative outcomes for socially vulnerable and disadvantaged communities. The research community needs to develop theories and policies regarding automated transportation accessibility, reliability, and ease-of-use in disadvantaged communities to improve social mobility outcomes and equity. As part of

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broader sustainability goals, environment impacts, resilience, air quality and other social aspects would also be relevant for researchers to understand the adoption process of autonomous urban systems. Another research gap for autonomous urban systems is understanding how privacy can be maintained and enhanced. As autonomous urban systems are introduced, a large amount of consumers’ data is being collected and stored. Consumers do not want to fall prey to data breaches, where hackers can obtain private information, such as frequently traveled destinations, financial records, and other confidential information. Service providers, in efforts to obtain and maintain market power, do not want to share their own data publicly where competitors and consumers could identify and manipulate their company businesses. However, to enjoy the full benefits of those integrated, inter-dependent and autonomous urban systems, the public agencies would like to use this data to inform their decision making and regulate the service market, as well as improve publicly owned infrastructure and services for communities. It is crucial to understand, at various levels of automation, the risks and benefits of data sharing among different stakeholders and the resilience of the systems subject to probabilistic and stochastic system interruption.

4.3 Tradeoffs at the system of systems level

Urban and community systems are complex interconnected networks. There is need for new theories for systems-of-systems modeling to understand where automation can lead to significant improvements in sustainability, equity, and inclusion. This includes the development of socially relevant modular models, and the integration of those models to predict the impact of automation on land use, people’s behavior, overall energy, water and carbon footprints. This is currently hampered by poor understanding of the complex linkages between models, fragmented and disconnected data sets resulting from siloed efforts to date, the lack of theory for modeling complex community systems of systems, inadequate integration of disparate disciplines and the lack of ontology to bridge those communities, and the lack of a trained workforce that is capable of problem solving from a comprehensive view of system of systems rather than the more traditional viewpoint of a single system element. These shortcomings in our understanding lead to the following key research questions regarding the systems-level tradeoffs that will exist for automating selected components of urban systems and communities.

Research Question How does the integration of automation with humans and infrastructure in the loop systems affect tradeoffs between the underlying systems of systems? How will automation change each system within the system-of-systems framework?

What New Knowledge is Needed Quantitative analysis of the system-level sustainability tradeoffs that automation will introduce will require new knowledge. Specifically, we will require 1) new theories about how human behaviors (both short-term and long-term) will be changed by the adoption of automation strategies, 2) understanding of feedbacks and rebound effects from automation of selected systems (e.g. transportation or building infrastructure), 3) new theories to model the linkages and feedback between the elements of the system

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(e.g. increased number of personal transportation miles per year per person due to ease of access and low cost), 4) better understanding of system dynamics and uncertainty, and 5) data validation. What Opportunities Will This New Knowledge Create Addressing these specific knowledge gaps will create the tools needed to gain a more holistic view of sustainability of urban and community systems. It will enable quantitative analysis of the impact of automation on each system element and tradeoffs between systems. This will lead to the adoption of automation strategies that are efficient, equitable, and resilient, and that improve the quality of life for community residents.

There are existing models and datasets to leverage to build validated systems models to quantify the tradeoffs created by automation in urban and community systems. For example, we can leverage existing models and simulation tools for single systems or systems elements (e.g. FRED (Public health simulation), ISOs for electricity, agent-based activity simulation, traffic flow simulations). We can leverage existing machine learning techniques to understand and work with data collected on system performance, or through mining of existing open data platforms.

Importantly, we will need to create testbeds to evaluate the sustainability of a given automation scenario. These tests need to include all relevant stakeholders: All public stakeholders, private firms such as freight companies, health care service, mobility service, utilities and independent system operators (ISOs), local foundations, and scientists and engineers from a broad range of disciplines including economists, engineers, systems theorists/models, behavior scientists, social scientists, ethicists, sociologists and others. Finally, there is a need to create an educational program to develop a core curriculum that promotes interdisciplinary programs to encourage cross-system analysis and to identify the linkages between system components, and to educate a workforce capable of designing, engineering, and maintaining automated systems.

4.4 Governance - Community, Social, Economic, and Equity/Justice Issues with Respect to Automation

While research communities surrounding automation in urban systems have independently (in silos) made great strides in the last decade, less attention has been given to identifying convergence and synergies between these communities, and incorporating sustainability concepts and metrics from the beginning of technological developments can shift the trajectory of urban systems sustainability. The dynamic interplay of autonomy (human agency, self-rule, self-decision making) within autonomous systems was an important tension that workshop attendees discussed in earnest to better address the issue of how we can use autonomous systems to enable autonomy within a framework of sustainable urban systems. Similarly, there is a desire to ensure that automation in urban systems increases social mobility across society rather than polarize it. We want to ensure that automation enables and ensures transparency and accountability, especially when it comes to the deployment and development of automation. With respect to governance and the rule of law, who decides what is the “greater good” and how can

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automation help inform governance by shedding light on the tradeoffs and ensure that the data is not biased from the beginning. Given the diverse and interdisciplinary nature of workshop attendees, discussions of autonomous sustainable urban systems quickly evolved into the role of governance and the related community, social, economic and equity/justice issues with respect to automation. Research Question How do we promote governance of autonomous technologies in an urban environment to ensure sustainability, including equity, justice, and maximum positive social and economic impact, and how can technology aid such governance while preserving and respecting human autonomy? What New Knowledge is Needed Related to this research question are concerns regarding the lack of data to measure the impact of automation and autonomous systems on society. While there are measures of quantitative output (manufacturing production output changes as a result of the introduction of automation/robotics, for example), there is little and/or disconnected data equally across communities and no robust ways to translate the qualitative impacts on society as a result of autonomation. There is only preliminary empirical evidence of automation improving or worsening sustainability. We seek to better measure and model general human factors that affect the development of sustainable urban systems such as new technology to measure user satisfaction (for example, create an automatic feedback loop as part of the system). We require knowledge on how to quantify human action with respect to physical and natural systems to better measure the inter-relationship to resilience, social sustainability, active transportation (walking/bicycling) as a way to protect health (improve quality of life and longevity). There is concern that there are disciplinary blind spots that hinder good governance and therefore there is a need for more diverse domain experts to work collaboratively to solve these problems. There is a need for more transparency in order to build trust within communities and better align policy decisions with the intended outcomes and guide governance models. Better informed governance could help provide better outcomes for autonomous systems and increase the adoption of sustainable urban systems. We must also address the interconnectedness of urban areas with their rural neighbors and build governance and policies that are more regional in nature. We need to better capture and communicate/broadcast/share best practice of autonomous sustainable urban systems in order to help build trust across communities (equitably). Experiments are costly and many require that we measure impact through new data sources and methodologies that don’t yet exist. There is a desire/need for controlled testbeds or simulations where we could better measure the impact, consequences (intended and unintended) of automation. There is an urgency to create the buy-in needed through testbeds that are pilot projects – innovative, iterative projects that keep going, improve, fail fast and learn/iterate - in order to help build trust within communities. This will enable communities to develop regulatory frameworks that can more quickly identify when unintended consequences come up – for example, pilots on autonomous mobility can enable this type of framework.

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There is a need for more interdisciplinary research, including the introduction of new governance structures through design thinking. Basic science on how people make decisions about technology is missing and in order to better understand autonomous sustainable urban systems, this basic research question will need to be addressed along with the creation of a methodology in order to measure its impact. Similarly, more anthropological data sets (pairing qualitative with quantitative data) is also needed. In addition to the individual datasets there is a need to measure how communities engage with autonomy, when the datasets are missing, to enable interventions that could be used to inform and address this gap through governance and policy decision. There are several existing capacities, datasets, methods that workshop attendees believed could be brought to bear to address the research questions. They include datasets from companies such as Nest (smart thermostats) and smart energy meters, public utility datasets, autonomous vehicle safety data, community based participatory research (PDPR), and methods such as randomized control trials, “difference-in-difference” methods, surveys, insurance data, etc. We also identified some partners to help solve these research questions and they include: community leaders, public utility companies, public-private partnerships, transit agencies, academics (working on automation, ethics, privacy/security, sustainability), unions, trade schools/community colleges, regional agencies such as the Southwestern Planning Commission (SPC), as well as Metro21: Smart Cities Institute at CMU and its affiliate, the MetroLab Network, an alliance of municipal/university partnerships focused on civic-tech innovation. What Opportunities Will This New Knowledge Create While we can create simpler, one-dimensional models for transportation systems, when we try to factor in the more complex issues of urban systems, it’s much more complex and complicated. This new knowledge will help create more robust models for autonomous sustainable urban systems that can more equitably and sustainably inform policy decisions and governance issues that engage multiple stakeholders and their different perspectives. This research will help enable a new model for community engagement that is transparent and trustworthy, therefore more sustainable and long-lasting. Addressing these research questions will help create a more holistic and robust ways of measuring true return on investment beyond financial considerations. It will enable a better linkage between sectors that now are silos of isolation (public utilities isolated from public health agencies isolated from corporations isolated from the citizens of the communities themselves). We will be able to better measure the complexity of the solution, the communication of values, the right financial incentives (for the private sector and for individuals) to ensure that the best possible societal outcomes. When determining the “best” societal outcome, efficiency isn’t always the optimal solution. This new knowledge will enable a strategy of interdisciplinary partnerships and deployments, developing a science for how to foster sustainable innovation within a system. It will help us better understand the relationship between autonomy and the economy and autonomation and human behavior so we can identify and address inefficiencies, and inequities. It will enable us to measure the impact of sustainable urban systems beyond just economic output (revenue, production, return on investment, etc.). This new knowledge will also establish the data and analysis frameworks to make sure that the tradeoffs and benefits between communities can be assessed. This will enable policy and decision makers to better

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understand the problems of equity and what the urban environment does affect this – such as differences in life expectancy across neighborhoods, public health clusters and transportation related to these issues, and green spaces and data regarding their impacts. This knowledge will also enable us to develop a science for understanding how to foster urban systems in the context of a system of systems utilizing networks such as the MetroLab Network in order to build scalability across urban regions and across the country. For example, this new knowledge can help empower citizen scientists who are empowered by the data uncovered in the autonomous urban systems, to help affect policy changes and inform governance (such as improving air quality, water quality, etc.) Through “autonomous automated autonomy” the goal is to have human and machine learning decision makers together, working towards the ultimate goal of a sustainable urban system. This system must help create a resilient, equitable, flexible governance process that evolves alongside the technology. By holistically addressing autonomous sustainable urban systems, we have the ability to uncover new knowledge on its impact on economic mobility through enabling the reskilling of workers more effectively and efficiently. This knowledge will help create policies to enable faster adoption to automation to reduce the length of negative impacts on employment transition, for example.

4.5 Buildings and the Built Environment, Land Use, & Resilience About 40 percent of the annual energy consumption in the U.S. occurs in buildings, which is similar to the proportion of the energy used in buildings in other countries. Commercial buildings, in particular, represent almost half of building energy use (i.e., 20 percent of the total)17. There are large opportunities to reduce the energy use in buildings through efficiency upgrades, optimized operation, and user engagement, as evidenced by many studies (e.g.18,19 A large fraction of the energy used by heating, ventilation and air conditioning (HVAC) systems is wasted due to faulty operation20, so merely identifying and correcting these faults would result in a substantial reduction of the total energy used. Advances in sensing and wireless communication technologies have made it possible to instrument more and more buildings, which has led to numerous new opportunities to better understand and optimize their energy consumption patterns. Though there are significantly more sensing and actuation points in buildings today, leveraging them to make improved data-driven decision-making poses engineering and scientific challenges spanning areas as diverse as computing (e.g., devising efficient algorithms for data processing), hardware (e.g., designing low-power, low-cost sensors) and government (e.g., enacting policies to promote standard information models). Research Question What opportunities does automation enable us to improve the productivity of urban living by aligning the goals of energy efficiency, human comfort/experience, and food production? What new knowledge is needed? The relationships between indoor and outdoor environments are not well understood at the temporal and/or spatial scale that they are required to answer this question. For example, the relationship between outdoor/indoor air quality is not understood well-enough to drive decisions at the level of the building

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automation system. There is also a general lack of connected empirical data regarding energy efficiency interventions, human comfort, light pollution, air quality, etc., especially at the scales that would matter for answering these questions at the city or neighborhood level. The little empirical data that exists does so in silos and requires manual integration. Furthermore, the efforts to enhance empirical data collection and, ultimately, enact policy and/or technological changes based on the knowledge they generate, will also require that we improve our understanding of the ways in which residents and firms respond to these. Some of the data and analyses needed required advances in sensor, computing, and battery technologies are also needed. Interdisciplinary advances are needed at the intersection of building science, energy policy, design optimization, life cycle assessment, automation design, and design and deployment of interior and exterior sensor systems. What Opportunities Will This New Knowledge Create This new knowledge will create opportunities for sustainable, healthy, efficient productive urban spaces. These include high performance, multi-functional green buildings, with lower/no ecological footprint and potential for integrated agrofood systems and nutrient reuse. The knowledge will also enable opportunities for neighborhoods with efficient residential density and sustainable land use. Some relevant partners to help solve these issues include utilities, transportation authorities, professional development organizations, and commercial building operating organizations.

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5 References 1. UN. 2018 Revision of World Urbanization Prospects. (2018). 2. IPCC. Climate Change 2014: Mitigation of Climate Change (Vol. 3). (Cambridge University

Press, 2019). 3. Milanovic, B. Global inequality recalculated and updated: the effect of new PPP estimates on

global inequality and 2005 estimates. J. Econ. Inequal. 10, 1–18 (2012). 4. National Academies of Sciences, Engineering, and Medicine and others. Pathways to urban

sustainability: challenges and opportunities for the United States. (National Academies Press, 2016).

5. Bogue, R. Towards the trillion sensors market. Sens. Rev. 34, 137–142 (2014). 6. Council, N. R. & others. Autonomy research for civil aviation: toward a new era of flight.

(National Academies Press, 2014). 7. Delbecq, A. L. & Van de Ven, A. H. A Group Process Model for Problem Identification and

Program Planning. J. Appl. Behav. Sci. 7, 466–492 (1971). 8. Anderson, J. et al. Autonomous Vehicle Technology: A Guide for Policymakers. (RAND

Corporation, 2016). doi:10.7249/RR443-2 9. Harper, C. D., Hendrickson, C. T., Mangones, S. & Samaras, C. Estimating potential increases in

travel with autonomous vehicles for the non-driving, elderly and people with travel-restrictive medical conditions. Transp. Res. Part C Emerg. Technol. 72, (2016).

10. Fagnant, D. J. & Kockelman, K. M. The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios. Transp. Res. Part C Emerg. Technol. 40, 1–13 (2014).

11. Greenblatt, J. B. & Saxena, S. Autonomous taxis could greatly reduce greenhouse-gas emissions of US light-duty vehicles. Nat. Clim. Chang. advance on, (2015).

12. Harper, C. D., Hendrickson, C. T. & Samaras, C. Exploring the Economic, Environmental, and Travel Implications of Changes in Parking Choices due to Driverless Vehicles: An Agent-Based Simulation Approach. J. Urban Plan. Dev. 144, 04018043 (2018).

13. Wadud, Z., MacKenzie, D. & Leiby, P. Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles. Transp. Res. Part A Policy Pract. 86, 1–18 (2016).

14. Brown, A., Gonder, J. & Repac, B. An Analysis of Possible Energy Impacts of Automated Vehicles. in 137–153 (2014). doi:10.1007/978-3-319-05990-7_13

15. Khan, A., Harper, C. D., Hendrickson, C. T. & Samaras, C. Net-societal and net-private benefits of some existing vehicle crash avoidance technologies. Accid. Anal. Prev. 125, 207–216 (2019).

16. Harper, C. D., Hendrickson, C. T. & Samaras, C. Cost and benefit estimates of partially-automated vehicle collision avoidance technologies. Accid. Anal. Prev. 95, (2016).

17. EIA. Monthly Energy Review. (Energy Information Administration, 2017). 18. Kiliccote, S., Piette, M. A. & Hansen, D. Advanced Controls and Communications for Demand

Response and Energy Efficiency in Commercial Buildings. (2006). 19. Froelich, J., Everitt, K., Fogarty, J., Patel, S. & Landay, J. Sensing opportunities for personalized

feedback technology to reduce consumption. in the {CHI} workshop on Defining the Role of {HCI} in the Challenge of Sustainability (2009).

20. Brambley, M. R. et al. Advanced sensors and controls for building applications: Market assessment and potential R & D pathways. (Pacific Northwest National Laboratory Washington, DC, USA, 2005).

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6 Appendix A: Workshop Agenda

Monday July 29, 2019

9:30 AM – 11:30 AM Room is open for networking and preparation (optional)

11:30 AM – 12:00 PM Workshop registration

12:00 PM – 1:00 PM Official welcome, kickoff presentations, and lunch

1:00 PM – 1:15PM Framing the workshop and expectations

1:15 PM – 2:45 PM Structured elicitation session

2:45 PM – 3:15 PM Break

3:15 PM – 3:45 PM Session to group ideas

3:45 PM – 4:00 PM Session to categorize and rank

4:15 PM – 5:00 PM Breakouts to write descriptions OR if 2 elicitation groups, report-outs

5:00 PM – 5:15 PM Break

5:15 PM – 5:45 PM Reflections by City of Pittsburgh’s Karina Ricks

5:45 PM – 6:00 PM Framing day 2 activities

6:00 PM – 7:00 PM Transition and networking

7:00 PM – 9:00 PM Working dinner

Tuesday July 30, 2019

8:30 AM – 9:00 AM Breakfast

9:00 AM – 9:15 AM Reflections presentation

9:15 AM – 9:30 AM Introducing breakout session charge and templates

9:30 AM – 11:30 AM Breakout sessions (Break as needed)

11:30 AM – 11:45 AM Synthesize reports for 5-minute report out flash talks

11:45 AM – 12:30 PM Lunch, with Keynote Speaker Dr. Paul Cohen, Founding Dean, School of Computing and Information, University of Pittsburgh

12:30 PM – 1:45 PM Breakout group reports

1:45 PM – 2:00 PM Break

2:00 PM – 3:00 PM Guided Discussion - main takeaways, finalize recommendations, leave with assigned action items

3:00 PM Adjourn

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7 Appendix B: Workshop Attendees

First Name Last Name Organization

Burcu Akinci Carnegie Mellon University

Abdullah Alarfaj Carnegie Mellon University

Dominic Bednar University of Michigan

Mario Berges Carnegie Mellon University

James Blakley Intel

Charles Catlett Argonne National Laboratory

Chelsea Cavlovic Carnegie Mellon University

Rachael Chambers Metro21

Paul Cohen University of Pittsburgh, School of Computing and Information

Jenna Cramer Green Building Alliance

Katherine Flanigan University of Michigan

Santiago Garces City of Pittsburgh

Ray Gastil Carnegie Mellon University

Corey Harper Carnegie Mellon University

Christine Hendren Team Helium LLC

Chris Hendrickson Carnegie Mellon University

Jose Holguin-Veras Rensselaer Polytechnic Institute

Paulina Jaramillo Carnegie Mellon University Michael Kane Northeastern University Kristen Kurland Carnegie Mellon University Jiayu Li Carnegie Mellon University Karen Lightman Carnegie Mellon University Leah Lizarondo 412 Food Rescue Alex London Carnegie Mellon University Greg Lowry Carnegie Mellon University Jerome Lynch University of Michigan Christopher Martin Bosch Research and Technology Center Destenie Nock Carnegie Mellon University Brendan O'Connor NC State University Albert Presto Carnegie Mellon University Sean Qian Carnegie Mellon University Eshwar Ravishankar North Carolina State University Karina Ricks City of Pittsburgh

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Thiago Rodrigues Carnegie Mellon University Costa Samaras Carnegie Mellon University Jonathan Sprinkle NSF Parth Vaishnav Carnegie Mellon University Yang Wang Missouri S&T Allanté Whitmore Carnegie Mellon University

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8 Appendix C: NGT and Workshop Process

8.1 Pseudo-NGT as Applied to Eliciting Research Priorities for the Role and Impact of Automation in Sustainable Urban Systems

Introduction The pseudo-Nominal Group Technique (pseudo-NGT) is an organized approach to eliciting opinions from a group of individuals, structured so as to facilitate discussion across a group while ensuring that diverse perspectives are heard. Guided by an appointed facilitator, each individual is given an equal opportunity to offer her or his views about the topic around which the pseudo-NGT session is centered. The approach utilized here differs in one small but important way from traditional NGT. In traditional NGT, participants in the group are asked to come prepared to advocate for one of a prescribed set of options that would be a priori identified and described in materials distributed ahead of the meeting by organizers. In the pseudo-NGT process utilized for this meeting, participants were instead asked to generate recommendations, in an open-ended sense, in reaction to a charge question and to some preparatory documents that summarized the challenges and opportunities for research in general in relation to Sustainable Urban Systems Through Automated Infrastructure Networks (SUSTAIN). After reflecting on preparatory materials and in consideration of their own individual expertise, participants were each asked to come prepared to advocate for the top priority research question to ask to understand how automation can improve sustainable urban systems. These facilitated discussions are typically most successful with group sizes ranging between 18-25 at the most. Given the workshop attendance of xx people, workshop participants were divided into two groups that each carried out a separate pseudo-NGT process, with each group responding to the same prompt. The output of NGT and pseudo-NGT processes is typically a list of priorities, distilled and sometimes ranked. As indicated by the charge to participants, this workshop was designed to generate a short list of key research questions to advance our understanding of the role of automation in sustainable urban systems. This list of opportunities was generated the first day through a guided brainstorm and structured grouping process. The resulting short list of opportunity areas were then addressed in further detail in dedicated smaller break-out groups on Day 2. These break-out groups were charged with working through a guided template to build out more detailed understanding of the knowledge gaps, capabilities and key opportunities. Ground Rules For best success in utilizing the tightly scheduled time for maximum output during the pseudo-NGT process, it is helpful to set expectations and agree to process-specific etiquette in advance of breaking into groups.

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Ground rules agreed upon for the facilitators of each of the three breakout groups were to: ● Capture participants ideas as close to verbatim as possible so that people are visibly able to see

that their input is driving the process. ● Gently but strictly enforce the schedule and NGT time limits using an audible timer. ● Make any real-time judgment calls about the process with the guiding principles in mind to make

sure everyone feels adequately heard yet trusts the leader to stay true to the structured process, and to avoid derailing tangential discussions by staying focused on the charge.

● Ground rules requested for the participants of each of the three breakout groups were to: ● Be on time and engaged for all portions of the sessions, ideally with zero connection to

technology. ● Honor time limits. ● Refrain from interrupting, honoring the NGT round robin structure to utilize one’s allotted turns

to voice any dissenting opinions. ● Honor the progressive design of the workshop, so that once ideas have been consolidated,

evaluated or voted on, the group focuses on the next steps at hand without referring to any potential previous disagreements. (In exchange, it is promised that dissent will be captured in sidebar and represented in workshop report.)

● Trust the process and be ready to harvest new ideas from yours and others’ contributions. Day 1 The goal of Day 1 was to generate a distilled list of priority research questions to address in order to understand how automation can improve sustainable urban systems Each of the two break-out groups had their membership pre-assigned by conference organizers, with a consideration toward maximizing a diversity of discipline, sector and perspective in each group. Each group met in a closed room set up in a U-shaped format so that all participants and the facilitator were visible to one another for the entire discussion process. As a starting point, each group was provided a suggested subset of overall FEW nexus sustainability challenges as listed in the NSF report circulated as a pre-read for the event, though participants were not required to limit themselves to only these areas if one that they felt strongly about fell outside those bounds. Round-Robin Displayed on the projector screen of each room was the charge to participants, to maintain focus on the day’s task: “What is the most important research question to ask to understand how automation can improve sustainable urban systems?”. The process consists of a timed round-robin elicitation of each individual’s opinions and reasoning for their nomination of top priority area, with multiple rounds carried out until everyone’s ideas were represented (the agenda was designed so that this would be possible within the timeframe; typically a group of ~20 people needs 1.5-2 hours for the round robin brainstorm process). Each workshop participant, going around the U-shaped table in order, was given a timed 90 seconds to present her or his case for why their suggestion should be ranked as a high priority for further attention in a Day 2 breakout group. (See Figure 1, excerpted from the brief training presentation made to all workshop participants prior to the pseudo-NGT process). Though participants were asked to address one topic per turn, in terms of content one could choose to use their allotted time in whatever manner they

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preferred: to advocate a new idea, to support a previously suggested choice, to critique or de-prioritize a previously suggested choice, or to offer a rebuttal to a previous critique. No visual aids were allowed by participants, but every person’s contribution was captured on a separate, numbered sheet of a flip chart, which were then placed in order around the perimeter of the room. Throughout this process, the wording on the flip charts is verified as adequately representing the intended meaning of the contributor; it is explicitly forbidden to focus on consolidating points, rather, all of the ideas are listed separately to maintain the purity and momentum of the brainstorm. For some participants, frustration at not being able to add a point or offer an addendum to the brainstormed idea during the flow of conversation can be a collateral effect of protecting the idea-sharing momentum and equal speaking time afforded to each person. To alleviate this, everyone was given a stack of post-it notes at the outset of the exercise and encouraged to write their questions, references, suggestions, and related thoughts with the number of the flip-chart sheet in the corner. After the NGT session, everyone was invited to place their post-its on the wall on the appropriate sheet. On the evening of the first day, the facilitator transcribed the written flip-charts and all associated post-it notes into an organized Word Document for distribution and reference of all break-out groups on the second day. At the end of this round-robin brainstorm process, the room is filled with numbered ideas representing the thoughts of all group members.

Figure 1: NGT Guidelines for Participants Consolidation The field of ideas is then combined and narrowed so that there are a feasible number of high priority ideas for the break-out groups to explore critically in the next phase. The facilitator leads the group through a loosely structured process of seeking consensus for which of the brainstormed areas are redundant or similar enough that they should be grouped into a single priority area. For this workshop, a prompt appeared on the wall of the room with a guiding criterion for whether or not two numbered sheets should be lumped together in one: if the priority was elevated to the top for further consideration on Day 2, would further evaluations in terms of challenges, existing capacities, datasets, and methods be notably different or would it make sense for them both to be part of the same targeted proposal? Would discussion of one area really cover both? The two brainstorming groups handled the grouping process according to

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their collective preference for whether to have people offer suggestions of ideas that jump out as belonging together, or whether the facilitator would systematically start with #1 and ask for any areas that should be consolidated, then move forward around the room. Once consolidated, a title was communally decided for each consolidated area that encompassed all aspects included in the grouped area. This process typically takes ~30 to ~45 minutes, and by the end of this exercise the group has produced a streamlined list of 6-8 priority research questions. The result of the Day 1 process was a list of 14 high priority research questions. These high priority questions were presented in plenary by a representative of each of the brainstorming groups, so that by the end of the day, all workshop participants were aware of the top 14. Day 2 The goal of Day 2 was to explore the highest priority ideas from Day 1 in detail, generating insight on next steps through exploration of existing datasets and methods, capacities to address knowledge gaps, and potentially important partnerships for addressing Sustainable Urban Systems Through Automated Infrastructure Networks. The primary success metric for the workshop was the highlighting and articulation of key research opportunities that are currently not being funded and could represent knowledge gaps ripe for impactful research. Final consolidation and ranking In the morning of Day 2, the facilitator presented the consolidated 14 ideas from the Day 1 process, along with the charge for Day 2. The clusters of flip charts were posted on the wall in groupings so that each of the 14 groupings were around the walls of a large room. Each participant was given 6 sticker dots to place on their 6 favorite options, and given 10 minutes to vote by placing a sticker on the title sheet of the cluster. The top 14 ideas and their respective numbers of votes were: 1. Mobility/Robocars/Transportation – 6 2. Building and Built Environment, Land Use, Resilience – 8 3. Infrastructure & Services Transition - 9 4. Human Factors - 7 5. Social/Economic Impact/ROI - 9 6. Info/Privacy/Sensors - 7 7. Adoption of Automation - 5 8. Design of Adaptive Autonomous Sustainable Urban Systems - 18 9. Trade-offs at the systems-of-systems level - 17 10. Governance - 9 11. Applications - 16 12. Equity/Justice - 14 13. Methodologies for Evaluating Impact - 2 14. Scalability and Flexibility - 7 With the participants from both brainstorming groups having had the opportunity to review all of the top 14 ideas in slightly more detail during the voting process, the facilitator led a rapid and organic process of

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combining some of the like areas, soliciting input and verification of the appropriateness of these groupings from the plenary group. This resulted in 5 consolidated winning ideas, which were then addressed by breakout groups. The 5 priority research question groupings were:

6. Infrastructure & Services Transition Combined with Design of Adaptive Autonomous Sustainable Urban Systems (Combination of #3 & #8 of the top 14; total 27 votes)

7. Trade-offs at the system of systems level (#9 of the top 14; total 19 votes)

8. Governance Combined with Equity and Justice Combined with Social Economic Impact (Combination of #5, #10 & #12 of the top 14; total 32 votes)

9. 11+1=Applications Combined with Mobility/Robocars/Transportation (Combination of #1 & #11 of the top 14; total 22 votes)

10. Building and the Built Environment, Land Use, & Resilience (#2 of the top 14; 8 votes) The facilitator noted that though we had to down select in order to prioritize our time in the workshop, the remaining top research question priorities from Day 1 that were not selected for further exploration in Day 2 breakouts were not being dismissed as less important or useful. The nature of lists emerging from the Pseudo-NGT process is that they are not typically parallel competing ideas, and therefore choices may not be either-or. Many of the research questions complement one another or may represent threads of concepts that pertain to multiple other ideas. Groups were provided with a document detailing the consolidated list of all ideas and post-its from the prior day, which they were encouraged to refer to and include any relevant pieces of the unselected #4, #6, #7, #13 and #14, or any of the other ideas outside their cluster, as useful. For each of the 5 prioritized areas, a smaller dedicated break-out group of between 4-6 people was asked to carry out a self-facilitated process to explore their idea further, guided by a minimally structured template. The groups self-selected based on interest and knowledge base. Part 1 of the template appears below in Figure 2. Groups were asked to explore the knowledge gaps by reflecting on what had been the barriers to solving the research question thus far, recording what known resources datasets are now available to assist in addressing the research question area, and brainstorming beneficial collaborations and partnerships for making an impact toward the research question area. One group member filled out the template to consolidate these ideas for the group.

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Figure 2: Break-out Group Template Page 1 Once satisfied with this discussion, each break-out group worked through the second page of the template to guide development of text for the final report. The prompts in this template were designed by the workshop leaders with guidance from the facilitator to scope the exercise; the intent of the prompts was to help participants work in a proposal mindset, envisioning what the motivation, novelty, and approaches might be relevant for addressing these key identified research questions. Part 2 of the template appears below in Figure 3.

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Figure 3: Break-out Group Template Page 2 At the end of Day 2, each group presented their results. Finally, in a 30-minute wrap-up discussion, the workshop participants participated in an informal ad-hoc round robin to present their response to the following question: If someone magically awarded you a grant today, what would you do with it to address the SUSTAIN space? The purpose of this exercise, which was a surprise to the participants in the “final discussion” session, was to get a reflexive prioritization of the most critical way the participant thought their expertise could add value to the host of interesting questions they had been spending two days engaging deeply in considering. This differs from the first exercise both in the fact that it is a flash-talk of a few seconds, and that the people have been immersed in interdisciplinary discussions, new ideas, and repeat themes that will have been amounting to a take-away within their own minds. The raw responses to this question were as follows:

1) How do I bring food production/management into a city in a sustainable way? Focus: a) Try to understand what the effects of this are at a systems level. b) Does it even make sense to do? c) How do I look at the interactions of the systems together that allows me to calculate the

efficiency gains and evaluate whether I’m doing what I want to do? d) With that application in mind I would see how all the other

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2) Shortage of collaboration between social scientists and engineers/natural scientists. Pursue a better understanding of the choices people make with regard to choosing different modes of transportation. Complex models in engineering systems – weather, building, transportation, etc. – but there is a shortage of understanding of behavioral modeling aspects.

3) Previous (#2) concept sentence applied to mobility. Meta-level – need for data and lack of evidence.

4) Data + privacy: We missed an opportunity to regulate financial services during the financial crisis – maybe this tech company focus on data ownership is going to be this chance to make a trade-off with corporate interests and data ownership.

5) Modeling the data and the decision-making processes to prove out the success of projects; how do you do this very quickly and repeatedly in different domains while minimizing the effects of unintended consequences. Using systems and simulation work,

6) Systems and science of change – opportunities for engineering models of social systems to work toward design of autonomy, especially in terms of decisions and learning, both by humans and by the controlled systems that we’re developing. That requires laboratory scale up to complex full city scale experiments at all timescales.

7) Systems of systems proposal, building off of what has been done in the energy-water nexus modeling. Develop a s-o-s model that looks at holistic modeling of sustainability, working with stakeholders to create an objectives hierarchy including the values and how they measure aspects of sustainability. Then integrate different extant models in the energy-water-food space, and use those to compare and contrast different automation approaches.

8) Sustainability in the science of cities itself is an issue – have to show some successes pretty soon so we have some wins and people don’t think of. Analogy of cities and tumors – really hard to change, involved systems that work extraordinarily well and persist. Cities are hard to kill – it is hard to have an impact. How do you pick a problem where you can have an impact? Food deserts. There must be a handful of pathologies of cities that have been resistant to change, that if you could bring the right technology to bear, you could show extraordinary success rapidly.

9) Integrate the decision-makers directly into the research realm in an immersive and interactive game environment. Develop a serious game or electronic game that social scientists and engineers would develop but could be played by municipal decision makers. This could be played with stochastic deployment of automation technologies and other background engineering mechanisms, but the decisions would be in the language of the people playing the game. (SIM-City expansion pack).

10) See how local cars impact our environmental sustainability. How zero occupancy travel could affect our mobility management, and how this would impact different socioeconomic groups from an environmental justice perspective.

11) Human factors remains a blind spot. Social aspect of changing cities, applying quantitative methodologies to understand behavioral influences and impacts of changes to systems.

12) How to put the power back to the people, very literally as an energy justice scholar. Thinking about ways to integrate community engagement into all of these problems, invite them to be part of the design of solutions and research methods. Build education programs to increase automate legitimacy and adoption. Industrial age Information age an energy transition is required, and we need to be inclusive in asking ourselves why automation is needed.

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13) How does automation make the decarbonization of the economy easier, and what ways can it make it harder, to what extent is it a red herring? Focus on one-two sectors, starting with transportation.

14) Three basic questions that define the relationship to data/information is and autonomy. Who knows where the information and how it flows? Who decides? Who decides who decides? Study these questions in a quantitative sense.

15) Urgency! [Decision-makers in cities] can’t wait - so we need to fail fast, and do pilot projects, at micro-scale, bring in community partners, iterate and inform policy change, decisions about investments, bring in public and private people and capital. Some of this doesn’t need to be novel technology that hasn’t been invented yet. Let’s use this in a public-private partnership in a fund working with municipalities.

16) Get pilots going on incentivizing the walkable city. Accept cultural, ability differences, etc. and then focus on using automated systems once we understand what we want to incentivize and how this can work so that new habits can form.

17) Choose an application as a test-bed, and would choose district level food-energy-water nexus and maximize productivity. This could be through environmental sustainability, human health and contentment. How to integrate existing technologies and what new technologies are needed with the least environmental impact.

18) Implementation of automated systems with application for robocars, building, etc. Scalability and feasibility of expanding automation systems across different applications and communities.

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9 Appendix D: Detailed Outputs from the Day 1 Brainstorm Groups

The tables below captures the detailed results of the Day 1 Pseudo-NGT Round Robin process. These are grouped under the top 14 consolidated ideas. The summary points were provided by the report-out representative at the end of Day 1. The “elicitation session text” includes each individual flip chart page as articulated, captured and verified with each idea numbered during the Day 1 process. Because the numbered elicitation responses were grouped into broader themes, the numbers listed are out of order. Other workshop participants were encouraged to add ideas on post-its and place them onto the appropriate flip chart sheets at the end of the session. These post-it comments are noted in this section as well.

1. Mobility, Robocars, Transportation Summary Points Elicitation Session Text

• What are the technologies and policies to maximize the benefits and minimize the damages from automated vehicles

• How do we ensure synergies across mobility modes?

• What is the feasibility and benefit of providing universal basic mobility?

1. Automated Vehicles (AVs). How can AV reduce CO2 from urban mobility ? Post-its: • What are policy interventions needed vs. how much is created / enabled through

market efficiencies? • What are the direct and indirect reductions? • Can we look at nano-filters to do this? • How to power automated vehicles? • Only if they are used in conjunction with public transportation 28. Should we ever build another mile of light-rail? What is the most efficient allocation of capital to enable mobility in cities? Post-its:

• What do we prioritize paying for? • What about cost of digital infrastructure?

21. How do we ensure there will be synergies between mobility modes and how do we quantify the impacts on health outcomes of a reduction in active transport?

22. What policies do we need to put in place to deal with increased zero occupancy travel demand from automatic vehicles? Post-its:

• Can we ban zero-passenger vehicles because they aren’t efficient? • The integration between TNC with automation increased sharing vs. zero

occupancy? Less vehicle ownership? 10. Is it viable or beneficial to offer universal basic mobility to urban citizens? Post-its:

• What costs are associated with universal mobility? & What are the factors that make this viable?

30. How might shared autonomous mobility affect sustainable urban systems? Post-its:

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• Shared autonomous mobility: how to weigh who I will or will not travel with? Should I be banned from expressing some preferences?

• Essentially, could there be HOV zones, neighborhoods or cities? (instead of lanes). What impact would that have on economic, environmental and social systems?

6. Is widespread fully automated vehicle technologically, economically and socially feasible in the next 40 years? Post-its:

• Argue this has been addressed and we are moving forward as a result. The time frame might be off (40 years) but it’s feasible for AVs to become ubiquitous.

• What is the role of 5G?

2. Building and Built Environment, Land Use, Resilience Summary Points Elicitation Session Text

• How can automated systems improve the Productivity of Urban Living in Shared Environments?

• Can automated building systems minimize people’s exposures to environmental contaminants and minimize building energy use?

• How do we promote the diversification equity and equality in these urban centers?

9. Can automating building energy systems aid in lowering its energy demand?

• Renewable energy more feasible? • Data analytics role? • Can we make hybrid buildings?

Post-its: • Making the savings bankable • Expand to extend space (with climate change etc.) • What is the cost of technology that is delayed in a way

that is not cognizant of human behavior 17. How do we increase density of use in single family home zones, without increasing parking density? Post-its Tying into #30 can there be HOV zones instead of lanes? Could this achieve the desired outcome? Diversity is work/ life will build wealth for more people by creating areas with high property values Urban sprawl consideration (better more efficient) with automation of passenger and energy, sprawl is likely 24. Can automated building systems minimize people’s exposures to environmental contaminants and minimize building energy use? Post-its: “Can” impact, probability, challenges 7. How do we promote the diversification equity and equality in these urban centers? ~Diversity within centers/clusters ~What moves? Do people move or do the things move?

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35. How can automated urban systems increase two connection between proximity/? And equity? Post-its: How will employment and job displacement look? And how can we prevent displacement with reskilling?

3. Infrastructure and Services Transition Summary Points Elicitation Session Text • What do we do with pre-

existing infrastructure as we transition to new automated systems, and how to manage equity, environmental, resilience, privacy, and economic impacts

• Examples are energy facilities, manufacturing, businesses

• What is the optimal capital allocation of infrastructure under uncertainty

8. How do we encourage leapfrogging of technologies How do we prevent “lock-in” of obsolete and unsustainable technologies? Given transfer o tech from where it is invented to other places in the world (think of old US trucks being sold in Mexico). Post-it:

• How can we maintain testing and regulatory flexibility while implementing emerging technology in urban areas?

31. What does the next generation of infrastructure management look like? • Multiscalar • Interdependent

Post-it: • How will the future of buildings and workplaces be affected?

5. What do we do with pre-existing infrastructure as we transition? E.g.: Manufacturing facilities, parking lots, urbanization, and rural areas? Post-its:

• As facilities go out of services, so do jobs associated in such facilities. This can prevent global acceptance for automation – what to do?

• Lock in value transitions. • How do you deal with transient ill-effects? Path dependency, Valley

of death, dead ends. 33. As we move toward more automated urban systems, what do we need to do for reskilling, and how does automation as it grows affect economic mobility? Post-it:

• What tasks/skills and professions will the move to sustainability create and require?

32. How can we integration and optimize automated infrastructure across: • Buildings, Transport, Food, Offices, Manufacturing

3. What are needed infrastructure changes to overcome any possible negative environmental impacts from vehicle automation e.g. power generation, vehicle tech Post-its:

• Look at material impact on environment as well, Limit the total number of vehicles, Is there anything we can do to prevent urbanization, while keeping the benefits?

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6. Is widespread fully automated vehicle technologically, economically and socially feasible in the next 40 years? Post-its:

• Argue this has been addressed and we are moving forward as a result. The time frame might be off (40 years) but it’s feasible for AVs to become ubiquitous.

• What is the role of 5G? How to transition to a more sustainable and resilient transportation network? How do we holistically value and optimize distributed energy resources in urban systems?

4. Human Factors Summary Points Elicitation Session Text

• Quantifying human factors that affect the development of human in the loop systems, and how do we quantify human action with respect to physical, natural, and cyber systems.

• How can automation improve quality of life?

• How to build trust and maintain and improve privacy

23. Is it possible (how?) to measure and model general human factors that affect the development of human in the loop systems.

• new tech on user satisfaction • impacts affect funded

Post-its: • At some stage, we need to make automated systems modular so that

user feedback can be incorporated. Can this be done? 11. How do we quantify human action with respect to physical and natural systems? Economic, etc. Post-its:

• Relationship to resilience; Social sustainability, active transportation (walking & cycling) – automation could reduce activities that protect health

14. How can automation improve the efficiency of (routines), daily trips, and what does that imply for urban systems and improving quality of life. How can we manage this, and balance different systems/sectors? Post-its:

• At what level do you measure efficiency? • What may be very efficient for an individual or an activity may be

globally optimal? • People are more than their schedules

36. How do we build trust into automation/urban systems? Post-its

• Automation is inevitable. How do we effectively communicate the “counterfactual” of non-automation to build trust?

• Urban/rural/suburban divideà How do you deal with the fact that physical infrastructure does not align with political boundaries?

• How do you learn from places where problems have been solved, given different histories/political systems?

• Trust relates to ALL [ideas] in this room. Do we try to improve society’s trust in tech or adjust use of tech to meet needs of a society with little trust?

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16. How do we include general population in decision-making about the future, especially those populations who will be impacted – to understand true impact. Especially Aging populations. Post-its:

• Enable sustainability efforts at a community level – there is not one “automation” for all of society’s necessities

• This is what makes “human action” (or the social system) component so interesting. If we can begin to quantify the social system component, we can see the output given a specific input social population.

• Who are the decision makers/stakeholders? • Model alternative scenarios to explain co-benefits and trade-offs?

5. Social and Economic Impact Summary Points Elicitation Session Text • Measurement

methodologies for ROI, equity, health assessment?

18. Show an ROI for all. How do we best build a public/private partnership that will enable an equitable and sustainable future? How can we measure ROI from a triple bottom line economy? Post-its:

• Tax incentives for co-housing and co-mobility • What do people do for themselves vs. what does the state do to

protect them? • ROI for whom? For what time frame?

15. Equity implicit in sustainability • How do we measure the impact of equity as we measure the impact

of sustainability? • Can something be sustainable but not equitable?

Post-its: • Economic feasibility as well • How do we ensure that automation in urban systems increases social

mobility across society rather than further polarize? 20. What are the resources needed to build the infrastructure to provide an autonomous urban network? Post-its:

• What are the resources and what are the losses of economy (i.e. jobs)

• Economic feasibility is a very important consideration that needs to be added

34. How do automated systems improve human health, mental health, and productivity? Post-it:

• Expand to address human agency and satisfaction

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2. What is the cost of NOT adopting automation for urban systems (e.g. environmental and social losses)? Post-it:

• Health and safety – lives lost, CO2/Pollution 26. How do we measure the delivery of a service/well-being that may or may not be related to service? Not using activity as a proxy.

6. Information, Privacy, and Sensors Summary Points Elicitation Session Text In order to measure automated systems, we need sensor technology; this creates enormous data and information opportunities to create resiliency and sustainability, but comes with some ethical and privacy considerations that require thoughtful design with safety in mind.

13. How can technology help us understand interdependence of human behaviors to continuously improve sustainability and eliminate unintended consequences?

• Sensor tech Post-its:

• Direct relationship to resilience • Role of data analytics can be analyzed

19. What is the value of infrastructure of automated urban sensors for resilience decision-making

• Info/privacy/sensors/security Post-its:

• Role of info in bringing transparency and accountability • Streamline info exchange

25. How do we protect privacy in an automated system? On demand mobility might mean every hour is rush hour – how to mitigate? Post-its:

• Capacity factors? • How to deliver personalized and optimized services while

still respecting privacy • What (if any) privacy or PII are we willing to tolerate for

increased automated sustainability? 12. What info is needed to determine baseline efficiencies that we need established so automated vehicle deployment is equitable? What are the benefits we want to achieve with this equity? 29. How do we measure sustainability when there are different technologies deployed in different communities? Rural/urban; low/high SES

• Equity • Sustainability

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What is the value of autonomous sensing in water infrastructure?

7. Adoption of Automation Summary Points Elicitation Session Text • How does heterogeneity of

adoption affect equity? • How to address adoption of

automation technology? • What will the roll-out look like,

temporally and spatially?

24. How does heterogeneity of adoption affect equity?

3. How to address adoption of automation technology? • Communication of tangible value across value chain • Massive technology adoption problem as much/more than

a technology problem • Complexity of implementing change at this scale –

technological, and societal 17. What does roll-out of automation look like?

• Sequencing spatially and temporally? • How do we spatially expand to support growing cities

and mega-cities? • How to plan for building and maintaining systems? • Interrelated decisions made by humans and machines in

partial roll-out, how does that impact sustainability?

8. Design of Adaptive Autonomous Sustainable Urban Systems Summary Points Elicitation Session Text • How do you design safeguards

against automation for the sake of it?

• How do we design systems that allow opt-out?

• How do we bake in the flexibility to continually update goals and definitions?

• How do we incorporate and bake in, employment/education/training issues?

23. How do we protect, support and change education to ensure automation still allows meaningful work?

• How to prepare for new types of jobs, and new education and training systems that enable this?

• Age and generational considerations 18. What are the safeguards that keep automated systems from being built without asking “why”? Often sustainability is very analog 21. When we do build autonomous urban systems, how do we bade in the flexibility needed to continually update what sustainability means as that changes?

23. How do you design automation that allows people to opt out, so that automation doesn’t impede autonomy?

• e.g. bikes in an automated vehicle rail world

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22. How can you use automation to incentivize sustainable behavior of individuals?

• Move toward public best interest

20. How do we consider automation, integration, interaction and sustainability across scales? Are we equipping people with tools to understand and engage with decision-making? Post-it:

• Cross-cutting sustainability metrics across fields: food, energy, transport. Go beyond CO2, ex: jobs, level of impacted green space, etc.

9. Trade-offs at the systems-of-systems level Summary Points Elicitation Session Text • How can we use automation to

understand links between sectors? • What is the role of automation in

achieving sustainable urban systems, since tech. alone will not be a solution.

• How to ensure that short-term efficiencies are not wiped out by unintended effects of automation?

• Can we develop a science for how to foster sustainable innovation within systems-of-systems?

8. How can we use automation to understand links between sectors?

• Huge data-gathering opportunity • Chance to reduce bias

Trade-offs between environmental quality and equity Post-it:

• Automated air quality assessments (measurements and models) at neighborhood resolution to drive decisions (school closing, city investments, etc.)

• Think broad – education, food, energy, transport systems

10. Strategy of interdisciplinary partnerships and deployments • Can we develop a science for how to foster

sustainable innovation within a system of systems? • Consider Metrolab Network as a test-bed lab

Post-It • Modeling these systems will go a long way • Idea – How can we calculate systems-level benefits

for a given automation solution? LCA? 12. What is the role of automation in achieving sustainable urban systems? How can we consider the following to ensure we do not believe tech alone with “solve” SUSTAIN challenges?

• Efficiency paradox and how to prevent it? • Energy conservation • Behavioral changes • Holistic systems view

12a. How to ensure that the short-term efficiencies gained by automation do not induce changes in demand that wipe out this initial gains? Post-it:

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• What are indirect effects (or rebound effects) of automation? How do they affect environmental justice?

25. How can we better understand the relationship between automation and the economy, between automation and human behavior, so we can identify and address inefficiencies

10. Governance Summary Points Elicitation Session Text • How can automation worsen

sustainability and how do we prevent that through governance?

• How do we ensure private profit-seeking interests don’t encroach on the systems?

• How do we ensure transparency and accountability (maybe leveraging automation for it)?

7. How can automation worsen sustainability, and how do we ensure the right people make decisions?

• Automation transfers processes from people to machines, whereas autonomy transfers decisions from people to machines.

• Who knows the data and where they flow to? • Who decides? • Who decides who decides? • In addressing these – move away from corporate

interests and into hands of people 1. In what ways can we be ensuring transparency and accountability, to build a strong network both technologically and socially? 1a. Transparency – can we use data from automation to gain insight, additional transparency as a possible improvement to governance.

• Power mapping: Who is benefitting and how? 13. How does centralization or distribution of control across agencies and/or agents affect the risk and performance of autonomous systems?

• What mix of stakeholders? (government, coordinated private sector, other entities?)

• Does the mix of stakeholders and impact of distribution or centralization differ by problem? (mobility, transportation, water, housing)

23. Meaningful employment and education and training systems

• How to prepare for new types of jobs? • Age/generational considerations

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11. Automated Applications Summary Points Elicitation Session Text • Reinvent transportation • Urban agriculture/food

delivery • Reimagine/invent lighting

and its effects

15. Can automation allow us to completely reinvent transportation that can

• Support 30 million people cities? • Be sustainable?

16. Umbrella idea that automation is used to improve human potential e.g.

• Food brought to schools automatically • Air quality notifications, e.g. making calls not to have school • Equity during heat events via city-wide automated assessments

that would inform emergency response Post-it:

• Look at the SHADE project 2. We can do food better. How can we integration food back into our built infrastructure?

• Automate • Repurpose existing infrastructure • Energy water loops • Transportation • Social science • New infrastructure

Post-it: • Automate excess food distribution to provide school

breakfast/lunch and food pantry (delivery to homes) as needed 9. How do we manage light, both natural and artificial, for more sustainable urban systems?

• Agriculture • Human health • Energy (e.g. passive building lighting)

Post-it: • Links between light and sustainable water treatment exist

29. What are the top technology/science development needs to enable applications?

12. Equity, Justice, and Automation Summary Points Elicitation Session Text • How are the benefits/burdens of

automation distributed? • How to engage communities • What are the right metrics to use? • What biases do we have and help

to persist with automation?

6. What are the benefits and burdens of automation? • How to engage communities? • What are the right metrics? • How do we evaluate the ecosystem interactions and

assess whether we’re using automation to improve sustainability, and for whom?

Post-It:

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• How do we do data analysis while assessing tradeoffs in burdens/benefits?

• Where in terms of applications does automation make sense? We shouldn’t try to do automation for the sake of automation.

14. Check-in of where we are with automation, critically: • What inherent social biases do we already see in

automation • What do we want to continue? • What do we need to change? • ~Are we seeing existing societal bias patterns reinforced

by some automation? 19. Regional equity and data analytics?

• How do you establish the data and analysis frameworks to make sure trade-offs in burdens/benefits between communities can be assessed?

3. How to understand problems of equity and what the urban environment does to affect this:

• Life expectancy differs across neighborhoods • Public health clusters and transportation relationship to

these issues • Green spaces and data regarding their impacts • Role for automation?

13. Methods for Evaluating Impact Summary Points Elicitation Session Text • How can automation worsen or

lead to sustainability? • What framework can be used to

evaluate autonomous urban systems throughout their life-cycle and assess aging, maintenance strategies?

7. How can automation worsen sustainability? e.g. through loss of personal/individual autonomy? 26. What are the economic and operational frameworks to evaluate aging systems and optimize maintenance and replacement strategies?

• Equity implications around low-income communities. Post-its:

• More about data analytics than automation… what happens when data suggest the need for politically difficult decisions?

4. How can automation lead to true resilience and sustainability? (Beyond technology)

• People and social systems and their interaction with automation?

• Financing and the role of private investment in driving advances.

Post-it: • What are links between automation and resilience? What

are the most important things to make resilient?

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14. Scalability and Flexibility Summary Points Elicitation Session Text • How do these questions relate to & serve

megacities? • What does the roll-out of automation

look like? • How do we consider automation,

integration and interaction sustainability across scales?

• Flexibility as sustainability (as a concept) changes

11. How do these questions relate to and serve megacities? (anything bigger than 10 million, up to 60 million)

• What do sustainable solutions look like at the mega-city scale and where does automation fit in?

Post-it: • Automate scheduling and placement of emergency

services based on modeling, data analysis, sensing heat waves

• Smart cities in developing countries may meet different needs than Pittsburgh. The way people behave may be different. The appropriate technologies may be different, governance will not be equal, etc.

17 What does roll-out of automation look like? • How do we spatially expand to support mega and

growing cities? 20. How do we consider automation, integration and interaction of sustainability across scales? Post-it:

• Cross-cutting sustainability metrics across fields: food, energy, transport. Go beyond CO2, ex: jobs, level of impacted green space, etc.

21. Flexibility as sustainability changes