Review of research on smart city governance in Pittsburgh, PA

1. Understanding Smart City Problems and
Opportunities:
Using the Knowledge Commons Framework in
Pittsburgh, Pennsylvania, USA
Prof. Michael Madison
University of Pittsburgh School of Law
@profmadison and michaelmadison.net/

2. Defining city resources
The people of a city constitute and rely on multiple layers of resources:
[1] material resources (often but not always infrastructures: buildings, roads,
sidewalks, parks);
[2] social and cultural resources (often function as infrastructure in economic
terms: neighborhoods, social organizations, education and professional
training, histories and ideologies including social trust, acceptance of legal
and political orders);
[3] political resources (formal voting and related accountability systems, links
between government organizations);
And
[4] systems of information resources, including systems for producing ,
curating, distributing, and accessing information that cross and link [1] – [3].
Rules and social norms for managing all of these resources in communal and
collective settings = governance. General governance questions includes:
Who participates and how? What are the guidelines and guardrails? What
are the outcomes and metrics? 2

3. Political resources
Social and cultural
resources
Material resources
Knowledge,
information, data
generation, flow,
and storage
WITHIN LAYERS
AND ACROSS
LAYERS
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Visualizing
resources
in the city

4. Defining smart city problems in terms of managing resources
Governance in the smart city relies on existing knowledge sharing and creates new
knowledge sharing. Investigating governance systematically across cases is supported
by the Knowledge Commons Framework (GKC) (see knowledge-commons.net).
Sharing? In the city, sharing information and knowledge of many sorts (“commons”) is
fundamental to ensuring that governments can provide for health, security, prosperity,
and equity for the community; that people can live their lives, have and enjoy jobs,
families, recreation and entertainment; and that they can plan for the future; resolve
conflicts, etc.
Sharing solves first-order social dilemmas. Key social dilemmas to which knowledge
sharing is a response: how does city govern itself as a community (community directed
activity) vs how do individuals govern themselves (self-directed activities)? Examples:
building codes, public health, safe streets. The “smart city” in the 21st c is an update to
earlier efforts by governments and private actors to collect and share data.
Sharing creates second-order social dilemmas. The smart city in practice creates new
social dilemmas: bias in favor of corporate interests; possibility of unnecessary
surveillance of residents; disruption of community and social trust relationships;
reinforcement of harmful elite or technocratic governance.
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5. The GKC framework is a research tool for understanding the character of
knowledge commons governance – managing of knowledge resources – in
case-specific context. Why use smart city tech? Who are the actors? What are
the resources? What are the rules? What are the outcomes?
Here: the case is Pittsburgh, Pennsylvania, USA
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6. Examples of Pittsburgh smart city systems, both old and new:
Data collection and integration for decision making:
The Allegheny Family Screening Tool (AFST) (funded by philanthropy)
Open data:
The Western Pennsylvania Regional Data Center (funded by philanthropy)
Data collection for government decision making:
Roadbotics, SurTrac (roads, traffic; spinouts of Carnegie Mellon)
Public/private partnerships:
Green Building Alliance as bridge between green building codes and private
developers
Make city welcoming to tech firms to build an innovation economy:
City of Pittsburgh welcomes autonomous vehicle firms (Argo, Aurora, Waymo)
testing vehicles on public streets; city partners with developers to build
Hazelwood Green on reclaimed steel mill site for off-street testing
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7. Questions for discussion:
What social problems were facing Pittsburgh, give or take 10 years go?
How did Pittsburgh believe that those problems could be solved by smart
tech, including data gathering and sharing?
How was Pittsburgh right, and how was Pittsburgh wrong?
What problems were created by Pittsburgh’s data gathering and sharing?
How should Pittsburgh do better, going forward?
Consider:
▪ Public sector actors (City of Pittsburgh, Allegheny County, Pittsburgh Public
Schools, Port Authority of Allegheny County)
▪ Higher ed (university) actors (CMU, Pitt)
▪ Private sector actors (tech companies, other Pittsburgh companies)
▪ Philanthropic actors (major Pittsburgh foundations)
▪ Community actors (community orgs, neighborhood leaders, others) 7

8. Thank you.
Questions?
Professor Michael Madison
https://michaelmadison.net/
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