Course Syllabus

Urban Analytics and Human-Centered Decision Making

 

Course Information

Title: Urban Analytics and Human-Centered Decision Making

Number: PLAN6941

Schedule: Mondays, 11:00am – 1:00pm

Room: 204 Fayerweather

 

Instructor Contact Information

Name: André Corrêa d'Almeida
Academic Title: Adjunct Associate Professor
Office Location: IAB 1435
Office Hours: By appointment Tuesdays, 10:00am – 1:00pm
Email Address: andre.dalmeida@columbia.edu
Class Webpage: Columbia Courseworks
Student Worker: TBD

 

Course Description
Bulletin Description:

This practical and multidisciplinary course helps students learn the skills and knowledge required to work with organizations in making urban innovation decisions involving technology. With a focus on institutions, data analytics and decision-making tools, and with the support of case studies, lectures and guest speakers, students work in teams with a real organization (a.k.a. client) throughout the semester. The team’s mission is to identify and address a critical issue the client faces regarding its urban innovation efforts. This year, the class will be divided into two groups to work on different projects. Locally, the project will be a smarter city initiative with the New York City Mayor's Office of the CTO. Globally, the project will be about innovation for municipal transparency and integrity with the city of Rio de Janeiro, Brazil, in partnership with ITS-Rio. No specific technical background on data science or computer science is needed.

 

Detailed Description:

Urban innovation matters because this is the only feasible way to improve the wellbeing of people when urbanization is happening faster than at any given time in history. In 2050 two thirds of the population will live in cities, 80% of the world’s GDP will be produced in cities and cities will be responsible for three-quarters of the energy consumption and 50% of greenhouse emissions. This means that the demand for efficiencies and enhanced performance is continual. While governments attempt to manage demands for expenditure to improve the quality of life this demands exceed local capacity/income. And, what’s more critical, this demand, pressure and impact will only grow.

This course is built upon concepts of development economics, international development, behavior sciences, political sciences, public policy and administration, urban innovation, data science, business management and research methods to help students learn the practical skills and knowledge needed to work across silos and make decisions about very complex urban development issues. Weekly sessions are mostly based on case-studies to provide students with real-world learning opportunities which will help them conceptualize and structure their work for the client.

 

Fall 2021 Client-based Projects

  1. Smarter City Initiative with the New York City Mayor's Office of the CTO

The New York City Internet of Things Strategy, released in March of 2021, describes the landscape of IoT use across society, outlines the state of the New York City’s IoT ecosystem, and establishes a set of near-term actions essential for creating a healthy, cross-sector IoT ecosystem in New York City – one that is productive, responsible and fair. Among the actions outlined is a commitment to research emerging IoT workforce needs in the NYC ecosystem, as connected technologies become increasingly more commonplace:

““[The City will] work to explore local IoT workforce needs among employers, including those related to distinct IoT jobs and existing jobs in which IoT is a supplemental skill set, and identify ways to integrate appropriate IoT skills into City training opportunities.””

The City’s Tech Talent Pipeline conducts ongoing industry engagement to understand local tech training needs, including those related to IoT. And the City has implemented selected IoT-related training programs in recent years, some of which are described in the Strategy. However, information about the state of the workforce, needs of employers, and any skills gaps that exist has proved difficult to capture comprehensively, and to keep up to date.

This project will be focused on identifying and implementing a solution to this challenge. Students will be asked to develop a method that can be used by the City to track existing and emerging IoT-related skills needs — e.g., through analyzing job postings and other source materials. This method should complement industry engagement work already in place and should be feasible for the City to implement on an ongoing basis. Specific project tasks include:

- Develop a method for developing data on the local IoT workforce needs;

- Quantify the scale of the need for IoT skill development, as well as what particular skills are in demand;

- Identify industries using IoT and which could most benefit from improved training and skill development;

- Outline needs to transition method/data to City stakeholders, and for the City to maintain this dataset, and reproduce the analysis performed on an ongoing basis.

 

  1. Innovation for Municipal Transparency and Integrity with the City of Rio de Janeiro.

The government of Rio de Janeiro is keen to improve its public governance and learn from best practices and better tools to implement new ways of public administration towards a more open government, closer to the citizens.

This project will be focused on assisting the municipality of Rio de Janeiro in its efforts to achieve greater transparency. In this sense, one of the biggest challenges of the current administration is the implementation of transparency and governance policies. Hence, the team will work together with the Secretariat of Government and Integrity of the municipality of Rio de Janeiro in developing a “transparency index” and a “control panel” to assess its 53 administrative bodies.

The implementation of a control panel with well-designed parameters and that makes use of technology to automate the filling and use of nudge techniques to increase compliance with the city's transparency policy is an effective public management tool and help foster the development of a culture of transparency and integrity in public administration. It will also serve as a tool for citizen participation and oversight of the public activities of the municipality. Specific project tasks include:

- Build transparency and integrity assessment parameters/analytics and a monitoring and assessment dashboard working closely with the Secretariat of Government and Integrity;

- Engage strategic city stakeholders in the design and prototyping of the final product;

- Pilot the implementation of a minimum viable product (MVP) data dashboard and incentive plan in one of the municipal secretariats.

- Prototype an incentive system framework for public officials and administration servants in order to mobilize all around the municipality's transparency plan and goals.

 

Course Goal(s):

The goal of this course is to equip students with the practical skills and knowledge required to professionally advise public and private organizations on how to apply data analytics to make urban innovation decisions. From problem scoping to data analytics to business recommendations and decision making. The deliverables of a semester’s work will be a PowerPoint deck, a professional report with recommendations and alternative scenarios, and two high-level presentations. Students can feature this report in job interviews.

See course structure below for a breakdown of skills, techniques and knowledge learned. The course is built on the premise that practical skills informed by intersecting bodies of knowledge are the foundations to develop critical competencies for problem-solving in urban context.

Learning Objectives:

- To learn and practice the tools, skills and knowledge required to work with organizations in making urban innovation decisions involving technology.

- To use the key tools, techniques and approaches employed by development organizations when diagnosing complex (multidisciplinary) development problems and opportunities.

- To identify and address critical issues clients face regarding their urban innovation efforts.

- To think innovatively about alternative policy and intervention approaches to urban and public innovation.

- To understand the uniqueness of urban and public innovation and how the private sector, civil society and academia can get involved.

 

Course Evaluation:

The evaluation will be based on the individual contribution to the class (students will be asked to prepare answers for questions associated with the weekly case-studies), mid-term group presentation to a panel of field experts and final presentation to the client. Presentations will be attended by both teams so that all students can learn from each other. In addition to the formal weekly class, groups are expected to me at least once a week to advance their client project.

 

Grade breakdown:

Mid-term presentation: 30%

Final PowerPoint deck: 20%

Final Presentation and Report: 30%

Individual Participation: 20%

 

Course Structure (by weekly session):

Part I: Institutional Context, Innovation Ecosystems and Client Needs/Requirements

  1. Introduction to Urban Innovation and Client Projects
    1. Topics: Course overview; project cycle; team building; individual roles.
    2. New Tools:
      1. Innovation Cycle and Project Cycle Canvas;
      2. The 9 Belbin Team Roles Framework.
    3. Key Activity: Opening meetings with the clients.
    4. Guest Speakers: Clients’ representatives
    5. Required Readings/Resources (pre-session): Happy City: Transforming Our Lives Through Urban Design (Chapters 1, 2).
  1. Problem/Opportunity Appraisal and the Becoming Smarter Framework
    1. Topics: Needs Assessment; cognitive bias; enquiring methods; research strategies.
    2. New Tools:
      1. Becoming Smarter Framework;
      2. Problem Tree;
      3. Objective Tree.
    3. Key Activity: Causal Analysis and problem/opportunity focus.
    4. Required Readings/Resources (pre-session):
      1. Smarter New York City: How City Agencies Innovate (Chapters: Introduction and Conclusion);
      2. World Development Report (Chapter 10). See here for the full report and here for the video.
  1. Stakeholders Analysis and Collective Action
    1. Topics: Stakeholders’ power; interests; collaboration.
    2. New Tools:
      1. Theory of Change;
      2. Stakeholders Table;
      3. Stakeholders Matrix.
    3. Key Activities:
      1. Specification of the Theory of Change;
      2. Stakeholders’ Mapping;
      3. Engagement Strategies.
    4. Required Readings/Resources (pre-session):
      1. Streetfight: Handbook for an Urban Revolution (Chapters 1, 6);
      2. Example of Problem Tree here and here, UNDP article on stakeholders engagement here and example of Theory of Change here.
  1. Institutional Analysis and Incentive Systems for Sustainable Urban Governance
    1. Topics: Formal and Informal Institutions; bounded behavior.
    2. New Tools:
      1. IAD Framework;
      2. PEST Matrix.
    3. Key Activities:
      1. Institutional Analysis;
      2. Case-study: LinkNYC: Re-Designing Telecommunication to Activate the 21st Twenty-First Century Creative City.
    4. Required Readings/Resources (pre-session)
      1. Urban Institutions and Politics: The Modern Period;
      2. The Role of Institutions in Sustainable Urban Governance;
      3. Smarter New York City: How City Agencies Innovate (Chapter 3).

 

Part II: Data, Collaboration and Ethics

  1. Logic Frameworks, Project Assumptions and Data (big and small)
    1. Topics: Intervention pathway; data needs; impact assessment, monitoring and evaluation (M&E).
    2. New Tools:
      1. LogFrame;
      2. Data Canvas.
    3. Key Activities:
      1. Develop the project’s LogFrame;
      2. Complete the project’s Data Canvas.
    4. Guest Speaker: City of New York Department of Transportation’s CTO.
    5. Required Readings/Resources (pre-session):
      1. Urban Analytics (Chapters 1-3);
      2. Smarter New York City: How City Agencies Innovate (Chapter 1).
      3. See example of LogFrame here.
  1. From Data Discovery to Data Storage
    1. Topics: Data needs; data collection; data creation.
    2. New Tools: Multiple tools and techniques to collect data that exists and create data that does not.
    3. Key Activities:
      1. Design a data framework and strategy;
      2. Build a data system (prototype for the project).
    4. Required Readings/Resources (pre-session)
      1. Smarter New York City: How City Agencies Innovate (Chapters 2, 4);
      2. World Development Report 2021: Data for Better Lives (Chapters 1-4). See also here.
  1. Mid-term Presentations to the Clients: 45 minutes each including Q&A

 

  1. Circular City Data, Data Collaboratives and Data Governance
    1. Topics: Data supply and demand; data marketplaces; PPPs.
    2. New Tools: Data Value Canvas, Data SWOT.
    3. Key Activities:
      1. Develop a data value canvas;
      2. Conduct a data SWOT.
    4. Required Readings/Resources (pre-session):
      1. The Circular City (all chapters);
      2. Assessing the Returns on Investment in Data Openness and Transparency.
  1. Data Ethics, Transparency and Risks: from data collection to data usage
    1. Topics: Ethics; legal considerations; challenges; public good.
    2. New Tools: Data Responsibility Framework.
    3. Key Activities: Develop a data responsibility framework and strategy.
    4. Required Readings/Resources (pre-session):
      1. City Data Exchange: Lessons learned from a public/private data collaboration;
      2. The State of Mobile Data for Social Good Report;
      3. Gender Gaps in Urban Mobility.

 

Part III: Urban Analytics and Decision Making

  1. Artificial Intelligence (AI) and Machine Learning (ML) Applications for Urban Challenges
    1. Topics: AI/ML tools and techniques for city data scraping and smarter cities; NLP; supervised machine learning; dashboards.
    2. New Tools: A portfolio of AI/ML tools and their taxonomies.
    3. Key Activity: Build a model/framework for data scraping
    4. Guest Speaker: TBD
    5. Readings/Resources (pre-session):
      1. AI Procurement in a Box;
      2. The State of AI Ethics.
  1. Principles of Human-Centered Design for Urban Innovation
    1. Topics: People; Needs; Empathy; Trust; Systems; Complexity; Prototyping/Validation.
    2. New Tools: Human-centered design framework.
    3. Key Activity: Apply human-centered design principles to the project.
    4. Readings/Resources (pre-session):
      1. A New City O/S: The Power of Open, Collaborative, and Distributed Governance (Chapters 1, 7);
      2. Designing the Human-Centered City.
  1. Decision Making Tools
    1. Topics: Decision making; scenario building; trade-offs; opportunity costs.
    2. New Tools:
      1. SWOT Matrix;
      2. Cost Benefit Analysis (CBA);
      3. Decision Trees.
    3. Key Activity: Develop a multi-criteria decision-making framework for the project with multiple alternative scenarios and contingency plan.
    4. Readings/Resources (pre-session): The Cost Benefit Analysis for the Concept of a Smart City: How to Measure the Efficiency of Smart Solutions?
  1. Localizing Sustainable Development Goals and the Urban Innovation Agenda post-2030
    1. Topics: SDGs, challenges for urban innovators; local and global alliances for happier and smarter cities.
    2. New Tools: A framework for local SDGs.
    3. Key Activity: Work on the final PPT and project report.
    4. Readings/Resources (pre-session):
      1. The Triumph of the City: How our Greatest Invention Makes Us Richer, Smarter, Greener, Healthier, and Happier (Chapter 9);
      2. Order without Design: How Markets Shape Cities (Chapters 1, 8).
  1. Final Presentations to the Clients: 45 minutes each including Q&A

 

***

Policies

Class Meetings and Attendance: Your success in this course depends on three things: 1) your presence in class; 2) your contributions in class discussions (demonstrating that you have completed the assigned readings); and 3) your contributions to your group’s project. Class attendance will be observed regularly and will factor prominently into your final grade. You are permitted one (1) unexcused absence from class meetings—all course members are expected to attend all class meetings.

If you expect to miss class(es) for religious observances or athletic participation, please inform me in writing (e-mail is fine) ahead of time. Weather and mass transit are unpredictable and occasionally cause delay or cancellation of academic activities. In these cases, excused absences from class will be granted only if the institute officially closes — if it’s open, I will be here and I expect that you will too. If you do miss class, I will expect an email explaining why you weren’t able to attend. In such instances, please make it your responsibility to find out what you missed.

Electronic Devices: Cell phones must be turned off and put away during class.

Conferences and Office Hours: If you need to speak with me regarding class matters, or any other matter, please feel free to email me so we can set up an appointment. Please bring materials/assignments/questions you wish to discuss with you to our office hours.

Students with disabilities: In compliance with Columbia University policy and equal access laws, I am available to discuss any and all appropriate academic accommodations that you may require as a student with a disability. Request for academic accommodations need to be made during the first two weeks of the semester, except for unusual circumstances, so that appropriate arrangements can be made. Students must register with Office of Disability Services (see: http://www.health.columbia.edu/docs/services/ods/index.html or call 212 854 2388) for disability verification and for determination of reasonable academic accommodation.

Academic Integrity: Academic integrity is expected of every Columbia University student in all academic undertakings. Integrity entails a firm adherence to a set of values (outlined in the Columbia University Student Handbook), and the values most essential to an academic community are grounded in the concept of honesty with respect to the intellectual pursuits of oneself and others. A Columbia student’s submission of work for academic credit indicates that the work is the student’s own. All outside assistance (including assistance from a classmate, roommate, friend or family member) should be acknowledged, and the student’s academic position truthfully reported at all times. In addition, Columbia students have a right to expect academic integrity from their peers. (For more information: http://www.arch.columbia.edu/bulletin/plagiarism.html)

Safety: All students are expected to adhere to the specific health and safety guidelines of Columbia University.

Student Responsibility for Learning: Students must take responsibility for their own learning in this course (and I would imagine all graduate level courses). This means that you have to read ahead of class and arrive prepared to engage in topical discourse. While the grading rubric is presented above, effort counts a lot in this course and what you will ultimately take from this course will depend strongly upon the effort you put forth. For my part, I will provide guidance for your project, help with the activities and facilitate class discussions on assigned readings. Ultimately, however, the responsibility to learn is your own.

Late or missed assignments: You are expected to submit all work when it is due. Late assignments will be marked down by one letter grade.

Incomplete (INC) grades: Because the material (group work) in this course does not lend itself to make-up, I will not entertain incompletes except in a case of true emergency. If an incomplete is given, you will receive partial credit towards the next offering of this course; you will not have the option to complete the work late and hand it in for credit after the end of the semester. I am holding the line on this because much of the learning will come from participation in the course’s group assignment. If you miss class, such learning opportunities are forfeited.

Course Summary:

Date Details Due