PhD Project on Responsible AI Governance for Smart City Development

PhD Project Title:Governing Responsible AI in Smart Cities: The Role of the Public Sector Supervisors:

• Adjunct Professor Luca Mora, School of Engineering: Department of Civil Engineering and Architecture: Academy of Architecture and Urban Studies
• Assistant Professor Ralf-Martin Soe, Office of Vice-Rector for Research: FinEst Centre for Smart Cities

School / Department / Research group: School of Engineering, Department of Civil Engineering and Architecture, Academy of Architecture and Urban Studies 1. Summary The Academy of Architecture and Urban Studies and the FinEst Centre for Smart Cities of Tallinn University of Technology (TalTech) invite applicants for a4-year PhD position in the field of responsible AI governance for smart city development. The project focuses on how public sector organizations and regulators translate abstract principles of responsible innovation, such as fairness, accountability, and transparency, into concrete governance structures, processes, and tools. This is afull-time, fully funded PhD position. It is offered within the prestigious European projectFinEst Twins, which has been instrumental in establishing theFinEst Centre for Smart Cities: a Tallinn-based research and innovation organization resulting from a joint venture between Tallinn University of Technology (Estonia), Aalto University (Finland), Forum Virium Helsinki (Finland), and two Ministries of the Estonian Government. Hosted at TalTech, the FinEst Centre for Smart Cities advances cutting-edge smart city research and translates scientific results into real-life innovations by supporting the design, experimentation, and scaling of user-driven smart city solutions. This PhD position provides the opportunity to conduct research under the supervision of experienced professors and researchers working at the intersection of smart city development, responsible innovation, public administration, digital transformation, and technology governance. The project is highly international in scope. The successful candidate will have opportunities to collaborate with a broad global network of leading universities and research centers already engaged with the supervisory team. These collaborations include colleagues from the Massachusetts Institute of Technology (MIT), University College London (UCL), The Polytechnic University of Hong Kong, The University of Edinburgh, Stanford University, Erasmus University Rotterdam, and Delft University of Technology, among others. 2. Description of the PhD Project The rapid diffusion of AI-enabled systems in cities – from predictive maintenance of infrastructure to algorithmic decision-making in transport, welfare, policing, and urban planning – exposes the deeply sociotechnical nature of contemporary urban governance. In response to growing concerns about discrimination, opacity, and even loss of control, public institutions and private organizations have embraced high-level principles such as fairness, privacy, security, accountability, and transparency. However, bringing these abstract principles into real-world practice is far from straightforward. Principles need to be translated into governance structures, procedures, decision rights, and technical tools that can guide the responsible design, deployment, and oversight of AI systems embedded in urban environments. Smart city development provides a particularly rich context for examining this translation process. AI systems are often introduced as part of broader smart city strategies that promise efficiency, sustainability, and improved public services in urban settings, which have become living laboratories for advanced AI-powered technological development. However, without appropriate governance mechanisms, these technologies can reinforce existing inequalities, create new dependencies, and erode public trust. During what can be described as AI-enabled smart city transitions, the sociotechnical systems of an urban environment are subject to multi-dimensional changes: new roles and responsibilities emerge, organizational routines are reconfigured, regulatory obligations evolve, and new instruments such as algorithm registers, impact assessments, audit procedures, and procurement guidelines are introduced. Together, these changes shape how responsible AI principles are interpreted, operationalized, and contested in practice. At the forefront of these transformations are public authorities and public sector organizations at city, regional, and national levels. They are expected to articulate a vision for responsible AI in urban governance, create institutional conditions that support responsible experimentation and innovation, and coordinate diverse coalitions of actors, including technology providers, civil society organizations, and residents. In this context, “governance mechanisms” encompass a wide range of elements: formal regulations and standards, organizational structures and committees, procurement and contracting practices, internal policies and guidelines, evaluation and auditing tools, data governance arrangements, training and capacity-building initiatives, and participatory processes for involving stakeholders and citizens. While there is an expanding body of normative work on responsible AI, empirical knowledge of how these mechanisms operate in practice, particularly in the smart city domain, remains fragmented and underdeveloped. To address this critical knowledge gap, this PhD project will adopt a cross-disciplinary and empirically grounded approach. It will connect theories and frameworks from smart city research, technology and innovation studies, public administration, and science and technology studies to investigate how public sector organizations and regulators translate responsible AI principles into actionable technology governance arrangements. The project will rely primarily on qualitative and mixed-method research designs. Data will be collected through techniques such as semi-structured and expert interviews, focus groups, collaborative workshops with stakeholders, participatory observation, and secondary data analyses. Examples of research questions that the proposed PhD project could focus on include, but are not limited to, the following:

• How do public authorities and regulators interpret key responsible AI principles (fairness, accountability, transparency, privacy, and safety) in the context of smart city development, and how do these interpretations differ across organizations and jurisdictions?
• What governance structures (for example, committees, departments, and advisory boards) are created to oversee AI-enabled urban systems, and how effective are they in influencing decision-making?
• How are responsible AI principles embedded into organisational processes such as project design, risk assessment, public procurement, contracting, and vendor management for smart city projects?
• Which tools and instruments (for example, algorithm registers, AI impact assessments, audit frameworks, ethical guidelines, or technical standards) are used to implement responsible AI in practice, and how are these tools developed, adapted, and institutionalized?
• How do public sector organizations manage trade-offs and tensions between competing principles and objectives, such as fairness versus efficiency, transparency versus security, or innovation versus risk aversion, when governing AI-enabled urban systems?
• How are citizens, civil society organizations, and other stakeholders involved in the governance of AI in smart city development, and what forms of participation or contestation influence the translation of principles into practice?
• How do multilevel governance arrangements (local, regional, national, and supranational) shape the capacity of public authorities to align AI governance mechanisms with broader legal, ethical, and policy frameworks?

The final focus of the dissertation will be refined in dialogue with the supervisors, taking into account the candidate’s background, interests, and emerging opportunities for empirical collaboration with partner cities and organizations. 3. Responsibilities and tasks The PhD candidate shall produce new insights into how public authorities and other organisations involved in smart city development translate responsible AI principles into governance structures, processes, and tools. The research activity shall be theoretically grounded. The PhD candidate will be responsible for identifying and connecting the relevant theoretical backgrounds in fields such as responsible AI, smart city studies, technology and innovation studies, public administration, and science and technology studies, and for ensuring that the research produces sound theoretical and practical contributions. In addition, the PhD candidate shall be responsible for selecting the most appropriate tools and methods for conducting the research, defining and refining the research questions, and detailing the overall research design in dialogue with the supervisors. The PhD candidate is expected to disseminate the results of their research through the preparation of journal articles and other scholarly outputs, and through active participation in research seminars, conferences, workshops, and guest lectures. 4. Requirements Applicants are required to meet the following requirements:

• Educational background: A university degree (MSc or equivalent) in disciplines related to public administration, urban studies, or related social sciences. Given the interdisciplinarity of the project, we also welcome applicants with degrees in fields such as anthropology, business and management, human geography, information systems, international relations, organisation studies, political science, psychology, science and technology studies, and sociology. An interest in responsible AI, technology governance, and/or smart city development will be considered an asset.
• Methodological skills:Familiarity with qualitative research methods and techniques is an additional asset. This may include experience with case study research and data collection methods like in-depth interviews, focus groups, stakeholder workshops, participant observation, and qualitative content or discourse analysis. Previous experience with qualitative data analysis software (such as Atlas.ti, NVivo, QDA Miner, or similar tools) is appreciated. Prior experience with mixed-methods designs or basic quantitative techniques is not a formal requirement, but would be considered an advantage.
• Research capacity and motivation: Proven ability to carry out independent research and to contribute to collaborative projects as part of a broader team. The PhD candidate should demonstrate a strong interest in developing theoretically grounded and empirically robust work, and in publishing scientific results in high-quality scholarly journals.
• Language skills: Good command of the English language (speaking and writing) is essential

The successful PhD candidate is expected to work full time for a duration of 4 years as a part of the Academy of Architecture and Urban Studies and FinEst Centre for Smart Cities. The PhD candidate is also required to fulfil the requirements of Tallinn University of Technology’s PhD Program. Additional funds will be provided for research trainings, conferences, and international mobility.

5. Application process and required application documents

The information for the PhD admission is available at TalTech´s web-page:https://taltech.ee/en/phd-admission.

Please submit your application, with all your application documents to Professor Luca Mora ([emailprotected]) The application must include the following documents:

• Motivation letter
• Curriculum Vitae, including details about your education and research experience;
• Copy of theidentification page of your passport or official Estonian identification document (ID-card, Temporary Residence Permit card);
• Foreign applicants must submitproof of English language proficiency which must be at least B2 level according to the Common European Framework of Reference for Languages. You can either submit an English language test certificate (IELTS Academic, TOEFL iBT, Cambridge English or Pearson Test of English Academic) or a written confirmation by an official from your degree awarding institution that you have completed your master´s degree programme taught fully in English.
• (A) Scans of originalqualification documents (bachelor’s degree and master's degree diplomas and academic transcripts) OR (B) scans ofcertified true copies of original qualification documents.

All applications will be assessed by the supervisory team. Shortlisted candidates will be invited to interview. The outcome of the selection process will be communicated to all applicants shortly after the application deadline.