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We are looking for an enthusiastic PhD candidate with a background in the field of policy analysis, public administration, policy sciences or a related field to study and develop organizational implementation arrangements for Artificial Intelligence (AI) for regulatory surveillance. The position is a for 4-year PhD track, financed by the Faculty of Technology, Policy and Management, department of Multi-Actor Systems in close collaboration with regulatory agencies.
Artificial Intelligence (AI) systems are increasingly used in regulatory processes. No wonder, AI promises a more effective regulatory supervision process, in which inspectors on the floor are advised on the basis of AI-generated risk analysis. Technically there are still many development possibilities. However, whether AI can be applied effectively and responsibly also raises organizational issues, such as:
- Professionalism of the inspectors. Risk analyses were conducted before the AI era. These often took place in the minds of professional inspectors and/or during work meetings. In other words: not only data, but also inspectors are an important source of knowledge about risks. Their knowledge is often implicit and based on years of experience. Application of AI can count on resistance from professionals. Not only that: too aggressive application of AI can come at the expense of their valuable knowledge.
- Data pollution. Too much risk-based supervision can lead to data pollution: data mainly comes in from those under supervision who have previously been identified as being high-risk. Other people under supervision can thus remain out of sight. They can change their behaviour. There will therefore always be a demand for risk-based random supervision, in which random samples are also used for supervision. Within an organization there are different ideas about the right ratio.
- Ethical issues. There is a lot of discussion about bias, protection of vulnerable individuals, transparency and privacy. Of course, these discussions also exist internally. This means that those involved – data scientists, inspectors, managers – make trade-offs between values. Many decisions about data and algorithms can be leading for the outcomes. These decisions increasingly seem to be made 'at the front', the data experts. This presents challenges with regard to the management of the data experts.
Based on these signals, we conclude that further development of AI has both technical and organizational dimensions. Successful development and implementation of AI will therefore have to be linked to the organization of supervisory practices.
How are technical development of AI and the supervisory organization connected and how can this connection be improved? Much literature on AI focuses on technical possibilities, while other literature deals with ethical concerns. Far less literature discusses the actual implementation and use of AI in organizational practice. A study into this subject should have two characteristics:
- The research is interdisciplinary. It has both innovative-technical aspects and social-scientific aspects. The question is about the interplay between the two.
- Connected to practice. We are looking for the application of AI in the context of practice. That is why we want to conduct empirical research, using one or more cases. The research will be carried out in close collaboration with the Dutch Food and Product Safety Authority (NVWA).
In this project you will study and develop arrangements that bring together the world of AI and managements of surveillance.
This requires understanding of AI (data science, machine learning, programming) and more intangible processes of organization, including organization structures, informal coordination and organizational politics. It includes both analysis and design efforts. It will involve conducting case studies at NVWA
We are looking for someone who:
- has a Master's degree and a background in policy analysis, public administration or a related field
- has affinity (and preferably also demonstratable experience) with AI
- has affinity (and preferably also experience) with organizational science
- has the ability and interest to cross disciplinary boundaries
- is fluent in English, both written and orally
- has pro-active communication skills and is able to work well in a team
Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.
Since the project is developed in close cooperation with a Dutch inspection agency (NVWA) that mostly communicates in Dutch, a candidate that speaks Dutch or is willing to learn the Dutch language is preferred.
Fixed-term contract: 4 years.
Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2541 per month in the first year to € 3247 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.
The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.
At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.
Challenge. Change. Impact!
The Faculty of TPM provides an important contribution to solving complex technical-social issues, such as energy transition, mobility, digitalisation, water management and (cyber) security. TPM does this with its excellent education and research at the intersection of technology, society and policy. We combine insights from both engineering and social sciences as well as the humanities. TPM develops robust models and designs, is internationally oriented and has an extensive network of knowledge institutions, companies, social organisations and governments.
Click here to go to the website of the Faculty of Technology, Policy and Management.
Delft University of Technology (TU Delft)
Mekelweg 2, 2628 CD, Delft
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