PhD position on algorithmic transparency and the right to explanation in a joint research initiative between Eindhoven University of Technology (TU/e), Tilburg University (TiU), and KPN (1,0 fte)

The goal of the project is to study how the principle of transparency of automated decision-making and the right to an explanation should be implemented to safeguard the right to data protection, considering competing legally ...

18 dagen geleden

Arbeidsvoorwaarden

Standplaats:
Warandelaan, Tilburg, Noord-Brabant
Dienstverband:
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
40 - 40 uur
Salarisindicatie:
€ 2222 - € 2840 per maand
Opleidingsniveau:
WO

Functieomschrijving

Theme: transparency of complex machine learning models

The goal of the project is to study how the principle of transparency of automated decision-making and the right to an explanation should be implemented to safeguard the right to data protection, considering competing legally protected rights and interests?

Transparency of Big Data algorithms is on top of the European policy agenda. It is part of the 2017 Council of Europe Big Data Guidelines. The ‘right to an explanation’ of the logic of automated decision-making is one of the key regulatory innovations of the General Data Protection Regulation and is aimed to strengthen transparency of data processing in general and of automated decision-making in particular. While the reform process is over and the Regulation will apply from May 2018, considerable lack clarity exists both as to the actual scope of this right under the Regulation, as well as how it should be implemented in practice by the data controllers.

The uncertainty exists both in terms of the balance with other protected interests and feasibility. Specifically, the key to understanding the logic of an automated decision often lies with the algorithm protected by IP while the Regulation states that the right to explanation is without prejudice to the Intellectual Property Rights. Furthermore, in addition to technical feasibility to ensure transparency of autonomous self-learning algorithms, there are feasibility concerns related to a natural limit to human cognitive abilities to perceive the logic behind automated decision-making, even more so when it is powered by modern artificial intelligence. Finding technical solutions to the algorithmic transparency problem is only secondary to and should be led by a thorough legal understanding of the transparency principle and the right to explanation.

The project is a collaboration of the Jheronimus Academy of Data Science (JADS), 's-Hertogenbosch (campus Mariënburg) and KPN. In a companion project a PhD researcher will be appointed to study the legal aspects of the transparency of models induced by machine learning algorithms.

Functie-eisen

The PhD research will be conducted under supervision of Prof. Eleni Kosta and Dr Nadya Purtova. It will deliver both long-term (thorough understanding of the notions of transparency and the right to explanation) and mid-term results (draft codes of conduct, policy papers, white papers, and best practices).

The successful candidate will:

  • Perform scientific research in the domain described;
  • Present results at (international) conferences;
  • Publish results in scientific journals;
  • Participate in activities of the group, mainly in 's-Hertogenbosch but sometimes also in Eindhoven, Tilburg and Amsterdam;
  • Assist in teaching undergraduate/graduate courses;
  • Be willing to work at multiple locations. Mariënburg campus in 's-Hertogenbosch will be the candidate's main office, but he or she may be temporary stationed at TU/e, TiU or at KPN Amsterdam.

Job qualifications

The successful candidate:

  • is an excellent student with a completed law degree (LLM);
  • has a strong demonstrable interest in regulation of algorithms;
  • has demonstrable knowledge of, or a willingness to familiarize him-herself with, current research into legal and regulatory aspects of artificial intelligence and algorithmic transparency, including but not limited to data protection law;
  • in addition to academic output, is able to produce short- and mid-term results aimed at policy and industry audiences (including KPN, the industry partner in the project). In this respect, some consultancy, policy or industry experience is an asset, although not required;
  • has an academic mind-set, good writing skills, and an excellent command of written and spoken English;
  • is able to work independently;
  • has strong analytic skills and values accuracy and nuance in his or her work.

Conditions

The PhD position gives an opportunity to perform cutting edge research in a large-scale joint data science project involving TiU, TU/e, JADS and KPN and bringing together expertise of several senior researchers. The PhD-candidate will be employed at Tilburg Law School, TiU, and hosted by Tilburg Institute for Law, Technology, and Society (TILT). TILT is one of the leading European research institutes in the field of regulation of technology. Tilburg University is rated among the top of Dutch employers and has excellent terms of employment.

We offer:

  • A full-time position;
  • The selected candidate will start with a contract for 16 months, concluded by an evaluation. Upon a positive outcome of the first-year evaluation, the candidate will be offered an employment contract for the remaining 32 months;
  • A gross salary of € 2,222 per month in the first year increasing up to € 2,840 per month in the fourth year;
  • A holiday allowance of 8% and an end-of-year bonus of 8.3% (annually);
  • Researchers from outside the Netherlands may qualify for a tax-free allowance equal to 30% of their taxable salary. The University will apply for such an allowance on their behalf;
  • Assistance in finding accommodation (for foreign employees);
  • The opportunity to perform cutting edge research in a large-scale joint data science project involving TiU, TU/e, JADS and KPN and bringing together expertise of several senior researchers;
  • Support for your personal development and career planning including participation in the EIT doctoral training, courses, summer schools, conference visits, research visits to other institutes (both academic and industrial), etc.;
  • A broad package of fringe benefits (including excellent technical infrastructure, savings schemes and excellent sport facilities).

Bedrijfsomschrijving

The project is a collaboration of the Jheronimus Academy of Data Science (JADS), 's-Hertogenbosch (campus Mariënburg) and KPN.

Tilburg Law School

Tilburg Law School

Tilburg Law School (TLS) is a modern and specialized university. With a broad variety of international programmes and innovating research, the Tilburg Law School stands for high quality. Research at the Tilburg Law School is conducted in an organisation that fosters diversity. The Tilburg Graduate Law School is responsible for the training and guidance of its Research Master students and of the Faculty’s PhD researchers. With its open and inspiring atmosphere, this school is a congenial working environment.

JADS: New research initiative on data science

The Jheronimus Academy of Data Science (JADS) is the unique collaboration of two renowned universities bringing together their top academics to further the emerging and multidisciplinary academic field of data science. JADS not only offers nine academic educational programs (Bachelor, Master, PD.ENG, PhD and Professional) but also hosts three research centers; the Data Science Center Eindhoven (DSC/e), the Data Science Center Tilburg (DSC/t), and the Data Science Center Den Bosch (DSC/db) at the new Mariënburg campus. At these centers we conduct groundbreaking research on data science and create concrete societal value.

The new Mariënburg campus on Data Science is located in a historic and beautiful former convent in the heart of the medieval city of ‘s-Hertogenbosch and is within walking distance from the central train station. It is the place where academics with engineering and business/social competences meet each other and participate in a wide-spread data science ecosystem. It is a buzzing and diverse place where learning based on data has center stage. The Mariënburg campus hosts lecture halls, academic labs, student apartments, data start-ups, corporate field labs, a coder dojo, and a data artist. By mixing students, academics, and companies, all on the topic of data science, we aim to cross-fertilize, innovate and transform data into value-adding insights and wisdom to advance companies, governments and society at large.

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