Big Data and Law

Professional Learning

Big Data | AI & Law

Big Data | AI & Law

Date: Location: Tilburg

The program Big Data | AI & Law offers you a broad spectrum on the legal, regulatory and ethical issues that arise with the development and use of Big Data and Artificial Intelligence.

During this program,  you will get a comprehensive view on the latest developments in Big Data and Artificial Intelligence (AI) related to the law and legal practice, including how to apply GDPR in all phases of the development and deployment of AI systems, and what risk management tools are required to ensure Algorithmic Accountability.

We will fully cover the draft proposal for an EU Regulation laying down harmonized rules on artificial intelligence (draft Artificial Intelligence Act) that was presented by the European Commission in April 2021. Having followed this program, you have an up-to-date understanding of the privacy, data protection and ethical challenges of Big Data and Artificial Intelligence and you will be able to apply law and regulations when dealing with such technologies.

This program will be offered at the Faculty Club of Tilburg University. 

Register now for Big Data | AI & Law

Become an expert in the field of both big data and law

Having followed the Big Data | AI & Law program, you will be acquainted with the legal issues in relation to the data revolution including topics like the GDPR, Algorithmic Accountability and responding to ethical dilemmas. You will know exactly which role Big Data and AI are taking in today’s legal landscape and know how to deal with Big Data and AI related legal and ethical issues in everyday practice. You will familiarize yourself with the EC proposal for an AI Regulation and be able to follow the relevant legislative developments.

The Big Data | AI & Law program in short

  • Start: Next program starts on November 7, 2022
  • Price: € 2,900 (Tilburg University alumni receive a 10% discount)
  • Duration:  4 full days
  • NovA hours: 24
  • Location: The Faculty Club, Tilburg University Campus
    Route description
  • Language of instruction:  English

Why the Big Data | AI & Law program of Tilburg University?

  • From start-ups to corporates and the public sector, big data and AI touch all of us. The program will help you and your organization anticipate and adapt to a changing world while keeping an eye on the ethical and societal impact of big data.
  • You will become familiar with privacy/data protection and accountability issues and ethical challenges that arise when using big data and AI. You will also learn how to apply the law in relation to these technologies
  • This program offers you an introduction in the essentials of national and European law and regulation in light of big data and AI developments. On top of the key privacy, data protection and accountability issues relevant for big data and AI, the program covers various ethical issues and dilemma’s that arise in relation to the use of Big Data and AI.
  • You will familiarize yourself with the provisions of the EC proposal for the AI Regulation and the new rules it is going to bring along.

Standard program Big Data | AI & Law

Day 1 – November 7

Artificial Intelligence & Society: The Big Picture (morning session)

Description

This morning session of the first day will give a general introduction to societal issues relating to AI. We will look at the history of AI and see how its definition evolved in relation to technical and social developments. We will also look at utopian and dystopian images of AI in public debate and popular culture. Finally, the module will deal with patterns in the AI strategies of different countries.

Learning goals for this session are:

  1. Understand different currents in AI and their evolution
  2. Analyse frames of human interaction with AI
  3. Differentiate common patterns as well unique elements in national AI strategies
Artificial Intelligence meets the Law: From the GDPR to the draft AI Regulation (afternoon session)

Description

Most companies already deploy machine learning algorithms, which are algorithms that can learn from and make predictions on data, but cannot explain their outcomes (they are a ‘black box’).  Although the European General Data Protection Regulation (GDPR) does not provide for compliance requirements specific to applying machine learning algorithms, the combined requirements of the GDPR entail that machine learning algorithms need to be designed, developed and applied in a transparent, predictable and verifiable manner (‘Algorithmic Accountability’). This is also in line with recent guidance on deployment of AI issued by the European Data Protection Board. This afternoon session will analyse in depth the provisions of the GDPR that are relevant for AI, it will discuss the draft AI Regulation and will explain what Algorithmic Accountability means in practice, including:

  • Analyse the relevant data protection principles in play, such as fair, lawful and transparent processing & accountability;
  • Identify the special challenges that arise with regard to these principles in the context of AI big data analytics;
  • Discuss additional challenges that arise when AI involves automated decision-making based on profiling;

Day 2 – November 14

AI How to implement Algorithmic Accountability (10 steps for white box – development) morning & afternoon session

Description

The morning and afternoon session of the second day will build upon the topics and issues dealt with and explained in the afternoon session of the first day. Prof. Lokke Moerel and Mr. Marijn Storm will discuss in detail the 10 steps to implement to achieve algorithmic accountability in accordance with the GDPR and the draft AI Regulation.

Participants will get insights on:

  • The latest on how to address unlawful bias in algorithms
  • How to deploy an algorithm to prevent existing unlawful discrimination
  • Cursing in the privacy church: why we need sensitive data categories to address bias
  • What do the EDPB and EU Data Protection Authorities expect and what can actually be achieved?
  • How to train AI if you need to make distinctions between minority groups, like in healthcare
  • When does disparate impact turn into disparate treatment?
  • Alternatives to facilitate explainability to individuals if the AI is a black box
  • How to document the development process and comply with the DPIA requirements under GDPR
  • If we follow GDPR, are we OK under the draft AI Regulation?
  • If we follow GDPR, are we also OK elsewhere in the world?
  • If we follow GDPR, do we have to do more about ethics?

Day 3 - November 21

Controlling AI: how to establish a governance framework to facilitate responsible adoption and scale of AI (morning session)

Description

Supervisory authorities around the globe, typically consider the so-called three lines of defense model as best practice for risk management and internal control. This model is not fit-for-purpose when it comes to digital innovation. Because new technologies are not fully regulated yet, it is difficult to perform a clear-cut compliance check. AI opens up a whole new range of design issues and associated ethical dilemma’s.  Years of controls by the compliance function have undermined the self-learning capacity of the business to make contextual assessments and factor in ethical considerations. This leaves the compliance department with no other option but to reject the innovation. Responsible innovation is only possible if the relevant compliance experts are part of the innovation team and if teams take joint responsibility for compliance.

  • How to adapt the 3-lines-of-defense model to ensure responsible innovation
  • How to train your data scientists and innovation teams on ethical dilemmas
  • How to implement quality assurance and business controls to ensure ‘responsible AI’
Responsible AI in practice: Interactive case study & reflections on real-life challenges around AI risk and accountability (afternoon session)

Description

In our increasingly information-based and algorithmic society it is not surprising that the attention for Responsible AI is rapidly growing. Responsible AI is about organizations ensuring that their use of AI fulfills a number of criteria. First, that it’s ethically sound and complies with regulations in all respects; second, that it’s underpinned by a robust foundation of end-to-end governance; and third, that it’s supported by strong performance pillars addressing bias and fairness, interpretability and explainability, and robustness and security.

While theories in this domain still are in an early stage of development, practice is already placing designers, developers, users, and subjects of these AI systems before important risks, dilemmas and choices.

In this session we will dive into the practice of Responsible AI. Through an interactive case study, we will look at what it takes to develop an AI algorithm and what the key risks and considerations are in doing so. Furthermore, we will explore current approaches and instruments for AI Accountability, using examples from practice.

Day 4 - November 28

Ethical issues in relation to Big Data & AI (morning session)

Description

The morning session of the fourth day will deal with the relevance and use of ethics in relation to big data analytics. Topics will include the relevance of ethics for privacy, accountability, transparency and fairness. We will also consider the new problems on the individual, group and societal level that are arising through data analytics, algorithms and AI, and will discuss how ethical frameworks intersect with legal ones in guiding the real-world activities of data scientists. Goals for this module are for participants to:

  1. Understand the different perspectives on ethics in relation to data science, and be able  to apply these perspectives to evaluate practice;
  2. Differentiate between the risks of data analytics that are addressed by current data protection frameworks and those that are not;
  3. Determine which conceptual framework to apply to a given problem, and how to relate ethical principles and practice broader problems in relation to emerging data analytic techniques.
Where Ethics meets Personal Protection - practical dilemma's and ways of dealing with them (afternoon session)

Description

The day will end with a discussion of ethical dilemma’s encountered in practice when developing and implementing AI tooling

  • In retail (loyalty programs)
  • Distribution (optimization)
  • HR recruiting tools
  • Fraud prevention tooling
  • Financial services (inclusive financing, customer duty of care)

Practical information Big Data | AI & Law program 

Location

The classes will be held at The Faculty Club, Tilburg University Campus 

Route description

Time schedule

Each class starts at 09:30 hrs. and ends around 17:00 hrs. The complete program Big Data | AI & Law equals 24 NovA hours. At the end of the program your will receive a certificate upon request stating the sessions/modules and associated hours.

Costs and lifelong learning discount for Tilburg University alumni

The tuition fee for Big Data | AI & Law is € 2,900 for the 4-day program. The tuition fee includes all course materials and catering, but does not include lodging expenses. Tilburg University alumni receive a 10% discount.

Tilburg University Alumni

Lifelong learning is needed in our everchanging environment. At Tilburg University we want to encourage and stimulate lifelong learning. To make participating in Professional Learning programs even more appealing Tilburg University offers a 10% discount on every Professional Learning program for Tilburg University alumni.

To apply for the discount simply state you are a Tilburg University alumnus in the registration form of the program you are interested in. 

Your profile

The program Big Data | AI & Law is open to everyone who is interested to learn more about big data and law.

Teaching methods

The program Big Data | AI & Law consist of a combination of keynotes, lectures, workshops and discussions led by experts in the field. All sessions are characterized by a mix of theoretical and practical aspects of big data and law.

COVID-19

If the Dutch government imposes new restrictions due to rising infection rates, and as a result of this the course is not allowed to take place physically, then the course will be offered completely online.

General terms and conditions Professional Learning

You can register for this course only by filling out the online registration form on the website. You will immediately receive a digital confirmation of your admission.

General terms and conditions Professional Learning

Course fee

The course fee is due 14 days before the start of the course. No VAT will be charged for this course.

Changes

Tilburg University reserves the right to change parts of the course in the event of unforeseen circumstances or recent developments. You will be informed of any changes as soon as possible.

COVID-19

If the Dutch government imposes new restrictions due to rising infection rates, and as a result of this the course is not allowed to take place physically, then the course will be offered completely online.

Cancellation

Cancellation by a course participant needs to take place in writing. If you cancel in writing not later than four weeks before the first course day, the course fee will be refunded. Tilburg University reserves the right to cancel the course if an insufficient number of participants have registered.

Evaluation

After every course day, the course participants will be given an evaluation form. It is very important for the further development of the post-academic courses to receive the course participants’ feedback through these evaluation forms. The information obtained will be used as much as possible in organizing and designing future courses.

Complaints

The course participant can report any complaints to Tilburg University in writing. The complaint needs to be described in detail. Complaints do not suspend the obligation to pay the course fee. If the complaint is upheld by Tilburg University, the course participant will receive a reduction of the course fee.

Big Data | AI & Law

Are you interested?

Contact

Krisztina Dubach-Pataki

Program Coordinator

Taner Kuru

Moderator

prof. dr. Eleni Kosta

Academic director

prof. dr. Lokke Moerel

Academic director