GATE involves in its activities graduate and post graduate students from its partner organisations – primarily in its scientific and collaborative research projects and related activities but also in other activities, as appropriate. The GATE scientists transfer knowledge and facilitate contact and interaction with the Institute through teaching in its partner organisations. The primary aim of the education is to prepare high-level specialists able to address the contemporary problems and to integrate quickly in the real business environment. The GATE member organisations and companies are invited to advise on the curriculum and, after agreement with the partners, take part in the teaching.

Course Title: The Artificial Intelligence Act: building an AI governance programme for your business

Course Delivered by: Ivo Emanuilov, Boyan Dafov

Duration: 3 hours

Who is this for: This course is designed for business executives, chief operating officers, chief technical officers and other C-level executives, senior data scientists, as well as lawyers and legal counsels of companies developing, deploying and using artificial intelligence solutions.

What you will learn:

  • Understand the requirements of the AI Act as they apply to your company, your use case, and your workflows and operations
  • Understand the interaction between the AI Act and other legal instruments, such as the General Data Protection Regulation, the Data Act and the Copyright and Neighbouring Rights Act
  • Understand how generative AI impacts your data protection compliance and intellectual property management, including the use of copyright protected works as training data, model training and inference, and managing opt-outs through terms and conditions and machine-readable means
  • Get support in and blueprints for building your company’s AI governance programme through our action learning approach to problem solving
  • Gain hands-on experience in an interactive session that involves prototyping a solution to a shared problem or challenge with the implementation of the AI Act

Course delivery: This course is designed as an on-premises course to be delivered as an interactive workshop in a classroom setting.

Description: This course helps business executives and senior data scientists develop their company’s AI governance strategy. It explains the differences between AI law and ethics and covers core topics of the EU Artificial Intelligence Act. The course introduces the essentials of the risk-based approach to AI governance and examines its impact on AI development and new business opportunities. Participants will learn what an AI management system should include, including prohibited practices, risk management, data governance, technical documentation and record-keeping, transparency, human oversight, accuracy, robustness, and cybersecurity. The course features an interactive session where participants, guided by legal and technical experts, prototype solutions to common AI Act implementation problems in businesses and develop a blueprint for an AI governance programme.

Course Outline

Session 1: Introduction to the AI Act: from compliance to governance (1 hour)

  • Practical differences between AI ethics and AI law in a commercial context
  • Introduction to the regulatory architecture of the AI Act and its scope of application
  • Essentials of the risk-based approach to AI governance
  • Expected impact of the AI Act on your development workflows and company operations

Session 2: Building blocks of an AI governance programme (1 hour)

  • ISO/IEC 42001: the standard for AI management systems
  • Risk management
  • Data governance and data management
  • Technical documentation and record-keeping
  • Transparency and provision of information
  • Human oversight
  • Accuracy, robustness and cybersecurity

Session 3: Interactive workshop: let’s prototype a solution to your business problems under the AI Act (1 hour)

  • A real-world use case will be explored based on participants’ preferences expressed during the registration process
  • An end-to-end compliance solution to be problem will be prototyped in collaboration with the participants
  • Lessons learned and policy insights will be discussed, eg, real or perceived uncertainty in the application of the regulation, feasibility of prototyped solution, and desired improvement in future iterations

Interactive elements:

This course is designed to engage participants actively with multiple interactive elements that enhance learning and application of the content:

  • Group discussions: Each session includes dedicated time for group discussions, allowing participants to share insights, challenge each other’s thinking, and collaboratively explore complex topics related to AI regulation and governance.
  • Policy prototyping exercise: Policy prototyping is a design approach used to test and improve the effectiveness of a proposed policy. It involves creating low-resource, quickly deployed versions of policies to evaluate their potential impacts and feasibility before full implementation. This method allows you to learn about the strengths and weaknesses of an idea, identify new directions, and make adjustments in a low-risk environment. Our approach is based on use cases collected from the participants during their registration for the course.
  • Action learning: Unlike most “one-size-fits-all” training offers, you get to work on real business challenges and develop tangible tools or documents, such as an AI governance programme, that you can immediately apply in your work environment.

Credentials:
Meet our esteemed instructors, each a recognised expert in their field, holding advanced degrees and possessing extensive experience.

Ivo Emanuilov is an experienced researcher at GATE Institute specialising in the field of AI and data law, policy and regulation. He is an intellectual property lawyer and a computer programmer with a background in computer science, mathematics and system programming. He holds degrees in law and computer science from Sofia University, University of Cambridge, University of London and KU Leuven. He advises companies, governments and research organisations on legal, business and technology matters related to intellectual property management, data protection and governance, AI and open source. He specialises in open source and commercial software licensing, development of IP strategy and IP management systems, IP risk management, policies and assessment of machine learning models, training data sets and data sharing agreements. With over 10 years of international post-qualification experience as a practising lawyer in Bulgaria and as part of CiTiP – an imec research group at KU Leuven in Belgium, he combines advanced legal and technical knowledge and business acumen to provide practical and innovative solutions for clients in the manufacturing, automotive, semiconductor, aerospace, defence, and biometric technology domains.

Boyan Dafov is а researcher at GATE Institute. His work at the Institute is focused on the applications of various techniques for Data Analysis and Artificial Intelligence in the field of disinformation. His interests include Artificial Intelligence, Political Science, Teaching and Entrepreneurship. Boyan holds a BSc Computer Science from Sofia University St Kliment Ohridski, an MSc Artificial Intelligence and an MA Political Science. He is a part-time research assistant in Mathematical Logic, Logic Programming, Formal Languages ​​and Artificial Intelligence in the undergraduate programmes at the Faculty of Mathematics and Informatics of Sofia University.