Mon, 20 Jan

• 8:30 – 9:00

  Welcome Speech – WP9 Leads

  Lecturers:  Sanda Filip (Vice-Rector University of Oradea), Cristian Miheș (Dean Faculty of  Law Oradea),  Dorin Coita (Vice-Dean FSE Oradea),   Wouter van Heeswijk (University of Twente, MSCA WP7 Lead),  Catarina Simões da Silva & Ioana Coita (MSCA – WP9 Leads), Marius Vlad Pop (FinNex Doctoral Researcher)

• 9:00 – 11:00

• Introduction to Ethics (1/2)

  • Location: Biblioteca Universității, University Of Oradea 📍Directions

  Lecturer: Frédérik Sinan Bernard (University of Twente)

  This intensive course provides a comprehensive introduction to ethical theories and their critical application within the realms of mathematics, statistics, and data science and beyond, in social sciences. Designed specifically for PhD students and faculty members of the MSCA DIGITAL FINANCE network, the 2-part lecture bridges foundational philosophical concepts with contemporary issues in technology and finance.

  Focus Areas: Financial Data Space (Ethical Considerations: Data privacy, consent, and ownership; Philosophical Lens: Kant’s duty-based ethics emphasizing respect for individuals’ rights; Application: Balancing the need for data in research with stringent privacy regulations like GDPR), Artificial Intelligence for Financial Markets (Ethical Challenges: Market manipulation, algorithmic bias, and transparency; Philosophical Lens: Utilitarianism and Rawls’ theory of justice to assess the broader societal impact;

  Application: Developing fair AI models that promote equitable financial opportunities), Explainable and Fair AI( Ethical Imperative: Transparency and accountability in AI; Philosophical Lens: Aristotle’s virtue ethics highlighting honesty and integrity; Application: Crafting AI algorithms that are not only effective but also interpretable and just), Driving Digital Innovations with Blockchain (Ethical Dilemmas: Privacy vs. transparency, environmental sustainability; Philosophical Lens: Balancing utilitarian benefits with Kantian duties to society; Application: Innovating blockchain solutions mindful of ethical trade-offs), Sustainability of Digital Finance (Ethical Focus: Long-term social and environmental consequences; Philosophical Lens: Aristotle’s concept of the common good and Rawls’ principles of fairness; Application: Promoting responsible fintech developments that align with ESG criteria).

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• 11:00 – 11:05

  Coffee Break

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• 11:05 – 13:50

  Ethical guidelines for AI models

  Lecturer: Catarina Silva (University of Coimbra)

  This session explores ethical guidelines for AI models, focusing on principles such as fairness, transparency, accountability, and privacy. Participants will examine real-world case studies and regulatory frameworks to understand the challenges and best practices in developing and deploying ethical AI systems. The session aims to equip researchers with tools to navigate ethical dilemmas and design AI models that align with societal values while fostering trust and minimizing risks.

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• 13:50 – 15:30

  Lunch Break

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• 15:30 – 17:20

  Ethicality Requirements Elicitation and Analysis

  Lecturer: Renata Guizzardi (University of Twente)

  As systems increasingly impact societal norms, ensuring ethicality in their design and implementation has become a critical concern. This course explores the foundational principles, methods, and frameworks for eliciting and analyzing ethicality requirements in technology-driven projects. Students will engage with interdisciplinary perspectives, including ethics, engineering, and behavioral science, to understand the complexities of translating abstract ethical principles into actionable system requirements.

  Key topics include stakeholder identification, the role of biases in ethical decision-making, regulatory and compliance considerations, and techniques for managing ethical trade-offs in system design. Through case studies, practical exercises, and collaborative projects, participants will develop skills to systematically capture ethical concerns and integrate them into the requirements engineering process.

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• 17:20 – 17:30

  Coffee Break

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• 17:30 – 18:30

  Ethics for Financial Analysts

  Lecturer: Stefan Theußl (Research Innovation Hub of Raiffeisen Research at RBI Group)

  In the rapidly evolving landscape of AI and digital finance, ethical considerations are paramount for financial analysts. This talk delves into the core ethical principles outlined by the EFFAS Principle of Ethical Conduct [1], as well as the CFA Institute Code of Ethics and Standards of Professional Conduct [2], emphasizing the imperative to act with integrity, competence, diligence, and respect. Financial analysts are called to prioritize the interests of clients and the integrity of the investment profession above personal gains, exercising independent professional judgment and promoting ethical behavior. These principles become increasingly crucial as analysts begin to interact with AI technologies, both as tools for drafting assessments and as interfaces for client engagement.

  19:00 – 21:00

  Networking Dinner

Tue, 21 Jan

Location: Oradea Fortess, Building F, Oradea Tech Hub 📍Directions

• 9:00 – 9:55

  Data Science in a mathless Digital Society

  Lecturer: Wolfgang Karl Härdle (Humboldt-Universität zu Berlin)

  In an increasingly digitalized world, the demand for actionable insights from data has never been greater. Yet, paradoxically, we find ourselves in a society where mathematical literacy is often sidelined in favor of intuitive, user-friendly interfaces. This talk explores how data science can thrive in a “mathless” digital society, where the emphasis shifts from technical expertise to accessibility and democratization. We will examine the role of automation, machine learning, and no-code tools in bridging the gap between complex algorithms and practical decision-making. Case studies will illustrate how these advancements empower individuals and organizations to harness the power of data without requiring deep mathematical knowledge. The talk also addresses the risks of oversimplification and the need for ethical frameworks to guide the responsible use of data-driven technologies. 

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• 10:00 – 10:55

  XAI for Finance

  Lecturer: Daniel Pele (University of Economics in Bucharest)

  In the rapidly evolving field of artificial intelligence, transparency and trust are critical for ensuring the ethical and effective deployment of AI systems. This course, Introduction to Explainable AI (XAI), provides a foundational understanding of the principles, methods, and tools used to make AI models interpretable and explainable to diverse stakeholders.

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• 11:00 – 11:50

  Cognitive biases – from humans to machines

  Lecturer: Xiaohong Huang (University of Twente)

  Cognitive biases, the systematic deviations from rational decision-making, shape human judgment and behavior in profound ways. As artificial intelligence and machine learning systems increasingly influence critical decision-making processes, understanding how these biases manifest in machines is essential. This course delves into the origins, mechanisms, and impacts of cognitive biases, exploring their transition from human cognition to algorithmic design and application.

  Students will examine key cognitive biases such as anchoring, confirmation bias, and availability heuristics, investigating their implications for human behavior and the risks they pose when embedded in AI systems. Topics include bias detection and mitigation strategies, the interplay between biased data and algorithms, and the ethical considerations of designing bias-aware systems. Case studies from diverse fields such as healthcare, finance, and social media will provide real-world context to theoretical insights.

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• 11:50 – 12:00

  Coffee Break

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• 12:00 – 12:50

  Ethicality Requirements Elicitation and Analysis

  Lecturer: Renata Guizzardi (University of Twente)

  As systems increasingly impact societal norms, ensuring ethicality in their design and implementation has become a critical concern. This course explores the foundational principles, methods, and frameworks for eliciting and analyzing ethicality requirements in technology-driven projects. Students will engage with interdisciplinary perspectives, including ethics, engineering, and behavioral science, to understand the complexities of translating abstract ethical principles into actionable system requirements.

  Key topics include stakeholder identification, the role of biases in ethical decision-making, regulatory and compliance considerations, and techniques for managing ethical trade-offs in system design. Through case studies, practical exercises, and collaborative projects, participants will develop skills to systematically capture ethical concerns and integrate them into the requirements engineering process.

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• 13:00 – 13:50

  AI Act – regulation & compliance

  Lecturer: Cristian Mihes (Faculty of Law – University of Oradea)

  The AI Act is a significant piece of legislation aimed at regulating artificial intelligence (AI) within the European Union. It establishes a comprehensive legal framework to ensure the development and deployment of AI systems are safe, transparent, and aligned with fundamental rights. The Act categorizes AI systems based on risk levels, with stricter regulations for high-risk applications and bans on those deemed unacceptable, such as social scoring by governments.

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• 14:00 – 15:30

  Lunch Break

  Visit to Oradea Musem

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• 15:40 – 16:30

  Implications and future scenarios about the use of GenAI in banking and society

  Lecturer: Renato Rocha Souza (Research Innovation Hub of Raiffeisen Research at RBI Group)

  The presentation will cover an introduction to large language models (LLMs), highlighting their capabilities and the transformative potential they hold for various industries. We will briefly discuss the concept of Artificial General Intelligence (AGI) and the future scenarios it might enable, emphasizing the profound societal changes that could arise. Additionally, we will explore the potential of Generative AI (GenAI) to revolutionize creative industries, content generation, and personalized experiences. We will address the pervasive issue of biases in LLMs and their ethical ramifications. As AI systems become increasingly integrated into various sectors, the biases inherent in LLMs can lead to unfair or discriminatory outcomes. We will examine the sources of these biases, including training data and algorithmic design, and their potential impacts on marginalized communities. By fostering a dialogue on responsible AI practices, we aim to raise awareness and promote the creation of more equitable and trustworthy AI systems.

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• 16:40 – 17:30

  Diversity aspects in Banking/ Fintech

  Lecturer: Ioana Popa (Banca Transilvania)

  As we look ahead, the AI enabled future is not anymore about tech, or STEM as we used to know them. It is about creativity, about shaping the technologies for their best of use. Education plays a key role in this transformation. By encouraging young women, or experienced professionals to thrive using these tools, we can ensure that technologies of tomorrow embed diverse needs, perspectives and enable deeper expertise.

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• 17:30 – 18:30

  Ethical Boundary in AI-Based Risk and Scoring Models in retail banking industry – study case

  Lecturer: Ionut Verzea (FinNex)

  The era of artificial intelligence (AI) in risk evaluation is reshaping the financial sector, surpassing the limitations of traditional scoring models that relied on limited data categories. With technological advancements enabling the processing of larger datasets with greater accuracy and speed, the potential to develop more efficient and secure risk assessment systems has never been greater.

  19:00 – 21:00

  Networking Dinner

Wed, 22 Jan

Location: Biblioteca Universității, University Of Oradea, Str Universitatii nr 1. 📍Directions

• 9:00 – 9:50

  Explainable Reinforcement Learning

  Lecturer: Wouter van Heeswijk (University of Twente) 

  In the talk “Explainable Reinforcement Learning,” we delve into the explainable AI techniques that are applicable to sequential decision making in finance. The presentation begins by outlining foundational explainable AI techniques, proceeds with techniques tailored to reinforcement learning in the computer science domain, and ends with the green field of explainable reinforcement learning in finance.

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• 9:50 – 10:30

  Introduction to Ethics (2/2)

  Lecturer: Frédérik Sinan Bernard (University of Twente)

  This intensive course provides a comprehensive introduction to ethical theories and their critical application within the realms of mathematics, statistics, and data science and beyond, in social sciences. Designed specifically for PhD students and faculty members of the MSCA DIGITAL FINANCE network, the 2-part lecture bridges foundational philosophical concepts with contemporary issues in technology and finance.

  Focus Areas: Financial Data Space (Ethical Considerations: Data privacy, consent, and ownership; Philosophical Lens: Kant’s duty-based ethics emphasizing respect for individuals’ rights; Application: Balancing the need for data in research with stringent privacy regulations like GDPR), Artificial Intelligence for Financial Markets (Ethical Challenges: Market manipulation, algorithmic bias, and transparency; Philosophical Lens: Utilitarianism and Rawls’ theory of justice to assess the broader societal impact; Application: Developing fair AI models that promote equitable financial opportunities), Explainable and Fair AI( Ethical Imperative: Transparency and accountability in AI; Philosophical Lens: Aristotle’s virtue ethics highlighting honesty and integrity; Application: Crafting AI algorithms that are not only effective but also interpretable and just), Driving Digital Innovations with Blockchain (Ethical Dilemmas: Privacy vs. transparency, environmental sustainability; Philosophical Lens: Balancing utilitarian benefits with Kantian duties to society; Application: Innovating blockchain solutions mindful of ethical trade-offs), Sustainability of Digital Finance (Ethical Focus: Long-term social and environmental consequences; Philosophical Lens: Aristotle’s concept of the common good and Rawls’ principles of fairness; Application: Promoting responsible fintech developments that align with ESG criteria).

   

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• 10:30 – 11:15

  Ethics in Social Science Research with a Focus on Experimental Economics

  Lecturer: Jana Peliova (University of Economics in Bratislava)

  The convergence of digital finance with ethical and sustainability considerations is reshaping the financial landscape, presenting both opportunities and challenges. The talk aims to provide a comprehensive understanding of how ethical principles and sustainability objectives can be integrated into digital finance, guiding the sector towards responsible innovation and long-term value creation.

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• 11:15 – 11:30

  Coffee Break

   

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• 11:30 – 12:00

  Transparency and Bias in Financial Models

  Lecturer:  Karsten Wenzlaff (University of Hamburg) &  Olivija Filipovska (Geostrategic Institute Global Skopje)

  The rapid advancement of digital technologies has fundamentally transformed the financial sector, introducing both unprecedented opportunities and complex ethical challenges. This talk, titled “Ethics in Digital Finance,” will explore the multifaceted ethical considerations that arise from the integration of digital innovations in financial services. The talk aims to provide a comprehensive understanding of the ethical landscape in digital finance, offering insights into how financial institutions can navigate these challenges to foster trust and integrity in the digital age. 

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• 12:00 – 12:45

  Embedding Corporate Digital Responsibility in Financial Services Organisations

  Lecturer: Adriana Tiron-Tudor (University of Babes-Bolyai in Cluj)

  As digital transformation reshapes the financial services landscape, organizations face growing expectations to act responsibly in their use of technology. Corporate Digital Responsibility (CDR) encompasses a commitment to ethical, sustainable, and accountable practices in the design, deployment, and governance of digital systems. This course provides a comprehensive framework for understanding and integrating CDR principles into financial services organizations.

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• 12:45 – 13:00

  Ethics in AI for tax research tool – application

  Lecturer: Matilda Barrow (Thomson Reuters)

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• 13:00 – 14:15

  Lunch Break

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• 14:20 – 17:40

• 17:40 – 18:30