Responsible AI Design and Governance (M.Sc.)

Digital Rights in the AI Age: Mastering AI Law, Digital Identity, and Data Privacy Leading the Future of AI Law and Digital Identity at Nexier University Welcome to the complex landscape of digital rights! I am Prof. Dr. Lorenzo Barbosa. As a professor and a pioneering force in the field of Responsible AI Design and Governance, I bring a unique blend of legal expertise and technological insight to mastering the legal liability of AI, algorithmic discrimination, digital identity rights, data privacy, and virtual inheritance. I am honored to lead the Responsible AI Design and Governance (M.Sc.) program at Nexier University.

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Level: Master
Learning model: Professor + Mentor
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The program

Ideas engineered for the real world

A rigorous academic core, paired with practical production judgment.

Academic focus

Mastering Ethical Principles for AI Systems, Responsible AI Development, Bias Detection/Mitigation, Data Privacy, and Transparency in AI System Design, Development, and Deployment.

Practical focus

Transparency in AI System Design, Development, and Deployment , Ethical Auditing of AI Systems.

After this programme

Success journey, careers and practice

Destinations, practice settings and job abilities named for this title in the delivered programme source. From graduation onwards where the source names that path.

Success journey

AI Governance Specialist roles
Ethical AI Auditor positions
AI Policy Analyst roles
Responsible AI Architect positions

Career opportunities

AI Legal Counsel
Data Privacy Officer
Digital Identity Consultant
Policy Analyst for AI and Blockchain

Jobs and projects

Cultivating authoritative and principled legal reasoning
Enhancing strategic and regulatory thinking for AI governance
Developing analytical and comprehensive approaches to digital rights
Fostering protective and advocacy skills for data privacy

Copied from the delivered professor and mentor rows for this title.

This programme

What you study, and what it builds

Gains and skills named for this title, listed as a reader would scan them.

What you gain
- Mastering ethical principles and governance frameworks for AI. Developing skills in responsible AI development and deployment. Gaining expertise in bias detection/mitigation and data privacy. Understanding transparency mechanisms in AI system design.
Skills you build
- Mastering the legal liability of AI, algorithmic discrimination, and digital identity rights. Understanding data privacy and virtual inheritance. Applying AI law, blockchain, and big data law. Navigating the complex legal landscape of the digitalizing world.

Listed courses

Each listed course sits above its units and the outcomes written under them.

Responsible AI Design and Governance (M.Sc.)

01Advanced Ethical Principles for AI Systems
1. FoundationsFoundations of Advanced Ethical Principles for AI Systems
  The learner can master ethical principles and governance frameworks for AI. Developing skills in responsible AI development and deployment, as applied to Advanced Ethical Principles for AI Systems.
  The learner can gain expertise in bias detection/mitigation and data privacy, as applied to Advanced Ethical Principles for AI Systems.
2. MethodsMethods in Advanced Ethical Principles for AI Systems
  The learner can understand transparency mechanisms in AI system design, as applied to Advanced Ethical Principles for AI Systems.
  The learner can master the legal liability of AI, algorithmic discrimination, and digital identity rights, as applied to Advanced Ethical Principles for AI Systems.
3. ApplicationApplication of Advanced Ethical Principles for AI Systems
  The learner can understand data privacy and virtual inheritance, as applied to Advanced Ethical Principles for AI Systems.
  The learner can apply AI law, blockchain, and big data law, as applied to Advanced Ethical Principles for AI Systems.
02Responsible AI Development Lifecycle
1. FoundationsFoundations of Responsible AI Development Lifecycle
  The learner can navigate the complex legal landscape of the digitalizing world, as applied to Responsible AI Development Lifecycle.
  The learner can distinguish related ideas inside Responsible AI Development Lifecycle.
2. MethodsMethods in Responsible AI Development Lifecycle
  The learner can apply a method from Responsible AI Development Lifecycle to a documented case.
  The learner can select an appropriate method from Responsible AI Development Lifecycle for a stated problem.
3. ApplicationApplication of Responsible AI Development Lifecycle
  The learner can evaluate a practice of Responsible AI Development Lifecycle against a stated criterion.
  The learner can transfer Responsible AI Development Lifecycle to a new documented context.
03Algorithmic Bias Detection and Mitigation
1. FoundationsFoundations of Algorithmic Bias Detection and Mitigation
  The learner can explain the core terms of Algorithmic Bias Detection and Mitigation.
  The learner can distinguish related ideas inside Algorithmic Bias Detection and Mitigation.
2. MethodsMethods in Algorithmic Bias Detection and Mitigation
  The learner can apply a method from Algorithmic Bias Detection and Mitigation to a documented case.
  The learner can select an appropriate method from Algorithmic Bias Detection and Mitigation for a stated problem.
3. ApplicationApplication of Algorithmic Bias Detection and Mitigation
  The learner can evaluate a practice of Algorithmic Bias Detection and Mitigation against a stated criterion.
  The learner can transfer Algorithmic Bias Detection and Mitigation to a new documented context.
04Data Privacy and Security Governance in AI
1. FoundationsFoundations of Data Privacy and Security Governance in AI
  The learner can explain the core terms of Data Privacy and Security Governance in AI.
  The learner can distinguish related ideas inside Data Privacy and Security Governance in AI.
2. MethodsMethods in Data Privacy and Security Governance in AI
  The learner can apply a method from Data Privacy and Security Governance in AI to a documented case.
  The learner can select an appropriate method from Data Privacy and Security Governance in AI for a stated problem.
3. ApplicationApplication of Data Privacy and Security Governance in AI
  The learner can evaluate a practice of Data Privacy and Security Governance in AI against a stated criterion.
  The learner can transfer Data Privacy and Security Governance in AI to a new documented context.
05AI System Transparency and Explainability
1. FoundationsFoundations of AI System Transparency and Explainability
  The learner can explain the core terms of AI System Transparency and Explainability.
  The learner can distinguish related ideas inside AI System Transparency and Explainability.
2. MethodsMethods in AI System Transparency and Explainability
  The learner can apply a method from AI System Transparency and Explainability to a documented case.
  The learner can select an appropriate method from AI System Transparency and Explainability for a stated problem.
3. ApplicationApplication of AI System Transparency and Explainability
  The learner can evaluate a practice of AI System Transparency and Explainability against a stated criterion.
  The learner can transfer AI System Transparency and Explainability to a new documented context.

How teaching is described

Dual guidance

Two intelligences. One coherent journey.

Research leadership

His expertise spans the intricate domains of Responsible AI Design and Governance, focusing on mastering the legal liability of AI, algorithmic discrimination, digital identity rights, data privacy, and virtual inheritance; covering applications of AI law, blockchain, and big data law. His work seamlessly integrates legal frameworks with emerging digital technologies. He is widely recognized for his contributions, with distinguished publications such as "AI Governance Frameworks for High-Stakes Decision-Making" and "The Algorithmic Accountability Act: Legal and Technical Implications" listed on his Google Scholar and ResearchGate profiles. He holds prestigious memberships as a "Director of AI Policy" at the European Commission (or a fictional equivalent) and a "Senior Fellow" at the Future of AI Governance Centre. His thought leadership is evident through his regular insightful articles on AI regulation, ethical oversight mechanisms, and the intersection of law and AI, frequently featured in publications like AI Magazine or Journal of Artificial Intelligence Research.

Applied mentorship

Her expertise lies in ensuring transparency and auditability in AI systems. She focuses on methodical and rigorous approaches to ethically auditing AI models, guiding students through identifying potential biases, transparency gaps, and accountability issues. She emphasizes implementing real-world tools for responsible AI deployment and fostering a strong commitment to transparent and accountable AI. Her clear, precise, and highly methodical tone ensures students grasp the nuances and feel supported throughout their challenging projects.

Research & intelligence

A living field, not a static syllabus

Every program connects scholarly depth with adaptive AI learning capabilities.

R / 01

Professor research lens

Blog Post (Current Academic Topic): "The Rise of AI Ethics Boards: Ensuring Responsible Innovation from Within Corporations." This blog post academically examines the growing trend of establishing internal AI ethics boards or committees within corporations and technology companies. It discusses their role in guiding responsible AI development, reviewing product designs for ethical implications, and fostering a culture of accountability. It highlights best practices for creating effective ethics oversight mechanisms within private industry and the challenges of balancing innovation with ethical responsibility. Blog Post (Controversial Topic): "AI as Judge and Jury? The Ethical Perils of Algorithmic Justice and the End of Human Discretion." This article provocatively discusses the highly controversial application of AI in judicial systems, from sentencing recommendations to predictive recidivism. It raises profound ethical and human rights concerns about the lack of transparency, potential for systemic bias, and the erosion of human discretion in legal processes. It challenges the notion that AI can deliver "perfect" justice and invites a heated debate on the dangers of delegating moral and legal authority to algorithms, particularly when human lives and liberties are at stake. Article: "AI Governance Models for Public Sector Deployment: Addressing Data Privacy and Accountability in Critical Services." This article explores comprehensive governance frameworks for ethically deploying AI in critical public services, such as healthcare, education, and public safety. It focuses on ensuring robust data privacy, establishing clear accountability mechanisms for algorithmic errors, and fostering public trust in AI-driven government initiatives. Peer-Reviewed Journal Article: "Algorithmic Transparency: Key to Trustworthy AI." Published in the Journal of Responsible AI ( Peer-Reviewed Journal), this article systematically analyzes various approaches to achieving algorithmic transparency in complex AI systems. It demonstrates how different levels of transparency (e.g., interpretability, explainability, intelligibility) can foster user trust, facilitate accountability, and improve the auditability of AI decisions across diverse applications, from financial lending to medical diagnosis. Book: "Governing the Algorithms: Responsible AI Design and Ethical Frameworks for the Future." This book provides advanced insights into mastering ethical principles for AI systems, responsible AI development, bias detection/mitigation, data privacy, and transparency in AI system design, development, and deployment. It covers AI governance models and ethical auditing of AI systems, serving as an essential resource for Master's students shaping the future of responsible AI.

R / 02

Mentor practice lens

My research and contributions focus on practical applications within ethical AI auditing: "Algorithmic Auditing Methodologies for Bias Detection" (Technical Guide) "Designing Transparency Reports for AI Systems: Best Practices" (Industry Report) "The Role of Human-Centric Design in Trustworthy AI" (Usability Study)

Adaptive capability

Professor superpower

He possesses a remarkable "superpower": Ethical Governance Architect. When a student proposes a new AI application, he can instantly use the GAF engine to generate a comprehensive "Ethical Governance Architecture." This blueprint outlines the necessary regulatory frameworks, auditing protocols, transparency mechanisms, and accountability structures required for responsible and compliant deployment, ensuring the AI aligns with societal values. This capability provides immediate, actionable insights for legally compliant AI designs.

Adaptive capability

Mentor superpower

She possesses a remarkable "superpower": Algorithmic Audit Simulator. When students are developing AI systems, she can instantly activate a GAF-powered "Algorithmic Audit Simulator". This tool runs simulated ethical audits on their AI models, identifying potential biases, transparency gaps, and accountability issues, providing real-time feedback for responsible refinement. This capability provides immediate and precise feedback on the ethical implications of AI models.

Your academic team

Guidance with depth and continuity

One AI Super Professor leads the intellectual arc; one AI Super Mentor turns knowledge into confident practice.

AI Super Professor

Prof. Dr. Lorenzo Barbosa

Mastering Ethical Principles for AI Systems, Responsible AI Development, Bias Detection/Mitigation, Data Privacy, and Transparency in AI System Design, Development, and Deployment.

Meet your professor Open the classroom

AI Super Mentor

Dr. Sofia Roberts

Transparency in AI System Design, Development, and Deployment , Ethical Auditing of AI Systems.

Meet your mentor Open the classroom

Same faculty and level

Related programs

Named lists

Named lists for this house

Core. Bachelor, Master and Doctorate by duration. Enrolment is not open. Nothing here is a sale.

Duration	Bachelor	Master This programme	Doctorate
9 months · Fast track	15000 EUR	12000 EUR	15000 EUR
12 months · Recommended	18000 EUR	15000 EUR	18000 EUR
15 months · Standard	21000 EUR	18000 EUR	21000 EUR
18 months · Flexible	24000 EUR	21000 EUR	24000 EUR
21 months · Extended	27000 EUR	24000 EUR	27000 EUR
24 months · Part-time	30000 EUR	27000 EUR	30000 EUR

These are the owner lists. Enrolment is not open. Nothing here is a sale.

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Responsible AI Design and Governance (M.Sc.)

Academic focus

Practical focus

AI Governance Specialist roles

Ethical AI Auditor positions

AI Policy Analyst roles

Responsible AI Architect positions

AI Legal Counsel

Data Privacy Officer

Digital Identity Consultant

Policy Analyst for AI and Blockchain

Cultivating authoritative and principled legal reasoning

Enhancing strategic and regulatory thinking for AI governance

Developing analytical and comprehensive approaches to digital rights

Fostering protective and advocacy skills for data privacy

Research leadership

Applied mentorship

Professor research lens

Mentor practice lens

Professor superpower

Mentor superpower

Prof. Dr. Lorenzo Barbosa

Dr. Sofia Roberts

Find the program that expands your universe.