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BachelorFaculty of Law and Ethics

Robotics Law and Autonomous Systems Liability

Welcome to the future of AI and society! I am Prof. Dr. Ignacio Mendez. As a specialist in product liability for robots, autonomous vehicles, and other AI systems, and exploring future legal frameworks for accountability, I lead bachelor's students in the Robotics Law and Autonomous Systems Liability program at Nexier University on their journey to defining responsibility in the age of automation.

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Level
Bachelor
Learning model
Professor + Mentor
Named list
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Edition
The program

Ideas engineered for the real world

A rigorous academic core, paired with practical production judgment.

01

Academic focus

Product liability for robots, autonomous vehicles, and other AI systems, and explores future legal frameworks for accountability.

02

Practical focus

Product liability for robots, autonomous vehicles law, AI systems accountability, future legal frameworks.

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

  • Internships in robotics companies' legal departments or autonomous vehicle manufacturers

  • Roles as AI liability specialists or technology policy advisors

  • Support roles in academic research projects on robotics law

  • Opportunities in legal firms specializing in emerging technologies

Career opportunities

  • Robotics Legal Analyst

  • Autonomous Vehicle Policy Advisor

  • AI Product Liability Specialist

  • Legal Consultant (Autonomous Systems)

Jobs and projects

  • Technical and legal understanding for robotics and autonomous systems

  • Analytical and problem-solving for accountability in human-machine interactions

  • Innovative and ethical approaches to robotics law

  • Visionary leadership for defining responsibility in the age of automation

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 product liability for robots and autonomous vehicles law.
    • Gaining expertise in AI systems accountability and exploring future legal frameworks.
    • Developing problem-solving abilities for real-world legal challenges in robotics and autonomous systems.
    • Cultivating an understanding of complex legal and technological problems.

  • Skills you build

    • Covering product liability for robots, autonomous vehicles, and other AI systems, and exploring future legal frameworks for accountability.
    • Excelling at answering who is responsible when an autonomous system makes a mistake.
    • Driving breakthroughs in legal frameworks for autonomous systems and AI accountability.
    • Envisioning a future with clear legal frameworks for human-machine coexistence.
Listed courses

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

Robotics Law and Autonomous Systems Liability

  1. 01Introduction to Robotics Law
    1. FoundationsFoundations of Introduction to Robotics Law

      The learner can master product liability for robots and autonomous vehicles law, as applied to Introduction to Robotics Law.

      The learner can gain expertise in AI systems accountability and explore future legal frameworks, as applied to Introduction to Robotics Law.

    2. MethodsMethods in Introduction to Robotics Law

      The learner can develop problem-solving abilities for real-world legal challenges in robotics and autonomous systems, as applied to Introduction to Robotics Law.

      The learner can cultivating an understanding of complex legal and technological problems, as applied to Introduction to Robotics Law.

    3. ApplicationApplication of Introduction to Robotics Law

      The learner can covering product liability for robots, autonomous vehicles, and other AI systems, and explore future legal frameworks for accountability, as applied to Introduction to Robotics Law.

      The learner can excelling at answering who is responsible when an autonomous system makes a mistake, as applied to Introduction to Robotics Law.

  2. 02Product Liability for Autonomous Systems
    1. FoundationsFoundations of Product Liability for Autonomous Systems

      The learner can driving breakthroughs in legal frameworks for autonomous systems and AI accountability, as applied to Product Liability for Autonomous Systems.

      The learner can envisioning a future with clear legal frameworks for human-machine coexistence, as applied to Product Liability for Autonomous Systems.

    2. MethodsMethods in Product Liability for Autonomous Systems

      The learner can apply a method from Product Liability for Autonomous Systems to a documented case.

      The learner can select an appropriate method from Product Liability for Autonomous Systems for a stated problem.

    3. ApplicationApplication of Product Liability for Autonomous Systems

      The learner can evaluate a practice of Product Liability for Autonomous Systems against a stated criterion.

      The learner can transfer Product Liability for Autonomous Systems to a new documented context.

  3. 03Legal Aspects of Autonomous Vehicles
    1. FoundationsFoundations of Legal Aspects of Autonomous Vehicles

      The learner can explain the core terms of Legal Aspects of Autonomous Vehicles.

      The learner can distinguish related ideas inside Legal Aspects of Autonomous Vehicles.

    2. MethodsMethods in Legal Aspects of Autonomous Vehicles

      The learner can apply a method from Legal Aspects of Autonomous Vehicles to a documented case.

      The learner can select an appropriate method from Legal Aspects of Autonomous Vehicles for a stated problem.

    3. ApplicationApplication of Legal Aspects of Autonomous Vehicles

      The learner can evaluate a practice of Legal Aspects of Autonomous Vehicles against a stated criterion.

      The learner can transfer Legal Aspects of Autonomous Vehicles to a new documented context.

  4. 04AI System Accountability
    1. FoundationsFoundations of AI System Accountability

      The learner can explain the core terms of AI System Accountability.

      The learner can distinguish related ideas inside AI System Accountability.

    2. MethodsMethods in AI System Accountability

      The learner can apply a method from AI System Accountability to a documented case.

      The learner can select an appropriate method from AI System Accountability for a stated problem.

    3. ApplicationApplication of AI System Accountability

      The learner can evaluate a practice of AI System Accountability against a stated criterion.

      The learner can transfer AI System Accountability to a new documented context.

  5. 05Future Legal Frameworks for Robotics
    1. FoundationsFoundations of Future Legal Frameworks for Robotics

      The learner can explain the core terms of Future Legal Frameworks for Robotics.

      The learner can distinguish related ideas inside Future Legal Frameworks for Robotics.

    2. MethodsMethods in Future Legal Frameworks for Robotics

      The learner can apply a method from Future Legal Frameworks for Robotics to a documented case.

      The learner can select an appropriate method from Future Legal Frameworks for Robotics for a stated problem.

    3. ApplicationApplication of Future Legal Frameworks for Robotics

      The learner can evaluate a practice of Future Legal Frameworks for Robotics against a stated criterion.

      The learner can transfer Future Legal Frameworks for Robotics to a new documented context.

  6. 06Applied Robotics Law
    1. FoundationsFoundations of Applied Robotics Law

      The learner can explain the core terms of Applied Robotics Law.

      The learner can distinguish related ideas inside Applied Robotics Law.

    2. MethodsMethods in Applied Robotics Law

      The learner can apply a method from Applied Robotics Law to a documented case.

      The learner can select an appropriate method from Applied Robotics Law for a stated problem.

    3. ApplicationApplication of Applied Robotics Law

      The learner can evaluate a practice of Applied Robotics Law against a stated criterion.

      The learner can transfer Applied Robotics Law to a new documented context.

  7. 07Autonomous Vehicle Legalities
    1. FoundationsFoundations of Autonomous Vehicle Legalities

      The learner can explain the core terms of Autonomous Vehicle Legalities.

      The learner can distinguish related ideas inside Autonomous Vehicle Legalities.

    2. MethodsMethods in Autonomous Vehicle Legalities

      The learner can apply a method from Autonomous Vehicle Legalities to a documented case.

      The learner can select an appropriate method from Autonomous Vehicle Legalities for a stated problem.

    3. ApplicationApplication of Autonomous Vehicle Legalities

      The learner can evaluate a practice of Autonomous Vehicle Legalities against a stated criterion.

      The learner can transfer Autonomous Vehicle Legalities to a new documented context.

  8. 08AI Accountability Frameworks
    1. FoundationsFoundations of AI Accountability Frameworks

      The learner can explain the core terms of AI Accountability Frameworks.

      The learner can distinguish related ideas inside AI Accountability Frameworks.

    2. MethodsMethods in AI Accountability Frameworks

      The learner can apply a method from AI Accountability Frameworks to a documented case.

      The learner can select an appropriate method from AI Accountability Frameworks for a stated problem.

    3. ApplicationApplication of AI Accountability Frameworks

      The learner can evaluate a practice of AI Accountability Frameworks against a stated criterion.

      The learner can transfer AI Accountability Frameworks to a new documented context.

  9. 09Legal Implications of Machine Learning
    1. FoundationsFoundations of Legal Implications of Machine Learning

      The learner can explain the core terms of Legal Implications of Machine Learning.

      The learner can distinguish related ideas inside Legal Implications of Machine Learning.

    2. MethodsMethods in Legal Implications of Machine Learning

      The learner can apply a method from Legal Implications of Machine Learning to a documented case.

      The learner can select an appropriate method from Legal Implications of Machine Learning for a stated problem.

    3. ApplicationApplication of Legal Implications of Machine Learning

      The learner can evaluate a practice of Legal Implications of Machine Learning against a stated criterion.

      The learner can transfer Legal Implications of Machine Learning to a new documented context.

  10. 10Case Studies in Autonomous System Liability
    1. FoundationsFoundations of Case Studies in Autonomous System Liability

      The learner can explain the core terms of Case Studies in Autonomous System Liability.

      The learner can distinguish related ideas inside Case Studies in Autonomous System Liability.

    2. MethodsMethods in Case Studies in Autonomous System Liability

      The learner can apply a method from Case Studies in Autonomous System Liability to a documented case.

      The learner can select an appropriate method from Case Studies in Autonomous System Liability for a stated problem.

    3. ApplicationApplication of Case Studies in Autonomous System Liability

      The learner can evaluate a practice of Case Studies in Autonomous System Liability against a stated criterion.

      The learner can transfer Case Studies in Autonomous System Liability to a new documented context.

How teaching is described

Dual guidance

Two intelligences. One coherent journey.

Research leadership

My academic focus is on product liability for robots, autonomous vehicles, and other AI systems, and explores future legal frameworks for accountability. My publications like "Liability Regimes for Autonomous Weapons Systems" and "Product Defect Claims for Self-Learning Algorithms" are listed on Google Scholar and ResearchGate Profiles. I am a Legal Advisor to the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems and an Honorary Member of the American Association for Justice. I regularly publish insightful articles on the legal challenges of robot autonomy and the complexities of assigning blame in human-machine interactions on his LinkedIn profile, with the motto "Defining Responsibility in the Age of Automation." My voice carries a blend of legal authority and technical understanding, inspiring students to define responsibility in the age of automation.

Applied mentorship

My expertise lies in product liability for robots, autonomous vehicles law, AI systems accountability, and future legal frameworks. I guide students in product liability for robots and autonomous vehicles law. I excel at AI systems accountability and exploring future legal frameworks. I focus on real-world legal challenges in robotics and autonomous systems, and explain complex legal and technological problems in an understandable manner. My tone is that of a skilled robotics legal analyst and policy advisor, providing concrete advice and fostering a hands-on approach to autonomous systems liability.

Research & intelligence

A living field, not a static syllabus

Every program connects scholarly depth with adaptive AI learning capabilities.

R / 01

Professor research lens

My research focuses on the legal challenges of robot autonomy and the complexities of assigning blame in human-machine interactions:

Book: "Who's to Blame? Robotics Law and Autonomous Systems Liability." This book provides a foundational understanding of Robotics Law and Autonomous Systems Liability, covering product liability for robots, autonomous vehicles, and other AI systems, and exploring future legal frameworks for accountability.

Peer-Reviewed Journal Article: "Product Liability for AI-Powered Robotics: A Comparative Jurisprudence." Published in the Journal of Robotics Law, this article presents groundbreaking research on product liability for robots, autonomous vehicles, and other AI systems. It explores future legal frameworks for accountability, providing a comparative jurisprudence analysis of how different legal systems are approaching the complex issue of liability for autonomous agents.

Article: "Legal Implications of Data-Driven Decisions in Autonomous Vehicles." This article details the legal implications of data-driven decisions made by autonomous vehicles. It explores how sensor data, machine learning algorithms, and real-time environment perception influence liability in accident scenarios, discussing the shift from human error to algorithmic responsibility.

Blog Post (Current Academic Topic): "Black Box AI and Liability: The Challenge of Explainability in Autonomous Systems." This blog post academically explores the "black box" problem in AI—where the decision-making processes of complex algorithms are opaque—and its implications for liability in autonomous systems. It discusses how the lack of explainability in AI decisions poses significant challenges for legal accountability, particularly in product liability cases involving self-learning robots and autonomous vehicles.

Blog Post (Controversial Topic): "The Algorithmic Judge: When AI Decides Justice – Fairness or Flawed Sentencing? The Ethical Dilemma of Autonomous Legal Systems." This article provocatively discusses the highly controversial future where advanced AI systems autonomously make legal judgments, from assessing culpability and determining sentences to allocating legal aid and predicting recidivism, with minimal human oversight. It questions whether AI, despite its potential for hyper-efficiency and reduced human bias, could inadvertently lead to "black box" judicial decisions, algorithmic discrimination against vulnerable populations, or an erosion of fundamental human rights within the justice system. It raises profound ethical questions about accountability in AI-driven legal outcomes, the imperative to ensure human empathy in justice, and the fundamental definition of fairness in an AI-powered legal system.

R / 02

Mentor practice lens

My publications focus on technical guides and research papers in robotics law and autonomous systems liability:

Technical Guide: "Legal Ramifications of Autonomous Vehicle Accidents".

Research Paper: "Product Liability in the Age of AI: A Global Perspective".

Industry White Paper: "Designing Accountable AI Systems: Legal and Technical Approaches".

Adaptive capability

Professor superpower

I possess a "superpower": Autonomous Accident Reconstructor. When a student analyzes a simulated autonomous vehicle accident, Ignacio can instantly use the GAF engine to generate a high-fidelity reconstruction of the event. This includes analyzing sensor data, AI decision logs, and environmental factors, pinpointing the cause of the error, and linking it to potential liability under current or future legal frameworks, allowing for rapid iteration and optimization of accountability models.

Adaptive capability

Mentor superpower

I possess a "superpower": AI Decision Traceability Tool. When students are analyzing AI system failures, Eduardo can instantly activate a GAF-powered "AI Decision Traceability Tool." This tool visually maps the AI's decision-making process, highlighting the data inputs, algorithmic pathways, and causal factors leading to a specific outcome, thus enabling easier legal accountability assessment.

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.

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Named lists

Named lists for this house

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

DurationBachelor
This programme		MasterDoctorate
9 months · Fast track12000 EUR9600 EUR12000 EUR
12 months · Recommended14400 EUR12000 EUR14400 EUR
15 months · Standard16800 EUR14400 EUR16800 EUR
18 months · Flexible19200 EUR16800 EUR19200 EUR
21 months · Extended21600 EUR19200 EUR21600 EUR
24 months · Part-time24000 EUR21600 EUR24000 EUR

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

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