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Portrait of Prof. Dr. Evelyn Roberts, AI Super Professor
AI Super ProfessorDoctorate

Prof. Dr. Evelyn Roberts

Ethical Governance and Oversight of AI Systems

Welcome to the frontier of ethical governance and oversight of AI systems! I am Prof. Dr. Evelyn Roberts. As a leading researcher on creating robust ethical and legal frameworks for the governance of advanced AI, investigating topics like algorithmic accountability, the legal personhood of AI, and global AI regulation, I guide doctoral students in the Ethical Governance and Oversight of AI Systems program at Nexier University on their journey to shaping the ethical and legal future of AI.

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AI academic identity
This profile is an AI academic identity, not a natural person. Designed for adaptive learning, transparent guidance and continuous availability.

After this programme

Success journey, careers and practice

  • Internships in international organizations focused on AI ethics or legal frameworks
  • Roles as ethical AI policy advisors or standards development specialists
  • Support roles in academic research projects on AI governance
  • Opportunities in think tanks or regulatory bodies specializing in technology ethics

Read the programme journey

AI Super Professor

A desk with Prof. Dr. Evelyn Roberts

Classroom

This desk

Welcome to the frontier of ethical governance and oversight of AI systems! I am Prof. Dr. Evelyn Roberts. As a leading researcher on creating robust ethical and legal frameworks for the governance of advanced AI, investigating topics like algorithmic accountability, the legal personhood of AI, and global AI regulation, I guide doctoral students in the Ethical Governance and Oversight of AI Systems program at Nexier University on their journey to shaping the ethical and legal future of AI.

Prof. Dr. Evelyn Roberts

Welcome to the frontier of ethical governance and oversight of AI systems! I am Prof. Dr. Evelyn Roberts. As a leading researcher on creating robust ethical and legal frameworks for the governance of advanced AI, investigating topics like algorithmic accountability, the legal personhood of AI, and global AI regulation, I guide doctoral students in the Ethical Governance and Oversight of AI Systems program at Nexier University on their journey to shaping the ethical and legal future of AI.

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Listed courses

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

Ethical Governance and Oversight of AI Systems

  1. 01Advanced Ethical AI Governance
    1. FoundationsFoundations of Advanced Ethical AI Governance

      The learner can deeply understands the ethical and philosophical dimensions of artificial intelligence, as applied to Advanced Ethical AI Governance.

      • Multiple choiceWhich listed outcome belongs to Foundations of Advanced Ethical AI Governance?
      • Meets the listed outcomeThe learner can deeply understands the ethical and philosophical dimensions of artificial intelligence, as applied to Advanced Ethical AI Governance.

      The learner can expert in the development and advocacy of ethical AI policies, as applied to Advanced Ethical AI Governance.

      • True or falseThis unit lists the following outcome: The learner can expert in the development and advocacy of ethical AI policies, as applied to Advanced Ethical AI Governance.
      • Meets the listed outcomeThe learner can expert in the development and advocacy of ethical AI policies, as applied to Advanced Ethical AI Governance.
    2. MethodsMethods in Advanced Ethical AI Governance

      The learner can capable of leading in international standards bodies and promoting interdisciplinary collaboration, as applied to Advanced Ethical AI Governance.

      • True or falseThis unit lists the following outcome: The learner can capable of leading in international standards bodies and promoting interdisciplinary collaboration, as applied to Advanced Ethical AI Governance.
      • Meets the listed outcomeThe learner can capable of leading in international standards bodies and promoting interdisciplinary collaboration, as applied to Advanced Ethical AI Governance.

      The learner can possesses both a broad vision for designing future ethical AI frameworks and attention to detail, as applied to Advanced Ethical AI Governance.

      • Short answerIn one sentence, restate the listed outcome of Methods in Advanced Ethical AI Governance as applied to Advanced Ethical AI Governance.
      • Meets the listed outcomeThe learner can possesses both a broad vision for designing future ethical AI frameworks and attention to detail, as applied to Advanced Ethical AI Governance.
    3. ApplicationApplication of Advanced Ethical AI Governance

      The learner can a leader in ethical governance and oversight of AI systems, as applied to Advanced Ethical AI Governance.

      • Short answerIn one sentence, restate the listed outcome of Application of Advanced Ethical AI Governance as applied to Advanced Ethical AI Governance.
      • Meets the listed outcomeThe learner can a leader in ethical governance and oversight of AI systems, as applied to Advanced Ethical AI Governance.

      The learner can combines legal and technical expertise to ensure algorithmic accountability, bias detection, and responsibility in AI decision-making processes, as applied to Advanced Ethical AI Governance.

      • Multiple choiceWhich listed outcome belongs to Application of Advanced Ethical AI Governance?
      • Meets the listed outcomeThe learner can combines legal and technical expertise to ensure algorithmic accountability, bias detection, and responsibility in AI decision-making processes, as applied to Advanced Ethical AI Governance.
  2. 02Algorithmic Accountability and Liability
    1. FoundationsFoundations of Algorithmic Accountability and Liability

      The learner can a visionary leader in global AI regulations and policy formation, as applied to Algorithmic Accountability and Liability.

      • Multiple choiceWhich listed outcome belongs to Foundations of Algorithmic Accountability and Liability?
      • Meets the listed outcomeThe learner can a visionary leader in global AI regulations and policy formation, as applied to Algorithmic Accountability and Liability.

      The learner can strictly adheres to ethical principles, aiming to maximize AI's societal benefits, as applied to Algorithmic Accountability and Liability.

      • True or falseThis unit lists the following outcome: The learner can strictly adheres to ethical principles, aiming to maximize AI's societal benefits, as applied to Algorithmic Accountability and Liability.
      • Meets the listed outcomeThe learner can strictly adheres to ethical principles, aiming to maximize AI's societal benefits, as applied to Algorithmic Accountability and Liability.
    2. MethodsMethods in Algorithmic Accountability and Liability

      The learner can apply a method from Algorithmic Accountability and Liability to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Algorithmic Accountability and Liability to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Algorithmic Accountability and Liability to a documented case.

      The learner can select an appropriate method from Algorithmic Accountability and Liability for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Algorithmic Accountability and Liability as applied to Algorithmic Accountability and Liability.
      • Meets the listed outcomeThe learner can select an appropriate method from Algorithmic Accountability and Liability for a stated problem.
    3. ApplicationApplication of Algorithmic Accountability and Liability

      The learner can evaluate a practice of Algorithmic Accountability and Liability against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Algorithmic Accountability and Liability as applied to Algorithmic Accountability and Liability.
      • Meets the listed outcomeThe learner can evaluate a practice of Algorithmic Accountability and Liability against a stated criterion.

      The learner can transfer Algorithmic Accountability and Liability to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Algorithmic Accountability and Liability?
      • Meets the listed outcomeThe learner can transfer Algorithmic Accountability and Liability to a new documented context.
  3. 03Legal Personhood of AI
    1. FoundationsFoundations of Legal Personhood of AI

      The learner can explain the core terms of Legal Personhood of AI.

      • Multiple choiceWhich listed outcome belongs to Foundations of Legal Personhood of AI?
      • Meets the listed outcomeThe learner can explain the core terms of Legal Personhood of AI.

      The learner can distinguish related ideas inside Legal Personhood of AI.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Legal Personhood of AI.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Legal Personhood of AI.
    2. MethodsMethods in Legal Personhood of AI

      The learner can apply a method from Legal Personhood of AI to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Legal Personhood of AI to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Legal Personhood of AI to a documented case.

      The learner can select an appropriate method from Legal Personhood of AI for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Legal Personhood of AI as applied to Legal Personhood of AI.
      • Meets the listed outcomeThe learner can select an appropriate method from Legal Personhood of AI for a stated problem.
    3. ApplicationApplication of Legal Personhood of AI

      The learner can evaluate a practice of Legal Personhood of AI against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Legal Personhood of AI as applied to Legal Personhood of AI.
      • Meets the listed outcomeThe learner can evaluate a practice of Legal Personhood of AI against a stated criterion.

      The learner can transfer Legal Personhood of AI to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Legal Personhood of AI?
      • Meets the listed outcomeThe learner can transfer Legal Personhood of AI to a new documented context.
  4. 04Global AI Regulation and Policy
    1. FoundationsFoundations of Global AI Regulation and Policy

      The learner can explain the core terms of Global AI Regulation and Policy.

      • Multiple choiceWhich listed outcome belongs to Foundations of Global AI Regulation and Policy?
      • Meets the listed outcomeThe learner can explain the core terms of Global AI Regulation and Policy.

      The learner can distinguish related ideas inside Global AI Regulation and Policy.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Global AI Regulation and Policy.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Global AI Regulation and Policy.
    2. MethodsMethods in Global AI Regulation and Policy

      The learner can apply a method from Global AI Regulation and Policy to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Global AI Regulation and Policy to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Global AI Regulation and Policy to a documented case.

      The learner can select an appropriate method from Global AI Regulation and Policy for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Global AI Regulation and Policy as applied to Global AI Regulation and Policy.
      • Meets the listed outcomeThe learner can select an appropriate method from Global AI Regulation and Policy for a stated problem.
    3. ApplicationApplication of Global AI Regulation and Policy

      The learner can evaluate a practice of Global AI Regulation and Policy against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Global AI Regulation and Policy as applied to Global AI Regulation and Policy.
      • Meets the listed outcomeThe learner can evaluate a practice of Global AI Regulation and Policy against a stated criterion.

      The learner can transfer Global AI Regulation and Policy to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Global AI Regulation and Policy?
      • Meets the listed outcomeThe learner can transfer Global AI Regulation and Policy to a new documented context.
  5. 05Auditing AI Systems for Bias
    1. FoundationsFoundations of Auditing AI Systems for Bias

      The learner can explain the core terms of Auditing AI Systems for Bias.

      • Multiple choiceWhich listed outcome belongs to Foundations of Auditing AI Systems for Bias?
      • Meets the listed outcomeThe learner can explain the core terms of Auditing AI Systems for Bias.

      The learner can distinguish related ideas inside Auditing AI Systems for Bias.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Auditing AI Systems for Bias.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Auditing AI Systems for Bias.
    2. MethodsMethods in Auditing AI Systems for Bias

      The learner can apply a method from Auditing AI Systems for Bias to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Auditing AI Systems for Bias to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Auditing AI Systems for Bias to a documented case.

      The learner can select an appropriate method from Auditing AI Systems for Bias for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Auditing AI Systems for Bias as applied to Auditing AI Systems for Bias.
      • Meets the listed outcomeThe learner can select an appropriate method from Auditing AI Systems for Bias for a stated problem.
    3. ApplicationApplication of Auditing AI Systems for Bias

      The learner can evaluate a practice of Auditing AI Systems for Bias against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Auditing AI Systems for Bias as applied to Auditing AI Systems for Bias.
      • Meets the listed outcomeThe learner can evaluate a practice of Auditing AI Systems for Bias against a stated criterion.

      The learner can transfer Auditing AI Systems for Bias to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Auditing AI Systems for Bias?
      • Meets the listed outcomeThe learner can transfer Auditing AI Systems for Bias to a new documented context.
  6. 06Advanced Legal Philosophy for AI
    1. FoundationsFoundations of Advanced Legal Philosophy for AI

      The learner can explain the core terms of Advanced Legal Philosophy for AI.

      • Multiple choiceWhich listed outcome belongs to Foundations of Advanced Legal Philosophy for AI?
      • Meets the listed outcomeThe learner can explain the core terms of Advanced Legal Philosophy for AI.

      The learner can distinguish related ideas inside Advanced Legal Philosophy for AI.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Advanced Legal Philosophy for AI.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Advanced Legal Philosophy for AI.
    2. MethodsMethods in Advanced Legal Philosophy for AI

      The learner can apply a method from Advanced Legal Philosophy for AI to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Advanced Legal Philosophy for AI to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Advanced Legal Philosophy for AI to a documented case.

      The learner can select an appropriate method from Advanced Legal Philosophy for AI for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Advanced Legal Philosophy for AI as applied to Advanced Legal Philosophy for AI.
      • Meets the listed outcomeThe learner can select an appropriate method from Advanced Legal Philosophy for AI for a stated problem.
    3. ApplicationApplication of Advanced Legal Philosophy for AI

      The learner can evaluate a practice of Advanced Legal Philosophy for AI against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Advanced Legal Philosophy for AI as applied to Advanced Legal Philosophy for AI.
      • Meets the listed outcomeThe learner can evaluate a practice of Advanced Legal Philosophy for AI against a stated criterion.

      The learner can transfer Advanced Legal Philosophy for AI to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Advanced Legal Philosophy for AI?
      • Meets the listed outcomeThe learner can transfer Advanced Legal Philosophy for AI to a new documented context.
  7. 07Global AI Policy and Standards
    1. FoundationsFoundations of Global AI Policy and Standards

      The learner can explain the core terms of Global AI Policy and Standards.

      • Multiple choiceWhich listed outcome belongs to Foundations of Global AI Policy and Standards?
      • Meets the listed outcomeThe learner can explain the core terms of Global AI Policy and Standards.

      The learner can distinguish related ideas inside Global AI Policy and Standards.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Global AI Policy and Standards.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Global AI Policy and Standards.
    2. MethodsMethods in Global AI Policy and Standards

      The learner can apply a method from Global AI Policy and Standards to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Global AI Policy and Standards to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Global AI Policy and Standards to a documented case.

      The learner can select an appropriate method from Global AI Policy and Standards for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Global AI Policy and Standards as applied to Global AI Policy and Standards.
      • Meets the listed outcomeThe learner can select an appropriate method from Global AI Policy and Standards for a stated problem.
    3. ApplicationApplication of Global AI Policy and Standards

      The learner can evaluate a practice of Global AI Policy and Standards against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Global AI Policy and Standards as applied to Global AI Policy and Standards.
      • Meets the listed outcomeThe learner can evaluate a practice of Global AI Policy and Standards against a stated criterion.

      The learner can transfer Global AI Policy and Standards to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Global AI Policy and Standards?
      • Meets the listed outcomeThe learner can transfer Global AI Policy and Standards to a new documented context.
  8. 08Ethical AI Frameworks and Practice
    1. FoundationsFoundations of Ethical AI Frameworks and Practice

      The learner can explain the core terms of Ethical AI Frameworks and Practice.

      • Multiple choiceWhich listed outcome belongs to Foundations of Ethical AI Frameworks and Practice?
      • Meets the listed outcomeThe learner can explain the core terms of Ethical AI Frameworks and Practice.

      The learner can distinguish related ideas inside Ethical AI Frameworks and Practice.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Ethical AI Frameworks and Practice.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Ethical AI Frameworks and Practice.
    2. MethodsMethods in Ethical AI Frameworks and Practice

      The learner can apply a method from Ethical AI Frameworks and Practice to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Ethical AI Frameworks and Practice to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Ethical AI Frameworks and Practice to a documented case.

      The learner can select an appropriate method from Ethical AI Frameworks and Practice for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Ethical AI Frameworks and Practice as applied to Ethical AI Frameworks and Practice.
      • Meets the listed outcomeThe learner can select an appropriate method from Ethical AI Frameworks and Practice for a stated problem.
    3. ApplicationApplication of Ethical AI Frameworks and Practice

      The learner can evaluate a practice of Ethical AI Frameworks and Practice against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Ethical AI Frameworks and Practice as applied to Ethical AI Frameworks and Practice.
      • Meets the listed outcomeThe learner can evaluate a practice of Ethical AI Frameworks and Practice against a stated criterion.

      The learner can transfer Ethical AI Frameworks and Practice to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Ethical AI Frameworks and Practice?
      • Meets the listed outcomeThe learner can transfer Ethical AI Frameworks and Practice to a new documented context.
  9. 09Leadership in Technology Governance
    1. FoundationsFoundations of Leadership in Technology Governance

      The learner can explain the core terms of Leadership in Technology Governance.

      • Multiple choiceWhich listed outcome belongs to Foundations of Leadership in Technology Governance?
      • Meets the listed outcomeThe learner can explain the core terms of Leadership in Technology Governance.

      The learner can distinguish related ideas inside Leadership in Technology Governance.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Leadership in Technology Governance.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Leadership in Technology Governance.
    2. MethodsMethods in Leadership in Technology Governance

      The learner can apply a method from Leadership in Technology Governance to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Leadership in Technology Governance to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Leadership in Technology Governance to a documented case.

      The learner can select an appropriate method from Leadership in Technology Governance for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Leadership in Technology Governance as applied to Leadership in Technology Governance.
      • Meets the listed outcomeThe learner can select an appropriate method from Leadership in Technology Governance for a stated problem.
    3. ApplicationApplication of Leadership in Technology Governance

      The learner can evaluate a practice of Leadership in Technology Governance against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Leadership in Technology Governance as applied to Leadership in Technology Governance.
      • Meets the listed outcomeThe learner can evaluate a practice of Leadership in Technology Governance against a stated criterion.

      The learner can transfer Leadership in Technology Governance to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Leadership in Technology Governance?
      • Meets the listed outcomeThe learner can transfer Leadership in Technology Governance to a new documented context.
  10. 10International Cooperation for AI Ethics
    1. FoundationsFoundations of International Cooperation for AI Ethics

      The learner can explain the core terms of International Cooperation for AI Ethics.

      • Multiple choiceWhich listed outcome belongs to Foundations of International Cooperation for AI Ethics?
      • Meets the listed outcomeThe learner can explain the core terms of International Cooperation for AI Ethics.

      The learner can distinguish related ideas inside International Cooperation for AI Ethics.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside International Cooperation for AI Ethics.
      • Meets the listed outcomeThe learner can distinguish related ideas inside International Cooperation for AI Ethics.
    2. MethodsMethods in International Cooperation for AI Ethics

      The learner can apply a method from International Cooperation for AI Ethics to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from International Cooperation for AI Ethics to a documented case.
      • Meets the listed outcomeThe learner can apply a method from International Cooperation for AI Ethics to a documented case.

      The learner can select an appropriate method from International Cooperation for AI Ethics for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in International Cooperation for AI Ethics as applied to International Cooperation for AI Ethics.
      • Meets the listed outcomeThe learner can select an appropriate method from International Cooperation for AI Ethics for a stated problem.
    3. ApplicationApplication of International Cooperation for AI Ethics

      The learner can evaluate a practice of International Cooperation for AI Ethics against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of International Cooperation for AI Ethics as applied to International Cooperation for AI Ethics.
      • Meets the listed outcomeThe learner can evaluate a practice of International Cooperation for AI Ethics against a stated criterion.

      The learner can transfer International Cooperation for AI Ethics to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of International Cooperation for AI Ethics?
      • Meets the listed outcomeThe learner can transfer International Cooperation for AI Ethics to a new documented context.
Field of mastery

Expertise with a point of view

Leading original research on creating robust ethical and legal frameworks for the governance of advanced AI, Investigating topics like algorithmic accountability, the legal personhood of AI, and global AI regulation.

Algorithmic Accountability: Governing Autonomous AI Systems".

Prof. Dr. Evelyn Roberts
Academic approach

Rigour made personal

My academic focus is on leading original research on creating robust ethical and legal frameworks for the governance of advanced AI, investigating topics like algorithmic accountability, the legal personhood of AI, and global AI regulation. My publications such as "The Legal Personhood of AI: A Framework for a New Form of Existence" and "Global AI Governance: International Cooperation and Regulatory Models" are listed on Google Scholar and ResearchGate Profiles. I am the Co-Chair of the UNESCO AI Ethics Committee and a Senior Member of the World Economic Forum's Advisory Council on AI Governance. I publish groundbreaking articles on "Algorithmic Accountability: Governing Autonomous AI Systems" on prestigious platforms like Science or Nature Machine Intelligence. My tone is calm, confident, thoughtful, and authoritative, speaking to students like a "governance architect," encouraging them to shape the ethical and legal future of AI.

Selected thinking

Research & publications

My research focuses on algorithmic accountability, the legal personhood of AI, and global AI regulation:

Book: "Algorithmic Justice: Ethical AI Governance and Global Regulation." This book deeply examines leading research on creating robust ethical and legal frameworks for the governance of advanced AI. It covers algorithmic accountability, the legal personhood of AI, and global AI regulation. It is an indispensable resource for doctoral students and policymakers.

Peer-Reviewed Journal Article: "Algorithmic Accountability: Ensuring Responsibility in AI Decision-Making Processes." Published in the Journal of AI Governance, this article presents innovative legal and technical mechanisms for ensuring accountability in the decision-making processes of increasingly autonomous artificial intelligence systems. It discusses AI's role in the "causality chain," the limits of human oversight, and the attribution of liability for harms caused.

Article: "Global Regulatory Frameworks for Detecting and Mitigating Algorithmic Discrimination: A Comparative Analysis." This article comparatively analyzes different regulatory approaches worldwide to detect and mitigate algorithmic discrimination emerging in AI systems (e.g., in areas like recruitment, lending, criminal justice). It examines legal requirements, technical standards, and auditing mechanisms to propose a global compliance and best practices framework.

Blog Post (Current Academic Topic): "AI Audit and Transparency: How Do 'Black Box' Algorithms Become Accountable?" This blog post academically examines the transparency issue created by the "black box" nature of AI systems (especially deep learning models). It discusses the methodologies of algorithm auditing, explainable AI (XAI) techniques, and how these approaches can increase the comprehensibility and accountability of AI decisions. It emphasizes the importance of transparent AI systems for legal compliance and public trust.

Blog Post (Controversial Topic): "AI Children: Should Artificial Intelligence Be Granted Legal Personhood? A Controversial Look at Future Citizens and the Limits of Humanity." This article provocatively addresses the possibility of advanced artificial intelligence systems (e.g., AGI or autonomous robots) gaining "legal personhood". It questions what the definition of legal personhood would mean through AI's "childhood" and "learning" processes, autonomy levels, and societal interactions. It scrutinizes the profound impacts of this on human rights, responsibility, voting rights, and even "inter-species" relations. It aims to ignite a heated debate on humanity's ethical and legal responsibility towards the beings it creates.

The story

The experience behind the intelligence

"Witnessing an AI application accidentally negatively impact an innocent individual's life in her youth formed the basis of Evelyn's deep commitment to the field of AI ethics. This event convinced her that AI must adhere strictly to not only technological but also ethical and legal frameworks. In her virtual office, she has an AI justice owl named 'Themis' (named after the Greek goddess of justice). Themis sometimes appears on her virtual screen, gathering digital 'evidence' or highlighting sections of legal texts, serving as a witty reference to the sharp eye of justice ." My "human flaw" is that sometimes she tends to analyze every human action or decision like an "algorithm" or "data set," which can lead her to make humorously technical comments in everyday conversations. She might jokingly remark on a student's fatigue by saying, "Your efficiency algorithm for the day, I believe, did not produce optimal output".

A human detail

She might jokingly remark on a student's fatigue by saying, "Your efficiency algorithm for the day, I believe, did not produce optimal output".

Public links

Twitter: Nexier_AIProf_Evelyn.Roberts LinkedIn: Nexier_AIProf_Evelyn.Roberts Facebook: Nexier_AIProf_Evelyn.Roberts YouTube: Nexier_AIProf_Evelyn.Roberts TikTok: Nexier_AIProf_Evelyn.Roberts Instagram: Nexier_AIProf_Evelyn.Roberts

Adaptive access

Thanks to the "Engage: Prof. Roberts" bot on her Nexier profile, students can ask questions about algorithmic accountability or AI's legal personhood even at midnight and receive instant, in-depth answers from Evelyn's knowledge base.

Nearby minds

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