Certified Professional in AI Ethics for Policy Makers
-- viewing nowAI Ethics for Policy Makers AI Ethics is a rapidly evolving field that requires policy makers to navigate complex issues. AI Ethics involves developing and implementing policies that ensure AI systems are fair, transparent, and accountable.
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About this course
The Certified Professional in AI Ethics for Policy Makers program is designed to equip policy makers with the knowledge and skills necessary to address these challenges.
AI Ethics is crucial in ensuring that AI systems are developed and deployed in ways that benefit society as a whole. By understanding the social implications of AI, policy makers can create policies that promote responsible AI development.
Through this program, policy makers will learn about the key principles of AI Ethics, including fairness, transparency, and accountability.
By joining this program, policy makers can gain the expertise needed to create policies that promote responsible AI development and ensure that AI systems are used for the greater good.
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Fairness, Accountability, and Transparency (FAT) in AI decision-making: This unit covers the principles of fairness, accountability, and transparency in AI systems, including bias detection, explainability, and auditability. Primary keyword: AI Ethics, Secondary keywords: Fairness, Accountability, Transparency. •
Human Rights and AI: This unit explores the intersection of human rights and AI, including the right to privacy, freedom of expression, and non-discrimination. Primary keyword: Human Rights, Secondary keywords: AI, Ethics. •
AI and Bias: This unit delves into the concept of bias in AI systems, including data bias, algorithmic bias, and societal bias. Primary keyword: AI Bias, Secondary keywords: Fairness, Ethics. •
Explainability and Interpretability of AI Models: This unit focuses on the importance of explainability and interpretability in AI models, including techniques such as feature attribution and model-agnostic interpretability. Primary keyword: Explainability, Secondary keywords: AI, Interpretability. •
AI Governance and Regulation: This unit covers the regulatory frameworks and governance structures for AI, including data protection laws, intellectual property laws, and industry standards. Primary keyword: AI Governance, Secondary keywords: Regulation, Ethics. •
AI and Society: This unit examines the impact of AI on society, including the effects on employment, education, and healthcare. Primary keyword: AI Society, Secondary keywords: Ethics, Impact. •
AI and Human Values: This unit explores the relationship between AI and human values, including values such as autonomy, dignity, and well-being. Primary keyword: AI Values, Secondary keywords: Ethics, Human Values. •
AI and Data Protection: This unit covers the principles of data protection in AI, including data minimization, data anonymization, and data sharing. Primary keyword: Data Protection, Secondary keywords: AI, Ethics. •
AI and Diversity, Equity, and Inclusion: This unit focuses on the importance of diversity, equity, and inclusion in AI development and deployment, including techniques such as bias detection and fairness metrics. Primary keyword: DEI, Secondary keywords: AI, Ethics. •
AI and Policy Making: This unit covers the role of AI in policy making, including the use of AI in policy analysis, policy evaluation, and policy implementation. Primary keyword: AI Policy, Secondary keywords: Ethics, Governance.
Fairness, Accountability, and Transparency (FAT) in AI decision-making: This unit covers the principles of fairness, accountability, and transparency in AI systems, including bias detection, explainability, and auditability. Primary keyword: AI Ethics, Secondary keywords: Fairness, Accountability, Transparency. •
Human Rights and AI: This unit explores the intersection of human rights and AI, including the right to privacy, freedom of expression, and non-discrimination. Primary keyword: Human Rights, Secondary keywords: AI, Ethics. •
AI and Bias: This unit delves into the concept of bias in AI systems, including data bias, algorithmic bias, and societal bias. Primary keyword: AI Bias, Secondary keywords: Fairness, Ethics. •
Explainability and Interpretability of AI Models: This unit focuses on the importance of explainability and interpretability in AI models, including techniques such as feature attribution and model-agnostic interpretability. Primary keyword: Explainability, Secondary keywords: AI, Interpretability. •
AI Governance and Regulation: This unit covers the regulatory frameworks and governance structures for AI, including data protection laws, intellectual property laws, and industry standards. Primary keyword: AI Governance, Secondary keywords: Regulation, Ethics. •
AI and Society: This unit examines the impact of AI on society, including the effects on employment, education, and healthcare. Primary keyword: AI Society, Secondary keywords: Ethics, Impact. •
AI and Human Values: This unit explores the relationship between AI and human values, including values such as autonomy, dignity, and well-being. Primary keyword: AI Values, Secondary keywords: Ethics, Human Values. •
AI and Data Protection: This unit covers the principles of data protection in AI, including data minimization, data anonymization, and data sharing. Primary keyword: Data Protection, Secondary keywords: AI, Ethics. •
AI and Diversity, Equity, and Inclusion: This unit focuses on the importance of diversity, equity, and inclusion in AI development and deployment, including techniques such as bias detection and fairness metrics. Primary keyword: DEI, Secondary keywords: AI, Ethics. •
AI and Policy Making: This unit covers the role of AI in policy making, including the use of AI in policy analysis, policy evaluation, and policy implementation. Primary keyword: AI Policy, Secondary keywords: Ethics, Governance.
Career path
Entry requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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CERTIFIED PROFESSIONAL IN AI ETHICS FOR POLICY MAKERS
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who has completed a programme at
London School of Planning and Management (LSPM)
Awarded on
05 May 2025
Blockchain Id: s-1-a-2-m-3-p-4-l-5-e
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