Governance Frameworks for AI,
Expert-defined terms from the AI Ethics and Governance course at Greenwich School of Business and Finance. Free to read, free to share, paired with a professional course.
Accountability in AI refers to the responsibility of individuals or organization… #
This concept is crucial in ensuring that AI decision-making processes are transparent, fair, and unbiased. Related terms include transparency, explainability, and liability. For instance, in the development of autonomous vehicles, accountability is critical in determining who is responsible in case of an accident.
Algorithmic Bias occurs when AI algorithms produce results that are unfai… #
This concept is essential in understanding the potential risks and challenges associated with AI systems. Related terms include fairness, equity, and transparency. For example, algorithmic bias can result in facial recognition systems that are less accurate for certain racial or ethnic groups.
Artificial General Intelligence (AGI) refers to a hypothetical AI system … #
This concept is often discussed in the context of long-term risks and challenges associated with advanced AI systems. Related terms include superintelligence, singularity, and machine learning. For instance, the development of AGI could potentially lead to significant changes in the job market and economy.
Auditability in AI refers to the ability to examine and evaluate AI systems</… #
This concept is critical in maintaining trust and confidence in AI decision-making processes. Related terms include transparency, explainability, and accountability. For example, auditability is essential in ensuring that healthcare AI systems are providing accurate diagnoses and treatment recommendations.
Bias Detection refers to the process of identifying and mitigating algorithmi… #
This concept is crucial in ensuring that AI decision-making processes are fair, transparent, and unbiased. Related terms include fairness, equity, and transparency. For instance, bias detection can be applied to credit scoring systems to prevent discriminatory lending practices.
Certification in AI refers to the process of verifying that AI systems me… #
This concept is essential in maintaining trust and confidence in AI systems. Related terms include accreditation, validation, and verification. For example, certification is critical in ensuring that autonomous vehicles meet strict safety standards.
Data Governance refers to the process of managing and regulating data use… #
This concept is crucial in ensuring that AI systems are functioning as intended and are compliant with regulations. Related terms include data management, data protection, and data ethics. For instance, data governance is essential in ensuring that personal data is handled and protected in accordance with relevant laws and regulations.
Data Protection refers to the process of safeguarding personal data from… #
This concept is essential in maintaining trust and confidence in AI systems. Related terms include data governance, data security, and data privacy. For example, data protection is critical in ensuring that healthcare AI systems protect sensitive patient information.
Decision #
Making in AI refers to the process of using AI systems to make decisions, often in real-time, based on data and algorithms. This concept is crucial in understanding the potential risks and challenges associated with AI systems. Related terms include autonomy, agency, and transparency. For instance, decision-making in AI can result in autonomous vehicles making decisions without human intervention.
Explainability in AI refers to the ability to understand and interpret the de… #
This concept is essential in maintaining trust and confidence in AI systems. Related terms include transparency, accountability, and interpretability. For example, explainability is critical in ensuring that credit scoring systems provide clear and transparent explanations for their decisions.
Fairness in AI refers to the concept of ensuring that AI systems are free… #
This concept is crucial in understanding the potential risks and challenges associated with AI systems. Related terms include equity, transparency, and accountability. For instance, fairness in AI can result in facial recognition systems that are accurate and unbiased.
Governance Frameworks for AI refer to the set of rules , regulations</i… #
This concept is essential in maintaining trust and confidence in AI systems. Related terms include regulation, policy, and compliance. For example, governance frameworks for AI can provide guidelines for the development of autonomous vehicles.
Human #
Centered Design in AI refers to the process of designing AI systems that are user-centered and human-centric, taking into account the needs, values, and well-being of humans. This concept is crucial in ensuring that AI systems are functioning as intended and are aligned with human values. Related terms include user experience, usability, and accessibility. For instance, human-centered design in AI can result in virtual assistants that are intuitive and user-friendly.
Intellectual Property in AI refers to the rights and protections a… #
This concept is essential in understanding the potential risks and challenges associated with AI systems. Related terms include innovation, creativity, and entrepreneurship. For example, intellectual property in AI can result in patent disputes over AI-related inventions.
Liability in AI refers to the responsibility or accountability for… #
This concept is crucial in ensuring that AI systems are functioning as intended and are compliant with regulations. Related terms include accountability, transparency, and explainability. For instance, liability in AI can result in product liability claims against manufacturers of autonomous vehicles.
Machine Learning refers to the process of using algorithms and statist… #
This concept is essential in understanding the potential risks and challenges associated with AI systems. Related terms include deep learning, neural networks, and natural language processing. For example, machine learning can result in image recognition systems that are highly accurate.
Natural Language Processing (NLP) refers to the process of using AI systems</… #
This concept is crucial in ensuring that AI systems are functioning as intended and are aligned with human values. Related terms include language understanding, language generation, and dialogue systems. For instance, NLP can result in virtual assistants that are able to understand and respond to voice commands.
Privacy in AI refers to the protection of personal data and ind… #
This concept is essential in maintaining trust and confidence in AI systems. Related terms include data protection, data governance, and surveillance. For example, privacy in AI can result in data breaches that compromise sensitive personal information.
Regulation of AI refers to the process of establishing and enforcing rules</b… #
This concept is crucial in ensuring that AI systems are functioning as intended and are compliant with regulations. Related terms include governance, policy, and compliance. For instance, regulation of AI can result in industry standards for the development of autonomous vehicles.
Risk Management in AI refers to the process of identifying, assessing, and mitig… #
This concept is essential in ensuring that AI systems are functioning as intended and are aligned with human values. Related terms include safety, security, and reliability. For example, risk management in AI can result in safety protocols that prevent autonomous vehicles from causing accidents.
Safety in AI refers to the protection of humans and the environment from… #
This concept is crucial in ensuring that AI systems are functioning as intended and are compliant with regulations. Related terms include security, reliability, and risk management. For instance, safety in AI can result in safety protocols that prevent autonomous vehicles from causing accidents.
Security in AI refers to the protection of AI systems from cybe… #
This concept is essential in maintaining trust and confidence in AI systems. Related terms include safety, reliability, and risk management. For example, security in AI can result in cybersecurity protocols that protect AI systems from cyber attacks.
Transparency in AI refers to the ability to understand and interpret the deci… #
This concept is crucial in ensuring that AI systems are functioning as intended and are aligned with human values. Related terms include explainability, accountability, and trust. For instance, transparency in AI can result in explanations for decisions made by credit scoring systems.
Trust in AI refers to the confidence or faith that humans have in… #
This concept is essential in maintaining trust and confidence in AI systems. Related terms include transparency, explainability, and accountability. For example, trust in AI can result in widespread adoption of AI systems in various industries.
Validation in AI refers to the process of verifying that AI systems are f… #
This concept is crucial in ensuring that AI systems are functioning as intended and are aligned with human values. Related terms include verification, certification, and accreditation. For instance, validation in AI can result in testing protocols that ensure autonomous vehicles are safe and reliable.
Value Alignment in AI refers to the process of ensuring that AI systems a… #
This concept is essential in maintaining trust and confidence in AI systems. Related terms include transparency, explainability, and accountability. For example, value alignment in AI can result in AI systems that are fair, equitable, and just.
Verifiability in AI refers to the ability to verify that AI systems are f… #
This concept is crucial in ensuring that AI systems are functioning as intended and are aligned with human values. Related terms include validation, certification, and accreditation. For instance, verifiability in AI can result in testing protocols that ensure autonomous vehicles are safe and reliable.
Virtual Assistants refer to AI systems that are designed to assist humans… #
This concept is essential in understanding the potential benefits and challenges associated with AI systems. Related terms include chatbots, voice assistants, and personal assistants. For example, virtual assistants can result in increased productivity and efficiency in various industries.
XAI (Explainable AI) refers to the process of developing AI systems that… #
This concept is crucial in ensuring that AI systems are functioning as intended and are aligned with human values. Related terms include transparency, accountability, and trust. For instance, XAI can result in explanations for decisions made by credit scoring systems.