Foundations of AI Governance
Expert-defined terms from the Professional Certificate in AI Governance for Supply Chain Management course at LearnUNI. Free to read, free to share, paired with a professional course.
Accountability in AI refers to the responsibility of individuals or organ… #
Related terms include transparency, explainability, and fairness. In the context of AI governance for supply chain management, accountability is crucial to ensure that AI systems are aligned with organizational values and objectives, and that their decisions and actions are auditable and justifiable.
Actionable Insights refer to the practical and relevant informatio… #
Related terms include predictive analytics, prescriptive analytics, and business intelligence. In the context of AI governance for supply chain management, actionable insights are critical to optimize supply chain operations, improve forecasting, and enhance overall performance.
Adversarial Attack refers to a malicious attempt to manipulate or deceive… #
Related terms include cybersecurity, data poisoning, and model evasion. In the context of AI governance for supply chain management, adversarial attacks can compromise the integrity and reliability of AI systems, highlighting the need for robust security measures and vulnerability assessments.
AI Ethics refers to the principles and guidelines that govern the… #
Related terms include fairness, transparency, and accountability. In the context of AI governance for supply chain management, AI ethics is essential to ensure that AI systems are designed and used in ways that respect human rights, promote diversity, and minimize harm.
Algorithmic Bias refers to the systematic and unintended errors or… #
Related terms include fairness, equity, and justice. In the context of AI governance for supply chain management, algorithmic bias can have significant consequences, such as perpetuating inequalities or discriminations, highlighting the need for regular audits and mitigation strategies.
Anomaly Detection refers to the identification of unusual or ab… #
Related terms include predictive analytics, machine learning, and data mining. In the context of AI governance for supply chain management, anomaly detection is critical to detect and prevent supply chain disruptions, counterfeiting, or other security threats.
Artificial General Intelligence (AGI) refers to a hypothetical AI system… #
Related terms include narrow AI, superintelligence, and singularity. In the context of AI governance for supply chain management, AGI is still a topic of speculation and research, but its potential implications for supply chain management are significant, highlighting the need for proactive planning and strategic governance.
Artificial Intelligence (AI) refers to the simulation of human intelli… #
Related terms include machine learning, deep learning, and natural language processing. In the context of AI governance for supply chain management, AI is a critical technology that can optimize supply chain operations, improve forecasting, and enhance overall performance.
Augmented Intelligence refers to the collaboration between humans and AI… #
Related terms include human-computer interaction, human-centered design, and cognitive augmentation. In the context of AI governance for supply chain management, augmented intelligence is essential to ensure that AI systems are designed and used in ways that complement human capabilities, rather than replacing them.
Automation refers to the use of machines or software to … #
Related terms include robotics, process automation, and machine learning. In the context of AI governance for supply chain management, automation is critical to optimize supply chain operations, improve efficiency, and reduce costs.
Bias Detection refers to the identification of systematic errors o… #
Related terms include fairness, equity, and justice. In the context of AI governance for supply chain management, bias detection is essential to ensure that AI systems are fair, transparent, and accountable, highlighting the need for regular audits and mitigation strategies.
Blockchain refers to a distributed and decentralized ledger techno… #
Related terms include distributed ledger technology, cryptocurrency, and smart contracts. In the context of AI governance for supply chain management, blockchain is critical to ensure the integrity and authenticity of supply chain data, enabling real-time tracking and visibility.
Business Intelligence (BI) refers to the process of analyzing and… #
Related terms include data analytics, predictive analytics, and performance management. In the context of AI governance for supply chain management, BI is essential to optimize supply chain operations, improve forecasting, and enhance overall performance.
Cloud Computing refers to the delivery of computing resources and… #
Related terms include cloud infrastructure, cloud storage, and cloud security. In the context of AI governance for supply chain management, cloud computing is critical to enable the deployment and management of AI systems, ensuring scalability and flexibility.
Cognitive Computing refers to the simulation of human cognition in… #
Related terms include artificial intelligence, machine learning, and natural language processing. In the context of AI governance for supply chain management, cognitive computing is essential to optimize supply chain operations, improve forecasting, and enhance overall performance.
Collaborative Robots (Cobots) refer to robots that are designed to wor… #
Related terms include human-robot interaction, robotics, and automation. In the context of AI governance for supply chain management, cobots are critical to optimize supply chain operations, improve efficiency, and reduce costs.
Computer Vision refers to the ability of machines to interpret<… #
Related terms include machine learning, deep learning, and image processing. In the context of AI governance for supply chain management, computer vision is essential to optimize supply chain operations, improve forecasting, and enhance overall performance.
Cybersecurity refers to the practice of protecting digital informa… #
Related terms include data security, network security, and threat intelligence. In the context of AI governance for supply chain management, cybersecurity is critical to ensure the integrity and authenticity of supply chain data, enabling real-time tracking and visibility.
Data Analytics refers to the process of examining and interpret… #
Related terms include business intelligence, predictive analytics, and data science. In the context of AI governance for supply chain management, data analytics is essential to optimize supply chain operations, improve forecasting, and enhance overall performance.
Data Governance refers to the process of managing and overseein… #
Related terms include data management, data quality, and data security. In the context of AI governance for supply chain management, data governance is critical to ensure the integrity and authenticity of supply chain data, enabling real-time tracking and visibility.
Data Mining refers to the process of discovering and extracting… #
Related terms include predictive analytics, business intelligence, and data analytics. In the context of AI governance for supply chain management, data mining is essential to optimize supply chain operations, improve forecasting, and enhance overall performance.
Data Quality refers to the degree to which data is accurate , co… #
Related terms include data governance, data management, and data security. In the context of AI governance for supply chain management, data quality is critical to ensure the integrity and authenticity of supply chain data, enabling real-time tracking and visibility.
Data Science refers to the field of study that combines data an… #
Related terms include data analytics, machine learning, and predictive analytics. In the context of AI governance for supply chain management, data science is essential to optimize supply chain operations, improve forecasting, and enhance overall performance.
Decision Support System (DSS) refers to a computer #
based system that supports and enables decision-making by providing data analysis and modeling capabilities. Related terms include business intelligence, predictive analytics, and data analytics. In the context of AI governance for supply chain management, DSS is critical to optimize supply chain operations, improve forecasting, and enhance overall performance.
Deep Learning refers to a type of machine learning that uses ne… #
Related terms include artificial intelligence, machine learning, and natural language processing. In the context of AI governance for supply chain management, deep learning is essential to optimize supply chain operations, improve forecasting, and enhance overall performance.
Digital Twin refers to a virtual replica of a physical system or p… #
Related terms include simulation, modeling, and predictive analytics. In the context of AI governance for supply chain management, digital twin is critical to optimize supply chain operations, improve forecasting, and enhance overall performance.
Explainable AI (XAI) refers to the ability of AI systems to explain</i… #
Related terms include transparency, accountability, and fairness. In the context of AI governance for supply chain management, XAI is essential to ensure that AI systems are transparent, explainable, and auditable, highlighting the need for regular audits and mitigation strategies.
Fairness refers to the principle of ensuring that AI systems are free<… #
Related terms include accountability, transparency, and ethics. In the context of AI governance for supply chain management, fairness is critical to ensure that AI systems are fair, transparent, and accountable, highlighting the need for regular audits and mitigation strategies.
Human #
Centered Design refers to a design approach that prioritizes human needs and experiences, enabling the creation of intuitive and user-friendly systems. Related terms include user experience, human-computer interaction, and design thinking. In the context of AI governance for supply chain management, human-centered design is essential to ensure that AI systems are designed and used in ways that complement human capabilities, rather than replacing them.
Internet of Things (IoT) refers to the network of physical devices… #
Related terms include industrial internet of things, smart devices, and connected systems. In the context of AI governance for supply chain management, IoT is critical to optimize supply chain operations, improve forecasting, and enhance overall performance.
Machine Learning refers to a type of artificial intelligence that… #
Related terms include deep learning, natural language processing, and predictive analytics. In the context of AI governance for supply chain management, machine learning is essential to optimize supply chain operations, improve forecasting, and enhance overall performance.
Natural Language Processing (NLP) refers to the ability of machines</i… #
Related terms include machine learning, deep learning, and language translation. In the context of AI governance for supply chain management, NLP is critical to optimize supply chain operations, improve forecasting, and enhance overall performance.
Predictive Analytics refers to the use of statistical models and <… #
Related terms include data analytics, business intelligence, and data mining. In the context of AI governance for supply chain management, predictive analytics is essential to optimize supply chain operations, improve forecasting, and enhance overall performance.
Prescriptive Analytics refers to the use of advanced analytics and… #
Related terms include predictive analytics, business intelligence, and data analytics. In the context of AI governance for supply chain management, prescriptive analytics is critical to optimize supply chain operations, improve forecasting, and enhance overall performance.
Reinforcement Learning refers to a type of machine learning that e… #
Related terms include deep learning, machine learning, and artificial intelligence. In the context of AI governance for supply chain management, reinforcement learning is essential to optimize supply chain operations, improve forecasting, and enhance overall performance.
Risk Management refers to the process of identifying , assessing… #
Related terms include compliance, governance, and security. In the context of AI governance for supply chain management, risk management is critical to ensure the integrity and authenticity of supply chain data, enabling real-time tracking and visibility.
Robotic Process Automation (RPA) refers to the use of software robots<… #
Related terms include automation, process automation, and machine learning. In the context of AI governance for supply chain management, RPA is critical to optimize supply chain operations, improve efficiency, and reduce costs.
Security refers to the practice of protecting digital information… #
Related terms include cybersecurity, data security, and threat intelligence. In the context of AI governance for supply chain management, security is critical to ensure the integrity and authenticity of supply chain data, enabling real-time tracking and visibility.
Supply Chain Management refers to the coordination and management … #
Related terms include operations management, logistics management, and procurement management. In the context of AI governance, supply chain management is critical to optimize supply chain operations, improve forecasting, and enhance overall performance.
Sustainability refers to the practice of meeting the needs of the… #
Related terms include environmental sustainability, social responsibility, and corporate social responsibility. In the context of AI governance for supply chain management, sustainability is essential to ensure that AI systems are designed and used in ways that promote social responsibility and environmental sustainability.
Transparency refers to the principle of ensuring that AI systems are o… #
Related terms include explainability, fairness, and ethics. In the context of AI governance for supply chain management, transparency is critical to ensure that AI systems are transparent, explainable, and auditable, highlighting the need for regular audits and mitigation strategies.
Trust refers to the confidence and faith that individuals and orga… #
Related terms include transparency, explainability, and fairness. In the context of AI governance for supply chain management, trust is essential to ensure that AI systems are designed and used in ways that promote trust and confidence, highlighting the need for regular audits and mitigation strategies.
Value Chain refers to the series of activities and processes</i… #
Related terms include supply chain management, operations management, and business strategy. In the context of AI governance for supply chain management, value chain is critical to optimize supply chain operations, improve forecasting, and enhance overall performance.
Vulnerability refers to the weakness or exposure of AI systems to… #
Related terms include security, cybersecurity, and threat intelligence. In the context of AI governance for supply chain management, vulnerability is critical to ensure the integrity and authenticity of supply chain data, enabling real-time tracking and visibility.