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International Standards (ISO/IEC 22989) for Artificial Intelligence: Part 2/4

Updated: Jan 2

Worldwide standardizations for Artificial Intelligence (AI)

  • ISO (International Organization for Standardization)

  • IEC (International Electrotechnical Commission)

 

Focus on ISO/IEC 22989:2023 : Artificial intelligence concepts & terminology





Artificial intelligence (AI) is a rapidly growing field that has the potential to revolutionize the way we live and work. However, with this growth comes a need for standardization and clarity in the terminology used to describe AI concepts and technologies. This is where the ISO/IEC 22989:2023 standard comes in. This standard provides a comprehensive list of terms and definitions related to AI, helping to establish a common language for professionals in the field.

ISO/IEC 22989:2023 covers concepts related to AI, such as machine learning, deep learning, and natural language processing. Machine learning is a type of AI that allows machines to learn from data without being explicitly programmed. Deep learning is a subset of machine learning that uses neural networks to learn from large amounts of data. Natural language processing (NLP) is a type of AI that allows machines to understand and interpret human language.



ISO/IEC 22989:2023 also considers some other key technologies that are used in AI systems, such as cloud computing, big data, and natural language processing. Cloud computing is a technology that allows users to access computing resources over the internet. Big data is a term used to describe large and complex datasets that are difficult to process using traditional data processing methods. Natural language processing is a technology that allows machines to understand and interpret human language.

 

Definitions


ISO/IEC 22989:2023 defines some of the key components of AI systems, such as algorithms, models, and datasets. For example - an algorithm is a set of instructions that a machine follows to perform a specific task. A model is a representation of a system or process that can be used to make predictions or decisions. A dataset is a collection of data that is used to train an AI system.


Here are some of the other key terms and definitions covered in the ISO/IEC 22989:2023 standard:


  • Artificial intelligence (AI): The ability of a machine to exhibit intelligent behaviour similar to that of a human.

  • Machine learning: A type of AI that allows machines to learn from data without being explicitly programmed.

  • Deep learning: A subset of machine learning that uses neural networks to learn from large amounts of data.

  • Natural language processing (NLP): A type of AI that allows machines to understand and interpret human language.

  • Algorithm: A set of instructions that a machine follows to perform a specific task.

  • Model: A representation of a system or process that can be used to make predictions or decisions.

  • Dataset: A collection of data that is used to train an AI system.

  • Expert system: An AI system that is designed to mimic the decision-making abilities of a human expert in a particular field.

  • Decision support system: An AI system that is designed to help humans make better decisions by providing them with relevant information and analysis.

  • Autonomous system: An AI system that can operate independently without human intervention.

  • Cloud computing: A technology that allows users to access computing resources over the internet.

  • Big data: A term used to describe large and complex datasets that are difficult to process using traditional data processing methods.

  • Bias: The tendency of AI systems to reflect the biases of their developers or the data on which they are trained.

  • Privacy: The protection of personal information in the context of AI systems.

  • Safety: The potential risks associated with the use of AI systems, such as the risk of accidents or unintended consequences.


These are just a few examples of the many terms and definitions covered in the standard.






Types of AI


One of the most important sections is the one that defines the different types of AI systems. These include expert systems, decision support systems, and autonomous systems. Expert systems are AI systems that are designed to mimic the decision-making abilities of a human expert in a particular field. Decision support systems are AI systems that are designed to help humans make better decisions by providing them with relevant information and analysis. Autonomous systems are AI systems that can operate independently without human intervention.

 

Ethics & Society


Another key consideration is to define the ethical and social implications of AI. These include issues such as bias, privacy, and safety. Bias refers to the tendency of AI systems to reflect the biases of their developers or the data on which they are trained. Privacy refers to the protection of personal information in the context of AI systems. Safety refers to the potential risks associated with the use of AI systems, such as the risk of accidents or unintended consequences.


AI System Lifecycle


Another important topic is the different stages of the AI system life cycle. These include design, data and models, verification and validation, deployment, and operation and monitoring. The design stage involves planning and designing the AI system. The data and models stage involves collecting and processing data and building models. The verification and validation stage involves testing and validating the AI system. The deployment stage involves implementing the AI system in a real-world environment. The operation and monitoring stage involves monitoring the AI system to ensure that it is functioning properly.




 

AI stakeholder landscape


ISO/IEC 22989:2023 also defines some of the key stakeholders in the AI ecosystem, such as developers, users, and regulators. Developers are the individuals or organizations that create AI systems. Users are the individuals or organizations that use AI systems. Regulators are the individuals or organizations that set and enforce the legal requirements for AI systems.

The ISO/IEC 22989:2023 standard is a crucial resource for professionals in the field of artificial intelligence (AI). It provides a comprehensive list of terms and definitions related to AI, establishing a common language for the industry. The standard defines basic concepts such as machine learning, deep learning, and natural language processing, as well as key components of AI systems such as algorithms, models, and datasets. It also defines the different types of AI systems, including expert systems, decision support systems, and autonomous systems, and identifies key stakeholders such as developers, users, and regulators. Overall, the ISO/IEC 22989:2023 standard is an essential resource for anyone working in the field of AI. It ensures that professionals are speaking the same language and working towards the same goals, while also addressing important ethical and social considerations.


The ISO/IEC 22989:2023 standard is useful for a wide range of professionals working in the field of artificial intelligence (AI). This includes:


  • AI developers and engineers who need to understand the key concepts, terms, and definitions related to AI systems.

  • Business leaders and decision-makers who need to understand the potential benefits and risks of AI systems for their organizations.

  • Regulators and policymakers who need to develop regulations and policies related to AI systems.

  • Researchers and academics who need to stay up to date with the latest developments in the field of AI.

  • Students and educators who need to learn about the fundamental concepts and principles of AI.

 

Final thoughts


In conclusion, the ISO/IEC 22989:2023 standard provides a comprehensive list of terms and definitions related to AI, helping to establish a common language for professionals in the field. It defines some of the basic concepts related to AI, as well as the key components of AI systems and the different types of AI systems. It also defines the different stages of the AI system life cycle, the key technologies used in AI systems, and the ethical and social implications of AI. This standard is an important resource for anyone working in the field of AI, helping to ensure that everyone is speaking the same language and working towards the same goals. The ISO/IEC 22989:2023 standard serves as a valuable resource for establishing a common language and understanding within the field of AI, covering a wide range of terms, definitions, and concepts essential for professionals in the industry.


Our team are experts in international corporate governance, risk and standards. Including emerging technologies such as Artificial Intelligence (AI). Contact us at contact@bolthq.io or talk to our own AI expert below.


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