A holistic approach to analysis that focuses on the way that a system's constituent parts interrelate and how systems work over time and within the context of larger systems. Essential for solving complex problems and designing systems that account for interdependencies and dynamics.
A detailed description of a system's behavior as it responds to a request from one of its stakeholders, often used to capture functional requirements. Essential for understanding and documenting how users will interact with a system to achieve their goals.
AI systems that can dynamically adjust their behavior based on new data or changes in the environment. Important for developing systems that can respond to real-time changes and improve over time.
A structured set of breakpoints used to create responsive designs that work seamlessly across multiple devices. Important for maintaining consistency and usability in responsive design.
Site Reliability Engineering (SRE) is a discipline that incorporates aspects of software engineering and applies them to infrastructure and operations problems to create scalable and highly reliable software systems. Crucial for maintaining the reliability and efficiency of complex software systems.
A principle stating that a system should be liberal in what it accepts and conservative in what it sends, meaning it should handle user input flexibly while providing clear, consistent output, similar to the principle of fault tolerance. Essential for designing robust and user-friendly interfaces that accommodate a wide range of user inputs and behaviors while maintaining reliability and clarity in responses.
An inference method used in AI and expert systems where reasoning starts from known facts and applies rules to derive new facts. Important for developing intelligent systems that can build knowledge and solve problems incrementally in digital products.
Interactive Voice Response (IVR) is an automated telephony system that interacts with callers, gathers information, and routes calls to the appropriate recipient. It improves customer service and automates information retrieval.
The practice of developing artificial intelligence systems that are fair, transparent, and respect user privacy and rights. Crucial for ensuring that AI technologies are developed responsibly and ethically.
A principle stating that productivity increases when the computer and its user interact at a pace that ensures neither has to wait on the other. Important for designing responsive systems that enhance user productivity.
The ability of a system, product, or process to handle increased loads or expand without compromising performance or efficiency. Essential for ensuring that products and systems can grow and adapt to increasing demands.
The practice of designing applications specifically for a particular operating system or platform, leveraging its unique features and capabilities. Important for delivering high-performance and responsive user experiences.
The study of the relationships between people, practices, values, and technologies within an information environment. Helps in understanding and designing systems that are sustainable and adaptive to human and environmental changes.
The design of interactive digital products, environments, systems, and services. Crucial for creating engaging and user-friendly digital experiences.
Designing systems and processes to effectively respond to and manage crises, ensuring resilience and quick recovery. Crucial for preparing for unexpected events and minimizing their impact.
A mode of thinking, derived from Dual Process Theory, that is fast, automatic, and intuitive, often relying on heuristics and immediate impressions. Important for understanding how users make quick decisions and respond to design elements instinctively, aiding in the creation of intuitive and user-friendly interfaces.
The process of integrating knowledge into computer systems to solve complex problems, often used in AI development. Important for developing intelligent systems that can perform complex tasks and support decision-making in digital products.
The process of linking language to its real-world context in AI systems, ensuring accurate understanding and interpretation. Crucial for improving the relevance and accuracy of AI-generated responses.
Trust, Risk, and Security Management (TRiSM) is a framework for managing the trust, risk, and security of AI systems to ensure they are safe, reliable, and ethical. Essential for ensuring the responsible deployment and management of AI technologies.
Artificial Intelligence of Things (AIoT) is the integration of AI with the Internet of Things (IoT) to create smart systems that can learn and adapt. Crucial for developing advanced, intelligent products that offer enhanced user experiences and operational efficiencies.
The tendency to believe that things will always function the way they normally have, often leading to underestimation of disaster risks. Important for understanding risk perception and designing systems that effectively communicate potential changes.
A structure or framework used to create effective prompts for AI systems, ensuring clarity and context. Important for standardizing and improving AI prompt design.
Guidelines and principles designed to ensure that AI systems are developed and used in a manner that is ethical and responsible. Crucial for building trust and ensuring the responsible use of AI technologies.
Responsive Web Design (RWD) is an approach to web design that makes web pages render well on a variety of devices and window or screen sizes. Essential for creating flexible, adaptive web experiences that maintain functionality and aesthetics across different platforms and devices.
A theory that emphasizes the role of emotions in risk perception and decision-making, where feelings about risk often diverge from cognitive assessments. Important for designing systems that account for emotional responses to risk and improve decision-making.
A team responsible for developing and maintaining the foundational systems and services that support other teams and products. Crucial for ensuring scalability and efficiency across the organization.
A specific viewport dimension at which a website's layout adjusts to provide an optimal viewing experience across different screen sizes. Crucial for responsive web design to ensure usability on various devices.
A professional who designs, builds, and maintains systems for processing large-scale data sets. Essential for enabling data-driven decision-making and supporting advanced analytics in organizations.
A system where outputs are fed back into the process as inputs, allowing for continuous improvement based on user responses. Crucial for iterative development and continuous improvement in design and product management.
The practice of collecting, processing, and using data in ways that respect privacy, consent, and the well-being of individuals. Essential for building trust and ensuring compliance with legal and ethical standards.
A framework for assessing and improving an organization's ethical practices in the development and deployment of AI. Important for ensuring that AI systems are developed responsibly and ethically.
Systematic errors in AI models that arise from the data or algorithms used, leading to poor outcomes. Important for ensuring fairness and accuracy in AI systems.
The mathematical study of waiting lines or queues. Useful for optimizing user flow and reducing wait times in user interfaces.
Dynamic Systems Development Method (DSDM) is an agile project delivery framework focused on delivering business value early and continuously. Essential for ensuring that projects align with business goals and user needs through iterative processes.
The degree to which users feel they have control over their actions and decisions when interacting with a product or system. Crucial for designing systems that empower users and enhance their sense of control and satisfaction.
The practice and science of classification, often used to organize content and information. Essential for improving findability and usability in information systems.
The process of designing and refining prompts to elicit accurate and relevant responses from AI models. Crucial for optimizing the performance of AI applications.
The Principle of Front Doors is an information architecture guideline that acknowledges multiple entry points into a website or system. Crucial for ensuring that all entry points provide a coherent and navigable experience.
A temporary increase in the frequency and intensity of a behavior when reinforcement is first removed. Useful for understanding user behavior changes in response to modifications in design or system features.
eXtreme Programming (XP) is an agile software development methodology focused on customer satisfaction and continuous improvement. It enhances software quality and responsiveness to changing requirements through frequent releases of functional software.
The process of enabling users to take control of their interactions with a product or system, enhancing their confidence and satisfaction. Crucial for designing systems that provide users with the tools and information they need to make informed decisions.
The ability of users to influence the behavior and outcomes of a system or product, allowing them to interact with it according to their preferences. Essential for creating user-friendly interfaces that allow for flexibility and customization.
Observe, Orient, Decide, and Act (OODA) is a decision-making framework often used in strategic planning and rapid response situations. Crucial for agile decision-making and strategic planning in dynamic environments.
Content or functionality that is built into a platform or device rather than being provided by an external application. Important for ensuring seamless integration and optimal performance.
A prompt or cue that initiates a behavior or response, often used in behavior design to encourage specific actions. Crucial for designing systems that effectively prompt desired user behaviors.
A system that allows customers to access information and perform tasks on their own without the need for assistance from customer service representatives. Important for improving customer experience and reducing support costs.
The study and application of ethical considerations in the development, implementation, and use of technology. Crucial for ensuring that technological advancements align with ethical standards and societal values.
Ensuring that user experiences are consistent across different platforms, such as web, mobile, and desktop. Essential for creating a seamless and cohesive user experience across multiple devices.
An approach to information architecture that starts with the details and builds up to a comprehensive structure. Useful for designing flexible and detailed systems that can adapt to user needs.
The hypothesis that safety measures may lead to behavioral changes that offset the benefits of the measures, potentially leading to risk compensation. Crucial for understanding risk behavior and designing systems that account for compensatory behaviors.
A collection of reusable UI components that can be used to build applications. Helps in maintaining consistency and efficiency in the design and development process.
A professional responsible for designing and managing data structures, storage solutions, and data flows within an organization. Important for ensuring efficient data management and supporting data-driven decision-making in digital product design.
A theoretical concept in economics that portrays humans as rational and self-interested agents who aim to maximize their utility. Important for understanding economic decision-making and designing systems that align with rational behavior.
A framework used in graphic and web design to organize content in a structured and consistent manner. Essential for creating balanced and readable layouts.
Knowledge Organization System (KOS) refers to a structured framework for organizing, managing, and retrieving information within a specific domain or across multiple domains. Essential for improving information findability, enhancing semantic interoperability, and supporting effective knowledge management in digital environments.
A method used in AI and machine learning to ensure prompts and inputs are designed to produce the desired outcomes. Essential for improving the accuracy and relevance of AI responses.
The degree to which the operations and decisions of an AI system are understandable and explainable to users. Crucial for building trust and ensuring ethical AI use.
ModelOps (Model Operations) is a set of practices for deploying, monitoring, and maintaining machine learning models in production environments. Crucial for ensuring the reliability, scalability, and performance of AI systems throughout their lifecycle, bridging the gap between model development and operational implementation.
Retrieval-Augmented Generation (RAG) is an AI approach that combines retrieval of relevant documents with generative models to produce accurate and contextually relevant responses. Essential for improving the accuracy and reliability of AI-generated content.
A method of categorizing information in more than one way to enhance findability and user experience. Crucial for improving navigation, search, and overall usability of complex information systems.