Social Foraging
The behavior of seeking information or resources based on social interactions and cues. Important for understanding how users gather information in social contexts and designing systems that support collaborative information seeking.
358 topics found for:
“systems design”
Informational Influence
The change in opinions or behavior that occurs when individuals conform to the information provided by others. Important for understanding social dynamics and designing systems that leverage social proof and peer influence.
Gambler’s Fallacy
A cognitive bias where individuals believe that past random events affect the probabilities of future random events. Important for designers to understand user decision-making biases related to randomness.
Wizard of Oz Testing
A usability testing method where users interact with a system they believe to be autonomous, but which is actually operated by a human. Essential for testing concepts and interactions before full development.
Sunk Cost Fallacy
The tendency for individuals to continue a behavior or endeavor as a result of previously invested resources (time, money, or effort) rather than future potential benefits. Important for understanding decision-making biases and designing systems that help users avoid irrational persistence.
Usability Testing
A technique used to evaluate a product or system by testing it with real users to identify any usability issues and gather qualitative and quantitative data on their interactions. Crucial for identifying and resolving usability issues to improve user satisfaction and performance.
SRS
Software Requirements Specification (SRS) is a detailed document that outlines the functional and non-functional requirements of a software system. Crucial for ensuring clear communication and understanding between stakeholders and the development team.
KYC
Know Your Customer (KYC) is a process used by businesses to verify the identity of their clients and assess potential risks of illegal intentions for the business relationship. Essential for preventing fraud, money laundering, and terrorist financing, particularly in financial services, while also ensuring compliance with regulatory requirements and building trust with customers.
Bounded Rationality
A concept that humans make decisions within the limits of their knowledge, cognitive capacity, and available time, leading to satisficing rather than optimal solutions. Crucial for designing systems and processes that account for human cognitive limitations and decision-making processes.
Present Bias
A cognitive bias where individuals give stronger weight to payoffs that are closer to the present time compared to those in the future. Important for understanding user time-related decision-making and designing systems that encourage long-term thinking.
Risk-as-Feelings Theory
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.
Survivorship Bias
A cognitive bias that occurs when conclusions are drawn from a non-representative sample, focusing only on successful cases and ignoring failures. Crucial for making accurate assessments and designing systems that consider both successes and failures.
Computational Thinking
A problem-solving process that includes logical reasoning, pattern recognition, abstraction, and algorithmic thinking. Important for developing efficient and effective solutions in digital product design and development.
ModelOps
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.
Tree Testing
A usability technique used to evaluate the findability and labeling of topics in a website's structure by having participants find specific items in a simplified text version of the site. Crucial for improving information architecture and ensuring users can navigate a website effectively.
AI Transparency
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.
Cluster Navigation
A navigation system that groups related links or content into clusters for easier access. Important for enhancing user experience by simplifying access to related information.
Machine Learning Bias
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.
Optimism Bias
A cognitive bias that causes people to believe they are less likely to experience negative events and more likely to experience positive events than others. Crucial for understanding user risk perception and designing systems that account for unrealistic optimism.
Intertemporal Choice
The study of how people make choices about what and how much to do at various points in time, often involving trade-offs between costs and benefits occurring at different times. Crucial for designing systems that account for delayed gratification and long-term planning.
Regret Aversion
A tendency to avoid making decisions that might lead to regret, influencing risk-taking and decision-making behaviors. Crucial for understanding decision-making processes and designing systems that minimize regret.
Intentionality Bias
The tendency to attribute intentional actions to others' behaviors, often overestimating their intent. Important for understanding and mitigating biases in user interactions and feedback.
Adaptive Control of Thought
A cognitive architecture model that explains how humans can learn and adapt to new tasks. Useful for understanding user learning and behavior adaptation, informing better user experience design.
Inflection Point
A moment of significant change in a process or system, where the direction of growth, performance, or trend shifts markedly. Important for recognizing critical transitions in design or business strategies, enabling timely adjustments and informed decision-making.
NPD
New Product Development (NPD) is the complete process of bringing a new product to market, from idea generation to commercialization. Essential for companies to innovate, stay competitive, and meet evolving customer needs through a structured approach to creating and launching new offerings.
XAI
Explainable AI (XAI) are AI systems that provide clear and understandable explanations for their decisions and actions. This transparency is crucial for building trust and confidence in AI applications across various domains.
Generative Modeling
The use of algorithms to generate new data samples that resemble a training dataset, often used in AI for creating realistic outputs. Important for developing creative and innovative solutions in digital product design, such as content generation and simulation.
KPI
Key Performance Indicators (KPIs) are quantifiable measures used to evaluate the success of an organization, employee, or project in meeting objectives for performance. Essential for tracking progress, making informed decisions, and aligning efforts with strategic goals across various business functions, including product design and development.
Naive Allocation
A heuristic where individuals evenly distribute resources across all options, regardless of their specific needs or potential. Useful for understanding and designing around simplistic decision-making strategies.
Myopic Loss Aversion
A cognitive bias where individuals tend to avoid risks when they perceive potential losses more acutely than potential gains. Important for understanding decision-making behavior in users and designing systems that mitigate risk aversion.
Surrogation
The process by which a measure or metric comes to replace the underlying objective it is intended to represent, leading to distorted decision-making. Important for ensuring that metrics accurately reflect true objectives and designing systems that prevent metric manipulation.
IoT
Internet of Things (IoT) refers to a network of interconnected physical devices embedded with electronics, software, sensors, and network connectivity, enabling them to collect and exchange data. Essential for creating smart, responsive environments and improving efficiency across various industries by enabling real-time monitoring, analysis, and automation.
MQL
Marketing Qualified Lead (MQL) is a prospective customer who has shown interest in a company's product or service and meets specific criteria indicating a higher likelihood of becoming a customer. Essential for prioritizing leads and optimizing the efficiency of sales and marketing efforts by focusing resources on prospects most likely to convert.
PoC
Proof of Concept (PoC) is a demonstration, usually in the form of a prototype or pilot project, to verify that a concept or theory has practical potential. Crucial for validating ideas, demonstrating feasibility, and securing support for further development in product design and innovation processes.
Human-AI Collaboration
The combined efforts of humans and AI systems to achieve better outcomes than either could alone. Important for leveraging the strengths of both humans and AI in various tasks.
Hotfix
A quick and often temporary fix applied to a software product to address an urgent issue without going through the full development cycle. Essential for maintaining the stability and functionality of digital products in the face of critical issues.
Expert Evaluation
Also known as Expert Review, a method where experts assess a product or system against established criteria to identify usability issues and areas for improvement. Essential for leveraging expert insights to enhance product quality and usability.
Turing Test
A test proposed by Alan Turing to determine if a machine's behavior is indistinguishable from that of a human. Important for evaluating the intelligence of AI systems.
Prospect Theory
A behavioral economic theory that describes how people choose between probabilistic alternatives that involve risk, where the probabilities of outcomes are known. Crucial for understanding decision-making under risk and designing systems that align with user behavior.
Cybersecurity
The practice of protecting systems, networks, and programs from digital attacks, unauthorized access, and data breaches. Essential for safeguarding sensitive information, maintaining user trust, and ensuring the integrity and functionality of digital products and services.
Creative AI
AI systems designed to generate creative content, such as art, music, and literature. Important for exploring new forms of artistic expression and automating creative processes.
Biometric Inputs
The use of biological data (e.g., fingerprints, facial recognition) for user authentication and interaction with digital systems. Crucial for enhancing security and user experience through advanced authentication methods.
Pre-Trained Transformer
An AI model that has been pre-trained on a large dataset and can be fine-tuned for specific tasks. Essential for developing state-of-the-art NLP applications.
RLHF
Reinforcement Learning from Human Feedback (RLHF) is a machine learning technique that uses human input to guide the training of AI models. Essential for improving the alignment and performance of AI systems in real-world applications.
Depth of Processing
A theory suggesting that information processed at a deeper, more meaningful level is better remembered than information processed at a shallow level. Crucial for designing educational and informational content that enhances retention and understanding.
Subadditivity Effect
A cognitive bias where the total probability assigned to a set of events is less than the sum of the probabilities assigned to each event individually. Important for understanding how users estimate probabilities and make decisions under uncertainty.
Standard Economic Model
A theoretical framework in economics that assumes individuals act rationally and seek to maximize utility, used to predict economic behavior and outcomes. Important for understanding traditional economic theories and designing systems that account for rational decision-making.
Decision Tree
A tree-like model of decisions and their possible consequences, used in data mining and machine learning for both classification and regression tasks. Valuable for creating interpretable models in digital product design and user behavior analysis.
Haptics
The technology of transmitting and understanding information through touch. Crucial for enhancing user interactions with devices and systems through tactile feedback.
Selective Exposure
The tendency for individuals to favor information that aligns with their existing beliefs and to avoid information that contradicts them. Crucial for understanding how users engage with content and designing systems that present balanced perspectives.
Generative AI
A type of artificial intelligence capable of generating new content, such as text, images, and music, by learning from existing data. Important for automating creative processes and generating novel outputs.
InfoVis
Information Visualization (InfoVis) is the study and practice of visual representations of abstract data to reinforce human cognition. Crucial for transforming complex data into intuitive visual formats, enabling faster insights and better decision-making.
Synthetic Data
Artificially generated data that mimics real data, used for training machine learning models. Crucial for training models when real data is scarce or sensitive.
Pilot
A preliminary version of a project or system used to test and validate its feasibility before full-scale implementation. Crucial for identifying potential issues and making necessary adjustments to improve the final product.
Social Loafing
The tendency for individuals to put in less effort when working in a group compared to when working alone, due to reduced accountability. Crucial for understanding group dynamics and designing systems that ensure individual accountability.
Data Science
An interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Essential for driving data-informed decision making, predicting trends, and uncovering valuable insights in digital product design and development.
Allais Paradox
A decision-making paradox that shows people's preferences can violate the expected utility theory, highlighting irrational behavior. Important for understanding inconsistencies in user decision-making and designing better user experiences.
GTD
Getting Things Done (GTD) is a productivity methodology that emphasizes capturing tasks, organizing them, and taking action. Essential for improving personal and team productivity and task management.
Incremental Innovation
The process of making small, continuous improvements to products, services, or processes over time. Important for sustaining growth and maintaining competitiveness through ongoing improvements.
Git
A distributed version control system for tracking changes in source code during software development. Essential for collaborative development and managing codebase evolution in digital product design.