A theory that explains how individuals determine the causes of behavior and events, including the distinction between internal and external attributions. Crucial for understanding user behavior and designing experiences that address both internal and external factors.
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 principle that suggests the simplest explanation is often the correct one, favoring solutions that make the fewest assumptions. Crucial for problem-solving and designing straightforward, efficient solutions.
The ability to use learned knowledge and experience, often increasing with age and accumulated learning. Important for understanding how expertise and knowledge accumulation impact design and decision-making.
The process of distinguishing a product or service from its competitors in a way that is meaningful to the target market. Important for creating a unique value proposition and gaining a competitive edge.
A component in neural networks that allows the model to focus on specific parts of the input, improving performance. Essential for developing advanced AI models, particularly in natural language processing.
A cognitive bias where people see patterns in random data. Important for designers to improve data interpretation and avoid false conclusions based on perceived random patterns.
The mathematical study of waiting lines or queues. Useful for optimizing user flow and reducing wait times in user interfaces.
The phenomenon where individuals' expectations about a situation influence their actual experience of that situation. Useful for understanding the influence of expectations on outcomes.
The phenomenon where external incentives diminish intrinsic motivation, leading to reduced performance or engagement. Important for designing motivational strategies that do not undermine intrinsic motivation.
The tendency for people's perception to be affected by their recurring thoughts at the time. Important for understanding how current thoughts influence user perception and decision-making.
A psychological phenomenon where people remember uncompleted or interrupted tasks better than completed tasks. Crucial for designing engaging experiences that leverage task incompletion to maintain user interest.
A phenomenon where people are more likely to remember information when they are in the same state of consciousness as when they learned it. Important for understanding how context affects memory recall and designing experiences that facilitate better retention.
A cognitive bias where people attribute group behavior to the characteristics of the group members rather than the situation. Crucial for understanding team dynamics and avoiding misattribution in collaborative settings.
Above the Line (ATL) refers to marketing activities carried out at a macro level to reach a large audience through mass media such as TV, radio, and print ads. Essential for building brand awareness and reaching a wide audience.
The tendency for people to believe that others are telling the truth, leading to a general assumption of honesty in communication. Important for understanding communication dynamics and designing systems that account for this bias.
A cognitive bias where individuals overestimate the accuracy of their judgments, especially when they have a lot of information. Important for understanding and mitigating overconfidence in user decision-making.
A philosophical approach to culture and literature that seeks to confront the social, historical, and ideological forces and structures that produce and constrain it. Valuable for analyzing and addressing power dynamics and biases in design.
A cognitive bias where people underestimate the complexity and challenges involved in scaling systems, processes, or businesses. Important for understanding the difficulties of scaling and designing systems that address these challenges.
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.
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.
A decision-making strategy that involves choosing an option that meets the minimum requirements rather than seeking the optimal solution, balancing effort and outcome. Important for designing user experiences that accommodate decision-making under constraints.
A reading pattern where users focus on individual elements or "spots" of interest on a page, rather than following a linear path. Crucial for designing engaging and attention-grabbing content layouts.
A cognitive bias where people perceive an outcome as certain while it is actually uncertain, based on how information is presented. Crucial for understanding and mitigating biased user decision-making.
A dark pattern where the cancellation process is intentionally complicated to discourage users from canceling. Designers must avoid complicating cancellations and respect user decisions with a straightforward process.
A cognitive bias where people focus on the most noticeable or prominent information while ignoring less conspicuous details. Important for understanding user decision-making and ensuring balanced presentation of information.
A cognitive bias where people overemphasize information that is placed prominently or in a way that catches their attention first. Crucial for designing interfaces and information displays that manage user attention effectively.
Generative Pre-trained Transformer (GPT) is a type of AI model that uses deep learning to generate human-like text based on given input. This technology is essential for automating content creation and enhancing interactive experiences.
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.
The tendency to cling to one's beliefs even in the face of contradictory evidence. Important for understanding resistance to change and designing interventions that address this bias.
Not Invented Here (NIH) syndrome refers to the aversion to using or buying products, research, or knowledge developed outside an organization. This mindset can hinder innovation and collaboration.
An area in a market or industry that is currently underserved or unaddressed, presenting opportunities for innovation and new business ventures. Important for identifying gaps in the market that can be filled with new products, services, or solutions.
A strategy or plan that outlines how a company will launch a product to market, including target audience, marketing tactics, and sales strategy. Essential for successfully launching products and capturing market share.
A type of model architecture primarily used in natural language processing tasks, known for its efficiency and scalability. Essential for state-of-the-art NLP applications.
A type of sensory memory that briefly holds visual information for a fraction of a second. Useful for understanding how users process visual information and designing interfaces accordingly.
The tendency to judge the strength of arguments based on the believability of their conclusions rather than the logical strength of the arguments. Important for understanding cognitive biases that affect decision-making and user perceptions.
A set of ten general principles for user interface design created by Jakob Nielsen to improve usability. Essential for evaluating and improving user interface designs.
The phenomenon where people continue a failing course of action due to the amount of resources already invested. Important for recognizing and mitigating biased decision-making.
The process of developing and maintaining a brand to ensure it meets business goals and customer expectations. Crucial for sustaining brand equity and achieving long-term success.
An approach to design that explores and creates provocative scenarios of future possibilities to stimulate discussion and critical thinking about the direction of design and society. Important for pushing the boundaries of conventional design thinking and envisioning future implications.
The tendency to believe that large or significant events must have large or significant causes. Important for understanding cognitive biases in decision-making and designing systems that present accurate causal relationships.
The study of the interplay between individuals and their surroundings, including built environments and natural settings. Essential for designing spaces that enhance well-being and productivity.
The application of behavioral science principles to improve the design and usability of digital products, focusing on user behavior and interactions. Important for creating user experiences that are intuitive and engaging by leveraging behavioral insights.
A cognitive bias that limits a person to using an object only in the way it is traditionally used. Important for designers to foster creative problem-solving and innovation.
The psychological phenomenon where people prefer options that are not too extreme, but just right. Crucial for designing products and experiences that cater to the majority preference.
A logical fallacy where anecdotal evidence is used to make a broad generalization. Crucial for improving critical thinking and avoiding misleading conclusions.
A cognitive bias where people disproportionately prefer smaller, immediate rewards over larger, later rewards. Important for understanding and designing around user decision-making and reward structures.
The study of the principles that govern human behavior, including how people respond to stimuli and learn from their environment. Crucial for designing user experiences that anticipate and influence user behavior.
A phenomenon where an item that stands out is more likely to be remembered than other items, often used in design to highlight important elements. Crucial for designing interfaces that effectively capture user attention.
The study of social relationships, structures, and processes. Important for understanding the impact of social dynamics on user behavior and designing for social interactions.
Anchoring (also known as Focalism) is a cognitive bias where individuals rely heavily on the first piece of information (the "anchor") when making decisions. Crucial for understanding and mitigating initial information's impact on user decision-making processes.
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.
A method in natural language processing where multiple prompts are linked to generate more complex and contextually accurate responses. Essential for enhancing the capability and accuracy of AI models in digital products that rely on natural language understanding.
The psychological phenomenon where humorous content is more easily remembered and perceived positively by users. Useful for creating engaging and memorable user experiences.
The use of behavioral science insights to inform and guide strategic decision-making in organizations. Crucial for developing strategies that effectively influence behavior and drive business success.
An iterative design process that uses algorithms and computational tools to generate a wide range of design solutions based on defined constraints and goals. Crucial for exploring innovative and optimized design solutions.
The tendency for people to pay more attention to items placed in the center of a visual field. Crucial for designing layouts that maximize visibility and impact of key elements.
The tendency to overestimate how much our future preferences and behaviors will align with our current preferences and behaviors. Important for understanding user behavior and designing experiences that account for changes over time.
Also known as the 68-95-99.7 Rule, it states that for a normal distribution, nearly all data will fall within three standard deviations of the mean. Important for understanding the distribution of data and making predictions about data behavior in digital product design.
The study of how humans interact with systems and products, focusing on improving usability and performance. Crucial for designing user-friendly systems and products.