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.
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.
A preliminary testing phase conducted by internal staff to identify bugs before releasing the product to external testers or customers. Crucial for ensuring product quality and functionality before broader release.
A type of bias that occurs when the observer's expectations or beliefs influence their interpretation of what they are observing, including experimental outcomes. Essential for ensuring the accuracy and reliability of research and data collection.
The process of encoding sensory input that has particular meaning or can be applied to a context, enabling deeper processing and memory retention. Important for understanding how information is processed and stored, enhancing design of educational content.
A set of algorithms, modeled loosely after the human brain, designed to recognize patterns and perform complex tasks. Essential for developing advanced AI applications in various fields.
A cognitive bias where individuals underestimate their own abilities and performance relative to others, believing they are worse than average. Important for understanding self-perception biases among designers and designing systems that support accurate self-assessment.
A cognitive bias where individuals favor others who are perceived to be similar to themselves, affecting judgments and decision-making. Crucial for understanding biases in team dynamics and decision-making processes among designers.
Web Content Accessibility Guidelines (WCAG) are a set of guidelines developed by WAI to make web content more accessible. Essential for ensuring that websites are usable by individuals with disabilities, thereby promoting inclusivity and compliance with accessibility standards.
A cognitive approach where information is processed at a surface level, focusing on basic features rather than deeper meaning, often leading to poorer memory retention. Important for designing educational and informational content that encourages deeper processing and understanding.
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 collection of reusable components, guided by clear standards, that can be assembled to build any number of applications, ensuring consistency and efficiency. Crucial for maintaining design consistency and efficiency across products.
Technologies that enable machines to understand and interpret data on the web in a human-like manner, enhancing connectivity and usability of information. Essential for improving data interoperability and accessibility on the web.
A marketing strategy where affiliates earn a commission for driving sales or traffic to a company's website. Crucial for product managers and marketers to expand reach and drive sales through partnerships.
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.
A visual representation of the stages a sales opportunity goes through, helping to track progress and forecast revenue. Important for managing sales processes and predicting future sales.
The final interaction a customer has with a brand before making a purchase. Important for understanding which touchpoints drive conversions.
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.
Representational State Transfer (REST) is an architectural style for designing networked applications based on stateless, client-server communication. Essential for building scalable and efficient web services.
Garbage In-Garbage Out (GIGO) is a principle stating that the quality of output is determined by the quality of the input, especially in computing and data processing. Crucial for ensuring accurate and reliable data inputs in design and decision-making processes.
A strategic management template for developing new business models or documenting existing ones, detailing elements like value proposition, infrastructure, and customers. Important for understanding and designing business strategies that align with product and user experience goals.
A writing and design principle that suggests that things grouped in threes are more satisfying, effective, and memorable for audiences. Important for creating impactful and memorable content and designs.