Technology Ethics
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.
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.
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.
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.
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.
The principles and guidelines that govern the moral and ethical aspects of design, ensuring that designs are socially responsible and beneficial. Crucial for creating designs that are ethical, inclusive, and socially responsible.
Technology designed to change attitudes or behaviors of users through persuasion and social influence, but not coercion. Crucial for designing systems that effectively influence user behavior while maintaining ethical standards.
The study of computers as persuasive technologies, focusing on how they can change attitudes or behaviors. Important for designing systems that effectively influence user behavior ethically.
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.
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.
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.
Human in the Loop (HITL) integrates human judgment into the decision-making process of AI systems. Crucial for ensuring AI reliability and alignment with human values.
Adhering to laws, regulations, and guidelines relevant to business operations and product development. Crucial for ensuring products and practices meet legal and ethical standards.
Artificial Superintelligence (ASI) is a hypothetical AI that surpasses human intelligence and capability in all areas. Important for understanding the potential future impacts and ethical considerations of AI development.
A dark pattern where users' activities are tracked without their explicit consent or knowledge. Designers must avoid this practice and ensure clear communication about tracking to respect user privacy.
A pop-up dialog that appears when a user attempts to leave a page or application, which can be used to prevent loss of progress or data, or to confirm user intent. While it can be used ethically to prevent data loss or confirm actions, designers must avoid using it to deceive, delay, block, or interfere with the user's intent, thus ensuring it does not become a dark pattern.
A strategic framework that designs user experiences to guide behavior and decisions towards desired outcomes. Crucial for creating effective and ethical influence in digital interfaces.
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.
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.
A framework that incorporates privacy considerations into the design and development of products and services from the outset. Crucial for ensuring user privacy and compliance with data protection regulations.
A dark pattern where it's easy to subscribe but very difficult to cancel the subscription. Awareness of this tactic is important to provide straightforward and user-friendly subscription management.
Human-Computer Interaction (HCI) is the study of designing interfaces and interactions between humans and computers. It ensures that digital products are user-friendly, efficient, and satisfying.
Social, Technological, Economic, Environmental, Political, Legal, and Ethical (STEEPLE) is an analysis tool that examines the factors influencing an organization. Crucial for comprehensive strategic planning and risk management in product design.
Product Development is the process of bringing a new product to market or improving an existing one. Crucial for innovation, meeting customer needs, and maintaining a competitive edge.
A design pattern that combines human and machine intelligence to enhance decision-making and problem-solving. Important for leveraging AI to support and amplify human capabilities.
AI as a Service (AIaaS) is a service model where AI tools and algorithms are provided over the internet by a third-party provider. Essential for making advanced AI capabilities accessible to businesses.
The design of products, devices, services, or environments for people with disabilities or specific needs. Crucial for creating inclusive products that can be used by everyone, including those with disabilities.
User Experience (UX) refers to the overall experience of a person using a product, system, or service, encompassing all aspects of the end-user's interaction. Crucial for creating products that are not only functional but also enjoyable, efficient, and satisfying to use.
Interaction Design (IxD) focuses on creating engaging interfaces with well-thought-out behaviors. Crucial for ensuring intuitive and effective user interactions.
A principle that suggests people are more likely to comply with requests or follow suggestions from authority figures. Important for designing persuasive experiences and understanding user compliance.
Numeronym for the word "Accessibility" (A + 11 letters + Y), designing for ease of use by all people, ensuring equal access to those with disabilities. Crucial for ensuring inclusivity and compliance with accessibility standards.
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.
In AI and machine learning, a prompt that specifies what should be avoided or excluded in the generated output, guiding the system to produce more accurate and relevant results. Crucial for refining AI-generated content by providing clear instructions on undesired elements, improving output quality and relevance.
Fundamental guidelines that inform and shape the design process, ensuring consistency, usability, and effectiveness in product creation. Essential for creating coherent, user-centered designs that align with organizational goals and user needs.
Product Strategy is a framework that outlines how a product will achieve its business goals and satisfy customer needs. Crucial for guiding product development, prioritizing features, and aligning the team around a clear vision.
Minimum Viable Product (MVP) is a version of a product with just enough features to be usable by early customers who can then provide feedback for future product development. Essential for validating product ideas quickly and cost-effectively, allowing teams to learn about customer needs without fully developing the product.
The practice of guiding and inspiring teams to create effective, user-centered design solutions that align with business goals. Crucial for fostering a culture of innovation, collaboration, and excellence in design practices within organizations.
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.
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.
Unique Buying Proposition (UBP) is a statement that highlights the unique benefits and value a product or service offers to customers. Crucial for differentiating a product in the market and attracting customers.
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.
A design philosophy that emphasizes core design principles over rigid adherence to standardized processes. Essential for maintaining creativity and innovation in large-scale, process-driven environments.
Easy, Attractive, Social, and Timely (EAST) is a behavioral insights framework used to influence behavior. Important for designing interventions and user experiences that effectively change behavior.
Minimum Viable Feature (MVF) is the smallest possible version of a feature that delivers value to users and allows for meaningful feedback collection. Crucial for rapid iteration in product development, enabling teams to validate ideas quickly and efficiently while minimizing resource investment.
Moment of Truth (MoT) refers to any instance where a customer interacts with a brand, product, or service in a way that leaves a significant impression. Crucial for identifying key touchpoints in the customer journey and optimizing them to enhance overall user experience and brand perception.
The level of sophistication and integration of design practices within an organization's processes and culture. Essential for assessing and improving the effectiveness of design in driving business value and innovation.
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.
Large Language Model (LLM) is an advanced artificial intelligence system trained on vast amounts of text data to understand and generate human-like text. Essential for natural language processing tasks, content generation, and enhancing human-computer interactions across various applications in product design and development.