09 Terms to Remember
Adaptive Interfaces: User interfaces that dynamically adjust based on user behavior, preferences, and performance to enhance usability and reduce cognitive load.
Algorithmic Bias: Systematic and repeatable errors in a computer system that create unfair outcomes, such as favoring one group over another.
Artificial Intelligence (AI): The simulation of human intelligence in machines programmed to think and learn like humans.
Automation: The use of technology to perform tasks with minimal human intervention.
Cognitive Ergonomics: The subfield of human factors dealing with mental processes such as perception, memory, and reasoning as they affect interactions with systems.
Cognitive Workload: The amount of mental effort required to perform a task.
Controllability: The degree to which humans can influence or direct the actions of an AI system.
Emotion-Aware Systems: AI systems that use various sensors and analysis techniques to detect and respond to users’ emotional states.
Ergonomics: The scientific discipline and profession concerned with the understanding of interactions among humans and other elements of a system.
Explainable AI (XAI): AI systems designed to make their decision-making processes transparent and understandable to human users.
Generative AI: A type of artificial intelligence that can produce new content, such as text, images, or audio, based on patterns learned from existing data.
Human Factors: An interdisciplinary science applying knowledge about human capabilities and limitations to system design.
Human-AI Collaboration: The process of humans and AI systems working together, leveraging their respective strengths.
Human-Centered AI: An approach to AI design and implementation that prioritizes human needs, capabilities, and well-being.
Human-Computer Interaction (HCI): The study of how people interact with computers and the design of user interfaces.
Job Characteristics Model: A framework identifying five core job dimensions (skill variety, task identity, task significance, autonomy, and feedback) that contribute to meaningful work.
Job Displacement Anxiety: Fear or stress related to the potential loss of one’s job due to automation or AI.
Job Redesign: The process of altering job tasks, responsibilities, and workflows, often influenced by the integration of AI.
Machine Learning (ML): A type of artificial intelligence that allows systems to learn from data, identify patterns, and make decisions with minimal human intervention.
Natural Language Processing (NLP): A field of artificial intelligence that enables computers to understand, interpret, and generate human language.
Organizational Ergonomics: The subfield of ergonomics concerned with the optimization of sociotechnical systems, including organizational structures, policies, and processes.
Physical Ergonomics: The subfield of human factors focusing on the human body’s interaction with physical tools and workspaces.
Predictive Analytics: The use of statistical and AI techniques to forecast future outcomes or trends based on historical data.
Process Automation: The use of software and technology to automate complex business processes and functions.
Psychological Safety: A belief that one will not be punished or humiliated for speaking up with ideas, questions, concerns, or mistakes.
Reskilling: The process of learning new skills to perform a different job or adapt to changes in an existing job.
Sociotechnical Systems Theory: A theory that advocates for the joint optimization of both the social (human) and technical (technology) aspects of a work system to achieve overall effectiveness.
Transparency: The degree to which the internal workings and decision-making processes of an AI system are understandable to humans.
Usability: The ease with which users can learn to use a system, its efficiency, memorability, error rate, and user satisfaction.
Vigilance: The ability to maintain focused attention and detect infrequent or subtle changes over prolonged periods.
Work Design: The application of sociotechnical systems principles and techniques to the humanization of work, concerned with the content and organization of workers’ tasks, activities, relationships, and responsibilities.
Workplace Dynamics: The interactions and relationships among individuals and groups within a work environment, influenced by AI.