[SOON: AI+PSYCHOLOGY DESIGN SPRINT]
AI+Psychology
AI+Psychology
AI+Psychology
AI+Psychology
Master AI Interface & Experience Design
with the depth of Psychology
Design AI Interfaces with
Human Understanding:
Psychology-First Digital Experiences
AI+HCI Glossary
[5]
Algorithmic Aversion
The tendency for humans to prefer human judgment over algorithmic recommendations, even when the algorithm demonstrably outperforms humans.
[4]
Explainable AI (XAI)
Design approaches that make AI systems' decisions and behaviors understandable to users, addressing the "black box" problem of complex algorithms.
[3]
Trust Calibration
The process of developing appropriate levels of user trust in AI systems—neither overtrusting nor undertrusting—based on the system's actual capabilities and limitations.
[2]
Cognitive Load
The mental effort required to process information during human-AI interaction, which designers must carefully manage to prevent user fatigue and frustration.
[1]
Anthropomorphism
The attribution of human characteristics, behaviors, or emotions to non-human entities, particularly AI systems, affecting user perception and trust.
[6]
Social Presence
The perception that an AI system is present as a social entity during interaction, influencing user engagement and satisfaction.
[7]
Affective Computing
The development of systems that can recognize, interpret, process, and simulate human emotions to create more intuitive human-AI interactions.
[8]
Mental Models
The internal representations users develop to understand and predict how an AI system works, which significantly influence their interactions.
[9]
Transparency
The degree to which an AI system's operation, data usage, and decision-making processes are visible and understandable to users.
[10]
Professional Identity Threat
The perception that AI systems might undermine one's professional role, expertise, or value, potentially creating resistance to adoption.
AI+HCI Glossary
[5]
Algorithmic Aversion
The tendency for humans to prefer human judgment over algorithmic recommendations, even when the algorithm demonstrably outperforms humans.
[4]
Explainable AI (XAI)
Design approaches that make AI systems' decisions and behaviors understandable to users, addressing the "black box" problem of complex algorithms.
[3]
Trust Calibration
The process of developing appropriate levels of user trust in AI systems—neither overtrusting nor undertrusting—based on the system's actual capabilities and limitations.
[2]
Cognitive Load
The mental effort required to process information during human-AI interaction, which designers must carefully manage to prevent user fatigue and frustration.
[1]
Anthropomorphism
The attribution of human characteristics, behaviors, or emotions to non-human entities, particularly AI systems, affecting user perception and trust.
[6]
Social Presence
The perception that an AI system is present as a social entity during interaction, influencing user engagement and satisfaction.
[7]
Affective Computing
The development of systems that can recognize, interpret, process, and simulate human emotions to create more intuitive human-AI interactions.
[8]
Mental Models
The internal representations users develop to understand and predict how an AI system works, which significantly influence their interactions.
[9]
Transparency
The degree to which an AI system's operation, data usage, and decision-making processes are visible and understandable to users.
[10]
Professional Identity Threat
The perception that AI systems might undermine one's professional role, expertise, or value, potentially creating resistance to adoption.
Psychological Dimensions
of Human-AI Interaction
[1]
Cognitive Processing
Mental model formation
Information processing capacity
Decision-making patterns
Learning and adaptation
[2]
Emotional Responses
Trust development
Anxiety and resistance
Emotional attachment
User satisfaction
[3]
Behavioral Patterns
Usage Patterns
Interaction Strategies
Reliance and Delegation Behavior
Adaptation and Co-evolution
Feedback and Correction
Collaboration Dynamics
Research Library
Dear Oliver,
I hope you're doing well! I wanted to share my excitement about creating websites with Framer's intuitive no-code platform.
Let's explore it together!Looking forward to discussing more about our design adventures!
Confirmation bias in AI-assisted decision-making: AI triage recommendations congruent with expert judgments increase psychologist trust and recommendation acceptance
The role of socio-emotional attributes in enhancing human-AI collaboration
Beyond Isolation: Towards an Interactionist Perspective on Human Cognitive Bias and AI Bias
Dear Oliver,
I hope you're doing well! I wanted to share my excitement about creating websites with Framer's intuitive no-code platform.
Let's explore it together!Looking forward to discussing more about our design adventures!
Confirmation bias in AI-assisted decision-making: AI triage recommendations congruent with expert judgments increase psychologist trust and recommendation acceptance
The role of socio-emotional attributes in enhancing human-AI collaboration
Beyond Isolation: Towards an Interactionist Perspective on Human Cognitive Bias and AI Bias
Research Library
Dear Oliver,
I hope you're doing well! I wanted to share my excitement about creating websites with Framer's intuitive no-code platform.
Let's explore it together!Looking forward to discussing more about our design adventures!