Design, Human-Computer Interaction
AI is reshaping HCI by enabling more intuitive, personalized experiences.
“AI For Good” Isn’t Good Enough: A Call for Human-Centered AI
In his talk, "AI For Good” Isn’t Good Enough: A Call for Human-Centered AI", Professor James Landay elaborates on his argument for an authentic Human-Centered AI.
In his talk, "AI For Good” Isn’t Good Enough: A Call for Human-Centered AI", Professor James Landay elaborates on his argument for an authentic Human-Centered AI.
Six interdisciplinary research teams received a total of $3 million to pursue groundbreaking ideas in the field of AI.
Six interdisciplinary research teams received a total of $3 million to pursue groundbreaking ideas in the field of AI.
How Culture Shapes What People Want From AI
There is an urgent need to incorporate the perspectives of culturally diverse groups into AI developments. We present a novel conceptual framework for research that aims to expand, reimagine, and reground mainstream visions of AI using independent and interdependent cultural models of the self and the environment. Two survey studies support this framework and provide preliminary evidence that people apply their cultural models when imagining their ideal AI. Compared with European American respondents, Chinese respondents viewed it as less important to control AI and more important to connect with AI, and were more likely to prefer AI with capacities to influence. Reflecting both cultural models, findings from African American respondents resembled both European American and Chinese respondents. We discuss study limitations and future directions and highlight the need to develop culturally responsive and relevant AI to serve a broader segment of the world population.
There is an urgent need to incorporate the perspectives of culturally diverse groups into AI developments. We present a novel conceptual framework for research that aims to expand, reimagine, and reground mainstream visions of AI using independent and interdependent cultural models of the self and the environment. Two survey studies support this framework and provide preliminary evidence that people apply their cultural models when imagining their ideal AI. Compared with European American respondents, Chinese respondents viewed it as less important to control AI and more important to connect with AI, and were more likely to prefer AI with capacities to influence. Reflecting both cultural models, findings from African American respondents resembled both European American and Chinese respondents. We discuss study limitations and future directions and highlight the need to develop culturally responsive and relevant AI to serve a broader segment of the world population.
The AIMI-HAI Partnership Grant is designed to fund new and ambitious ideas that reimagine artificial intelligence in healthcare, using real clinical data sets, with near term clinical applications.
The AIMI-HAI Partnership Grant is designed to fund new and ambitious ideas that reimagine artificial intelligence in healthcare, using real clinical data sets, with near term clinical applications.
The Stanford HAI co-director has blazed a trail by keeping humans at the center of emerging technologies.
The Stanford HAI co-director has blazed a trail by keeping humans at the center of emerging technologies.
All Work Published on Design, Human-Computer Interaction
“AI For Good” Isn’t Good Enough: A Call for Human-Centered AI
In his talk, "AI For Good” Isn’t Good Enough: A Call for Human-Centered AI", Professor James Landay elaborates on his argument for an authentic Human-Centered AI.
“AI For Good” Isn’t Good Enough: A Call for Human-Centered AI
In his talk, "AI For Good” Isn’t Good Enough: A Call for Human-Centered AI", Professor James Landay elaborates on his argument for an authentic Human-Centered AI.
Six interdisciplinary research teams received a total of $3 million to pursue groundbreaking ideas in the field of AI.
Six interdisciplinary research teams received a total of $3 million to pursue groundbreaking ideas in the field of AI.
How Culture Shapes What People Want From AI
There is an urgent need to incorporate the perspectives of culturally diverse groups into AI developments. We present a novel conceptual framework for research that aims to expand, reimagine, and reground mainstream visions of AI using independent and interdependent cultural models of the self and the environment. Two survey studies support this framework and provide preliminary evidence that people apply their cultural models when imagining their ideal AI. Compared with European American respondents, Chinese respondents viewed it as less important to control AI and more important to connect with AI, and were more likely to prefer AI with capacities to influence. Reflecting both cultural models, findings from African American respondents resembled both European American and Chinese respondents. We discuss study limitations and future directions and highlight the need to develop culturally responsive and relevant AI to serve a broader segment of the world population.
There is an urgent need to incorporate the perspectives of culturally diverse groups into AI developments. We present a novel conceptual framework for research that aims to expand, reimagine, and reground mainstream visions of AI using independent and interdependent cultural models of the self and the environment. Two survey studies support this framework and provide preliminary evidence that people apply their cultural models when imagining their ideal AI. Compared with European American respondents, Chinese respondents viewed it as less important to control AI and more important to connect with AI, and were more likely to prefer AI with capacities to influence. Reflecting both cultural models, findings from African American respondents resembled both European American and Chinese respondents. We discuss study limitations and future directions and highlight the need to develop culturally responsive and relevant AI to serve a broader segment of the world population.
The AIMI-HAI Partnership Grant is designed to fund new and ambitious ideas that reimagine artificial intelligence in healthcare, using real clinical data sets, with near term clinical applications.
The AIMI-HAI Partnership Grant is designed to fund new and ambitious ideas that reimagine artificial intelligence in healthcare, using real clinical data sets, with near term clinical applications.
The Stanford HAI co-director has blazed a trail by keeping humans at the center of emerging technologies.
The Stanford HAI co-director has blazed a trail by keeping humans at the center of emerging technologies.