Guess the Data: Data Work to Understand How People Make Sense of and Use Simple Sensor Data from Homes

Abstract: Simple smart home sensors, e.g. for temperature or light, increasingly collect seemingly inconspicuous data. Prior work has shown that human sensemaking of such sensor data can reveal domestic activities. Such sensemaking presents an opportunity to empower people to understand the implications of simple smart home sensors. To investigate, we developed and field-tested the Guess the Data method, which enabled people to use and make sense of live data from their homes and to collectively interpret and reflect on anonymized data from the homes in our study. Our findings show how participants reconstruct behavior, both individually and collectively, expose the sensitive personal data of others, and use sensor data as evidence and for lateral surveillance within the household. We discuss the potential of our method as a participatory HCI method for investigating design of the IoT and implications created by doing data work on home sensors.

26/04/2020

Awareness, Understanding, and Action: A Conceptual Framework of User Experiences and Expectations about Indoor Air Quality Visualizations

Yi-Shyuan Chiang, Ruei-Che Chang, Yi-Lin Chuang and
Shih-Ya Chou, Hao-Ping Lee, I-Ju Lin, Jian-Hua Jiang Chen, Yung-Ju Chang

voice activated personal assistants, interaction design, speed dating, conversational agents, social robots, embodied agents

10:19

03/05/2021

SuPEr-SAM: Using the Supervision Signal From a Pose Estimator to Train a Spatial Attention Module for Personal Protective Equipment Recognition

Adrian Sandru, Georgian-Emilian Duta, Mariana-Iuliana Georgescu, Radu Tudor Ionescu

Keywords Paper

4:52

07/08/2020

Do Privacy and Security Matter to Everyone? Quantifying and Clustering User-Centric Considerations About Smart Home Device Adoption

adversarial network, neural networks, anomaly detection, unsupervised learning, supervision, autoencoders, multivariate time series

12:56

16/11/2020

Integrating Egocentric Localization for More Realistic Point-Goal Navigation Agents

Samyak Datta, Oleksandr Maksymets, Judy Hoffman and
Stefan Lee, Dhruv Batra Georgia Tech &, Facebook AI Research, Devi Parikh Georgia Tech &, Facebook AI Research

3d human behavior analysis, privacy preserving machine learning, multimodal data, depth imaging, thermal imaging, 3d object detection, tracking

2:57

25/04/2020

Broadening Exposure to Socio-Political Opinions via a Pushy Smart Home Device

Tom Feltwell, Gavin Wood, Phillip Brooker and
Scarlett Rowland, Eric Baumer, Kiel Long, John Vines, Julie Barnett, Shaun Lawson

Keywords Paper

filter bubble, echo chamber, selective exposure, viewpoint diversity, smart home technology, socio-political discussion, pushy device, nolan chart

15:05

06/12/2021

Sina Mohseni, Fan Yang, Shiva Pentyala and
Mengnan Du, Yi Liu, Nic Lupfer, Xia Hu, Shuiwang Ji, Eric Ragan

Keywords Paper

Qualitative and quantitative studies of social media, Credibility of online content, Trust, reputation, recommendation systems, Human computer interaction, social media tools, navigation and visualization

8:01

14/09/2020