Ubiquitous Sensing and Compensation
The various sensors that you may interact with on a daily basis, such as cameras, microphones, those found in your phone such as an accelerometer for capturing movement, and even biosensors such as those found in smartwatches to monitor heart rate, have significant applications across several domains, from smart healthcare to emotion recognition. To study these applications, it’s often required that researchers have access to a diverse participant pool that interacts with these sensors in controlled environments such as a research lab and in more natural settings outside of the lab. Data collection is therefore a critical part of these evaluations.
We’d like to know more about these data collection procedures from your point of view. We are particularly interested in gathering information about the compensation amounts that potential participants feel is most appropriate for these data collection procedures. With your insight, we hope to provide the research community with new information that will help to structure data collection procedures more appropriately, ensure participants feel valued and appreciated for their support of the research, and provide participants with suitable amounts of compensation that promote compliance to the study’s procedures. We will gather your input via an online survey. It should take no more than 5 minutes to complete.
This study is considered minimal risk and your participation is voluntary. Although there is no compensation for completing the survey, we greatly appreciate your efforts should you decide to participate. You may decline or withdraw from participation at any time without penalty. Although we will collect demographic data such as gender and age, we will not collect personally identifying information.
This research is being conducted by the University of South Florida. This study has been approved by USF IRB Pro# STUDY000019. It is led by Drs. Tempestt Neal and Shaun Canavan, faculty members in the Department of Computer Science and Engineering. If you are a USF student, is 18 years old or older, and would like to participate, please click here.
Credibility and Bias in Online Information
We are seeking individuals 18 years old or older to participate in an online survey to assess if the perception of an article’s credibility is influenced by fact-checking through artificial intelligence and/or professional journalists. Information on the web is in great abundance. However, due to freedom of speech, anonymity, and lack of standardization, there is no clear indication of whether something read on the internet is credible or not. Although this has been a recognized issue for a while, the modern political landscape has brought it to the forefront of our collective conversation. Our specific aims are to (1) determine if providing an AI analysis, journalist analysis, and no analysis of misinformation may affect your perception of credibility of a snippet from a political article and to (2) determine if your prior understanding of AI or demographics affect your trust in AI to judge the credibility of online text.
This study involves an online survey that should take no more than 13 minutes to complete. You will be asked to rate the credibility of four short political articles. This study is considered minimal risk, and your participation is voluntary. You may decline or withdraw from participation at any time without penalty. If you are a student, your decision to or not to participate will not affect your grade or student status. Although we will collect demographic data such as gender and age, we will not collect personally identifying information.
This research is being conducted by the University of South Florida. It is led by Matthew Sumpter (Department of Computer Science and Engineering) with faculty advisor, Dr. Tempestt Neal, (Department of Computer Science and Engineering. This study is being conducted for research purposes. If you are 18 years old or older, and would like to participate, please click here. (IRB Approved Study #STUDY000388)