Author Information

Daniel A. MarteFollow

Is this project an undergraduate, graduate, or faculty project?

Undergraduate

group

Authors' Class Standing

(marted@my.erau.edu) Daniel A. Marte , Embry-Riddle Aeronautical University -Graduate Student 2 (WalterN1@my.erau.edu) Nathan Walters , Embry-Riddle Aeronautical University -Graduate Student 3 (adkinse3@my.erau.edu) Evan Adkins, Embry-Riddle Aeronautical University -Graduated 4 (MilnerM1@my.erau.edu) Mattie Milner , Embry-Riddle Aeronautical University -Graduate Student 5 (AnaniaE1@my.erau.edu) Emily Anania , Embry-Riddle Aeronautical University -Graduate Student 6 (RiceS15@erau.edu) Stephen Rice , Embry-Riddle Aeronautical University - Professor 7 (Winte25E@erau.edu) Scott Winter , Embry-Riddle Aeronautical University - Professor

Lead Presenter's Name

Daniel A. Marte

Faculty Mentor Name

Stephen Rice

Abstract

Background and Objectives: Unmanned aerial systems (UAS), also known casually as drones, have changed the ways in which many industries conduct business. One prevalent example would be their use by police organizations (local patrols, SWAT, and etc.) to revolutionize their surveillance capabilities. Many major city police commissioners have stated their interests in welcoming the use of unmanned aerial vehicles (UAV). Past studies have analyzed citizen’s emotions in regard to privacy concerns focusing on the amount of time the drones spent patrolling--either twenty-four hours a day or in mission only conditions. The purpose of this study was to determine what variables predict privacy concerns. In other words, do political affiliations, location, or gender affect a participant’s emotions toward their privacy?

Methods: Two hundred participants were surveyed through Amazon’s Mechanical Turk (MTurk). They were presented with hypothetical scenarios involving police issued UAV patrols occurring near their residence. Following the scenario, they were asked to rate statements from a validated UAV privacy scale and then complete a set of demographic questions that served as potential predictors.

Results
A linear regression analysis revealed two significant predictors. First, females were more likely to express privacy concerns during the UAS missions compared to their male counterparts (B = .31). Second, people who rated themselves are more conservative also expressed more privacy concerns compared to people who rated themselves as more liberal (B = .30).

Conclusion
When conducting UAS missions in public or near housing residences, it is important to take note of the privacy concerns raised by residents and other citizens in the area.These findings reveal that females and conservative-leaning people tend to have more privacy concerns about UAS missions than male, liberal-leaning people.

Keywords: Unmanned aerial systems/vehicles, Mechanical Turk, privacy scale, drones, moderation

Did this research project receive funding support (Spark or Ignite Grants) from the Office of Undergraduate Research?

Yes, Spark Grant

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Privacy Concerns about UAS Missions: A Regression Analysis

Background and Objectives: Unmanned aerial systems (UAS), also known casually as drones, have changed the ways in which many industries conduct business. One prevalent example would be their use by police organizations (local patrols, SWAT, and etc.) to revolutionize their surveillance capabilities. Many major city police commissioners have stated their interests in welcoming the use of unmanned aerial vehicles (UAV). Past studies have analyzed citizen’s emotions in regard to privacy concerns focusing on the amount of time the drones spent patrolling--either twenty-four hours a day or in mission only conditions. The purpose of this study was to determine what variables predict privacy concerns. In other words, do political affiliations, location, or gender affect a participant’s emotions toward their privacy?

Methods: Two hundred participants were surveyed through Amazon’s Mechanical Turk (MTurk). They were presented with hypothetical scenarios involving police issued UAV patrols occurring near their residence. Following the scenario, they were asked to rate statements from a validated UAV privacy scale and then complete a set of demographic questions that served as potential predictors.

Results
A linear regression analysis revealed two significant predictors. First, females were more likely to express privacy concerns during the UAS missions compared to their male counterparts (B = .31). Second, people who rated themselves are more conservative also expressed more privacy concerns compared to people who rated themselves as more liberal (B = .30).

Conclusion
When conducting UAS missions in public or near housing residences, it is important to take note of the privacy concerns raised by residents and other citizens in the area.These findings reveal that females and conservative-leaning people tend to have more privacy concerns about UAS missions than male, liberal-leaning people.

Keywords: Unmanned aerial systems/vehicles, Mechanical Turk, privacy scale, drones, moderation

 

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