Regulating Habit-Forming Technology

Tech developers, like slot machine designers, strive to maximize the user’s “time on device.” They do so by designing habit-forming products— products that draw consciously on the same behavioral design strategies that the casino industry pioneered. The predictable result is that most tech users spend more time on device than they would like, about five hours of phone time a day, while a substantial minority develop life-changing behavioral problems similar to problem gambling. Other countries have begun to regulate habit-forming tech, and American jurisdictions may soon follow suit. Several state legislatures today are considering bills to regulate “loot boxes,” a highly addictive slot-machine- like mechanic that is common in online video games. The Federal Trade Commission has also announced an investigation into the practice. As public concern mounts, it is surprisingly easy to envision consumer regulation extending beyond video games to other types of apps. Just as tobacco regulations might prohibit brightly colored packaging and fruity flavors, a social media regulation might limit the use of red notification badges or “streaks” that reward users for daily use. It is unclear how much of this regulation could survive First Amendment scrutiny; software, unlike other consumer products, is widely understood as a form of protected “expression.” But it is also unclear whether well-drawn laws to combat compulsive technology use would seriously threaten First Amendment values. At a very low cost to the expressive interests of tech companies, these laws may well enhance the quality and efficacy of online speech by mitigating distraction and promoting deliberation

Quantifying Parkinson\u27s Disease Symptoms Using Mobile Devices

Current assessments for evaluating the progression of Parkinson’s Disease are largely qualitative and based on small sets of data obtained from occasional doctor-patient interactions. There is a clinical need to improve the techniques used for mitigating common Parkinson’s Disease symptoms. Available data sets for researching the disease are minimal, hindering advancement toward understanding the underlying causes and effectiveness of treatment and therapies. Mobile devices present an opportunity to continuously monitor Parkinson’s Disease patients and collect important information regarding the severity of symptoms. The evolution of digital technology has opened doors for clinical research to extend beyond the clinic by incorporating complex sensors in commonly used devices. Leveraging these sensors to quantify characteristic Parkinson’s Disease symptoms may drastically improve patient care and the reliability of symptom assessment. The goal of this project is to design and develop a system for measuring and analyzing the cardinal symptoms of Parkinson’s using mobile devices. An application for the iPhone and Apple Watch is developed, utilizing the sensors on the devices to collect data during the performance of motor tasks. Assessments for tremor, bradykinesia, and postural instability are implemented to mimic UPDRS evaluations normally performed by a neurologist. The application connects to a cloud-based server to transfer the collected data for remote access and analysis. Example MatLab analysis demonstrates potential approaches for extracting meaningful data to be used for monitoring the progression of Parkinson’s Disease and the effectiveness of treatment and therapies. High-level verification testing is performed to show general efficacy of the assessment tasks. The system design successfully lays the groundwork for a mobile device-based assessment tool to objectively measure Parkinson’s Disease symptom

NetChoice v. Bonta

BRIEF OF FAIRPLAY AND THE PUBLIC HEALTH ADVOCACY INSTITUTE AS AMICI CURIAE IN SUPPORT OF DEFENDAN