Projects 2019

Affect & Facial Recognition in Hiring

AFOG Supported Project
Fellows: Sofia Gutierrez-Dewar, Mehtab Khan, and Joyce Lee

Affective computing is the study and development of systems that can recognize, interpret, process, and simulate human emotion. Powered by artificial intelligence, emerging applications of affect recognition in the workplace raise pressing ethical and regulatory questions: what happens when an automated understanding of human affect enters the real world, in the form of systems that have life-altering consequences? This is particularly pertinent in the realm of workplace surveillance, with no clear answers about how to address privacy, bias, and discrimination problems. As the underlying technologies are generally proprietary and therefore opaque, their impact can only be assessed with a deeper look into how they are designed and implemented. In collaboration with Coworker.org, a nonprofit that helps people organize for improvements in their jobs and workplace, we thus aim to evaluate applications of affect recognition and the potential risks and implications of these technologies.

Algorithmic Intermediation and Workplace Surveillance – Emerging Threats to the Democracy of Work

AFOG Supported Project
Fellows: Eric Harris Bernstein, Julia Hubbell, Nandita Sampath, and Matthew Spring

Advanced analytical software is changing the dynamics between workers and their employers, exacerbating the existing power asymmetry. Combined with AI, technologies like facial recognition, email monitoring, and audio recordings can all be analyzed to infer workers’ emotions and behavior to determine facets of worker productivity or whether an employee is, for example, “threatening.” This technology often reinforces racial and gender bias, and little is known about how the results of these analyses affect managerial decisions like promotions and terminations. Not only is this surveillance a huge loss of privacy for employees, but it may also have a negative impact on their stress levels or ability to perform in the workplace. Our project will investigate the different workplace surveillance technologies on the market and their effects on workers, and then provide potential policy responses to these issues.

Coordinated Entry System Research and Development for a Continuum of Care in Northern California

CLTC & AFOG Supported Project
Fellows: Zoe Kahn, Yuval Barash, Michelle Chen, Mahmoud Hamsho, and Amy Turner

Governments are increasingly using technology to allocate scarce social service resources, like housing services. In collaboration with a Continuum of Care in Northern California, this project will involve using qualitative research methods (i.e. interviews, participatory design, and usability testing) to conduct a needs assessment and system recommendation around “matching” unhoused people to appropriate services. Our goal is to identify matching systems (or design requirements) that suit the needs of diverse housing service providers across the county without compromising the needs and personal information of vulnerable populations. In addition to efficiency, we will consider how systems handle values such as privacy, security, autonomy, dignity, safety, and resiliency.

Engaging Expert Stakeholders about the Future of Menstrual Biosensing Technology

CLTC Supported Project
Fellows: Noura Howell, Sarah Fox, Franchesca Spektor, and Richmond Wong

Networked sensor technologies are increasingly present in daily life. While promising improved health and efficiency, they also introduce far-reaching issues around cybersecurity, privacy, autonomy, and consent that can be difficult to predict or resist. We examine menstrual tracking technologies as a case for understanding the current and near future implications of increasingly pervasive techniques of intimate data collection. These technologies collect sensitive data (e.g., menstrual flow quality, medicine use, sexual activity) and predict period dates and fertility. Last year we reviewed privacy policies of current menstrual tracking applications, which informed our design of speculative near-future technologies exploring surveillance concerns. This year, with continued support, we will engage expert stakeholders of menstrual tracking around these speculative designs to broaden the discussion of cybersecurity, privacy, and fairness concerns. We will also share our research findings with a broad audience to help scaffold the collective reimagination and reconfiguration of intimate biosensing.

Engineering Mindfulness: How the Meditation Technology Industry Shapes Mental Wellbeing

Fellows: Rebecca Jablonsky

This project explores how the meditation technology industry shapes contemporary understandings of mental health and wellbeing. By conducting ethnographic research with creators and users of meditation apps, it will investigate the values embedded into the design of these digital tools. How do creators of meditation apps define and codify metrics for measuring health and wellbeing within their products, through tools like sensors, AI-driven algorithmic interactions, and behavioral design? What does the increasing popularity of meditation apps such as Headspace, Calm, and Insight Timer reflect about what seemingly commonsense concepts such as the self, health, happiness, and the good life have come to mean in the digital age?

Factors affecting Trust among vulnerable populations

CLTC Supported Project
Fellows: Varshine Chandrakanthan and Rajasi Desai

In this project we aim to understand the trust dynamics and the factors affecting trust for vulnerable populations like human rights defenders, activists, journalists who document and upload sensitive media, as well as people who receive this media in order to use it as evidence. We will work to understand the ecosystem in which at-risk populations operate and then discover potential areas where trust plays a pivotal role, finally, we will suggest potential factors that play a pivotal role in shaping trust in applications for at-risk populations.

Moral Stands and Monetized Platforms: The Role of Tech Worker Organizing In Shaping Corporate Moral Language

Special Project Fellow
Fellows: Nataliya Nedzhvetskaya

What happens when a company’s actions diverge from its rhetoric? Grounding my research in the framework of moral language and the digital economy, I seek to understand how language is understood, co-opted, and contested in present-day tech worker organizing efforts. To recruit an increasingly sought-after pool of talent, tech companies compete for workers in terms of moral justifications as well as economic incentives, presenting a case for how their work contributes towards the greater social good. Reminiscent of the twentieth-century labor movement, tech worker organizing is an attempt to challenge the limitations of capitalism by extending their leverage outside of company boundaries and past the initial hiring day. The primary focus of my research will be to understand how organizers use language to frame their efforts and to compare and contrast their choice of language against that of the tech companies at which they are organizing.

Public-Private Data Relationships: Understanding the Everyday Processes

CLTC Supported Project
Fellows: Yan Fang

Over the past two decades, Internet technology companies have developed products and services that collect large amounts of information about people. Government agencies at the federal, state, and local levels often seek these user data for law enforcement purposes, yet such data are increasingly held by commercial firms. How do firms’ collection of user data affect law enforcement? My project explores this question through interviews with staff at law enforcement agencies and at Internet technology companies.

Re-imagining Password Management for Low-Technology Proficiency Users

CLTC Supported Project
Fellows: Ching-Yi Lin, Ayo Animashaun, Amy Huang, and Jing Wu

Passwords and login information control access to some of the most important aspects of life, such as banking and finances, medical services, and other sensitive personal information. According to Pew Research, 44% of online adults ages 30 to 64 say they have a hard time keeping track of their passwords. These “password challenged” internet users are more likely to keep track of their passwords by writing them down on a piece of paper, saving them in a digital note or by saving them in their web browser – all things that are considered less desirable practices among cybersecurity experts. We hope to design a solution that constructively engages competing values of security and ergonomics as it relates to the development of password management systems. We will integrate concepts from areas such user experience design, privacy & security, and behavioral economics to develop a tool that achieves balance among these competing values. Our objective is to improve password generation habits with a tool that strengthens digital security and reduces the potential for breaches and privacy harms.

The state of smartphone-based observational studies: ethical and practical considerations in informed consent and health data disclosure

Fellows: Madelena Ng

In the precision medicine era, clinical research increasingly needs “big data” to gain finer insights into the prediction and prevention of disease. Today, a person’s health profile extends beyond the clinic with the continuous monitoring capabilities of mobile health wearables, sensors, apps, Internet of Things (IoT), etcetera. Researchers are developing smartphone-based observational studies as a way to collect these disparate streams of data from people. Many of these studies rely on the Apple ResearchKit framework to guide the development of their informed consent, study activity and task, and data collection workflows. However, whether the evolving risks and benefits associated with continuous health data collection are adequately conveyed to research participants through the current framework remains unclear. This study aims to achieve a more nuanced understanding of the ethical, practical, and sociotechnical influences that govern the course of these studies and pinpoint areas for improvement.

Why can I search for houses in foreclosure? Investigating the Embedded Values of Online Real Estate Platforms

Fellows: Elizabeth Resor and Sofia Lopez

Online real estate tools like Trulia, Zillow, and Redfin list houses in foreclosure and pre-foreclosure. Though the most basic foreclosure and pre-foreclosure information is public record, we argue that the data presented on these real estate websites are fundamentally different from the “public” data and that the act of including them (along with other troubling datasets like school “scores” and crime statistics) is value-laden. Our research plan is two-fold. We will “follow the data,” attempting to trace the multiple sources used to create the final presentation of foreclosure on these real estate websites. At the same time we will attempt to triangulate the effects of listing foreclosures by consulting with scholars of planning, housing law, real estate taxes (some foreclosures are caused by real estate taxes not mortgage payments), and housing economics. The sites for the research will be the cities in which the research team members live – the East Bay Area and San Antonio.

Banner Photo Credit: “UC Berkeley South Hall” by I School IMSA is licensed under CC BY 2.0