Citizen Technologist

The CTSP Blog

Symposium: “Governing Machines – Defining and Enforcing Public Policy Values in AI Systems”

CTSP is proud to be a co-sponsor of  the 23rd Annual BCLT/BTLJ Symposium: Governing Machines: Defining and Enforcing Public Policy Values in AI Systems

Algorithms that analyze data, predict outcomes, suggest solutions, and make decisions are increasingly embedded into everyday life. Machines automate content filtering, drive cars and fly planes, trade stocks, evaluate resumes, assist with medical diagnostics, and contribute to government decision-making. Given the growing role of artificial intelligence and machine learning in society, how should we define and enforce traditional legal obligations of privacy, non-discrimination, due process, liability, professional responsibility, and reasonable care?

This symposium will convene scholars and practitioners from law, policy, ethics, computer science, medicine, and social science to consider what roles we should allow machines to play and how to govern them in support of public policy goals.

Co-sponsored by: CTSP, the Center for Long-Term Cybersecurity, and the Algorithmic Fairness and Opacity Working Group (AFOG) at UC Berkeley.

Bonus!

Two 2017 CTSP fellows will be panelists:

  • Amit Elazari on “Trust but Verify – Validating and Defending Against Machine Decisions”
  • Uri Hacohen on “Machines of Manipulation”

Using Crowdsourcing to address Disparities in Police Reported Data: Addressing Challenges in Technology and Community Engagement

This is a project update from a CTSP project from 2017: Assessing Race and Income Disparities in Crowdsourced Safety Data Collection (with Kate BeckAditya Medury, and Jesus M. Barajas)

Project Update

This work has led to the development of Street Story, a community engagement tool that collects street safety information from the public, through UC Berkeley SafeTREC.

The tool collects qualitative and quantitative information, and then creates maps and tables that can be publicly viewed and downloaded. The Street Story program aims to collect information that can create a fuller picture of transportation safety issues, and make community-provided information publicly accessible.

 

The Problem

Low-income groups, people with disabilities, seniors and racial minorities are at higher risk of being injured while walking and biking, but experts have limited information on what these groups need to reduce these disparities. Transportation agencies typically rely on statistics about transportation crashes aggregated from police reports to decide where to make safety improvements. However, police-reported data is limited in a number of ways. First, crashes involving pedestrians or cyclists are significantly under-reported to police, with reports finding that up to 60% of pedestrian and bicycle crashes go unreported. Second, some demographic groups, including low-income groups, people of color and undocumented immigrants, have histories of contentious relationships with police. Therefore, they may be less likely to report crashes to the police when they do occur. Third, crash data doesn’t include locations where near–misses have happened, or locations where individuals feel unsafe but an issue has not yet happened. In other words, the data allow professionals to react to safety issues, but don’t necessarily allow them to be proactive about them.

One solution to improve and augment the data agencies use to make decisions and allocate resources is to provide a way for people to report transportation safety issues themselves. Some public agencies and private firms are developing apps and websites whether people can report issues for this purpose. But one concern is that the people who are likely to use these crowdsourcing platforms are those who have access to smart phones or the internet and who trust that government agencies with use the data to make changes, biasing the data toward the needs of these privileged groups.

Our Initial Research Plan

We chose to examine whether crowdsourced traffic safety data reflected similar patterns of underreporting and potential bias as police-reported safety data. To do this, we created an online mapping tool that people could use to report traffic crashes, near-misses and general safety issues. We planned to work with a city to release this tool to and collected data from the general public, then work directly with a historically marginalized community, under-represented in police-reported data, to target data collection in a high-need neighborhood. We planned to reduce barriers to entry for this community, including meeting the participants in person to explain the tool, providing them with in-person and online training, providing participants with cell phones, and compensating their data plans for the month. By crowdsourcing data from the general public and from this specific community, we planned to analyze whether there were any differences in the types of information reported by different demographics.

This plan seemed to work well with the research question and with community engagement best practices. However, we came up against a number of challenges with our research plan. Although many municipal agencies and community organizations found the work we were doing interesting and were working to address similar transportation safety issues we were focusing on, many organizations and agencies seemed daunted by the prospect of using technology to address underlying issues of under-reporting. Finally, we found that a year was not enough time to build trusting relationships with the organizations and agencies we had hoped to work with. Nevertheless, we were able to release a web-based mapping tool to collect some crowdsourced safety data from the public.

Changing our Research Plan

To better understand how more well-integrated digital crowdsourcing platforms perform, we pivoted our research project to explore how different neighborhoods engage with government platforms to report non-emergency service needs. We assumed some of these non-emergency services would mirror the negative perceptions of bicycle and pedestrian safety we were interested in collecting via our crowdsourcing safety platform. The City of Oakland relies on SeeClickFix, a smartphone app, to allow residents to request service for several types of issues: infrastructure issues, such as potholes, damaged sidewalks, or malfunctioning traffic signals; and non-infrastructure issues such as illegal dumping or graffiti. The city also provides phone, web, and email-based platforms for reporting the same types of service requests. These alternative platforms are collectively known as 311 services. We looked at 45,744 SeeClickFix-reports and 35,271 311-reports made between January 2013 and May 2016. We classified Oakland neighborhoods by status as community of concern. In the city of Oakland, 69 neighborhoods meet the definition for communities of concern, while 43 do not. Because we did not have data on the characteristics of each person reporting a service request, we made the assumption that people reporting requests also lived in the neighborhood where the request was needed.

How did communities of concern interact with the SeeClickFix and 311 platforms to report service needs? Our analysis highlighted two main takeaways. First, we found that communities of concern were more engaged in reporting than other communities, but had different reporting dynamics based on the type of issue they were reporting. About 70 percent of service issues came from communities of concern, even though they represent only about 60 percent of the communities in Oakland. They were nearly twice as likely to use SeeClickFix than to report via the 311 platforms overall, but only for non-infrastructure issues. Second, we found that even though communities of concern were more engaged, the level of engagement was not equal for everyone in those communities. For example, neighborhoods with higher proportions of limited-English proficient households were less likely to report any type of incident by 311 or SeeClickFix.

Preliminary Findings from Crowdsourcing Transportation Safety Data

We deployed the online tool in August 2017. The crowdsourcing platform was aimed at collecting transportation safety-related concerns pertaining to pedestrian and bicycle crashes, near misses, perceptions of safety, and incidents of crime while walking and bicycling in the Bay Area. We disseminated the link to the crowdsourcing platform primarily through Twitter and some email lists. . Examples of organizations who were contacted through Twitter-based outreach and also subsequently interacted with the tweet (through likes and retweets) include Transform Oakland, Silicon Valley Bike Coalition, Walk Bike Livermore, California Walks, Streetsblog CA, and Oakland Built. By December 2017, we had received 290 responses from 105 respondents. Half of the responses corresponded to perceptions of traffic safety concerns (“I feel unsafe walking/cycling here”), while 34% corresponded to near misses (“I almost got into a crash but avoided it”). In comparison, 12% of responses reported an actual pedestrian or bicycle crash, and 4% of incidents reported a crime while walking or bicycling. The sample size of the responses is too small to report any statistical differences.

Figure 1 shows the spatial patterns of the responses in the Bay Area aggregated to census tracts. Most of the responses were concentrated in Oakland and Berkeley. Oakland was specifically targeted as part of the outreach efforts since it has significant income and racial/ethnic diversity.

Figure 1 Spatial Distribution of the Crowdsourcing Survey Responses

Figure 1 Spatial Distribution of the Crowdsourcing Survey Responses

 

In order to assess the disparities in the crowdsourced data collection, we compared responses between census tracts that are classified as communities of concern or not. A community of concern (COC), as defined by the Metropolitan Transportation Commission, a regional planning agency, is a census tract that ranks highly on several markers of marginalization, including proportion of racial minorities, low-income households, limited-English speakers, and households without vehicles, among others.

Table 1 shows the comparison between the census tracts that received at least one crowdsourcing survey response. The average number of responses received in COCs versus non-COCs across the entire Bay Area were similar and statistically indistinguishable. However, when focusing on Oakland-based tracts, the results reveal that average number of crowdsourced responses in non-COCs were statistically higher. To assess how the trends of self-reported pedestrian/cyclist concerns compare with police-reported crashes, an assessment of pedestrian and bicycle-related police-reported crashes (from 2013-2016) shows that more police-reported pedestrian/bicycle crashes were observed on an average in COCs across the Bay Area as well as in Oakland. The difference in trends observed in the crowdsourced concerns and police-reported crashes suggest that either walking/cycling concerns are greater in non-COCs (thus underrepresented in police crashes), or that participation from among COCs is relatively underrepresented.

Table 1 Comparison of crowdsourced concerns and police-reported pedestrian/bicycle crashes in census tracts that received at least 1 response

Table 1 Comparison of crowdsourced concerns and police-reported pedestrian/bicycle crashes in census tracts that received at least 1 response

Table 2 compares the self-reported income and race/ethnicity characteristics of the respondents with the locations where the responses were reported. For reference purposes, Bay Area’s median household income in 2015 was estimated to be $85,000 (Source: http://www.vitalsigns.mtc.ca.gov/income), and Bay Area’s population was estimated to be 58% White, per the 2010 Census, (Source: http://www.bayareacensus.ca.gov/bayarea.htm).

Table 2 Distribution of all Bay Area responses based on the location of response and the self-reported income and race/ethnicity of respondents

The results reveal that White, medium-to-high income respondents were observed to report more walking/cycling -related safety issues in our survey, and more so in non-COCs. This trend is also consistent with the definition of COCs, which tend to have a higher representation of low-income people and people of color. However, if digital crowdsourcing without widespread community outreach is more likely to attract responses from medium-to-high income groups, and more importantly, if they only live, work, or play in a small portion of the region being investigated, the aggregated results will reflect a biased picture of a region’s transportation safety concerns. Thus, while the scalability of digital crowdsourcing provides an opportunity for capturing underrepresented transportation concerns, it may require greater collaboration with low-income, diverse neighborhoods to ensure uniform adoption of the platform.

Lessons Learned

From our attempts to work directly with community groups and agencies and our subsequent decision to change our research focus, we learned a number of lessons:

  1. Develop a research plan in partnership with communities and agencies. This would have allowed us to ensure that we began with a research plan in which community groups and agencies were better able to partner with us on, and this would have ensured that the partners were on board the topic of interest and the methods we hoped to use.
  2. Recognize the time it takes to build relationships. We found that building relationships with agencies and communities was more time intensive and took longer that we had hoped. These groups often have limitations on the time they can dedicate to unfunded projects. Next time, we should plan for this in our initial research plan.
  3. Use existing data sources to supplement research. We found that using See-Click-Fix and 311 data was a way to collect and analyze information to add context to our research question. Although the data did not have all demographic information we had hoped to analyze, this data source added additional context to the data we collected.
  4. Speak in a language that the general public understands. We found that when we used the term self-reporting, rather than crowdsourcing, when talking to potential partners and to members of the public, these individuals were more willing to consider the use of technology to collect information on safety issues from the public as legitimate. Using vocabulary and phrasing that people are familiar with is crucial when attempting to use technology to benefit the social good.

CTSP Alumni Updates

We’re thrilled to highlight some recent updates from our fellows:

Gracen Brilmyer, now a PhD student at UCLA, has published a single authored work in one of the leading journals in archival studies, Archival Science: “Archival Assemblages: Applying Disability Studies’ Political/Relational Model to Archival Description” and presented their work on archives, disability, and justice at a number of events over the past two years, including The Archival Education and Research Initiative (AERI), the Allied Media Conference, the International Communications Association (ICA) Preconference, Disability as Spectacle, and their research will be presented at the upcoming Community Informatics Research Network (CIRN).

CTSP Funded Project 2016: Vision Archive


Originating in the 2017 project “Assessing Race and Income Disparities in Crowdsourced Safety Data Collection” done by Fellows Kate Beck, Aditya Medury, and Jesus Barajas, the Safe Transportation and Research Center will launch a new project, Street Story, in October 2018. Street Story is an online platform that allows community groups and agencies to collect community input about transportation collisions, near-misses, general hazards and safe locations to travel. The platform will be available throughout California and is funded through the California Office of Traffic Safety.

CTSP Funded Project 2017: Assessing Race and Income Disparities in Crowdsourced Safety Data Collection


Fellow Roel Dobbe has begun a postdoctoral scholar position at the new AI Now Institute. Inspired by his 2018 CTSP project, he has co-authored a position paper with Sarah Dean, Tom Gilbert and Nitin Kohli titled A Broader View on Bias in Automated Decision-Making: Reflecting on Epistemology and Dynamics.

CTSP Funded Project 2018: Unpacking the Black Box of Machine Learning Processes


We are also looking forward to a CTSP Fellow filled Computer Supported Cooperative Work conference in November this year! CTSP affiliated papers include:

We also look forward to seeing CTSP affiliates presenting other work, including 2018 Fellows Richmond Wong, Noura Howell, Sarah Fox, and more!

 

October 25th: Digital Security Crash Course

Thursday, October 25, 5-7pm, followed by reception

UC Berkeley, South Hall Room 210

Open to the public!

RSVP is required.

Understanding how to protect your personal digital security is more important than ever. Confused about two factor authentication options? Which messaging app is the most secure? What happens if you forget your password manager password, or lose the phone you use for 2 factor authentication? How do you keep your private material from being shared or stolen? And how do you help your friends and family consider the potential dangers and work to prevent harm, especially given increased threats to vulnerable communities and unprecedented data breaches?

Whether you are concerned about snooping family and friends, bullies and exes who are out to hack and harass you, thieves who want to impersonate you and steal your funds, or government and corporate spying, we can help you with this fun, straightforward training in how to protect your information and communications.

Join us for a couple hours of discussion and hands-on set up. We’ll go over various scenarios you might want to protect against, talk about good tools and best practices, and explore trade offs between usability and security. This training is designed for people at all levels of expertise, and those who want both personal and professional digital security protection.

Refreshments and hardware keys provided! Bring your laptop or other digital device. Take home a hardware key and better digital security practices.

This crash course is sponsored by the Center for Technology, Society & Policy and generously funded by the Charles Koch Foundation. Jessy Irwin will be our facilitator and guide. Jessy is Head of Security at Tendermint, where she excels at translating complex cybersecurity problems into relatable terms, and is responsible for developing, maintaining and delivering comprehensive security strategy that supports and enables the needs of her organization and its people. Prior to her role at Tendermint, she worked to solve security obstacles for non-expert users as a strategic advisor, security executive and former Security Empress at 1Password. She regularly writes and presents about human-centric security, and believes that people should not have to become experts in technology, security or privacy to be safe online.

RSVP here!

Backstage Decisions, Front-stage Experts: Interviewing Genome-Editing Scientists

by Santiago Molina and Gordon PherriboCTSP Fellows

This is the first in a series of posts on the project “Democratizing” Technology: Expertise and Innovation in Genetic Engineering

When we think about who is making decisions that will impact the future health and wellbeing of society, one would hope that these individuals would wield their expertise in a way that addresses the social and economic issues affecting our communities. Scientists often fill this role: for example, an ecologist advising a state environmental committee on river water redistribution [1], a geologist consulting for an architectural team building a skyscraper [2], an oncologist discussing the best treatment options based on the patient’s diagnosis and values [3] or an economist brought in by a city government to help develop a strategy for allocating grants to elementary schools. Part of the general contract between technical experts and their democracies is that they inform relevant actors so that decisions are made with the strongest possible factual basis.

The three examples above describe scientists going outside of the boundaries of their disciplines to present for people outside of the scientific community “on stage” [4]. But what about decisions made by scientists behind the scenes about new technologies that could affect more than daily laboratory life? In the 1970s, genetic engineers used their technical expertise to make a call about an exciting new technology, recombinant DNA (rDNA). This technology allowed scientists to mix and add DNA from different organisms; later giving rise to engineered bacteria that could produce insulin and eventually transgenic crops. The expert decision making process and outcome, in this case, had little to do with the possibility of commercializing biotechnology or the economic impacts of GMO seed monopolies. This happened before the patenting of whole biological organisms [5], and the use of rDNA in plants in 1982. Instead, the emerging issues surrounding rDNA were dealt with as a technical issue of containment. Researchers wanted to ensure that anything tinkered with genetically stayed not just inside the lab, but inside specially marked and isolated rooms in the lab, eventually given rise to well-established institution of biosafety. A technical fix, for a technical issue.

Today, scientists are similarly engaged in a process of expert decision making around another exciting new technology, the CRISPR-Cas9 system. This technology allows scientists to make highly specific changes, “edits”, to the DNA of virtually any organism. Following the original publication that showed that CRISPR-Cas9 could be used to modify DNA in a “programmable” way, scientists have developed the system into a laboratory toolbox and laboratories across the life sciences are using it to tinker away at bacteria, butterflies, corn, frogs, fruit flies, human liver cells, nematodes, and many other organisms. Maybe because most people do not have strong feelings about nematodes, most of the attention in both popular news coverage and in expert circles about this technology has had to do with whether modifications that could affect human offspring (i.e. germline editing) are moral.  

We have been interviewing faculty members directly engaged in these critical conversations about the potential benefits and risks of new genome editing technologies. As we continue to analyze these interviews, we want to better understand the nature of these backstage conversations and learn how the experiences and professional development activities of these expects influenced their decision-making. In subsequent posts we’ll be sharing some of our findings from these interviews, which so far have highlighted the role of a wide range of technical experiences and skills for the individuals engaged in these discussions, the strength of personal social connections and reputation in getting you a seat at the table and the dynamic nature of expert decision making.

[1]  Scoville, C. (2017). “We Need Social Scientists!” The Allure and Assumptions of Economistic Optimization in Applied Environmental Science. Science as Culture, 26(4), 468-480.

[2] Wildermuth and Dineen (2017) “How ready will Bay Area be for next Quake?” SF Chronicle. Available online at: https://www.sfchronicle.com/news/article/How-ready-will-Bay-Area-be-for-next-big-quake-12216401.php

[3] Sprangers, M. A., & Aaronson, N. K. (1992). The role of health care providers and significant others in evaluating the quality of life of patients with chronic disease: a review. Journal of clinical epidemiology, 45(7), 743-760.

[4] Hilgartner, S. (2000). Science on stage: Expert advice as public drama. Stanford University Press.

[5] Diamond v Chakrabarty was in 1980, upheld first whole-scale organism patent (bacterium that could digest crude oil).

Standing up for truth in the age of disinformation

Professor Deirdre K. Mulligan and PhD student (and CTSP Co-Director) Daniel Griffin have an op-ed in The Guardian considering how Google might consider its human rights obligations in the face of state censorship demands: If Google goes to China, will it tell the truth about Tiananmen Square?

The op-ed advances a line of argument developed in a recent article of theirs in the Georgetown Law Technology Review: “Rescripting Search to Respect the Right to Truth”

Social Impact Un-Pitch Day 2018

On Thursday, October 4th at 5:30pm the Center for Technology, Society & Policy (CTSP) and the School of Information’s Information Management Student Association (IMSA) are co-hosting their third annual Social Impact Un-Pitch Day!

Join CTSP and IMSA to brainstorm ideas for projects that address the challenges of technology, society, and policy. We welcome students, community organizations, local municipal partners, faculty, and campus initiatives to discuss discrete problems that project teams can take on over the course of this academic year. Teams will be encouraged to apply to CTSP to fund their projects.

Location: Room 202, in South Hall.

RSVP here!

Agenda

  • 5:40 Introductions from IMSA and CTSP
  • 5:45 Example Projects
  • 5:50 Sharing Un-Pitches

We’ve increased the time for Un-Pitches! (Still 3-minutes per Un-Pitch)

  • 6:40 Mixer (with snacks and refreshments)

 

Un-Pitches

Un-Pitches are meant to be informal and brief introductions of yourself, your idea, or your organization’s problem situation. Un-pitches can include designing technology, research, policy recommendations, and more. Students and social impact representatives will be given 3 minutes to present their Un-Pitch. In order to un-pitch, please share 1-3 slides, as PDF and/or a less than 500-word description—at this email: ctsp@nullberkeley.edu. You can share slides and/or description of your ideas even if you aren’t able to attend. Deadline to share materials: midnight October 1st, 2018.

Funding Opportunities

The next application round for fellows will open in November. CTSP’s fellowship program will provide small grants to individuals and small teams of fellows for 2019. CTSP also has a recurring offer of small project support.

Prior Projects & Collaborations

Here are several examples of projects that members of the I School community have pursued as MIMS final projects or CTSP Fellow projects (see more projects from 2016, 2017, and 2018).

 

Skills & Interests of Students

The above projects demonstrate a range of interests and skills of the I School community. Students here and more broadly on the UC Berkeley campus are interested and skilled in all aspects of where information and technology meets people—from design and data science, to user research and information policy.

RSVP here!

August 30th, 5:30pm: Habeas Data Panel Discussion

Location: South Hall Rm 202

Time: 5:30-7pm (followed by light refreshments)

CTSP’s first event of the semester!

Co-Sponsored with the Center for Long-Term Cybersecurity

Please join us for a panel discussion featuring award-winning tech reporter Cyrus Farivar, whose new book, Habeas Data, explores how the explosive growth of surveillance technology has outpaced our understanding of the ethics, mores, and laws of privacy. Habeas Data explores ten historic court decisions that defined our privacy rights and matches them against the capabilities of modern technology. Mitch Kapor, co-founder, Electronic Frontier Foundation, said the book was “Essential reading for anyone concerned with how technology has overrun privacy.”

The panel will be moderated by 2017 and 2018 CTSP Fellow Steve Trush, a MIMS 2018 graduate and now a Research Fellow at the Center for Long-Term Cybersecurity (CLTC). He was on a CTSP project starting in 2017 that provided a report to the Oakland Privacy Advisory Commission—read an East Bay Express write-up on their work here.

The panelists will discuss what public governance models can help local governments protect the privacy of citizens—and what role citizen technologists can play in shaping these models. The discussion will showcase the ongoing collaboration between the UC Berkeley School of Information and the Oakland Privacy Advisory Commission (OPAC). Attendees will learn how they can get involved in addressing issues of governance, privacy, fairness, and justice related to state surveillance.

Panel:

  • Cyrus Farivar, Author, Habeas Data: Privacy vs. the Rise of Surveillance Tech
  • Deirdre Mulligan, Associate Professor in the School of Information at UC Berkeley, Faculty Director, UC Berkeley Center for Law & Technology
  • Catherine Crump, Assistant Clinical Professor of Law, UC Berkeley; Director, Samuelson Law, Technology & Public Policy Clinic.
  • Camille Ochoa, Coordinator, Grassroots Advocacy; Electronic Frontier Foundation
  • Moderated by Steve Trush, Research Fellow, UC Berkeley Center for Long-Term Cybersecurity

The panel will be followed by a reception with light refreshments. Building is wheelchair accessible – wheelchair users can enter through the ground floor level and take the elevator to the second floor.

This event will not be taped or live-streamed.

RSVP here to attend.

 

Panelist Bios:

Cyrus [“suh-ROOS”] Farivar is a Senior Tech Policy Reporter at Ars Technica, and is also an author and radio producer. His second book, Habeas Data, about the legal cases over the last 50 years that have had an outsized impact on surveillance and privacy law in America, is out now from Melville House. His first book, The Internet of Elsewhere—about the history and effects of the Internet on different countries around the world, including Senegal, Iran, Estonia and South Korea—was published in April 2011. He previously was the Sci-Tech Editor, and host of “Spectrum” at Deutsche Welle English, Germany’s international broadcaster. He has also reported for the Canadian Broadcasting Corporation, National Public Radio, Public Radio International, The Economist, Wired, The New York Times and many others. His PGP key and other secure channels are available here.

Deirdre K. Mulligan is an Associate Professor in the School of Information at UC Berkeley, a faculty Director of the Berkeley Center for Law & Technology, and an affiliated faculty on the Center for Long-Term Cybersecurity.  Mulligan’s research explores legal and technical means of protecting values such as privacy, freedom of expression, and fairness in emerging technical systems.  Her book, Privacy on the Ground: Driving Corporate Behavior in the United States and Europe, a study of privacy practices in large corporations in five countries, conducted with UC Berkeley Law Prof. Kenneth Bamberger was recently published by MIT Press. Mulligan and  Bamberger received the 2016 International Association of Privacy Professionals Leadership Award for their research contributions to the field of privacy protection.

Catherine Crump: Catherine Crump is an Assistant Clinical Professor of Law and Director of the Samuelson Law, Technology & Public Policy Clinic. An experienced litigator specializing in constitutional matters, she has represented a broad range of clients seeking to vindicate their First and Fourth Amendment rights. She also has extensive experience litigating to compel the disclosure of government records under the Freedom of Information Act. Professor Crump’s primary interest is the impact of new technologies on civil liberties. Representative matters include serving as counsel in the ACLU’s challenge to the National Security Agency’s mass collection of Americans’ call records; representing artists, media outlets and others challenging a federal internet censorship law, and representing a variety of clients seeking to invalidate the government’s policy of conducting suspicionless searches of laptops and other electronic devices at the international border.

Prior to coming to Berkeley, Professor Crump served as a staff attorney at the ACLU for nearly nine years. Before that, she was a law clerk for Judge M. Margaret McKeown at the United States Court of Appeals for the Ninth Circuit.

Camille Ochoa: Camille promotes the Electronic Frontier Foundation’s grassroots advocacy initiative (the Electronic Frontier Alliance) and coordinates outreach to student groups, community groups, and hacker spaces throughout the country. She has very strong opinions about food deserts, the school-to-prison pipeline, educational apartheid in America, the takeover of our food system by chemical companies, the general takeover of everything in American life by large conglomerates, and the right to not be spied on by governments or corporations.

Data for Good Competition — Showcase and Judging

The four teams in CTSP’s Facebook-sponsored Data for Good Competition will be presenting today in CITRIS and CTSP’s Tech & Data for Good Showcase Day. The event will be streamed through Facebook Live on the CTSP Facebook page. After deliberations from the judges, the top team will receive $5000 and the runner-up will receive $2000.

Final Results:

Agenda:

Data for Good Judges:

Joy Bonaguro, Chief Data Officer, City and County of San Francisco

Joy Bonaguro the first Chief Data Officer for the City and County of San Francisco, where she manages the City’s open data program. Joy has spent more than a decade working at the nexus of public policy, data, and technology. Joy earned her Masters from UC Berkeley’s Goldman School of Public Policy, where she focused on IT policy.

Lisa García Bedolla, Professor, UC Berkeley Graduate School of Education and Director of UC Berkeley’s Institute of Governmental Studies

Professor Lisa García Bedolla is a Professor in the Graduate School of Education and Director of the Institute of Governmental Studies. Professor García Bedolla uses the tools of social science to reveal the causes of political and economic inequalities in the United States. Her current projects include the development of a multi-dimensional data system, called Data for Social Good, that can be used to track and improve organizing efforts on the ground to empower low-income communities of color. Professor García Bedolla earned her PhD in political science from Yale University and her BA in Latin American Studies and Comparative Literature from UC Berkeley.

Chaya Nayak, Research Manager, Public Policy, Data for Good at Facebook

Chaya Nayak is a Public Policy Research Manager at Facebook, where she leads Facebook’s Data for Good Initiative around how to use data to generate positive social impact and address policy issues. Chaya received a Masters of Public Policy from the Goldman School of Public Policy at UC Berkeley, where she focused on the intersection between Public Policy, Technology, and Utilizing Data for Social Impact.

Michael Valle, Manager, Technology Policy and Planning for California’s Office of Statewide Health Planning and Development

Michael D. Valle is Manager of Technology Policy and Planning at the California Office of Statewide Health Planning and Development, where he oversees the digital product portfolio. Michael has worked since 2009 in various roles within the California Health and Human Services Agency. In 2014 he helped launch the first statewide health open data portal in California. Michael also serves as Adjunct Professor of Political Science at American River College.

Judging:

As detailed in the call for proposals, the teams will be judged on the quality of their application of data science skills, the demonstration of how the proposal or project addresses a social good problem, their advancing the use of public open data, all while demonstrating how the proposal or project mitigates potential pitfalls.

Data for Good Competition — Call for Proposals

See the people and projects that advanced to the seed grant phase in 2018 and the final results.

The Center for Technology, Society & Policy (CTSP) seeks proposals for a Data for Good Competition. The competition will be hosted and promoted by CTSP in coordination with the UC Berkeley School of Information IMSA, and made possible through funds provided by Facebook.

Team proposals will apply data science skills to address a social good problem with public open data. The objective of the Data for Good Competition is to incentivize students from across the UC Berkeley campus to apply their data science skills towards a compelling public policy or social justice issue.

The competition is intended to encourage the creation of data tools or analyses of open data. Open datasets may be local, state, national, or international so long as they are publicly accessible. The data tool or analysis may include, but is not limited to:

  1. integration or combination of two or more disparate datasets, including integration with private datasets;
  2. data conversions into more accessible formats;
  3. visualization of data graphically, temporally, and/or spatially;
  4. data validations or verifications with other open data sources;
  5. platforms that help citizens access and/or manipulate data without coding experience; etc.

Issues that may be relevant and addressed via this competition include environmental issues, civic engagement (e.g., voting), government accountability, land use (e.g., housing challenges, agriculture), criminal justice, access to health care, etc. CTSP suggests that teams should consider using local or California state data since there may be additional opportunities for access and collaboration with agencies who produce and maintain these datasets.

The competition will consist of three phases:

  • an initial proposal phase when teams work on developing proposals
  • seed grant execution phase when selected teams execute on their proposals
  • final competition and presentation of completed projects at an event in early April 2018

Teams selected for the seed grant must be able to complete a working prototype or final product ready for demonstration at the final competition and presentation event. It is acceptable for submitted proposals to already have some groundwork already completed or serve as a substantial extension of an existing project, but we are looking to fund something novel and not already completed work.

Initial Proposal Phase

The initial proposal phase ends at 11:59pm (PST) on January 28th, 2018 when proposals are due. Proposals will then be considered against the guidelines below. CTSP will soon announce events to support teams in writing proposals and to share conversations on data for good and uses of public open data.

Note: This Data for Good Competition is distinct from the CTSP yearlong fellowship RFP.

Proposal Guidelines

Each team proposal (approximately 2-3 pages) is expected to answer the following questions:

Project Title and Team Composition

  • What is the title of your project, and the names, department affiliations, student classification (undergraduate/graduate), and email contact information?

Problem

  • What is the social good problem?
  • How do you know it is a real problem?
  • If you are successful how will your data science approach address this problem?  Who will use the data and how will they use it to address the problem?  

Data

  • What public open data will you be using?

Output & Projected Timeframe

  • What will your output be? How may this be used by the public, stakeholders, or otherwise used to address your social good problem?
  • Outline a timeframe of how the project will be executed in order to become a finished product or working prototype by the April competition. Will any additional resources be needed in order to achieve the outlined goal?

Privacy Risks and Social Harms

  • What, if any, are the potential negative consequences of your project and how do you propose to minimize them? For example, does your project create new privacy risks?  Are there other social harms?  Is the risk higher for any particular group?  Alternatively, does your project aim to address known privacy risks, social harms, and/or aid open data practitioners in assessing risks associated with releasing data publicly?

Proposals will be submitted through the CTSP website. Successful projects will demonstrate knowledge of the proposed subject area by explaining expertise and qualifications of team members and/or citing sources that validate claims presented. This should be a well-developed proposal, and the team should be prepared to execute the project in a short timeframe before the competition. Please include all relevant information needed for CTSP evaluation–a bare bones proposal is unlikely to advance to the seed funding stage.

Seed Grant Phase

Four to six teams will advance to the seed grant phase. This will be announced in February 2018. Each member of an accepted project proposal team becomes a CTSP Data for Good grantee, and each team will receive $800 to support development of their project. If you pass to the seed grant phase we will be working with you to connect you with stakeholder groups and other resources to help improve the final product. CTSP will not directly provide teams with hardware, software, or data.

Final Competition and Presentation Phase

This phase consists of an April evening of public presentation before judges from academia, Facebook, and the public sector and a decision on the competition winner. The top team will receive $5000 and the runner-up will receive $2000. 

Note: The presentation of projects will support the remote participation of distance-learning Berkeley students, including Master of Information and Data Science (MIDS) students in the School of Information.

Final Judging Criteria

In addition to examining continued consideration of the project proposal guidelines, final projects will be judged by the following criteria and those judgments are final:

  • Quality of the application of data science skills
  • Demonstration of how the proposal or project addresses a social good problem
  • Advancing the use of public open data

After the Competition

Materials from the final event (e.g., video) and successful projects will be hosted on a public website for use by policymakers, citizens, and students. Teams will be encouraged to publish a blogpost on CTSP’s Citizen Technologist Blog sharing their motivation, process, and lessons learned.

General Rules

  • Open to current UC Berkeley students (undergraduate and graduate) from all departments (Teams with outside members will not be considered. However, teams that have a partnership with an external organization who might use the tool or analysis will be considered.)
  • Teams must have a minimum of two participants
  • Participants must use data sets that are considered public or open.

Code of Conduct

This code of conduct has been adapted from the 2017 Towards Inclusive Tech conference held at the UC Berkeley School of Information:

The organizers of this competition are committed to principles of openness and inclusion. We value the participation of every participant and expect that we will show respect and courtesy to one another during each phase and event in the competition. We aim to provide a harassment-free experience for everyone, regardless of gender, sexual orientation, disability, physical appearance, body size, race, or religion. Attendees who disregard these expectations may be asked to leave the competition. Thank you for helping make this a respectful and collaborative event for all.

Questions

Please direct all questions about the application or competition process to CTSP@nullberkeley.edu.

Apply

Please submit your application at this link.