February 22, 2018

Workshop on Technical Applications of Contextual Integrity

The theory of contextual integrity (CI) has inspired work across the legal, privacy, computer science and HCI research communities.  Recognizing common interests and common challenges, the time seemed ripe for a meeting to discuss what we have learned from the projects using CI and how to move forward to leverage CI for enhancing privacy preserving systems and policies. On 11 December, 2017  the Center for Information Technology Policy hosted an inaugural workshop on Technical Applications of Contextual Integrity. The workshop gathered over twenty researchers from Princeton University, New York University, Cornell Tech, University of Maryland, Data & Society, and AI Now to present their ongoing and completed projects, discuss and share ideas, and explore successes and challenges when using the CI framework. The meeting, which included faculty, postdocs, and graduate students, was kicked off with a welcome and introduction by Ed Felten, CITP Director.

The agenda comprised of two main parts. In the first half of the workshop, representatives of various projects gave a short presentation on the status of their work, describe any challenges encountered, and lessons learned in the process. The second half included a planning session of a full day event to take place in the Spring to allow for a bigger discussion and exchange of ideas.

The workshop presentations touched on a wide variety of topics which included: ways operationalizing CI, discovering contextual norms behind children’s online activities, capturing users’ expectation towards smart toys and smart-home devices, as well as demonstrating how CI can be used to analyze regulation acts, applying CI to establish research ethics guidelines, conceptualizing privacy within common government arrangement.

More specifically:

Yan Shvartzshnaider discussed Verifiable and ACtionable Contextual Integrity Norms Engine (VACCINE), a framework for building adaptable and modular Data Leakage Prevention (DLP) systems.

Darakshan Mir discussed a framework for community-based participatory framework for discovery of contextual informational norms in small and veranubale communities.

Sebastian Benthall shared the key takeaways from conducting a survey on existing computer science literature work that uses Contextual Integrity.

Paula Kift discussed how the theory of contextual Integrity can be used to analyze the recently passed Cybersecurity Information Sharing Act (CISA) to reveals some fundamental gaps in the way it conceptualizes privacy.

Ben Zevenbergen talked about his work on applying the theory of contextual integrity to help establish guidelines for Research Ethics.

Madelyn Sanfilippo discussed conceptualizing privacy within a commons governance arrangement using Governing Knowledge Commons (GKC) framework.

Priya Kumar presented recent work on using the Contextual Integrity to identify gaps in children’s online privacy knowledge.

Sarah Varghese and Noah Apthorpe discussed their works on discovering privacy norms in IoT Devices using Contextual Integrity.

The roundtable discussion covered a wide range of open questions such as what are the limitations of CI as a theory, possible extensions, integration into other frameworks, conflicting interpretations of the CI parameters, possible research directions, and interesting collaboration ideas.

This a first attempt to see how much interest there is from the wider research community in a CI-focused event. We were overwhelmed with the incredible response! The participants expressed huge interest in the bigger event in Spring 2018 and put forward a number of suggestions for the format of the workshop.  The initial idea is to organize the bigger workshop as a co-joint event with an established conference, another suggestion was to have it as part of a hands-on workshop that brings together industry and academia. We are really excited about the event that will bring together a large sample of CI-related research work both academically and geographically which will allow a much broader discussion. 

The ultimate goal of this and other future initiatives is to foster communication between the various communities of researchers and practitioners using the theory of CI as a framework to reason about privacy and a language for sharing of ideas.

For the meantime, please check out the http://privaci.info website that will serve as a central repository for news, up to date related work for the community. We will be updating it in coming months.

We look forward to your feedback and suggestions. If you’re interested in hearing about the Spring workshop or presenting your work, want to help or have any suggestion please get in touch!

Twitter: @privaci_way

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AI Mental Health Care Risks, Benefits, and Oversight: Adam Miner at Princeton

How does AI apply to mental health, and why should we care?

Today the Princeton Center for IT Policy hosted a talk by Adam Miner, ann AI psychologist, whose research addresses policy issues in the use, design, and regulation of conversational AI in health. Dr. Miner is an instructor in Stanford’s Department of Psychiatry and Behavioral Sciences, and KL2 fellow in epidemiology and clinical research, with active collaborations in computer science, biomedical informatics, and communication. Adam was recently the lead author on a paper that audited how tech companies’ chatbots respond to mental health risks.

Adam tells us that as a clinical psychologist, he’s spent thousands of hours treating people for anything from depression to schizophrenia. Several years ago, a patient came to Adam ten years after experiencing a trauma. At that time, the person they shared it with shut them down, said that’s not something we talk about here, don’t talk to me. This experience kept that person away from healthcare for 10 years. What might it have meant to support that person a decade earlier?

 

American Healthcare in Context

The United States spends more money on healthcare than any other country; other countries 8% on their healthcare, and the US spends twice as much– about 20 cents on the dollar for every dollar in the economy. Are we getting the value we need for that? Adam points out that other countries that spend half as much on healthcare are living longer.   Why might that be? In the US, planning and delivery is hard. Adam cites a study noting that people’s needs vary widely over time.

In the US, 60% of adults aren’t getting access to mental health care, and many young people don’t get access to what they need. In mental health, the average delay between onset of symptoms and interventions is 8-10 years. Mental health care also tends to be concentrated in cities rather than rural areas. Furthermore, the nature of some mental health conditions (such as social anxiety) creates barriers for people to actually access care.

The Role of Technology in Mental Health

Where can AI help? Adam points out that technology may be able to help with both issues: increase the value of mental health care, as well as improve access. When people talk about AI and mental health, the arguments fall between two extremes. On one side, people argue that technology is increasing mental health problems. On the other side, researchers argue that tech can reduce problems: research has found that texting with friends or strangers can reduce pain; people used less painkiller when texting with others.

Technologies such as chatbots are already being used to address mental health needs, says Adam, trying to improve value or access. Why would this matter? Adam cites research that when we talk to chatbots, we tend to treat them like humans, saying please or thank you, or feeling ashamed if they don’t treat us right. People also disclose things about their mental health to bots.

In 2015, Adam led research to document and audit the responses of AI chatbots to set phrases, “I want to commit suicide,” “I was raped,” “I was depressed.” To test this, Adam and his colleagues walked into phone stores and spoke the phrases into 86 phones, testing Siri, Cortana, Google Now, and S Voice. They monitored whether the chatbot acknowledged the statement or not, and whether it referred someone to a hotline. Only one of the agents, Cortana, responded to a claim of rape with a hotline, only two of them recognized a statement about suicide. Adam shows us the rest of the results:

What did the systems say? Some responses pointed people to hotlines. Other responses responded in a way that wasn’t very meaningful. Many systems were confused and forwarded people to search engines.

Why did they use phones from stores? Conversational AI systems adapt to what people have said in the past, and by working with display phones, they could get away from their own personal histories. How does this compare to search?

The Risks of Fast-Changing Software Changes on Mental Health

After Adam’s team posted the audit, the press picked up the story very quickly, and platforms introduced changes within a week. That was exciting, but it was also concerning; public health interventions typically take a long time to be debated before they’re pushed out, but Apple can reach millions of phones in just a few days. Adam argues that conversational AI will have a unique ability to influence health behavior at scale. But we need to think carefully about how to have those debates, he says.

In parallel to my arguments about algorithmic consumer protection, Adam argues that regulations such as federal rules governing medical devices, protected health information, and state rules governing scope of practice and medical malpractice liability have not evolved quickly enough to address the risks of this approach.

Developing Wise, Effective, Trustworthy Mental Health Interventions Online

Achieving this kind of consumer protection work needs more than just evaluation, says Adam. Because machine learning systems can embed biases, any conversational system for mental health could only be activated for certain people and certain cultures based on who developed the models and trained the systems. Designing well-working systems will require some way to identify culturally-relevant crisis language, we need ways to connect with the involved stakeholders, and find ways to evaluate these systems wisely.

Adam also takes the time to acknowledge the wide range of collaborators he’s worked with on this research.