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Magazine: Features Managing crises, one text at a time

Managing crises, one text at a time

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Tags: Computing / technology policy, Electronic commerce, Networks, World Wide Web

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Jason Bennett is a software engineer with a bachelor's degree in computer science from the University of New Mexico. He started his career as a software engineer at Motorola and rose to engineering manager at Google before becoming director of engineering and vice president of engineering at several other companies. Today, he is CTO of CrisisTextLine, a not-for-profit organization operating throughout the U.S. providing counseling by texting 741741. Evolving from DoSomething.org, CrisisTextLine has grown from serving two area codes to all 295 in the U.S. Here, Bennett details the technology behind the platform that enables the exchange of millions of text messages, along with the many technical issues that arise due to scalability and user concern over data privacy and security.

The following interview has been condensed and edited for clarity.

XRDS: Describe your role as CTO of CrisisTextLine.

JASON BENNETT (JB): My primary goal is the execution of technology, planning and delivering on software stability, scalability, development, and maintenance. I strive to make agile product development better, lead architectural discussions, and mentor and develop the skills of my team.

Why did you choose phone text, which is an uncommon medium for intervention?

JB: Earlier, at DoSomething.org, as we received texts asking for help, we recognized text is the primary means of communication for a large segment of the population. We wanted to reach out to people whenever and wherever they were. That is how CrisisTextLine actually came into existence.

What made texting more effective compared to the alternatives?

JB: On the conscious part of the decision, we realized there was a huge wealth of data we received through this medium that wasn't available before and that can be used to help people better. Texting also proved more effective because people were more forthcoming and shared more details through text than through other media. In some cases, where privacy is important, text proved to be the solution, too. For example, when a victim of domestic violence is still in the home and wants to seek help, texting keeps the conversation private from the perpetrator.

Apart from SMS-based phone texting, what other texting platforms are available?

JB: We recently integrated our platform with Facebook; we launched our Kik (https://www.kik.com/) integration earlier this year. The goal is to eventually scale the medium and identify who might be in crisis, enabling us to see a prompt if someone needs help.

What challenges did you face in getting there?

JB: Setting up business partnerships takes the most time. Implementation is mostly trivial for us.

Do you plan to integrate voice or video calls?

JB: We have considered both and include it in our plan to think more about them. However, text is our primary platform for now, given that research and observations have shown texting is much more private, and users tend to be more forthcoming.

How do you protect user data from misuse?

JB: Privacy is very important to us, and there are two parts to it—policy and technology. On the policy side, we ensure all data analysis is done in-house. Any data shared with our partner universities for research is stripped of personally identifiable information. The data is never allowed to be downloaded and can be accessed only through our API. We also do background checks on all counselors who join the team. On the technology side, we use role-based authorization and two-factor authentication for anything that touches the data. Access to certain systems is restricted, even to the in-house deputy. All the data sits behind VPNs and firewalls. Most important, we encrypt all data.

What data can crisis counselors see concerning texters to be able to help them better?

JB: We know it would be helpful if the counselor had some background information about the texter, but that would violate texter privacy. Counselors know only what texters tell them. We do envision that we would want to use machine learning to identify certain patterns in texts to help guide the conversation better.

What are you able to predict from the data you have?

JB: For now, we focus on identifying trends, given a particular time, place, and words. For example, a working individual calling in at 9 PM on a Sunday night may be feeling suicidal.

What other technological challenges do you face?

JB: We mostly face what other tech startups face. Keeping the service up and scaling well. We do want to use machine learning to use the data in the most efficient way possible.

How has technology kept up with scalability and the growth of your organization?

JB: Our hardware and software are horizontally scalable, meaning we just need to add one more server to the load balancer to scale up. We have had to make some changes from when CrisisTextLine started out but nothing more than a few tweaks here and there and some query optimizations.

How does the architecture handle usage spikes at the time of a large-scale crisis?

JB: During the 2016 U.S. elections, we saw a spike. Our key performance indicator is to respond to every text in under five minutes. The health of the queue is determined by how many people are responded to in under five minutes. Most helplines handle their queue in the order of arrival. Our proprietary system, based on choosing certain words in the text sent, determines the severity of the immediate crisis and will put certain messages higher in the queue than others.

If you expand CrisisTextLine internationally, how will the technology scale?

JB: We want to help as many people as possible in every country. Perhaps we would look at a multi-tenant solution and bespoke software. There are a bunch of local requirements to adhere to; for example, the data might possibly have to be stored in each country.

A technical background helps, but some of the best developers I have met were music majors. It matters how much time you put in—through a school or through yourself.

What was it like to switch from for-profit to not-for-profit status?

JB: It was all about impact to us. Earlier, I wasn't helping as many people as I wanted to. My career has transitioned from embedded programming to e-commerce to ad tech and desktop visualization. The next step for me was not-for-profit.

How are the challenges different in a not-for-profit?

JB: Technologically, we face more or less the same challenges as any tech startup. What is different are the key performance indicator and the policies. For example, instead of asking how we can monetize something or maximize revenue with a feature, we ask how many more crisis counselors can we support if we build something and how many more lives can be saved by pushing a feature out.

With your bachelor's degree in computer science, what role has formal education played in your career?

JB: A CS background can give you a great foundation and depth of knowledge you wouldn't have otherwise. Is it a requirement? No. The requirement is really a desire to solve problems and break it down into logical groups. Some training—self-taught or through a university—is needed and depends on how much time you want to spend. Some of the best developers did not necessarily go through a CS degree. A technical background helps, but some of the best developers I have met were music majors. It matters how much time you put in—through a school or through yourself.

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Rahul R. Divekar is a Ph.D. student in the Department of Computer Science at Rensselaer Polytechnic Institute, Troy, NY. His research focus is on the intersection of computer and cognitive sciences, exploring areas of group dynamics and emotive analysis in conversations to enhance collective decision processes using AI. He has a master's degree in IT from Rensselaer Polytechnic Institute and a bachelor's degree in computer engineering from the University of Mumbai, India.

Nidhi Rastogi is a Ph.D. candidate in the Computer Science Department of Rensselaer Polytechnic Institute, Troy, NY, where she is leading innovation in anomaly detection in large networks using graph analytics. She holds a master's degree in computer science from the University of Cincinnati and has extensive work experience in networks at Verizon Wireless and GE Global Research. She is also committed to social good by using her skills in securing cyberspace, networks, graph analytics, machine learning, and AI.

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