To get technology right in Iowa and elsewhere, insight into data and human behavior is required – TechCrunch

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What happened in Iowa Democratic caucus last week is a textbook example of how applying technological approaches to work in the public sector can go very wrong, just as we need it to go well.

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While it is possible to conclude that Iowa teaches us that we should not allow technology anywhere near a government process, this is the wrong conclusion to reach, and it combines the complexity of what has and has not happened. Technology does not solve a broken policy and the key is understanding what it is good for.

What does it look like to get technology good at solving public problems? There are three key principles that can help to build technology of general interest more effectively: solve a real problem, design with and for users and start their lives in mind and small (testing, improving, testing).

Before we develop an app or mix a new technology in a political process, it is worth asking the question: what is the purpose of this app and what will an app do that will improve the existing process?

To do it right, start by understanding the people who will use what you build to solve a real problem. What do they actually need? In the case of Iowa, this would have meant that seasoned local organizers were asked what would help them in voting. It also means talking directly to district captains and caucus visitors and observing the unique process in which neighbors convince neighbors to go to another corner of a gym when their candidate has not been successful. In addition to questions about the idea of ​​a web application, it is crucial to test the application with real users under real circumstances to see how it works and make improvements.

When building such a critical game day app, you must test it under more realistic conditions, which means that acceptance and ease of use are important. Although Shadow (the company in charge of this build) did a lightweight test with some users, there was not the runway to adapt or learn from those for whom the app was designed. The app may have worked well, but it doesn't matter if people haven't used it or can't download it.

A model of how this works can be found in the Nursing family partnership, a high-impact non-profit that helps mothers with a low income.

This non-profit organization has adapted to receive feedback loops from mothers and nurses via e-mail and text messages. It even has a full-time role "responsible for supporting the vision of the organization to scale up the plan by listening and learning from primary, secondary and internal customers to assess what can be done to deliver an exceptional Nurse Family Partnership experience. "

Building on its personal assistance program, the Nurse Family Partnership has designed an app (together with Hopelab, a social innovation lab in collaboration with behavioral science-based software company Ayogo). The Goal Mama app builds on the relationship between nurses and mothers. It was developed with these customers in mind after research has shown that most mothers in the program used their smartphones intensively, so this would help to meet mothers where they were. Because of this approach to the use of technology and data to meet the needs of their staff and customers, they have it served 309,787 mothers in 633 provinces and 41 states.

Another example is the work of Built for zero, a national effort focused on the ambitious goal of ending homelessness in 80 cities and provinces. Community organizers start with the personal challenges of the unbelievers – they know that without understanding the person and their needs, they cannot build successful interventions that accommodate them. Their work combines a methodology of people-centered organization with smart data science to deliver constant assessment and improvement in their work, and they collaborate with the Tableau Foundation to build and train communities to collect data with new standards and progress towards a goal of zero homelessness.

Good technology always starts small, tests, learns and improves with real users. Parties, governments and non-profit organizations should elaborate on the learning methods that are common to tech startups and that are supported by Eric Reis in The Lean Startup. By starting with small tests and learning fast, technology of general interest recognizes the high use of technology to improve democracy: the lives of real people are at stake. With questions about fairness, justice, legitimacy and integrity on the line, starting small helps ensure that there is enough runway to make important changes and work the kinks.

Take for example the work of Alia. Launched by the National alliance for domestic staff (NDWA), it is the first benefits portal for cleaners. Domestic staff usually does not receive employee benefits, making things such as a day of illness or a visit to a doctor impossible without losing wages.

Thanks to the user-friendly interface, people who hire cleaning companies can directly contribute to their benefits, allowing employees to receive paid leave, accident insurance and life insurance. Alia's engineers benefited from in-depth user insights gained by connecting to a network of cleaners. In the growing gig economy, the Alia model can be instructive for a series of employees at local, provincial and federal level. Obama organizers dramatically increased volunteer work (up to 18%) in 2008 just by A / B testing the words and colors used for the call-to-action on their website.

There are many instructional technologies of general interest that focus on designing with (not just for) users. This includes work in civil society such as Center for Civic Design, ensure that people can have simple and seamless interactions with the government, and The principles for digital development, the first of which is & # 39; designing with the user & # 39 ;. There is also work within governments, from the Digital government service in the UK in the work of the Digital service United States, which was launched in the Obama administration.

Finally, it also helps to thoroughly understand the circumstances in which technology will be used. What are the experienced experiences of the people who will use the tool? Have the designers dug themselves in and attended a caucus to see how paper has captured body movements and changing thoughts in gyms, cafes and VFW halls?

In the case of Iowa, it requires understanding of the standards, rules, and culture of the caucuses. A political caucus is a unique situation.

Not to mention the Iowa this year Caucus has implemented various process changes to increase transparency but also to complex the process, which also had to be taken into account when deploying a technical solution. Understanding the circumstances in which technology is deployed requires a nuanced understanding of policy and behavior and how policy changes can affect design choices.

Building a technical solution without user research to see what people really need entails the risk that credibility is reduced and confidence is further compromised. Building the technology itself is often the easy part. The complex part is relational. It requires investment in capacity to engage, train, test and repeat.

We are used to same-day delivery and immediate streaming into our private and social lives, which raises our expectations for what we want from the public sector. The urge to modernize and streamline is what makes an app the solution. But building the next killer app for our democracy requires more than just prototyping a smashing tool.

Public interest technology means working on the broader, difficult challenge to restore confidence in our democracy. Every time we use technology to modernize a process, we must remember this end goal and ensure that we do it well.

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