Artificial Intelligence for Citizen Services and GovernmentThis paper explores the various types of AI applications, and current and future uses of AI in government delivery of citizen services, with a focus on citizen inquiries and information. It also offers strategies for governments as they consider implementing AI. Despite the clear opportunities, AI will not solve systemic problems in government, and could potentially exacerbate issues around service delivery, privacy, and ethics if not implemented thoughtfully and strategically. Agencies interested in implementing AI can learn from previous government transformation efforts, as well as private-sector implementation of AI. Government offices should consider ... six strategies for applying AI to their work ...Hila Mehr_bfdd1fb2-abf0-11e8-add2-30b0eff16937Hila Mehr is an Ash Center Technology and Democracy Fellow ('16 - '17) at Harvard Kennedy School. She works in Market Development and Insights at IBM. Previously, Hila worked for Living Cities, the Department of Defense, and SVA Design for Social Innovation. She holds an MPA from Columbia SIPA and a BA with General Honors from the University of Chicago. Hila is a StartingBloc Fellow in Social Innovation. Connect with her on Twitter (@hilamehr) or at hilamehr.com.Ash Center Technology and DemocracyHarvard UniversityAll views are the author's own and do not represent the official position of IBM, Harvard University, or any other companies or individuals mentioned. NetflixFrom online services like Netflix and Facebook, to chatbots on our phones and in our homes like Siri and Alexa, we are beginning to interact with artificial intelligence (AI) on a near daily basis. AI is the programming or training of a computer to do tasks typically reserved for human intelligence, whether it is recommending which movie to watch next or answering technical questions.FacebookGovernmentsSoon, AI will permeate the ways we interact with our government, too. CitiesFrom small cities in the US to countries like Japan, government agencies are looking to AI to improve citizen services. While the potential future use cases of AI in government remain bounded by government resources and the limits of both human creativity and trust in government, the most obvious and immediately beneficial opportunities are those where AI can reduce administrative burdens, help resolve resource allocation problems, and take on significantly complex tasks.CountriesCitizensMany AI case studies in citizen services today fall into five categories: answering questions, filling out and searching documents, routing requests, translation, and drafting documents.Government EmployeesThese applications could make government work more efficient while freeing up time for employees to build better relationships with citizens. With citizen satisfaction with digital government offerings leaving much to be desired, AI may be one way to bridge the gap while improving citizen engagement and service delivery. AI reduces administrative burdens, helps resolve resource allocation problems, and takes on significantly complex tasks._bfdd20f2-abf0-11e8-add2-30b0eff16937To explore AI applications and current and future uses of AI in government delivery of citizen services._bfdd21c4-abf0-11e8-add2-30b0eff16937GoalsMake AI a part of a goals-based, citizen-centric program_bfdd2264-abf0-11e8-add2-30b0eff169371Citizens AI should not be implemented in government just because it is a new, exciting technology. Government officials should be equipped to solve problems impacting their work, and AI should be offered as one tool in a toolkit to solve a given problem. The question should not be “how will we use AI to solve a problem,” but “what problem are we trying to solve, why, and how will we solve it?” If AI is the best means to achieve that goal, then it can be applied, otherwise it should not be forced. If AI is the right tool, it cannot be a single touch-point for citizens. McKinsey recommends agencies consider a citizen’s end-toend journey through a process. They report in their “Putting Citizens First” study that organizations that manage the entire customer journey from start to finish achieve higher levels of satisfaction and are more effective at delivery.17 Government offices can consider where and when AI can be a touchpoint, and what other technologies or human interaction touchpoints might be required in the citizen’s journey. In keeping with customer centricity, the technology also must be inclusive, with awareness for generational, educational, income, and language differences. _bfdd22fa-abf0-11e8-add2-30b0eff16937InputGet citizen input_bfdd2386-abf0-11e8-add2-30b0eff169372 Citizen input and support for AI implementations will be essential. “Governments should enable a genuine participatory, grassroots approach to both demystify AI as well as offer sessions for citizens to create an agenda for AI while addressing any potential concerns,” suggests Russon Gilman. Wallach agrees: “There needs to be a conversation in society about AI — to educate everyone from citizens to policymakers so that they truly understand how it works and its tradeoffs.” With that level of education, citizens can then offer other ways to be engaged with AI, and even help co-create ethics and privacy rules for use of their data. When it comes to building and deploying AI platforms, user feedback is essential both from citizens and government employee users. Onda recommends designing systems “to provide the right level of insight, depending upon individual user preferences.” _bfdd2412-abf0-11e8-add2-30b0eff16937ResourcesBuild upon existing resources_bfdd24a8-abf0-11e8-add2-30b0eff169373Adding the benefits of AI to government systems should not require building the systems from scratch. Though much evolution in AI has come from early government research, governments can also take advantages of the advances businesses and developers are making in AI. IT analyst firm IDC predicts that by 2018, 75 percent of new business software will include AI features.18 Nonprofits and research institutions offer the public access to world-class research and new releases of open-source machine intelligence programs allow users to inexpensively scale their use of AI. Implementations do not have to start only for entirely new programs or datasets either. One place to start would be integrating AI into existing platforms, like 311 and SeeClickFix, where there is existing data and engagement. _bfdd2534-abf0-11e8-add2-30b0eff16937Data & PrivacyBe data-prepared and tread carefully with privacy_bfdd25ca-abf0-11e8-add2-30b0eff169374 Many agencies will not be at the level of data management necessary for AI applications, and many may be lacking the significant amount of data needed to train and start using AI. But as government offices improve their data collection and management, best practices about the type of data that will be used and collected will be critical for future use with AI. “Collecting and aggregating the right type of data is critical for success,” says Onda. “Governments must think about the type of data they need, when the data expires (it has a shelf life), and how the data will be aggregated to provide context for a specific individual. Citizens must be able to trust the systems they are interacting with and know where their data is going.” Governments should be very transparent about the data collected and give citizens the choice to opt in when personal data will be used. There may be fewer privacy concerns if the only data being used is already provided to the government by citizens (such as IRS data). The privacy concerns become relevant when citizens have not provided consent or external datasets get mixed with government sources, explains Eaves. Data use also becomes concerning when the data is inaccurate. This can lead to a cascading effect as the data travels. “Transparency isn’t enough if the data is already off,” explains Russon Gilman, because “the algorithms and learning systems can be hidden, so the stakes are very high for democratic governance and ensuring equity in the public sector.” _bfdd266a-abf0-11e8-add2-30b0eff16937Ethics & Decision MakingMitigate ethical risks and avoid AI decision making_bfdd270a-abf0-11e8-add2-30b0eff169375AI is susceptible to bias because of how it is programmed and/or trained, or if the data inputs are already corrupted. A best practice for lessening bias is to involve multidisciplinary and diverse teams, in addition to ethicists, in all AI efforts. In addition, Matt Chessen, an AI researcher with the US Department of State, has recommended a new public policy profession that specializes in machine learning and data science ethics.19 Governments can also leverage the work of groups of technologists who have come together to create common sets of ethics for AI, such as the Asilomar AI Principles and the Partnership on AI. Given the ethical issues surrounding AI and continuing developments in machine learning techniques, AI should not be tasked with making critical government decisions about citizens. For example, the use of a risk-scoring system used in criminal sentencing and similar AI applications in the criminal justice system were found to be biased, with drastic repercussions for the citizens sentenced. These types of use cases should be avoided. Companies like Google and Microsoft are actively trying to improve machine learning models to prevent or correct bias, and have internal ethics boards that consider new algorithms -- government offices should uphold a similar practice. Until machine learning techniques improve, though, AI should only be used for analysis and process improvement, not decision support, and human oversight should remain prevalent. _bfdd27a0-abf0-11e8-add2-30b0eff16937AugmentationAugment employees, do not replace them._bfdd285e-abf0-11e8-add2-30b0eff169376EmployeesResearch highly varies in determining the threat of AI to jobs over the next two decades -- from 9 to 47 percent -- according to the 2016 White House report on automation and the economy. In some cases, AI may instead lead to increased and new employment directly and indirectly related to AI development and supervision. While job loss is a legitimate concern for civil servants, and blue and white collar workers alike as the technology evolves, early research has found that AI works best in collaboration with humans. Any efforts to incorporate AI in the government should be approached as ways to augment human work, not to cut headcount. Governments should also update fair labor practices in preparation for potential changes in workplaces where AI systems are in place._bfdd28fe-abf0-11e8-add2-30b0eff169372017-08-312018-08-29https://ash.harvard.edu/files/ash/files/artificial_intelligence_for_citizen_services.pdfOwenAmburOwen.Ambur@verizon.net