case study public services

GovTech: Putting People First

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Publications

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Public Service Delivery

This report   presents a four-stage framework and practical step by step guidance to clients and task teams looking to modernize administrative services. The guidebook focuses on improving citizen centricity, quality, efficiency and reach of e-services.  It includes advice on how citizen centricity can be incorporated into the modernization process, and highlights challenges governments may face in each stage. It includes a variety of country examples to illustrate good practices and current trends in service design and delivery.

A main objective of this  note  is to provide a planning framework that governments can use to comprehensively address the key institutional, governance, financial, and technology issues involved in ISD initiatives. It draws on the experience of several countries that have implemented ISD solutions, and it aims to provide World Bank staff and client governments with a practical understanding of the concepts behind integrated service delivery and the reforms and investments required to implement it.

Countries across the globe are establishing new and improving existing citizen service centers (CSCs) to better serve their citizens. This  note  provides an overview of recent developments impacting CSC operations as well as a CSC design guide meant to summarize essential issues that managers looking to establish CSCs may wish to consider

This  note  provides practical advice on how to adopt a human rights-based assessment for the design, strategy, and implementation of service delivery by citizen service centers. Designed for World Bank teams conducting preliminary assessments, the tool presented here can also be useful to clients such as citizen service center managers to deepen their understanding of the value of a human rightsbased assessment and to improve the quality, accessibility, and effectiveness of service delivery

Recent work has highlighted the importance of understanding and actively engaging within the local context of governance and service delivery challenges to actually improve services to the poor. A number of  tools   have been used to help assess local governance and service delivery challenges, monitor local performance, and build citizen-government-service provider connectivity. 

Public Service Delivery Country Examples

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CASE STUDY · UNICEF

UNICEF revamps fundraising for the future

By managing all fundraising and campaigning through a single, seamless platform, UNICEF can do more for children in need around the world.

3-MINUTE READ

Raising the bar for raising funds

Since its inception, The United Nations Children’s Fund (UNICEF) has never strayed from its mission to transform children’s lives. Now, thanks to a new fundraising and customer relationship management (CRM) platform, the organization is taking that mission to the next level.

By partnering with Accenture to launch a not-for-profit platform powered by Salesforce, local UNICEF teams in Southeast Asia can create better tactics and strategies that help improve supporter engagement. The solution also helps reduce risks through enhanced data privacy compliance and increases operational efficiencies through automation. In just a year, UNICEF teams across Thailand, Malaysia, Indonesia and the Philippines have successfully migrated contact information data for 1 million supporters to the new platform. 

A single, seamless Salesforce solution

UNICEF teamed up with Accenture to consolidate multiple systems around a centrally managed, Salesforce-powered CRM. This new platform integrates all supporter communications and fundraising into a single multi-channel solution including on- and offline activity, major-donor activation, advocacy and volunteer campaigns, trust and grant management, long-term legacy programs, and donations processing.

Working on an accelerated timeline, the initiative launched in Thailand in March 2022, just six months after the program kicked off. Subsequent launches rolled out in Malaysia (December 2022), Indonesia (May 2023) and in the Philippines in November 2023. 

UNICEF’s bespoke CRM solution is delivering:

Better experiences

Faster response time to customer questions and concerns, and seamless payment billing and transactions, leading to an increase in engagement.

Improved security

Supporter data security is enhanced, and donation receipts and reports that used to get lost in the mail are now sent electronically.

Enhanced marketing

The new platform enables UNICEF to better leverage digital marketing channels and analyze which campaigns could be best replicated.

Delivering for those in need

Now, UNICEF has a solution that allows it to manage all fundraising and campaigning with an organization-wide view of its supporters and their preferences, with real-time data to track their performance.

The entire process has been reinvented, with seamless transactions, payment billing connected to local banks, real-time insights and reports, and revamped marketing operations and donor services. All supporter queries and service requests are also integrated and tracked in Salesforce, regardless of how they reach out for assistance (through text, email or the call center, for example).

Ultimately, and most significantly, the biggest beneficiaries of this transformation will be the children at the heart and soul of UNICEF’s mission. 

Our unwavering collaboration with Accenture and shared passion for creating a better future enabled us to use technology in unprecedented ways in support of children's rights.

Jose Alba / Private Fundraising and Partnerships, UNICEF

Meet the team

Kinkini Roychoudhary

Managing Director, Asia Pacific Lead – Accenture Development Partnerships

Cahyoadi Tjondronegoro

Delivery Lead – Song

Israel Crisostomo

SalesForce Data Engineering Lead – Advanced Technology Centers in the Philippines

Chris Garcia

Salesforce BA Lead – Advanced Technology Centers in the Philippines

Jester Cabantog

Salesforce Solution Architect – Advanced Technology Centers in the Philippines

Evangeline Chan

Marketing Cloud Developer – Song

Francis Santos

Sales Cloud Developer – Advanced Technology Centers in the Philippines

Anna Capayas

Salesforce Data Engineer and Quality Assurance – Advanced Technology Centers in the Philippines

Aly Mercado

SalesForce Quality Assurance – Advanced Technology Centers in the Philippines

Top 40 Most Popular Case Studies of 2021

Two cases about Hertz claimed top spots in 2021's Top 40 Most Popular Case Studies

Two cases on the uses of debt and equity at Hertz claimed top spots in the CRDT’s (Case Research and Development Team) 2021 top 40 review of cases.

Hertz (A) took the top spot. The case details the financial structure of the rental car company through the end of 2019. Hertz (B), which ranked third in CRDT’s list, describes the company’s struggles during the early part of the COVID pandemic and its eventual need to enter Chapter 11 bankruptcy. 

The success of the Hertz cases was unprecedented for the top 40 list. Usually, cases take a number of years to gain popularity, but the Hertz cases claimed top spots in their first year of release. Hertz (A) also became the first ‘cooked’ case to top the annual review, as all of the other winners had been web-based ‘raw’ cases.

Besides introducing students to the complicated financing required to maintain an enormous fleet of cars, the Hertz cases also expanded the diversity of case protagonists. Kathyrn Marinello was the CEO of Hertz during this period and the CFO, Jamere Jackson is black.

Sandwiched between the two Hertz cases, Coffee 2016, a perennial best seller, finished second. “Glory, Glory, Man United!” a case about an English football team’s IPO made a surprise move to number four.  Cases on search fund boards, the future of malls,  Norway’s Sovereign Wealth fund, Prodigy Finance, the Mayo Clinic, and Cadbury rounded out the top ten.

Other year-end data for 2021 showed:

• Online “raw” case usage remained steady as compared to 2020 with over 35K users from 170 countries and all 50 U.S. states interacting with 196 cases.
• Fifty four percent of raw case users came from outside the U.S..
• The Yale School of Management (SOM) case study directory pages received over 160K page views from 177 countries with approximately a third originating in India followed by the U.S. and the Philippines.
• Twenty-six of the cases in the list are raw cases.
• A third of the cases feature a woman protagonist.
• Orders for Yale SOM case studies increased by almost 50% compared to 2020.
• The top 40 cases were supervised by 19 different Yale SOM faculty members, several supervising multiple cases.

CRDT compiled the Top 40 list by combining data from its case store, Google Analytics, and other measures of interest and adoption.

All of this year’s Top 40 cases are available for purchase from the Yale Management Media store .

And the Top 40 cases studies of 2021 are:

1.   Hertz Global Holdings (A): Uses of Debt and Equity

2.   Coffee 2016

3.   Hertz Global Holdings (B): Uses of Debt and Equity 2020

4.   Glory, Glory Man United!

5.   Search Fund Company Boards: How CEOs Can Build Boards to Help Them Thrive

6.   The Future of Malls: Was Decline Inevitable?

7.   Strategy for Norway's Pension Fund Global

8.   Prodigy Finance

9.   Design at Mayo

10. Cadbury

11. City Hospital Emergency Room

13. Volkswagen

14. Marina Bay Sands

15. Shake Shack IPO

16. Mastercard

17. Netflix

18. Ant Financial

19. AXA: Creating the New CR Metrics

20. IBM Corporate Service Corps

21. Business Leadership in South Africa's 1994 Reforms

22. Alternative Meat Industry

23. Children's Premier

24. Khalil Tawil and Umi (A)

25. Palm Oil 2016

26. Teach For All: Designing a Global Network

27. What's Next? Search Fund Entrepreneurs Reflect on Life After Exit

28. Searching for a Search Fund Structure: A Student Takes a Tour of Various Options

30. Project Sammaan

31. Commonfund ESG

32. Polaroid

33. Connecticut Green Bank 2018: After the Raid

34. FieldFresh Foods

35. The Alibaba Group

36. 360 State Street: Real Options

37. Herman Miller

38. AgBiome

39. Nathan Cummings Foundation

40. Toyota 2010

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Esri, the global leader in geographic information system (GIS) software, builds the most powerful mapping and spatial analytics technology available.

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Case Study: Arizona Public Service Innovates with GIS—Yesterday, Today, and Tomorrow

William (Bill) Meehan is the Director of Utility Solutions for Esri. He is responsible for business development and marketing Esri’s geospatial technology to global electric and gas utilities.A...

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• 255 items added with 313,966 views
• Nov 7, 2023 Nov 7, 2023 1:47 pm GMT

Case study originally posted here. 

Arizona Public Service (APS) is the largest electric utility in Arizona. It serves 2.7 million Arizonans over 35,000 square miles. Founded in 1886 as the Phoenix Gas and Electric Light Company, its territory stretches from the border town of Douglas to the vistas of the Grand Canyon. Its more than 6,000 employees power the vision of creating a sustainable energy future.

APS pioneered the use of geographic information system (GIS) technology in 1994 when it migrated its paper circuit maps to Esri’s ArcInfo software. It has been a leader in the GIS community since then. In addition, it has continued to strengthen its asset data. Recently, APS has commenced a statewide data conflation effort to improve spatial accuracy in addition to transmission and distribution data cleanup efforts in preparation for the ArcGIS Utility Network. When complete, APS will have one of the most comprehensive and reliable GIS models in the industry, its grid data spanning from the power plant generator breakers to each customer’s meter.

As with many utility projects, the focus has been on the grid GIS data. But APS knew that sharing and analyzing the GIS data had untapped potential. It further saw that resources were limited with the modernization efforts underway in IT. As a result, it needed to tap into the expertise within the business units. At the same time, APS did not want to create unsupported and unofficial applications.

The solution was to deploy Esri’s web and mobile tools to end users through something APS calls the GIS Power User Group. APS became more agile in implementing its apps that complied with IT standards and practices. This solution freed IT to manage the GIS infrastructure, hardware, and licensing. It was a win-win situation. Gartner refers to this concept as citizen development.  

APS has a long history of having a rich system of record of its transmission and distribution assets. This citizen development process moved the GIS from a limited office application to an enterprise one: GIS for nearly everyone in the company. In effect, the GIS has become a system of record and a system of engagement. One notable example is the hugely successful Mobile Vegetation Management (MVM) app. The GIS team partnered with the Forestry, Fire, & Resource Management group to digitally transform its work. This work included inspections, treatment, trimming, auditing, and reporting. This manual process was automated using Esri’s ArcGIS Survey123 and ArcGIS Field Maps apps.

Here are just of few examples of user-developed apps:

• Distribution Line Inspection
• UG Equipment Inspections
• Streetlight Data Corrections
• Customer Construction Contacts Lookup (on APS.com)
• Substation Nonelectrical Inspection App for Landscape, Property, and Weed Management
• Avian Protection Tracking 
• Defensible Space Around Poles (DSAP) Maintenance
• Wildfire Awareness Dashboard
• Quick Capture Aerial Vegetation Patrols
• Various Environmental Asset Inspections
• T&D Engineering Standards QA Inspections 

This geographic approach benefits the employees. It has accelerated APS’s digital transformation efforts. The GIS team trained end users on the tools and capabilities of GIS. The employees were excited to see their work in action—and quickly, sometimes within several days or weeks. 

“The GIS Power User Group will support an efficient and effective frontline GIS strategy for all business groups by developing and empowering power users to share innovative ideas, define standards, create and identify common data sources, and lead in change management for scaling GIS within the business.”  Rami Alygad, Manager, Smart Grid & GIS, APS

This success begets more innovation. This process also benefits the IT organization, freeing it to improve infrastructure, performance, governance, and scalability. The customers benefit. GIS apps essentially eliminated the error-prone and costly paper processes. They lower costs and increase data integrity. This process aligns with APS’s Customer Affordability Program. 

Applying GIS: Yesterday, Today, and Tomorrow

In the past, APS built a strong foundation with its Esri GIS. Its system is integrated with Schneider Electric’s Advanced Distribution Management System (ADMS) and CYME network analysis package. 

Today APS is moving its GIS to nearly all employees in the company with simple-to-use mobile and web apps. In addition, APS is in the process of installing Spatial Business Systems’ (SBS) Automated Utility Design (AUD) to streamline the design of GIS work streams. 

APS is still not satisfied. Its vision is to add more analytics. This involves crafting more dashboards for insight into the progress of projects. APS plans to use Esri’s demographic tools to gain additional insight into the relationship of its service to its diverse population. It plans to ramp up its use of GIS as a tool to analyze and understand its system from a customer perspective, focusing on customer experience, especially through the lenses of environmental, social, and governance strategies.

APS recently subscribed to a new Esri product that combines the convenience of a single learning management system (LMS) with the company’s high-quality e-learning resources created by experts in Esri technology and adult learning.  Esri Academy LMS integration  makes Esri’s extensive collection of e-Learning resources available to APS to enhance workforce expertise with GIS software. The LMS integration will be a key component to administering training to future GIS power users and proliferating the use of the system across the enterprise.

APS has fully embraced a geospatial strategy through its journey with GIS. In the past, the GIS team built a complete, accurate, and integrated system of record. Today, APS continues to expand its GIS reach as a system of engagement, aiming to reach its over 6,000 employees. Finally, APS expects to expand the system of insight for better decision-making for its employees, customers, and shareholders.

Learn more about Esri at  our Electric Utilities homepage , including  further Esri successes in Grid Modernization . 

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Esri software is deployed in more than 350,000 organizations including the world's largest cities, most national governments, and 75 percent of Fortune 500 companies. 

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The Intelligent, Responsible, and Humane Side of Social Media: A Case Study of a Partnership Between UP Police India and Facebook Saving Lives

• Published: 13 April 2024

Cite this article

• Amit Kumar 1 , 2 &
• Vibhuti Gupta   ORCID: orcid.org/0000-0002-8109-0890 3  

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The purpose of the case study is to demonstrate how social media and police (law enforcement) may work together in a thoughtful, ethical, and humanitarian way. By fusing human intelligence with intelligent systems, the case study contends, extraordinary accomplishments can be achieved. Additionally, it underlines the importance of the public-private partnership (PPP) model, in which the joint efforts of two parties; Uttar Pradesh Police (UPP) India and Facebook, representing the public and private sectors, respectively produced incredible results. Phenomenal achievements were made possible by this relationship, and numerous suicide attempts were averted. The case study reviewed cases between March 2022 and February 2024 and found that 321 precious lives were saved due to this partnership. The case study demonstrates how Facebook’s algorithm works to spot any posts that contain language that suggests self-harm or suicide and to issue a warning in the hopes of protecting a precious life. The UP Police’s social media unit gets notified of such posts, thanks to Facebook’s random forest learning algorithms, which then take action to save a priceless life. The case sheds some insight on the privacy concerns of Facebook account holders, the use of sophisticated technology by the police authorities, and its ethical implications as well. It provides some insight into the relevance of management principles to public services.

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Source: Model Adopted from Gupta and Kumar  2021

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The authors did not receive support from any organization for the submitted work. No funding was received to assist with the preparation of this manuscript. No funding was received for conducting this study. No funds, grants, or other support was received.

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The authors have no relevant financial or non-financial interests to disclose. The authors have no competing interests to declare that are relevant to the content of this article. One of the authors is a Police Officer, working in the same department but at a different posting. However, all authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. The authors have no financial or proprietary interests in any material discussed in this article.

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Kumar, A., Gupta, V. The Intelligent, Responsible, and Humane Side of Social Media: A Case Study of a Partnership Between UP Police India and Facebook Saving Lives. J Police Crim Psych (2024). https://doi.org/10.1007/s11896-024-09667-w

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DOI : https://doi.org/10.1007/s11896-024-09667-w

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These challenges, coupled with the COVID-19 pandemic, forced the FAA to reassess the way maintenance is performed and to use data to help weigh different investment options and better define financial priorities. It was clear that the FAA needed to apply data to answer critical business questions, such as which preventive maintenance interventions are most critical for the safety of the National Airspace System (NAS).

As organizational leaders wrestled with these different issues and the challenge of weighing diverse investment options, the FAA turned to the EY organization. FAA had lots of data; in fact, leadership frequently remarked that “they are data rich and insight poor.” But, how do could FAA access data that is spread across vast systems? Our role was to help them source, process and integrate millions of records from multiple types of different data sets.

Unstructured data was translated into structured data that could be used for analysis by employing natural language processing (NLP) to find commonalities in data and identify parts in maintenance logs. A pipeline was created to push data through and allow the FAA to utilize sensors to monitor issues and know where to send technicians to address them. These efforts created a reduction in maintenance hours and an enhanced planned maintenance schedule through remote monitoring activity on a broader scale.

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Data-driven asset monitoring and operational efficiency are only two of the realized benefits of a predictive maintenance approach. The FAA is able to control the cost of maintenance for both labor and parts and can source parts when needed. It also can develop a plan to build internal analytics capabilities that will lead to more accurate maintenance reporting.

We helped the FAA identify process and data quality improvement opportunities to enable prediction of equipment failures — resulting in 75% to 90% accuracy three to seven days in advance.

The journey from a reactive to a predictive maintenance capability

Aligning the maintenance maturity model with complex and evolving business realities.

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Like most government organizations today, the FAA was focused on varying levels of reactive, preventive and condition-based maintenance. Then, the COVID-19 pandemic hit and everything shut down. Work processes had to change as employees were directed to stay home. It was a wake-up call that demonstrated the need to change quickly and perform less planned maintenance. By understanding its data and monitoring it remotely, the FAA found that the overall system could be better optimized. Today, the agency has a more rounded perspective on what is driving the cost of operations and maintenance and which embedded technologies and learning models will provide insights to drive better business decisions and guide future investments.

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AI in Government: Examples, Challenges & Best Practices [2024]

Artificial intelligence adoption is increasing. 90% of top businesses have an ongoing AI investment. And customers who are delighted with the personalized experiences they get from brands, thanks to AI, start to expect the same experience from every organization they engage with.

According to Gartner , governments need to focus on scaling digital initiatives because more than 85% of governments without a total experience strategy by 2023 will fail to transform services. As a result, governments are following in the footsteps of businesses and are willing to invest in AI. For example, recently, Danish architecture firm BIG and Chinese tech company Terminus revealed their plans to build an “AI City” project named Cloud Valley in the south-western Chinese city of Chongqing.

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What does artificial intelligence offer to governments?

What AI offers to governments is similar to what AI offers to the private sector. These offerings can be classified into three categories:

• Savings due to operational efficiency: According to Governing magazine,  53% of state and local officials surveyed had excessive paperwork burdens that impacted their ability to get work done. According to Deloitte , automation of federal government employee tasks could save between 96.7 million and 1.2 billion hours annually. The same Deloitte study also reports that automation and AI have the potential to save between $3.3 billion and $41.1 billion. For automation opportunities, check our articles on RPA and intelligent automation in government .
• New/improved services: Citizen-facing applications like self-driving shuttles and personalized education improve the quality of services governments deliver to citizens.
• More data-driven decision making: Governments are collecting an abundant amount of data every day. Yet, without an accurate analysis, data is not adequate for actionable insights. Better decision making has the potential to both improve services and save costs.

What is the level of government’s interest in AI?

61% of government decision-makers state that AI is at least moderately functional in their organizations, according to a 2021 survey by KPMG. Moreover, 79% of them believe AI will improve bureaucratic efficiency.

What are AI applications/ use cases in government?

Government services, social welfare.

• identifying patterns in claims such as the same phone number or applications written in the same style
• processing social media profiles to check if there are any conflicting information compared to the applications. However, this may be perceived as an infringement of personal data in many countries.
• Building a machine learning algorithm that cross-checks patients with similar symptoms from different locations, detects patterns, and warns when an outbreak might occur.
• Using graph analytics, as in the case of China during COVID-19, to identify contacts with a known carrier of the virus
• Triaging patients: Though triaging patients has been used in hospitals’ emergency services, triaging became necessary after coronavirus spread. AI-powered tools can analyze patient data to predict patients’ risk scores so that doctors can prioritize.
• Handling citizens health related queries : Public health was endangered by misinformation about pandemic measures, particularly at the beginning of the COVID-19 pandemic, as well as ambiguity about what citizens might do to protect or quarantine themselves. Conversational AI technologies can assist governments in informing their people and assisting authorities in responding to frequently requested queries about health.

Domestic security

• Predicting a crime and recommending optimal police presence:  AI can be used to identify patterns in policing heat maps to forecast where and when next crimes are likely to occur as in the graph below. Though AI algorithms’ fairness in predictive policing is still questionable and it doesn’t favor minority groups , AI-based recommendations can be used to identify optimal police patrol presence.  Solutions like Palantir enable it to conduct geo-searches around locations of interest and view relevant arrest data for law enforcement.

• Surveillance: AI surveillance describes the process of ML and DL-based algorithms analyzing images, videos, and data recorded from CCTV cameras. Though techniques like facial recognition enable governments to identify people from video records, the ethical side of AI-powered surveillance is still controversial. For instance, IBM stopped offering, developing, or researching facial recognition technology for mass surveillance due to racial profiling and violations of basic human rights and freedoms.

• Autonomous drones: Autonomous military d rones are also referred to as Unmanned combat aerial vehicles (UCAV), are military weapons that carry combat payloads like missiles are usually under real-time human control, with varying levels of autonomy. One of the latest examples of military drones, though they were mostly piloted by humans, were used by Azerbaijan at Nagorno-Karabakh in the combat against Armenia.

Transportation

• The shuttle segment is less regulated than the automotive market.
• Consumers’ trust in autonomous shuttles is higher than other autonomous vehicles. According to a survey conducted by the University of Michigan, 86% of riders said they trusted shuttles after riding in it, as did 66% of nonriders. On the contrary, another survey highlights that 70% of Americans would not trust an autonomous vehicle.

• Monitoring social media to identify incidents:  Traffic congestions are an issue for citizens and governments alike. Congestions happen mostly due to accidents on roads, and it negatively impacts travel times, fuel consumption, and carbon emissions. Artificial intelligence can be used to monitor social media to identify tweets about recent accidents. Here is a research paper from the University of Wolverhampton on incident detection using NLP techniques.

• Personalized education: ML algorithms can help provide personalized education irrespective of the number of students. AI can analyze students’ progress and find the gaps  between what is taught and what is not yet understood.
• Marking exam papers: At the University of Michigan, students receive immediate feedback on their writing, even in large classes, thanks to AI. Automated text analysis reviews students’ work to identify strengths and recommend revisions.
• Classifying emergency calls based on their urgency: Voice recognition technologies & ML algorithms can help governments automate emergency call lines by understanding and categorizing queries.
• Fire prediction: ML & DL algorithms map the dryness of forests to predict wildfire better.

Public relations

• Scheduling meetings
• Answering FAQs
• Directing requests to the appropriate area within government
• Filling out forms
• Assisting with searching documents
• Helping out recruitment (e.g., United States Army )
• Checking on social media posts for citizen feedback purposes: Every minute, Twitter users tweet 347,222 times.  By processing a vast amount of data with AI, the public sector can gain feedback from citizens to improve their services.
• Document automation includes extraction and inputting of invoices, architectural drawings, certificates, charts, drawings,  forms, legal documents, and letters.
• Drafting documents & announcements: Automated content can be generated with Natural Language Generation (NLG), which is already being used in some newsrooms.
• Translation: AI enables a more efficient translation of government information. For example, the PyeongChang Winter Olympics in Korea will be using AI-based real-time translation services.

What are the challenges of AI in the public sector?

Unemployment is the scariest part of artificial intelligence if we disregard the hypothetical scenario of an AI takeover. Governments, as public service providers, should be concerned about the impact of AI on human jobs in government. To mitigate the impact of potential unemployment due to automation, governments need to ensure that humans focus on higher value-added tasks or move on to the private sector if their current tasks are going to be automated.

According to the European Commission’s Eurobarometer survey that presents European citizens’ thoughts on the influence of digitalization and automation on daily life

• 74% of respondents expect that more jobs will disappear than new jobs will be created due to the use of robots and artificial intelligence.
• 72% of respondents believe robots steal peoples’ jobs.
• 44% of respondents who are currently working think their current job could at least partly be done by a robot or artificial intelligence.

AI algorithms may contain biases due to prejudices of the algorithm development team or misleading data. Though building an unbiased AI algorithm is technically possible, AI can be as good as data, and people are the ones who create data. Therefore the best thing governments can do for AI bias is minimizing it by applying best practices .

Explainability

It is not easy to explain how all AI algorithms arrive at their predictions (i.e., inferences) however there are technical approaches being developed to overcome this shortcoming.

This is problematic for the public sector, where providing a rationale for decisions is more important than the private sector since the public sector is accountable to the public. In contrast, the private sector is foremost accountable to shareholders.

Accountability

Accountability of AI systems is an issue of AI ethics. Governments are like the US and the  UK are introducing new laws about companies’ AI algorithms’ accountability. It will be hypocrisy if governments and companies are not held accountable for accidents & false predictions their AI algorithms make.

Check our article on responsible AI to learn more.

Difficulty of transformation

AI transformation in government is difficult because

• Age of public servants : The workforce at the government is older than the private sector, making it potentially harder to implement to the culture change. According to U.S. Census Bureau research , about 24% of public-sector workers are millennials, compared with 34% in the private sector.
• More ambiguous/complex KPIs:  Compared to the private sector’s drive for profit, governments have more complex, harder-to-measure goals. As a result, government KPIs tend to be more activity-oriented rather than result-oriented making it harder to measure improvements.
• Number of stakeholders: Government watchdogs, labor unions, and opposition parties are all stakeholders whose view of AI will shape how the public will perceive AI in government. This makes communication about transformation projects even more important.

What are the best practices of AI for governments?

Some best practices of AI transformation are:

• Involve people more: Investments alone are not enough for AI projects. Human and processes aspects also help achieve success from AI projects.
• Enhance technology infrastructure: AI deployment may require the restructuring of the technology infrastructure for faster system integration.
• Improve data quality & collection:  AI is data hungry. Collecting high quality data is a prerequisite for numerous AI implementations.
• Involve the experts: Recruit professionals who are proficient in ML and AI deployments. AI consulting and custom AI development firms can provide the necessary experience and talent for governments.
• Reduce bias in AI: Follow best practices to reduce AI bias can also guide governments during their AI projects

Feel free to check our related article for more information.

Case studies

To learn more.

Leave us a comment if you know of other applications of AI in government. Here is a list of more AI-related articles you might be interested in:

• Artificial Intelligence (AI): In-depth Guide
• Future of AI according to top AI experts

You can also check out our list of AI tools and services:

• AI Consultant
• AI/ML Development Services
• Data Science / ML / AI Platform

And if you still have questions about AI applications in government, don’t hesitate to contact us:

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month. Cem's work has been cited by leading global publications including Business Insider , Forbes, Washington Post , global firms like Deloitte , HPE, NGOs like World Economic Forum and supranational organizations like European Commission . You can see more reputable companies and media that referenced AIMultiple. Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization. He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider . Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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Today, and good leaders matter more than ever. They must be stewards of the public trust with a passionate commitment to the public good, and they must demonstrate core values and critical competencies to achieve their agencies’ missions and desired impact.

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The Public Service Leadership Model seeks to set the standard for government leadership, outlining the core values and competencies that federal employees must demonstrate to best serve the public. The following case studies highlight public servants who have activated the model’s core principles to solve big challenges, drive impact and strengthen our country.

For decades, the federal government has worked to keep nuclear facilities around the world safe and secure. In the early 2000s, these efforts hit a snag when yearlong talks between the Energy Department and the Russian Defense Ministry stalled, leaving nuclear materials in the former Soviet country vulnerable to theft and misuse. Nicole Nelson-Jean, a recently hired 28-year-old working in the National Nuclear Security Administration’s Material Protection Control and Accounting Program, broke the logjam.

Arleas Upton Kea, the Federal Deposit Insurance Corporation’s former director of the Division of Administration, oversaw a rapid hiring surge and extensive culture change initiative that enabled the agency to meet the challenge of stabilizing and reinspiring confidence in the nation’s financial system during the 2008 recession.

When Sandeep Patel launched his career in government nearly a decade ago, he knew little about his new job at the Department of Health and Human Services. As an open innovation manager, his mandate was as abstract as it was critical: to help the agency use new tools and strategies to find innovative solutions to serious health challenges.

In 2014, a major crisis hit the Department of Veterans Affairs. Explosive reports claimed that the Phoenix Veterans Affairs Health Care System had for several years falsified data showing how long veterans were waiting to receive medical care. The VA is still making headlines today—but for different reasons. Thanks to its Veterans Experience Office and productive partnerships across and outside the VA, the agency has become a leading customer experience organization in government.

Each year, phony Medicare claims cost the American taxpayer billions of dollars and deprive those eligible for coverage—senior citizens, and people with disabilities and serious illnesses—of proper health care. These fraudulent schemes turn Medicare into a personal piggy bank for private interests who prey on the vulnerable and exploit the public good. One group, however, has protected this vital national asset with unprecedented success.

To solve pressing health challenges, Francis Collins has demonstrated a willingness to collaborate and engage others, a strong self-awareness with a unique blend of academic and emotional intelligence, a desire to lead change by taking calculated risks, and a steadfast focus on achieving results for individual patients. Throughout his four-decade career, Collins has leveraged these leadership competencies to improve the well-being of current and future generations worldwide.

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Determining the true value of a website: A GSA case study

Cleaning up: A hypothetical scenario

Consider this scenario: you’ve been told to clean up a giant room full of Things Your Agency Has Made in the Past and Now Maintains for Public Use . This means disposing of the Things that no longer add value, and sprucing up the Things that are still useful. How do you determine which Things belong in which category, especially when all the Things in that giant room have been used by the public, and available for all to see?

When the “things” we’re talking about are websites, this determination is often much more complicated than it might appear on the surface. This scenario is one facing web teams across the government, including at the U.S. General Services Administration (GSA), every single day. If you’re in this situation, consider all the ways you might begin to tackle this cleanup job.

Evaluating by visits

You decide to start by determining how many people visit each website each month. Delighted, you pull those numbers together and produce a chart that looks something like this:

The chart states that the 10 least-visited GSA websites had only about 66 visits in the past 30 days, whereas the top 10 websites averaged over 629,000 visits, and the agency average websites averaged over 244,000 monthly visits. So there you have it: clearly, it appears the websites with only 66 visits are the least useful and should be decommissioned. (Note that the low-traffic websites all show 66 visits because of the analytics tool’s statistical sampling methodology.)

However, you stop to examine one of the low-traffic sites. In studying it, you realize that it was never designed to have many visitors. Instead, it was designed to support a very small audience that only appears at random, unpredictable intervals; say, when a natural disaster strikes. Clearly, you don’t want to get rid of that website, since it’s meeting a specific need of a small but well-defined and important audience.

Through this consideration, you realize that using the number of visitors to determine the usefulness of a website incorrectly assumes:

• Each visit across all your websites is of the same value.
• Each audience, whether 66 people, or 629,000, have the same level of urgency and need for each website, even if one website is intended to serve a large, continuous audience, while another is designed to serve a small, irregular audience.

Since both of these assumptions are false, visitor numbers are not enough to determine the usefulness of a website. You need another evaluation tactic.

Evaluating by accessibility

After some consideration, you realize that all the websites have to be fully accessible to everyone, regardless of ability. You also have the tools and processes to help determine whether that standard has been reached. Excited, you start by assembling and running your automated accessibility tests.

Five websites stand out as having the worst accessibility errors, according to your tests. Clearly, these websites must go. As you prepare to get rid of them, however, you notice that the vast majority of the errors in the worst website are identical and all seem to originate from the same part of the website. You look closer and realize that the problem causing all those errors is actually quite basic and can be fixed easily, taking the worst website out of the bottom ranking. Looking at the other websites in your list, you realize that other errors that have surfaced are only errors in an automatic test, not a human one. Many of them aren’t on critical paths for the website’s use, so while they should be addressed, they are not meaningfully blocking access to the website.

That throws your entire evaluation into question: how can you possibly batch and judge the usefulness of a website by accessibility, if the severity and impact of each accessibility error varies so much? Instead, you must pair automated accessibility tests with manual testing to reach conclusions on the least accessible websites. That won’t help you quickly get rid of the lowest value websites, so yet another evaluation tactic is needed.

Evaluating by speed and performance

After considering the number of visits and the accessibility, you realize that an evaluation of usefulness needs to consider a basic question: is the performance and speed of the website reasonable? If a product is so frustratingly slow that people don’t use it, then nothing else matters.

To figure out which websites are so slow as to be essentially non-functional, you find a free online tool that tests website performance. Additionally, you get smart based on your previous experiments: this tool tests for a few different parameters, not just one element of performance. It then compiles these parameters into a single index score, so its results are compelling.

This performance metric shows you that, on average, your websites perform at 84% of a perfect 100% score, and there are a few low-performing websites at 26% performance or lower. This works for you; you know you need to get rid of your agency’s low-performing websites. As you’re planning to decommission these sites, however, a user visits one of them to complete a task and provides some feedback.

Evaluating by customer research

The user waits while the website slowly loads. Then, they interact with the website and exit the page. To gauge their satisfaction, you prompt them to give you feedback on the page by asking, “Was this page helpful?” The user shares:

“This website does work; it just works slowly. I’m willing to wait, though, because I need the information. There’s nowhere else to get this information, so please don’t get rid of this website; I have to come back and get information from it every month.”

After taking this customer research into account, you realize that visits, accessibility, performance, and speed do not, on their own, fully reflect the website’s value, so you still don’t know which websites to decommission.

At this point, you’ve discovered that evaluating websites is a multidimensional problem — one that cannot be determined by a single, simple metric. Indeed, even when you consider several metrics, your conclusions lack a customer’s perspective.

Determining the value of agency websites therefore must use an index that is not just composed of similar metrics (like the performance index) but is in fact a composite index of different datasets of different data types. This approach will allow you to evaluate the website’s purpose, function, and ultimately, value, to your agency and your customers. This aggregation of dataset types is known as a composite indicator.

Methodology: The Enterprise Digital Experience composite indicator

This is the story of evaluating websites in GSA. Websites seem simple to evaluate: do they work or not? But in truth, they are a multidimensional problem. In taking on the definition and evaluation of GSA public-facing websites, the Service Design team in GSA’s Office of Customer Experience researched and designed a composite indicator of multiple data sets of different types to evaluate the value of websites in GSA. Since 2021, we’ve been doing this by examining six things:

Accessibility , scored by our agency standard accessibility tool ( quantitative data, 21st Century IDEA Section 3A.1 )

Customer-centricity , scored by a human-centered design interview ( qualitative data, 21st Century IDEA Section 3A.6 and OMB Circular A-11 280.1 and 280.8 )

• Stated audience : Can the website team succinctly and precisely name their website’s primary audience?
• Stated purpose : Can the website team succinctly and precisely name their website’s primary purpose?
• Measurement of purpose : Does the website have a replicable means to measure if the website’s purpose is being achieved?
• Repeatable customer feedback mechanism : Does the website team have a repeatable customer feedback mechanism in place, such as an embedded survey, or recurring, well-promoted and attended meetings, or focus groups with customers? (Receiving ad hoc feedback from customer call centers or email submissions does not meet this mark.)
• Ability to action : Does the website team have a skillset that can contribute to rapidly improving the website based on feedback and need, such as human-centered design research, user experience, writing, or programming skills?
• Ability to measure impact : Does the website team have the ability to measure the impact of the improvements they implement? Have they devised and implemented a measurement methodology specifically for their changes (an ability to measure impact) or do they rely solely on blanket measures such as Digital Analytics Program data (no ability to measure impact)?

Performance and search engine optimization , scored by Google Lighthouse ( quantitative data, 21st Century IDEA Section 3A.8 )

Required links , scored by the Site Scanning Program ’s website scan ( quantitative data, 21st Century IDEA Section 3A.1 & 3E )

User behavior, non-duplication , scored by Google Analytics with related sites ( qualitative + quantitative data, 21st Century IDEA Section 3A.3 )

U.S. Web Design System implementation , scored by Site Scanning Program’s website scan ( qualitative + quantitative data, 21st Century IDEA Section 3A.1 & 3E )

View all sections of the law and the circular mentioned above:

• 21st Century IDEA (Public Law No. 115-336)
• OMB Circular A-11 (PDF, 385 KB, 14 pages, 2023)

We visualize this evaluation in website maps, rendered as charts that are available internally to GSA employees. This helps us see examples of good performers, such as Website A (on the left), and not-so-good performers, like Website B (on the right.)

In addition, these charts, like all maps [1] , contains some decisions that prioritize how the information is rendered. They include:

• An equal weight to all datasets and data types, regardless of fidelity . In the charts above, the slices spread out from 0 along even increments. Our measurement of customer-centricity gives equal weight to whether a site proactively listens to their customers, as well as to whether it has the resources to implement change.
• A direct comparison by slice . For example, our customer-centricity slice gives the same amount of distance from the center for listening to its customers as our required links slice gives for including information about privacy, regardless of the fact that customer listening is foundationally different (and more complicated) as an activity than including required links.

We made these decisions because to weight all of the metrics would be to travel down the coastline paradox [2] , meaning: we had to identify a stopping point for measurement and comparison that is somewhat arbitrary because, paradoxically, the more closely we measure and compare, the less clear the GSA digital ecosystem would become. These measures are the baseline because, broadly, they are fair in their unfairness: some things are easier to do, and some things are harder, but what is “easier” and what is “harder” differs depending on the resources available to each website team.

But even in comparing websites using charts and maps containing multiple dataset types, we’re missing some nuance. “Website A” is a simple, informational site, whereas “Website B” contains a pricing feature, which introduces additional complexities that are more difficult to manage than simple textual information. To give visibility to this nuance, the Service Design team uses these maps as part of a broader website evaluation package, which includes qualitative research interviews and subsequent evaluation write ups. These are sent to every website team within three weeks after we conduct the research interview. Taken together, the quantitative and qualitative data in the website evaluation packages allow GSA staff to consistently measure how digital properties are functioning, and what their impact is on customers.

Concluding which websites should exist

The reality is: value exists in dimensions, not in single data points, or even in single datasets. To further complicate things, the closer you look at single datasets, the more your decision-making process is complicated, rather than clarified. This is because each data type and each data point in complex systems can be broken down into infinitely smaller pieces, rendering decisions made based on these pieces more accurate, but also of smaller and smaller impact. [3]

None of the measures in the Enterprise Digital Experience composite indicator or their use as a whole pie results in an affirmation or denial of the value of a digital property to the agency or to the public; value will always exist as an interpretation of these datasets. The indicator can tell us how existing sites are doing, but not whether we should continue supporting them.

To understand whether a website is worth supporting and how to evolve it, the Service Design team pairs qualitative and quantitative data with mission and strategic priorities to evaluate which websites to improve, and which to stop supporting. To achieve this pairing, three elements must come together:

• Technical evaluations
• Regular dialogue with each website’s customers, including internal stakeholders and leadership
• Enterprise-level meta-analysis of a digital property’s functions in comparison to other digital properties

Customer dialogue is the responsibility of each team, and technical evaluations are readily available, thanks to tools like the Digital Analytics Program (DAP), but enterprise-level meta-analyses require a cross-functional view. This view can be attained through matrixed initiatives like GSA’s Service Design program, or cross-functional groups like GSA’s Digital Council, in collaboration with program teams and leadership.

From an enterprise perspective, the next phase in our evaluation of GSA properties is to apply service categories to each website, to better understand how GSA is working along categorical lines, instead of businesses or brands. Taxonomical work like this is the domain of enterprise architecture. Our service category taxonomy was compiled by using the Federal Enterprise Architecture Framework (FEAF) [4] as a starting point, and crosswalks a website’s designed function with its practical function, evaluated through general and agency use.

We’re starting to leverage service categories, and working with teams to create a more coalesced view of website value as we do so.

What can I do next?

Review an introduction to analytics to learn how metrics and data can improve understanding of how people use your website.

If you work at a U.S. federal government agency, and would like to learn more about this work, reach out to GSA’s Service Design team at [email protected] .

Disclaimer : All references to specific brands, products, and/or companies are used only for illustrative purposes and do not imply endorsement by the U.S. federal government or any federal government agency.

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