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Political and Public Policy Data Science

Introduction

The rapid development has brought technological aspects like data science into the major limelight for better governance. From the ages where the consensus decision was made after long years and months of discussion, to the modern age where decision making is a quick game Artificial Intelligence has bridged all the gaps. The majority of Governments’ across the world implement data science algorithms to deliver efficiency and effectiveness in their operations for societal welfare. Guess what; even this chase has taken a competitive turn so the Governments are all geared up to let data science talk their words and perceptions.

Use Cases of Political and Public Policy Data Science

Data Science features have proved their significance in all spheres of human existence and related matters too. One such sector with wide application of Data Science is Politics and Public Policies and political department. The strength of the strong governance lies in its effective planning backed by efficient implementation and it becomes possible with the support of Data Science.

Use CaseDescription
Identify Tax EvasionIt is the most normal tendency of the citizens to evade tax by misrepresenting real affairs and it leads to huge losses for the governments. Thus, to mitigate such issues Government uses modern data science algorithms that can easily detect tax-evading practices and patterns based on the available financial data.
DefenseIt is the priority concern of every government and a sophisticated matter too. As a result, full-proven planning and strategy implementation backed by healthy infrastructure is the core requirement of the department. Using the AI-driven data science concept predicting, tracking, and monitoring the border activities, terrorist approach, and logistics requirement become smarter and simpler.
Cyber SecurityA recently growing threat of cyber attacks, hacking; frauds, etc has created an alarming situation in the entire world. The sophisticatedly planned fraudulent and cyber bullying activities have made it difficult for people to identify the authentic players. Thus, the data science technique helps to monitor the systems and flag suspicious activities in advance.
Infrastructure DevelopmentThe infrastructure is the first visible indicator of a nation’s well-being. Education, healthcare facilities, and efficient transportation are the key elements where data science methodologies have created better difference by empowering the data collection, processing, analysis, and visualizing algorithms. Data science helps to identify the growth areas, arising threats, and recommendations relating to infrastructure development.
Street Crime AwarenessModern data science algorithms have brought big relief in the criminal world. Besides predicting criminal activities in most cases, data science plays a crucial role in investigating crime and analyzing the potential future threats. The improvised surveillance mechanism has made a safer difference in how the world looks at the crime and criminal world.
Law EnforcementThe process of framing rules and regulations certainly requires support from data science mechanisms, but enforcement of the law is another field where data science has acts as a convenient partner. The potent data science techniques help to convert available data into actionable insight by tapping the operational disputes and substituting them with solutions during the execution process.
Business EcosystemGovernment acts as the central factor while establishing and maintaining the business ecosystem. With the entire world heading towards entrepreneurship culture, the arising cases of de-registered firms are the most common observation. The data-driven algorithm is becoming the helping hand of the government for detecting the appearance of the company’s information in the financial data and helps to disclose illegal activities.
Resource ManagementThe resource being limited seeks a better allocation plan considering the nation’s population. Thus, data science emerges as the support system to bring revolution in the fuel, electricity, water, air, coal, and related departments. By providing the predictive comparative study between application and availability of such resources.

Metrics Used for Political and Public Policy Data Science

Every action results in some positive, negative or neutral reactions and this is termed as performance evaluation which is done keeping in mind the essential metrics.

Metric TypeMetricDescription
Financial MetricsBudgeting RatioIt is the quotient of government revenue and operating cost which is divided by the population size. Hence, falling revenue shall be considered as an alarming situation and improvement shall be placed in to receive rising revenue.
Bond RatingIt is a measure of financial stability which signifies the credit and performance quality of the government entities. The higher bonding rate reflects the lower interest rates and vice-versa. Thus, a bond rating is assigned by assessing the paying capacity of the government.
Personnel & Operating Cost RatioThe important metric refers to the ratio of personnel admin cost to the operating cost, as it indicates Governments’ ability to deliver effective services while maintaining the pre-determined budget.
Solvency Indicator Debt Per CapitaIt is a relation of government debt and population which provides insight into the debt-paying potential of the government.
Operational MetricsAudit FindingsIt refers to the total count of reported issues in the public entities to bring improvement and pay attention to the existing or growing opportunities.
Regulation QualityThe wholesome aim of the metric is to create room for better progress through quality practices. It requires proper consultation with related parties, drafting requirements, and suggesting regulatory alternatives.
Service MetricsHousing MetricsHere, the analysis of chronically homeless people is drawn and the existing gaps are identified to ensure proper shelter to the people in the country.
Infrastructure MetricsEvery nation and state is driven by a pre-determined budget allocation. As a result, infrastructure development accordingly takes place which leads to the creation of progressive facilities..
Environmental MetricsPopulation growth often leads to scarcity of resources. Resources, being in ultimate control of government undertakings shall be sustainably used. Also, the resource allotment should establish a balance between the environment and public expectations.
E-Government MetricsThe online functioning of the government can be eased out with the e-government metric where all the online tools and algorithm serves as the perk.
Citizen MetricsResident SatisfactionThe government rules and regulations are framed keeping in mind the satisfaction level of the residents. Such regulations are related to health, education, finance, etc.
Public ParticipationTo allow the general public to feel valued government focus on creating several participating programs where opinions, talents, and suggestions of the people are welcomed.
Voter TurnoverVoting System is the strength of the democratic nations at large. It facilitates the decision-making process of the authorities. Thus, the voting process shall be fair and authentic in nature to reduce voter turnover.
Human Resource MetricsEmployee Retention RateIt is the most important human resource metric that focuses on creating a healthy work and pay culture so that employee retention can be reduced. This leads to a reduction in hiring costs too.
Workforce DiversityEvery government focuses on creating an inclusive workforce blend in its organization. As a result, it considers the timely evaluation of the organizational culture so that monopoly, if exists can be removed.

Examples of Political and Public Policy Data Science

Though, the beneficial application of data science for government is not an untold story anymore yet the field requires immense research on the subject to bring its potential to the limelight. Some of the rare and prominent examples of Government data science are:

  • The data science algorithms have helped New York City to identify eligible residents for Earned Income Tax Credit. Moreover, it has also played a significant role in analyzing the traffic data to indicate the need for new road laws in San Francisco.
  • The police department of Virginia’s Fairfax and Homeland Security Investigations in New Orleans has reduced child trafficking cases using Data Science. On average 75% of child trafficking takes place through online advertising. Considering the fact Defense Advanced Research Project Agency (DARPA) in consultation with technology experts has developed applications to identify highly vulnerable children, locate and rescue them.
  • Using the AI technologies Las Vegas health department has analyzed more than 16,000 tweets indicating the food poisoning cases. It has helped the department to detect venues accurately and eradicate the risk of public hazards.
  • In Dubuque, data science machinery was used to work out the city plan to install and monitor water meters. As result, it led to an increase in leak detection by eight times and helps to conserve water more than 50 million gallons .
  • The Indonesian Government collaborated with local start-ups to manage predicted floods in Jakarta. The AL and ML-driven data science agencies have helped to identify flood locations and expedite quick response by communicating alerts. As a result, the flood created lesser panic and loss.
  • The UK-based Behavioral Insights Team (BIT) uses Data science algorithms t study traffic in East Sussex. With the appropriate data collection, the team is able to identify drivers at high risk of accidents owing to the high speed, rash driving, etc. As a result, timely intervention leads to reduced on-road calamites by 20%.
  • In Durham, the North Carolina police department used AI-driven data science technology to observe the pattern of criminal activities and identify hotspots. As a result, it leads to quicker intervention and reduced violent crime by 39% between 2007 to 2014.

Final Words

All the ongoing data science use cases in Government and political sector are quite evident that data scientists have a future full of possibilities and opportunities. The big moves of the Governments based on scientific data have always helped to prevent the majority of civilians from disastrous situations which were predicted accurately well in advance. As a result, it has led to the growing competency of government and departmental growth too. Thus, the need for an hour is to bridge the skill gap, by employing required number of data scientists for performing the efficient role.

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