A Policy Framework Towards the Use of Artificial Intelligence by Public Institutions: Reference to FATE Analysis

A Policy Framework Towards the Use of Artificial Intelligence by Public Institutions: Reference to FATE Analysis

DOI: 10.4018/978-1-7998-9609-8.ch002
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The greatest revolution in technology to date is artificial intelligence (AI). With rapid technological advances, government agencies, business, and academia are looking for guidance and standards around artificial intelligence. Several of the AI applications can be viewed as algorithms that make decisions, raising the question of when society will attempt to delegate decision making processes to computers. A crucial practical application should be in mind while creating a theoretical taxonomy about decisions and their context, in terms of norms, laws, and policies. Using artificial intelligence (AI), this study proposes a policy framework for the country by analysing FATE (fairness, accountability, transparency, and explainability). This study examines three core areas, namely public policy, artificial intelligence (AI), and decision making. As a means to better understand public policy, a description of how decision-making processes are based on the concept of artificial intelligence is presented.
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In today's technological age, artificial intelligence (AI) has become a major revolution that will disrupt every aspect of modern life (Chen, 2018). Various industries have already adopted AI to some extent. Similarly, the adoption of Artificial Intelligence (AI) technologies by government is being based on 'success stories' generated by the private sector (in areas such as health, taxation, and education). AI assists in this extremely complex process while offering advantages of automation apply, such as low human dependency, reliability, and efficiency. Artificial intelligence is helping companies sort through data and identify patterns that could empower them to make better decisions, revealing previously hidden information, (Pencheva, I.,et.al 2020) Data-driven decision-making is at the heart of this advancement by helping public entities make better access of data. By the help of AI, better decisions and governance with this latest generation of techniques can be achieved. Some states have already seen the potential of AI to help guide their decisions. With more access to data sources, applications supported by artificial intelligence will become more common in government . Again, Artificial intelligence tools reduce judgmental errors, which can be seen in public policy applications that use AI which reduces uncertainty associated with human limitations, thereby improving performance.

A number of countries across sectors, numerous government bodies, public organizations are leveraging data, artificial intelligence, and algorithms in their decision-making processes. Also, government is using big data analysis system for swift policy decisions, by considering artificial intelligence (AI) for making quick decisions, (de Sousa, W. G et.al.2019) To facilitate this, it has started working on implementing policy decisions defined by AI and begun basic research to facilitate this. Also, the combination of big data and machine learning algorithms could enable public sector organisations to improve their operations and provide better service delivery models. According to a 2017 report by Deloitte Insights, AI could free up government workers’ time by up to 30% within five to seven years, (articles/3832_AI-augmented-government/DUP_AI-augmented-government.pdf) It’s also expected to make routine tasks more efficient. AI has the potential to save the government a huge amount of money. It could also help avoid waste and fraud. So, AI is being used by many government customers to improve processes and cut costs. Most national strategies support the use of AI in the public sector, which is aimed at improving the quality of public services and increasing efficiency. Since, governments have access to a wealth of data, a number of types of information are accessible to the government, including data generated by organisations, programs and external agencies, as well as data generated by the Internet of Things (IoT). Government portal services are increasingly improved through the use of artificial intelligence-guided chatbots as tools for improving artificial intelligence, (Wang, Y et.al. 2020) .

Moreover, while a number of techniques have been developed to aid in research in the field of AI, understanding how AI will impact workers, organizations, the economy and government still unexamined (Faraj et.al.2018; Brynjolfsson & Mitchell, 2017). After technology has been adopted and diffused, it takes years for the production processes, the performance of organizations, legal issues, and social issues to transform, (Brynjolfsson & Mitchell, 2017). Furthermore, the privacy of personal information is a critical issue raised by AI, (Butterworth, 2018; Čerka et al., 2017), as a result public sector activities could be affected (positively or negatively) by these factors. These considerations lead to recognize a large gap in knowledge regarding AI's application in the public sector; although initiatives exist in several governmental sectors, it is still necessary to systematize information about AI's motivations, processes, outcomes, and results (Liu & Kim, 2018; Fernandes et al., 2018 Kouziokas, 2017; Pan, 2016; Ayoub & Payne, 2016). Since, the use of AI in government has been identified as a promising area of application this study demonstrated how different public administrations in the public domain are exploring the possibility of using AI to improve their policies and operations. Hence, the potential of AI in the public sector needs to be tapped, and extensive research is still required to truly harness the technologies and to address important issues/needs, (Androutsopoulou, A., et.al.2019) However, public sector organizations face challenges in adopting and implementing artificial intelligence as well as implementing these technologies in government(Kankanhalli, A et.al 2019), hence a comprehensive framework is recommended .

Key Terms in this Chapter

Data Privacy: It refers to the information privacy and protection of data and concern with the proper handling of sensitive data.

AI Deployment: Deployment is the method by which you integrate a machine learning model into an existing production environment to make practical business decisions based on data. It is one of the last stages in the machine learning life cycle and can be one of the most cumbersome.

Artificial Intelligence: AI is the development of computer systems that are able to perform tasks that would require human intelligence.

Policy Framework: A policy framework is document that sets out a set of procedures or goals, which might be used in negotiation or decision-making to guide a more detailed set of policies, or to guide ongoing maintenance of an organization's policies.

Governance: Governance is all the processes of interaction be they through the laws, norms, power or language of an organized society over a social system.

FATE: Fairness, accountability, transparency and explainability.

Government: Government, the political system by which a country or community is administered and regulated.

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