How to Create Intelligent Governments with Artificial Intelligence

How to Create Intelligent Governments with Artificial Intelligence

How to Create Intelligent Governments

Artificial Intelligence (AI) is opening up more opportunities for governments and citizens by combining human creativity with technology to drive progress in our modern society. 

The use of technology will change every sector: 

  • Primary sector of the economy (the raw materials industry, from energy to agriculture)
  • Secondary sector of the economy (manufacturing and construction)
  • Tertiary sector of the economy (the service industry)
  • Quaternary sector of the economy (information services)
  • Quinary sector of the economy (human services)

Artificial intelligence can reduce bureaucracy, deliver better public services for the benefit of citizens and enhance efficiency through automating routine government processes, coordination in the public administration.

Smart governments are applying intelligent digital technologies, such as AI and ML algorithms, and smart and sustainable solutions to improve bureaucratic efficiency and government’s decision making, foster positive relationships with citizens and business, or solve specific problems in critical fields such as health care, police, military, national defense, security services, taxation, waste management, water management, electrical grids, telecommunication networks and environmental protection.

How Artificial Intelligence Can Help Governments

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Image Source: Deloitte

Artificial intelligence can provide better automated services and deliver more security to citizens. Other technologies such as the Internet of Things (IoT), cloud computing, analytics, and blockchain, have triggered a shift towards a more intelligent society.

While AI creates new possibilities, it also invokes ‘angst’ and mistrust: the fear of job losses, or a world dominated by machine-powered intelligence instead of humans. The introduction of AI needs to go hand-in-hand with good governance models and ethics. 

Together with businesses, governments are forming AI strategies that steer the use of intelligent technologies related to fairness, safety, data privacy, transparency, citizen engagement, and the future of work.

What is Narrow AI?

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Image Source: Chris Noessel

Narrow AI is a term used to describe artificial intelligence systems that are specified to handle a singular or limited task. The antithesis to Narrow AI, sometimes referred to as weak AI, is called strong AI. Strong AI, unlike Narrow AI, is capable of handling a wide range of tasks rather than one particular task or problem. This variation of artificial intelligence can be roughly conceptualized as a foundation for neural networks emulating sentience or consciousness.

The OECD defines an Artificial Intelligence (AI) System as a machine-based system that can, for a given set of human defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments.

‒ AI system: An AI system is a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. AI systems are designed to operate with varying levels of autonomy.

‒ AI system lifecycle: AI system lifecycle phases involve: i) ‘design, data and models’; which is a context-dependent sequence encompassing planning and design, data collection and processing, as well as model building; ii) ‘verification and validation’; iii) ‘deployment’; and iv) ‘operation and monitoring’. These phases often take place in an iterative manner and are not necessarily sequential. The decision to retire an AI system from operation may occur at any point during the operation and monitoring phase.

‒ AI knowledge: AI knowledge refers to the skills and resources, such as data, code, algorithms, models, research, know-how, training programmes, governance, processes and best practices, required to understand and participate in the AI system lifecycle.

‒ AI actors: AI actors are those who play an active role in the AI system lifecycle, including organisations and individuals that deploy or operate AI.

‒ Stakeholders: Stakeholders encompass all organisations and individuals involved in, or affected by, AI systems, directly or indirectly. AI actors are a subset of stakeholders.

The European Commission followed with a modified definition:

“[A]rtificial intelligence system” (AI system) means software that is developed with one or more of the techniques and approaches listed bellow and can, for a given set of human-defined objectives, generate outputs such as content, predictions, recommendations, or decisions influencing the environments they interact with. 

  1. Machine learning approaches, including supervised, unsupervised and reinforcement learning, using a wide variety of methods, including deep learning; 
  2. Logic-and knowledge-based approaches, including knowledge representation, inductive (logic) programming, knowledge bases, inference and deductive engines, (symbolic) reasoning and expert systems; 
  3. Statistical approaches, Bayesian estimation, search and optimization methods. [the EC Artificial Intelligence Act]

Types of Narrow AI Applications That Could be Used By Governments

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Natural Language Processing (NLP)  – is also called computational linguistics and presents solutions in understanding human languages through computational models and processes

Speech Recognition – enables a computer to identify the words that a person speaks into a microphone or telephone and convert them into written text

Computer Vision – AI applications from this category use some form of image, video or facial recognition to gain information on the external environment and/or the identity of specific persons or objects

Machine Translation – is a sub-field of computational linguistics that focuses on the use of software to translate text or speech from one language to another

Robotics – is an interdisciplinary field integrating mechanical engineering, electrical engineering, information engineering, mechatronics, electronics, bioengineering, computer engineering, control engineering, software engineering, and that includes the designing, construction, operation, and use of robots

Rules-based systems – (also known as production systems or expert systems) are the simplest form of artificial intelligence. A rule-based system is a way of encoding a human expert's knowledge in a fairly narrow area into an automated system

Machine Learning –  It is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the systems which can learn from data, identify patterns and make decisions with minimal human intervention9 .

Spam-filters in email programs: – detect and block unwanted emails.

AI in cybersecurity solutions –  protect networks, programs, and data from attack, damage, or unauthorized access.

Chatbots –  converse with people via voice interfaces or text messages.

Fraud detection – detects, prevents and manages fraudulent patterns in the data.

AI in policing or social services – support and/or drive decisions in fields such as law enforcement, crime prevention, public safety, children welfare, social programs.

AI in HR – takes on key HR tasks including hiring, retaining talent, training, benefits and employee satisfaction.

Some big concerns brought by NAI to the public sectors are:

  • An international, commonly agreed definition of AI does not exist, only as a machine reproducing the cognitive capacities of a human being, with different types of automated learning.
  • Maturity of AI implementation in public structures, organizations and programs, AI pilots/PoCs, a few use cases in production on a limited scale, scaling-up use cases in production.
  • Algorithmic biases in relation to gender equality, discrimination and racism and unethical public and personal data governance.
  • Explainability brings two notions with itself: interpretability and transparency.
  • Losing jobs for people. According to a Eurobarometer survey published by the European Commission, 72% of respondents believe robots steal the jobs of people.

Should Governments Be Run By Artificial Intelligence?

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Image Source: National Journal

More and more people are asking today: Should the government be run by artificial intelligence? 

The question is motivated with an increasing understanding: most problems we have on our Mother-Earth, from local poverty to global risks, are created by …non-intelligent governments, all failing to follow “the good governance principle”, at local, national, transnational or global levels.

Artificial intelligence can help governments in the following aspects:

  • Participation, Representation, Fair Conduct of Elections
  • Responsiveness
  • Efficiency and Effectiveness
  • Openness and Transparency
  • Rule of Law
  • Ethical Conduct
  • Competence and Capacity
  • Innovation and Openness to Change
  • Sustainability and Long-term Orientation
  • Sound Financial Management
  • Human rights, Cultural Diversity and Social Cohesion
  • Accountability

Governments should be run by artificial intelligence in the near future for more efficiency.

How AI Governments' Intelligent Systems Reflect The Needs Of Citizens

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Image Source: Accenture

Here are some examples of how AI/ML/D/ contributes to public policy objectives:

  • filtering state officials and government workers as to expertise, skills, competency,
  • knowledge and integrity, or meritocratic principles;
  • receiving employment benefits at job loss, retirement, bereavement, childbirth, immediately, in an automated way;
  • classifying emergency calls based on their urgency;
  • detecting and preventing the spread of diseases;
  • assisting public servants in making welfare payments and immigration decisions;
  • adjudicating bail hearings;
  • triaging health care cases;
  • monitoring social media for public feedback on policies;
  • monitoring social media to identify emergency situations;
  • identifying fraudulent benefits claims;
  • predicting a crime and recommending optimal police presence;
  • predicting traffic congestion and car accidents;
  • anticipating road maintenance requirements;
  • identifying breaches of health regulations;
  • providing personalised education to students; marking exam papers;
  • monitoring/counting utility (electricity/water/waste/communications) bills;
  • plan new infrastructure projects;
  • assisting with defence and national security.

Conclusion

Artificial intelligence helps governments to provide a new level of convenience. Applications such as smart waste management systems have significantly reduced noise level, street congestion, and air quality for residents. Artificial intelligence can also improve mobility, advance education, protect food and water safety, decrease emissions, prevent crime & fraud detection, increase cross-border security and even save lives. Our world has the possibility to grow into a more intelligent and participatory society in the future with artificial intelligence, if paired with good ethics and governance models. The key is to achieve a symbiosis between human creativity and technology that creates the best experience for all. 

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Azamat Abdoullaev

Tech Expert

Azamat Abdoullaev is a leading ontologist and theoretical physicist who introduced a universal world model as a standard ontology/semantics for human beings and computing machines. He holds a Ph.D. in mathematics and theoretical physics. 

   

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