Directing AI for Better and Smarter Legislation

Table of Contents

Context: The article is discussing how Artificial Intelligence (AI) is being utilized by mature democracies for better legislative procedures and decision-making. It highlights the various ways in which AI tools can assist parliamentarians in preparing responses, conducting research, drafting legislations etc. It also emphasizes the potential benefits of using AI in the legislative process and how it can empower legislators to take into account citizen grievances, media opinions, and other factors that can influence their decision-making.

Background

What is Artificial Intelligence?

Artificial Intelligence (AI) is a concept that refers to the ability of machines to accomplish tasks that historically required human intelligence.
It includes various technologies such as machine learning, pattern recognition, big data, neural networks, and self-algorithms.
AI involves complex processes such as feeding data into machines and making them react as per different situations. The goal of AI is to create self-learning patterns where the machine can give answers to never-before-answered questions in a way that a human would.
Some examples of AI in action include:
- Virtual personal assistants such as Siri, Alexa, and Google Assistant, which use natural language processing and machine learning to perform tasks such as setting reminders, playing music, and answering questions.
- Recommendation systems used by online retailers and streaming platforms, which use machine learning algorithms to suggest products or content based on user preferences and behaviour.
- Fraud detection systems used by banks and credit card companies, which use machine learning to analyse transaction data and identify patterns that may indicate fraudulent activity.
- Autonomous vehicles, which use sensors, machine learning algorithms, and other AI technologies to navigate roads and avoid obstacles.
- Smart home devices, such as thermostats and security systems, which use machine learning to learn user behaviour and preferences and adjust settings accordingly.

Evolution of AI: Timeline

The evolution of Artificial Intelligence (AI) can be traced back to the mid-20th century when computer scientists first started developing machines that could perform tasks requiring human intelligence.

The birth of AI: In 1956, the field of AI was born when John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon organized the Dartmouth Conference, which is considered the birthplace of AI.
Rule-based systems: In the 1960s and 1970s, AI research focused on developing rule-based systems that could mimic human reasoning and decision-making.
Expert systems: In the 1980s, expert systems were developed that could perform specialized tasks by emulating the decision-making processes of human experts.
Machine learning: In the 1990s, machine learning algorithms were developed that could learn from data and improve their performance over time.
Big data: In the 2000s, the rise of big data and cloud computing made it possible to process massive amounts of data and train more powerful AI models.
Deep learning: In the 2010s, deep learning algorithms were developed that could analyze large amounts of data and recognize patterns with unprecedented accuracy.
Neural networks: In recent years, the development of neural networks has led to breakthroughs in natural language processing, image recognition, and other areas.

Branches of Artificial Intelligence:

Branch of AI	Description
Expert systems	AI systems that use knowledge and rules to make decisions
Machine learning	A technique that enables machines to learn from data and improve their performance
Deep learning	A subfield of machine learning that uses neural networks to analyze large amounts of data
Natural language processing	A technique that enables machines to understand and process human language
Computer vision	A technique that enables machines to interpret and understand visual information
Robotics	A field that combines AI with engineering to create machines that can perform physical tasks in the real world
Fuzzy logic	A technique that allows for imprecision and uncertainty in decision-making
Evolutionary algorithms	A technique that uses evolutionary principles to optimize AI systems
Swarm Intelligence	A technique that models collective behavior in groups of animals to solve problems
Artificial neural networks	A technique that uses interconnected nodes to process and analyze data

India and AI:

India is rapidly emerging as a major player in the field of Artificial Intelligence (AI). The country has a large pool of talented engineers, data scientists, and researchers who are working on cutting-edge AI projects.

As per the recent Global AI Index report, India is ranked 20th among 172 countries in terms of AI readiness and deployment. The report takes into account various factors such as talent, infrastructure, policy environment, research, and development, and commercial applications to assess the AI readiness of countries.
- India’s ranking in AI has improved compared to the previous years.
- The report highlights India’s strong talent pool and its potential to become a global leader in AI research and development.
- However, it also notes that there is a need for more investment in AI infrastructure and policies to support the growth of AI in India.
Contribution to GDP: It is estimated that AI will add 957 billion dollars to India’s GDP by the year 2035 boosting India’s annual growth by 1.3% points.
Key developments related to AI in India:
- National AI Strategy: In 2018, the Indian government launched a national AI strategy with the aim of positioning the country as a global leader in AI research and development. The strategy focuses on five key areas: healthcare, agriculture, education, smart cities, and infrastructure.
- AI Research Institutes: The Indian government has set up several research institutes dedicated to AI, such as the Indian Institute of Technology (IIT) Hyderabad, the Centre for Artificial Intelligence and Robotics (CAIR), and the Centre for Excellence in Artificial Intelligence.
- Startup Ecosystem: India has a vibrant startup ecosystem, and several AI startups have emerged in recent years. Some of the notable startups include Haptik, Niki.ai, and Mad Street Den.
- Corporate Investments: Several major corporations have also invested in AI research and development in India. For example, Google has set up an AI lab in Bangalore, while Microsoft has established an AI research lab in Bangalore and an AI engineering hub in Hyderabad.
- AI Applications: AI is being used across various sectors in India, such as healthcare, agriculture, finance, and education. For example, AI is being used to improve crop yields and predict weather patterns in agriculture, while it is being used to improve patient outcomes and reduce healthcare costs in healthcare.

Decoding the Editorial

The Article calls for an effective implementation of AI in India. The article suggests the following measures:

Codified Laws:
- The current laws in India are complex, opaque and there is a significant gap between law-making, law-implementing and law-interpreting organizations.
- The Indian government has taken steps to address this by setting up the India Code portal, which is a repository of laws and regulations.
- However, the portal cannot be relied upon entirely as a “single source of truth” due to the lack of a complete chain of laws and regulations.
Need for a Comprehensive and Accessible Repository:
- The article highlights the need for a 360° view of laws and regulations, including parent acts, subordinate legislation passed by the central government, and amendment notifications.
- This is particularly important in special situations such as the COVID-19 pandemic, where there were over 900 notifications issued by the central government and over 6,000 notifications issued by state governments related to COVID-19 measures.
- Having a comprehensive and easily accessible repository of laws and regulations would make it easier for entities, including AI systems, to understand and comply with the laws and regulations in India.
Central Law Engine for Integrating AI and Governance:
- To effectively integrate Artificial Intelligence (AI) into various aspects of governance in India, there is a need to make laws and regulations easily consumable by machines.
- This can be achieved by creating a central law engine, which would serve as a single source of truth for all acts, subordinate legislation, gazettes, compliances, and regulations.
- This would allow AI systems to access and understand the laws and regulations, making it easier to provide relevant information to citizens and businesses.
- For instance, an entrepreneur who wants to open a manufacturing unit in Maharashtra can use AI to determine which acts and compliances are applicable.
  - Similarly, citizens can use AI to check their eligibility for welfare schemes, with the system recommending eligible schemes based on the details provided by the citizens.

Potential of AI in assisting Parliamentarians

The article highlights the potential of Artificial Intelligence (AI) in assisting parliamentarians in India.

Managing Constituencies: Due to the huge population in India, parliamentarians face challenges in addressing citizens’ grievances and prioritizing issues that need immediate attention. AI can analyze citizens’ grievances and social media responses to flag such issues and help parliamentarians make informed decisions.
Citizen Inputs for Policy Making: Moreover, AI can also assist parliamentarians in seeking citizen inputs for public consultation of laws and preparing a manifesto. This can lead to better engagement with citizens and more informed decision-making.
Examples:
- The House of Representatives in the United States is using AI to automate the process of analyzing differences between Bills, amendments, and current laws.
  - This has been of immense help to legislative staff, who can now readily see the impact of amendatory provisions in Bills that they move through the legislative process.
- Netherlands House of Representatives has implemented the “Speech2Write” system to aid legislation,
- Japan’s AI tool assists in preparing responses and selecting relevant highlights in parliamentary debates, and
- Brazil has developed an AI system called Ulysses to support transparency and citizen participation.
- India is also innovating in this area by making parliamentary activities digital through initiatives such as ‘One Nation, One Application’ and the National e-Vidhan (NeVA) portal.
Therefore, the article suggests that AI tools can assist parliamentarians in preparing responses, enhancing research quality, obtaining information about any Bill, providing information on particular House rules, legislative drafting, amendments, interventions, etc., and can empower legislators to make informed decisions by having access to insights into citizen grievances, media opinions, and voices of citizen-centric associations.
Simulation of Laws:
- AI can be used to simulate and analyze the potential effects of laws by modelling various datasets such as the Census, household consumption, taxpayers, beneficiaries of various schemes, and public infrastructure.
- This can help uncover potential outcomes of a policy and also identify outdated laws that require amendment.
- For example, during the COVID-19 pandemic, it became clear that the Epidemic Diseases Act, 1897 was inadequate to address the situation.
- Similarly, many provisions in the Indian Penal Code (IPC) are outdated and controversial. AI can help identify such laws that need to be revised or repealed, thereby improving the legal system in India.

Way Forward

Therefore, the article suggests that AI should be used as a means to improve governance, provide better services to citizens, and make policy-making more efficient and effective.