Artificial Intelligence and Data Protection

Picture credits to talkehr.com

Abstract

Can a machine think sense or feel like a human being??? Today digital revolutions transform views of the human being about values, behavior, and priorities. Artificial intelligence or machine learning or deep learning is that technology that gradually permeates every aspect of our society, from the vital to the regular life. AI is a science and a set of computational technologies that are inspired by the ways people use their nervous systems to sense, learn, reason, and take action. Various sectors are benefited from these new technologies but on the other side, apprehension is, these new technologies may be misused or performed in unforeseen and potentially harmful ways. In this scenario, it has become a fundamental concern that every requisite innovation is socially preferably and justifiable. Today issue on the role of the law in governing AI systems is more relevant. How the law will struggle to keep up how courts, policymakers, and companies are stepping in to confront the unique legal and policy questions presented by the widespread adoption of AI.

Introduction

Technologies are innovated to make routine life easy and smooth. The world of technology is changing rapidly with computers, machines, and robots, replacing simple human activities. Artificial intelligence (AI) is one of such innovations. Fundamentally, AI is a machine that can think on its own. AI can be understood as the capability of a machine to reproduce intelligent behavior. In a broader sense, AI refers to biologically inspired information systems and includes manifold technologies like machine learning, deep learning, computer vision, natural language processing, machine reasoning, and strong AI. However AI relates to the similar task of using computers to understand human intelligence, but it does not confine itself to biologically observable methods. In general understanding “Artificial intelligence, a branch of computer science is the recreation of

human intelligence processes by machines especially computer system aims to create intelligent machines which can often act and react like humans and makes possible for computers to perform tasks involving human-like decision making, intelligence, learning skills or expertise.

Understanding AI

An intelligent entity has five attributes i.e.

(1) Communication,

(2) Internal knowledge,

(3) External knowledge,

(4) Goal-driven behavior, and

(5) Creativity.

AI technology includes Machine Learning (ML), Cognitive Computing, Deep Learning, Predictive application programming interfaces (APIs), Natural Language Processing (NLP), Image Recognition, Speech Recognition, etc. Highly technical,

specialized skill and the expert system is required in the process of Particular applications of artificial intelligence. AI includes programming of computers for a certain character such as Knowledge, Reasoning, problem-solving, Perception, Learning, Planning, and the ability to move objects. Knowledge Engineering and Machine learning is a core part of AI research. For a machine to act and react like

a human, it is necessary to machine must be possessed with accurate information of the world. To implement knowledge engineering AI is essentially to access properties, categories, objects, and their relations. It is a tedious task to insert reasoning, the power to solve the problem, and common sense in a machine. Machine learning and learning require ample supervision with numerical regressions and classification. Machine perception is capable to use sensory inputs to interpret the different aspects of

the world, while computer vision is the power to analyze visual inputs with a few sub-problems such as facial, object, and gesture recognition. Science fiction has been stimulating the interest of people for a very long time with the concept of

Artificial Intelligence into reality the first time with computers and now with robots and machines. This stimulation can be seen when a robot named Sophia was given the citizenship of the country by Saudi Arab. Robotics is a major field related to AI. It requires intelligence to handle tasks such as object manipulation and navigation, along with sub-problems of localization, motion planning, and mapping.

Origins of AI

It is said, Artificial Intelligence is not a new idea to the person who examines science creative writing. To understand AI and its nexus with our understanding of intelligence, one has to look into the development of the concept of AI. The term was first coined when people began trying to understand whether machines can truly think. In the 1940s McCulloch and Walter Pitts had first attempted

to understand intelligence in mathematical terms. John McCarthy had used the term “Artificial Intelligence” in the Dartmouth Conference at the Massachusetts Institute of Technology. He defined AI as the science and engineering of making intelligent machines, especially intelligent computer programs. According to him “every solid definition of intelligence relates it to human intelligence….” Alan Turing proposed a test in 1950 to prove a machine “as intelligent”. He proposed that a machine has to pass the Turing test to prove the computer is intelligent. The Turing test engaged a human being, as the ‘judge’, to ask questions via a computer terminal to two other entities, one of which will be a human being and the other will be a computer. If the judge (human being) regularly failed to appropriately differentiate the computer from the human, then the computer was said to have passed the test. Marvin Minsky defined AI, (in 1968), as a science of making machines do things that would require intelligence if done by men. In 1993, Luger and Stubblefield have given a modern definition of AI as the branch of computer science that is concerned with the automation of intelligent behavior. AI was defined by Stuart Russell and Peter Norvig as designing and building intelligent agents that receive percepts from the environment and take actions that affect that environment. This definition of AI brings together different subfields of computer vision, speech processing, natural language understanding, reasoning, knowledge representation, learning, and robotics, to achieve an outcome by the machine. David Poole and Alan Mackworth defined AI as the field that studies the synthesis and analysis of computational agents that act intelligently. Marcus Hutter (ANU) and Shane Legg (Google Deep Mind) proposed the “human-independent” definitions of AI as Intelligence measures an agent’s ability to achieve goals in a wide range of environments. Oxford dictionary has defined artificial intelligence as a computer system, able to perform tasks that normally require human intelligence. In layman terms, artificial intelligence is a technology that behaves and acts like humans or other animals. In popular terms, AI is a science and a set of computational technologies that are inspired by the ways people use their nervous systems to sense, learn, reason, and take action.

Types of AI Applications

Existing AI applications are forms of narrowAI or artificial specialized intelligence” (ASI), aim to solve specific problems or take actions within a limited set of parameters. When we communicate with a device to book film tickets or pay a gas bill or listen to GPS directions etc., we employ weak or narrowAI. Most recognizable products i.e. Apple’s Siri8 and Google’s self-drive cars are using

“weak” AI. It appears intelligent, but it still has defined functions. It has no self-awareness. When a person used a credit card an AI algorithm approves the transaction, use the GPS in a car, we use an AI algorithm. Using Google translate service, is part of AI and is based on statistical machine learning. The face recognition capability of our cameras is AI. AI can enable a machine to mimic “cognitive” functions that humans associate with other human minds, such as “learning” and “problem-solving.” AI which is used in mainstream technologies such as web search, smartphone applications are based on deep learning. Tasks such as trading stocks, flying military planes, and keeping a car within its lane

on the highway are now all within the domain of ASI (artificial specialized intelligence).

Opportunities of AI in various sectors

Many projects are taken to explore and implement AI for use in the public sector, including government, anti-corruption efforts, and similar activities. Predictably, the markets for AI services are growing and the broader economy shall be benefited enormously with potential AI services. AI technology may provide help to solve complex global challenges like climate change and resource

utilization on the impact of population growth by improved decision making with data-driven strategies. It is realized that AI has the potential to transform people’s lives for the better by introducing new information and digital personal assistants which can anticipate our needs. We can see the use of AI technology in education, Agriculture, etc.

AI in Manufacturing Industry and Service Sector

The use of industrial robots has increased significantly and demonstrably in the manufacturing industry. It may reduce production also. Skilled Robots are deploying in service industries services such as restaurants or hospitals. They are assisting disabled people, humans to avoid laborious or dangerous work. AI technology also has the potential to provide solutions to social challenges like caring for the aging population.

AI in Autonomous Vehicular Sector

Various research projects working on AI application in the automobile sector for Autonomous vehicles (AV) are advocated that it will reduce road accidents, reduce traffic congestion, reduce fuel consumption and emissions, improve road safety, improve the mobility of the elderly and disabled, and free up commuting time for other tasks. Drones (a specialized type of AV) are growing in popularity.

AI in Legal Profession

The future of the legal profession without AI software is hard to believe. Companies dealing in artificial intelligence technology have been looking out ways to develop technology for providing better, speedy, and accuracy in the legal profession also. The technological advancement in the legal profession has transformed the framework. Legal research is the most important aspect of practicing lawyers and because of technology, it has undergone a drastic development. From journals and reporters to CD-ROMS and Online software, legal technological innovation has changed the way how legal services were rendered. AI software helps the lawyer to find relevant case laws and applicable statutes. With this software complex legal questions can be answered in simple and basic language. Lawyers and firms are drafting and reviewing the contracts as well as the case documents with the help of software. There are different ways in which artificial intelligence technology is being currently applied in the legal profession around the globe and proving to be advantageous for law firms and lawyers respectively. Can a robot replace a lawyer?? Practically, robots cannot replace a lawyer’s role in court, but AI robots have the power to create and draft documents. Therefore, the clerical role of lawyers might be reduced to a large extent. Appearing and arguing a case before judges in the court might be the only role lawyer’s play.

Challenges

The debate is around regulating this technology in the country within the realm of municipal and international law. One of the foremost concerns surrounding AI is data protection because Every AI interface relies entirely on the data which is being fed into its system. Secondly, in the absence of the direct application of the human mind behind any action that an AI system undertakes, who is to be

blamed for the loss which is likely to be sustained by innocent users? It is also criticized that complete automation or complete dependency on the AI system may be risky to the human being. There some dangers in eliminating human oversight i.e. coming to depend entirely on the decisions of AI systems when we do not fully understand how these systems are making those decisions.

Data Protection Act

India has also not yet enacted specific legislation on data protection. However, the Indian legislature did amend the Information Technology Act (2000) (“IT Act”) to include Section 43A and Section 72A, which give a right to compensation for improper disclosure of personal information. Some people question govt that why it was introduced;

The data protection act grew out of public concern about privacy in the face of rapidly developing computer technology. It works in two ways, giving individuals certain rights whilst requiring those who use and record personal information on the computer to be open about that use. The data protection act become law on 12th July 1984 and was updated in 1998. The Indian central government subsequently issued the Information Technology (Reasonable Security Practices and Procedures and Sensitive Personal Data or Information) Rules, 2011 (the “Rules”) under Section 43A of the IT Act. A clarification of the above Rules was issued on 24 August 2011 (the “Clarification”). The Rules have imposed additional requirements on commercial and business entities in India relating to the collection and disclosure of sensitive personal data or information which have some similarities with the GDPR and the Data Protection Directive.  

India has introduced a biometric-based unique identification number for residents called ‘Aadhaar’. Aadhaar is regulated by the Aadhaar (Targeted Delivery of Financial and Other Subsidies Act) 2016 (“Aadhaar Act”) and rules and regulations issued thereunder.  Entities in regulated sectors such as financial services and telecom sector are subject to obligations of confidentiality under sectoral laws which require them to keep customer personal information confidential and use them for prescribed purposes or only in the manner agreed with the customer.

Finally, personal data is protected through indirect safeguards developed by the courts under common law, principles of equity, and the law of breach of confidence. In a landmark judgment delivered in August 2017 (Justice K.S Puttaswami & another Vs. Union of India), the Supreme Court of India has recognized the right to privacy as a fundamental right under Article 21 of the Constitution as a part of the right to “life” and “personal liberty”. “Informational privacy” has been recognized as being a facet of the right to privacy and the court held that information about a person and the right to access that information also needs to be given the protection of privacy (“Privacy Judgment”). The court stated that every person should have the right to control the commercial use of his or her identity and that the “right of individuals to exclusively commercially exploit their identity and personal information, to control the information that is available about them on the internet and to disseminate certain personal information for limited purposes alone” emanates from this right. This is the first time that the Supreme Court has expressly recognized the right of individuals over their data.

Fundamental rights are enforceable only against the state and instrumentalities of the state and the Supreme Court in the same judgment recognized that enforcing the right to privacy against private entities may require legislative intervention.

The Government of India, therefore, constituted a committee to propose a draft statute on data protection. The committee proposed draft law and the Government of India has issued the Personal Data Protection Bill 2019 (“PDP Bill”) based on the draft proposed by the committee. This will be India’s first law on the protection of personal data and will repeal S. 43A of the IT Act.

It states that anyone processing Personal data must comply with 8 enforceable principles of good practice. Data must be:

  • Fairy and lawfully enforced.
  • Processed for specified purposes
  • Adequate, relevant, and not excessive
  • Accurate and, where necessary, up to date
  • Not kept longer than necessary
  • Processed by the data subject’s rights
  • Secure
  • Not transferred to countries without adequate protection

Personal Data

Information about living identifiable individuals. Personal data do not have particularly sensitive, can be as little as name and address.  Personal data under Indian laws and rules are termed “personal information”. Personal information has been defined under the Rules as “any information that relates to a natural person, which either directly or indirectly, in combination with other information available or likely to be available with a body corporate, is capable of identifying such person”.

The PDP Bill proposes a similar definition but extends it to include any inference drawn from such data for profiling. There are no specific rules that govern the processing of personal data.

However, the Rules state that a body corporate or any person who processes personal information on behalf of the body corporate should provide a privacy policy

The PDP Bill proposes that the processing of personal data must comply with seven principles for processing, namely:

  • Processing of personal data has to be fair and reasonable;
  •  It should be for a specific purpose;
  • Only personal data necessary for the purpose should be collected;
  • It should be lawful;
  •  Adequate notice of the processing should be provided to the individual;
  •  Personal data processed should be complete, accurate, and not misleading; and

Personal data can be stored only as long as reasonably necessary to satisfy the purpose for which it is processed

Data Users

Those who control the content and use of a collection of personal data. They can be any type of company or organization. A data user does not necessarily own a computer. With the few exceptions data users have to register to the Data Protection registrar. They must give their name and address together with broad descriptions of:

  • The items of data held
  • The purpose for which the data are held
  • Who will have access to the data
  • The type of organization to whom the information may be disclosed i.e. shown or passed on to
  • Any overseas or territories to which the data may be transferred.

Conclusion

Our inability to answer the challenges arises due to the application of AI forces us to understand the weakness of our legal system to deal with AI. AI is the capability of a machine to imitate intelligent human behavior. To safeguard the integration of AI, a balanced approach would need to be adopted which efficiently regulates the functioning of AI systems but also maximizes its benefits.

Effective and strong Contract drafting- In India however AI technology is in its emerging stages but there are plenty of opportunities for private industries to participate and profit from its development. In the absence of a regularity framework, Contracts between the AI user and the AI developer are vital in

determining the liability of parties. Participants must outline their respective roles, responsibilities, and obligations in the contract. During the negotiation of a contract, the parties should identify the scope of services being offered, the warranties relating to the AI technology, the scope of liability (including limitations and exclusions) at the very least.

Parallel Approach- Artificial intelligence is the future and there is no denial, but in our quest of replacing ‘human errors’ with smart technology and strong AI, we need to move slowly and keep abreast of the parallel needs of upgrading the laws and literary framework in the country.

Two-layered protection model -Since 2017, more than 20 countries (including, India) have released discussion papers on AI. However, to date, no country has enacted specific legislation to comprehensively regulate the use of AI. Therefore, to be at forefront of this revolution, the Indian legislature should take pro-active steps to fill the regulatory lacunae and provide surety in this field. AI is growing

multi-fold technology and we do not know all the advantages or dangers associated with it. Therefore it is of utmost importance to have a two-layered protection model: one- technological regulators; and two- laws to control AI actions as well as for accountability of errors. The solution is not to hold back on innovation, but we have to innovate around: how do you keep people engaged when AI can do most things better than most people. In the meanwhile, in the absence of a regulatory framework, stakeholders should strive towards implementing measures that would protect them from unforeseen consequences and liabilities that may arise in the course of use and implementation of AI technology. A mere oversight at the contracting stage could lead to significant losses.

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