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Authored By: PROBLEM RELATED WITH USE OF AI IN THE DOMAIN OF IP: AN ANALYTICAL STUDY, Authored By: Navneet, Student B.A. LL.B (H.), 5th Year, Law College Dehradun, Uttaranchal University, Dehradun, Uttarakhand, India & Co-Authored By: Dr. Ratnesh Kumar Srivastava, Assistant Professor, Law College Dehradun, Uttaranchal University, Dehradun, Uttarakhand, India,
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Abstract
Artificial Intelligence (AI) is transforming the intellectual property (IP) landscape, presenting both challenges and opportunities for businesses and inventors. AI can create, manage, and exploit IP assets, raising complex legal and ethical issues related to ownership, patentability, copyright infringement, and data protection. On the other hand, AI can also help automate and streamline the management of IP assets, assist in the search and analysis of existing IP assets, create new business models, and improve IP enforcement. It is essential for policymakers and IP professionals to stay abreast of these developments to ensure that IP law evolves to meet the needs of this rapidly changing technological landscape. This paper discusses the challenges and opportunities that AI is presenting in the context of intellectual property rights.
Keywords: Artificial Intelligence, Intellectual Property, Ownership
INTRODUCTION
Technology is advancing in the modern developing world, and artificial intelligence (AI) is one of the main drivers of this advancement. Artificial means something which is not natural and intelligence is the ability to learn and use new information and skills. Various approaches have been made to define AI time and again. Simply being said about it, artificial intelligence refers to a machine’s ability to mimic intelligent behavior. John McCarthy, an American computer scientist who is regarded as the pioneer of artificial intelligence, for the very first time coined the term “artificial intelligence” in 1956[1]. At the Massachusetts Institute of Technology’s a conference was held in the name of Dartmouth Conference where he used the word for the first time and gave a definition of AI as the science and engineering of creating intelligent machines, particularly intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable. According to him there existed no “solid definition of intelligence that does not depend on relating it to human intelligence” because “we cannot yet characterize in general what kinds of computational procedures we want to call intelligent.”
MEANING OF ARTIFICIAL INTELLIGENCE
The task of defining AI is not an easy affair. Its field is so broad that it cannot be confined to a specific area of research. AI presently touches upon every aspect of life. Every researcher has defined AI differently as per its applicability in their own field. The question that encounters researcher in this field are question such as ‘what is intelligence, ‘how can intelligence be measured?’, ‘how does the brain work[2] All this question are necessary to be answered while trying to understand AI. Thus, AI has been considered to be more of an ambition now that seeks to understand how a human brain works and its cognitive capacity by creating some cognitive process that function similarly as human brain
WORKING OF ARTIFICIAL INTELLIGENCE
AI has a series of techniques clubbed together to perform its working. It involves various tools and processes that sets the work of AI going. These techniques includes
- Logic- AI uses logic in its functioning This form of AI are known as symbolic AI that aims to reproduce the reasoning mechanism of human beings. This logic that are built by AI are produced from prior knowledge and rules of logic to perform the task at hand. A popular example of symbolic AI is Expert System algorithm that can produce reasoning from known facts and rules. Such as diagnostic rules which are described by a physician can be transcribed into codes that will automatically diagnoses issues.
- Machine Learning– Machine learning is considered as a sub-field of AI. Harry Surden defines machine learning to be some computer algorithms which has the ability to learn from experience and also to improve its performance over various task. This learning is through “a statistical process that starts with a body of data and tries to derive a rule or procedure that explains the data or can predict future data [3] Machine learning techniques involves two steps. The first is learning phase where the machine learns from input data (example- pictures, pattern etc.) and to find parameters that fits appropriately to the task in hand. The second phase takes the learned parameters as inputs which are then kept on use for further task in order to solve them. This stage is known as inference stage. However, there are few problems in machine learning process.
- Supervised learning- In this process a machine learns a set of rules in order to perform a specific task from a given set of examples such as a million of pictures of cats and dogs identified as such the machine in the learning phase progressively changes its parameters in order to make the chances of error as small as possible upon known and unknown data. In the inference phase the algorithm perform its task upon unknow data by the learned parameters as inputs. Example- it will classify cats and dogs even on picture which it has not seen.
- Unsupervised learning- In this process the data that are provided are un-labelled or without any additional knowledge. In the learning phase the aim is to know the underlying structure of the data. The inference phase is same as in the supervised learning. The purpose of unsupervised learning is to find behavioral profile from recorded activities without any additional information. This form of AI learning is more popular as it can work upon un-labeled data which additionally makes the process inexpensive.
- Reinforcement learning- this form of learning is different from the other two processes as it does not rely upon any pre-existing set of data as inputs. Instead learning happens by direct interaction with the environment. In this process the machine performs an action and the state of environment changes with the action and machine gets a reward depending on the type of result. This reward system makes the machine discover the best action to perform aiming for the result to get. On of the recent form of reinforcement learning is AlphaGo where the action performed is a move upon the board, the board being an environment and the reward is the outcome which is winning or loosing the game
ARTIFICIAL INTELLIGENCE IN THE FIELD OF HEALTH CARE AND MEDICINE
The evolution of how digital technology and artificial intelligence (AI) have been used in healthcare has evolved over many years. MYCIN, an expert system developed by Stanford University enabled medical professionals to recognize bacterial diseases such bacteremia and meningitis, and to recommend a suitable course of action[4] MYCIN was not utilized in daily life. It was just used as an experimental model to show what AI is capable of. In 1986, with the help of a decision assistance system called DX plain, the University of Massachusetts using the patient’s symptoms created a list of potential diagnoses which was generated for the doctor’s reference. The University of Washington then put the Germ watcher expert system into practice for the patient’s identification of infections185. Since the start of the creation of AI-based medical applications in the twenty-first century has been a priority concern for IT based industries. According to IBM, the company that created the Watson supercomputer, AI t technologies can be used in healthcare to structure medical data. For example- processing natural language and turning it into clinical text, analyze patient information, such as abstracting treatment records into a patient’s medical history comparing clinical diagnostic findings to choose the best course of action, advancing medical philosophy by developing models of patient therapy based on comparable examples, as well as confirming medical theories. The term “artificial intelligence” (AI) refers to a group of technological solutions that mimic human cognitive functions, including the capacity for independent learning and decision-making without the aid of predetermined algorithms. When used to accomplish certain tasks, AI can yield results that are on par with or superior to those produced by human intellectual activity. This group of technological solutions consists of tools and services for data processing, decision making, and information and communication infrastructure, software (including program that use machine learning techniques), and software applications.
LAW RELATING TO ARTIFICIAL INTELLIGENCE AND INTELLECTUAL PROPERTY RIGHTS
The AI-driven advancements, which also involve AI ethics, data security, and privacy, must be accommodated by the existing IP regulations, including patent and copyright laws. The patentability of AI algorithms must also be determined by the IP policy. It is widely believed that AI can be created. The issue of dual inventor ship is an additional one. Can an AI and a human share an internship The role of AI in technology is expanding. It is believed to be only proper for the inventor to disclose any applications of AI. Inventors and ownership are clearly separated in typical applications. Here, the petitioner declares that he already owns the innovation. Ownership of AI inventions is a murky subject. Can we claim that those who make financial contributions to AI inventions or those who own the AI equipment are the owners? What about the people involved in creating AI algorithms? Why shouldn’t they gain from patent protection? The applicant must make all information available in order to receive a patent. Applying the principle of full disclosure to AI inventions is exceedingly challenging. It won’t be enough to only reveal the beginning method because the output data depends on the input data.
LAW RELATING TO ARTIFICIAL INTELLIGENCE IN THE FIELD OF TRADE AND E-COMMERCE
The popularity of e-commerce is increasing every month, which boosts this industry’s revenues and, of course, competition. For instance, the e-commerce retail sector in the UK lost 85,000 jobs in the first quarter of 2018, and over 30,000 retailers experienced serious financial difficulties. [5]In this sector, almost 70% of businesses and organizations claimed that their artificial intelligence (hence referred to as AI) projects were successful or extremely effective. More than 10% growth was indicated by three-quarters of respondents for a number of market metrics. Consequently, increased sales, satisfied customers, and lower costs have improved. Artificial intelligence is without a doubt the technology of the future and will gradually start to affect all aspects of human life. The key players in e-commerce are computer systems that offer a variety of Internet-based services, such as search engines, social media, application shops, communication services, and payment systems. The subject of the use of artificial intelligence and its legal control also arises in light of the rapid advancement of information technology and the necessity to make the sale process less expensive for the owners of such businesses (for instance, the cost of paying salaries to personnel, paying taxes for them, renting premises, etc.). For instance, chat bots are now often used in e-commerce.
However, before applying artificial intelligence for e-commerce, it is important to take into account the expense of developing and tailoring the program to the demands of the store (i.e., paying for IT personnel), the requirement for software upgrades, etc. Due to the fact that unfair competition, breaches of laws governing the collecting and processing of personal data, and other issues also occur in a virtual environment, all of the procedures discussed above require legal control at the state and international levels. An illustration of the procedure for gathering and organizing huge data is data mining. The data can range from the competitor’s price to the customer’s shopping cart. Then, in order to find patterns and links and provide useful information, this data is tracked and confirmed. Additionally, there is focused advertising, wherein artificial intelligence chooses (based on the data gathered) to present the prospective buyer with the seller’s product that will satisfy its needs (what colour most appeals to the buyer, which price category is more appropriate for the customer, etc.)[6]The same holds true for conversations with clients that follow a predetermined seller plan, which artificial intelligence can enhance and gradually adjust to meet the needs of each client. Big data can and should be exploited for business development, and this knowledge has already emerged in the world of e-commerce. Additionally, this information is regularly exploited for marketing. However, because of its overuse and inappropriateness, advertising is also coming to be viewed negatively. Custom targeting is ineffective now. Only modern solutions will enable brands to maintain their competitiveness. The integration of cutting-edge artificial intelligence technologies into digital platforms is one of them. They offer highly precise customization of advertising messages and boost the success of advertising efforts because of their sophisticated algorithms.
CHALLENGES IN INCORPORATION OF ARTIFICIAL INGTELLIGENCE IN INDIA
India’s socioeconomic, technological, and regulatory realities present particular challenges that must be acknowledged and taken into account when formulating policy and implementing the technology, despite the country’s great potential for the advancement of artificial intelligence in the governance sector
- Improved capacity and enhanced understanding of emerging technologies
To effectively adopt AI-driven solutions, the government must increase its capabilities. This would also require more openness to, knowledge of, and skill with information technologies—qualities that the people in charge of putting the solution into action, such as teachers, police officers, or government officials, may not have.[7] Given that the development of AIdriven solutions for governance is mostly being pursued through collaborations with the private sector, a significant portion of this capacity building may need to come from the private sector. The developer working with the private sector, the government body adopting the technology, and the government official or individual implementing the solution at the community level must all maintain open channels of communication in order to build capacity.
- Infrastructure-
According to our research, the necessary infrastructure has not yet been created for the successful and coordinated implementation of AIdriven solutions. For the purpose of developing algorithmic models that accurately capture the wide range of socio-economic realities in India that would need to be employed in predictive policing models, the inputs that may be used as training data in the law enforcement sector are not coherent or diverse enough. Infrastructure challenges in the field of education include a lack of internet connection and IoT device availability. In India as a whole, 31% of people have access to the internet as of 2016. Out of 444 million people, 269 million in urban India utilize the internet (or 60% of the population), whereas just 163 million in rural India use the service (17% of the population, according to the 2011 census). The then defence minister Nirmala Sitharaman has identified the absence of a sufficient technology infrastructure as a major barrier to the deployment of AI in the sector[8]
- Trust-
Genuine worries about potential cultural ambiguity arise from each society that has grown accustomed to employing conventional tools rather than algorithmic models, especially intelligent models, across sectors. Locally employed police officers and educators have obtained training and practical experience utilising methods unrelated to the usage of AI or knowledge derived from it. In many instances, their training and experience don’t even involve the usage of ICTs. Despite being enthusiastic about the strategic advantages of building autonomous solutions, the operational units of the defence forces do not entirely trust the CAIR-developed solutions.
- Funding-
In the modern day, finding funding to build AI-driven solutions is a difficulty for any expanding economy. By allocating Rs. 3,037 crores to the “Digital India Programme” in the 2018 budget, the government has once again demonstrated its support for the creation of AI-based solutions. This is done in an effort to increase funding and skill sets in the fields of robotics, artificial intelligence, and the Internet of Things (IoT). Under the direction of NITI Aayog, there has been some emphasis on creating a National Artificial Intelligence Program. International Centers for the Transformation of Artificial intelligence should be established, according to an NITI AAYOG report. The research suggests that, aside from the costs of the physical infrastructure and technological/computing infrastructure, seed money (in the range of INR 200 crore to INR 500 crore per ICTAI) through grants from the public and commercial sectors should cover the operational costs of the ICTAI for the first five years.415 Despite the fact that these are encouraging developments, it is yet unclear how financing will be allocated to various sub-sectors. Due to the ambiguity surrounding this matter, it’s likely that the majority of funds is allocated to some.
CONCLUSION
Although current AI offers us few ethical and legal issues, the main problem in this field is the projections of their capability to be more human like and pose new concerns. Social roles will be fulfilled by AI that are transparent and predictable enough. Artificial Super Intelligent algorithm which are not yet in existence do not need new kind of safety assurance in predictable context. AI that has sufficiently advanced mental state may be counted as person and must be regulated by a new set of rules and principles. And finally, the prospect of AIs with superhuman intelligence and superhuman abilities presents us with the extraordinary challenge of stating an algorithm that outputs super-ethical behavior.
REFERENCES
- Christoffer O. Hernces, “Artificial Intelligence Legal Responsibility and Civil Rights”, Tech Crunch, available at (last visited on Dec 25th 2010)
- Wolfgang Ertel, Introduction to Artificial intelligence 3 (Ian Mackie, Springer, 3rdedn, 2017)
- John McCarthy, “What Is AI? / Basic Questions”, JMC.STANFORD.EDU, available athttp://jmc.stanford.edu/artificial-intelligence/what-is-ai/index.html (last visited on March 12, 2021)
- What is Artificial Intelligence in Medicine? 2021, available at (last visited on April 20th 2021)
- Semenchuk, “Artificial Intelligence in Retail and E-Commerce: Expectations and Reality”, Everest.ua Sept. 2017, available at (last visited on July 26th 2020).
- The role of the technologies of the future in modern e-commerce”, Blog.imena.ua, available at (last visited on May 29th 2020)
- J. Philomina, & S. Amutha, “Information and communication technology awareness among teacher educators” 6 International Journal of Information and Education Technology, 603 (2018)
- Govt working report on applications of Artificial Intelligence for military use, Nirmala Sitharaman” available at (last visited on May 23rd 2020)
[1]Christoffer O. Hernces, “Artificial Intelligence Legal Responsibility and Civil Rights”, Tech Crunch, available at (last visited on Dec 25th 2010)
[2] Wolfgang Ertel, Introduction to Artificial intelligence 3 (Ian Mackie, Springer, 3rdedn, 2017)
[3] John McCarthy, “What Is AI? / Basic Questions”, JMC.STANFORD.EDU, available athttp://jmc.stanford.edu/artificial-intelligence/what-is-ai/index.html (last visited on March 12, 2021)
[4] What is Artificial Intelligence in Medicine? 2021, available at (last visited on April 20th 2021)
[5] O. Semenchuk, “Artificial Intelligence in Retail and E-Commerce: Expectations and Reality”, Everest.ua Sept. 2017, available at (last visited on July 26th 2020).
[6] The role of the technologies of the future in modern e-commerce”, Blog.imena.ua, available at (last visited on May 29th 2020)
[7] M.J. Philomina, & S. Amutha, “Information and communication technology awareness among teacher educators” 6 International Journal of Information and Education Technology, 603 (2018)
[8] Govt working report on applications of Artificial Intelligence for military use, Nirmala Sitharaman” available at (last visited on May 23rd 2020)
