- Biological Inventions
- Brand Valuation
- Competition Law
- Constitutional Law
- Consumer Law
- Copyright Infringement
- Copyright Litigation
- Corporate Law
- Digital Right Management
- Educational Conferences/ Seminar
- Fashion Law
- Hi Tech Patent Commercialisation
- Hi Tech Patent Litigation
- Intellectual Property
- Intellectual Property Protection
- IP Commercialization
- IP Licensing
- IP Litigation
- IP Practice in India
- IPAB Decisions
- Legal Issues
- Media & Entertainment Law
- News & Updates
- Patent Act
- Patent Commercialisation
- Patent Filing
- patent infringement
- Patent Licensing
- Patent Litigation
- Patent Marketing
- Patent Opposition
- Patent Rule Amendment
- Pharma- biotech- Patent Commercialisation
- Pharma/Biotech Patent Litigations
- Section 3(D)
- Social Media
- Sports Law
- Telecom Law
- Trademark Litigation
An Introduction to Artificial Intelligence
In recent times, Artificial Intelligence (AI) has become the talk of the hour. People are concerned with respect to the impact of AI on various fields. In the simplest of words, AI can be defined as “the capability of a machine to imitate intelligent human behaviour“ or “the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.” So, the basic aspiration behind the development of AI is to emulate the human capabilities of senses (by acquiring images, recording sound or speech etc), comprehend this sensation(by processing the data acquired through sensory devices), and then act upon it.
Although, the phenomenon seems to a recent one, AI is not a new phenomenon. Its foundations were developed for over 70 years by the works of prominent scientists like Alan Turing, Marvin Minsky, and John McCarthy. The history of AI is full of periods of enthusiasm and heavy investments towards the development of AI, followed by periods of disappointment and low investments, a phenomena has been called as ‘AI Winters’. But, it seems that this cycle of ‘AI winters’ is over, once and for all due to various factors. The factors being exponential growth in computation power as expected by Moore’s law, huge decrease in cost of storage of data, cloud computing, and explosion of digital data dubbed as ‘Big Data‘. These factors combined by development of Machine Learning(ML) i.e., the ability of a machine to learn without being explicitly programmed, and deep learning i.e., the technique that implements ML using algorithms that resemble neurons structure in a human brain, have put the development of AI in hyper speed. In Machine Learning process, the algorithm is fed with training data and by analysing this data the algorithm generated newer knowledge, quite like a child who is taught the basics of how to sketch and shade and then eventually he comes up with a masterpiece.
AI and The Legal Sector
With the potential benefits and capabilities of AI, it is not surprising that some leading law firms are adopting AI systems, as they want to automate tasks like data entry, data management and repetitive time consuming tasks. AI systems combined with Machine Learning ability could analyse thousands of pages of complex legal documentation and find relevant documents once it is shown a sample relevant document like a judicial precedent. These systems would be very effective in conducting due diligence, reviewing contracts and risk assessment.
- Predicting Legal Outcomes
AI systems have started to be used to predict the legal outcomes a case i.e., likelihood to win the case. A Deloitte Insight report predicts “radical changes” and “profound reforms in legal sector due to AI systems, that would automate around one lakh tasks performed in legal sector by 2036. While some are concerned about threat to their jobs, some expect that if used correctly AI systems could help legal firms to have small specialised workforce review what the AI tools have provided and then can focus more on better advisory work for client.
Another legal service provider called ‘Legalist Inc.’ using proprietary algorithms estimates the likelihood of success of a case, the likely duration of disposal of the case, the likely expected return on success, and suggests whether to settle or move forward with the litigation.
- Conducting Legal Research
For instance, ‘Ross‘ an AI powered by IBM Watson is capable of conducting legal research, case brief analysis, instant summarization of cases, track any legal development with respect to user’s legal issue, capable of answering substantive legal questions like what are the patent requirements in U.S.
- Finding Gaps
With respect of insolvency specifically, ‘LawPath’ helps businesses to find legal gaps by completing online questionnaire, which could be very helpful during the insolvency proceedings. So, in future the development of industry specific databases could help in checking the health of businesses specifically for solvency.
The KEY Point
The key point to note is that the emergence of AI is not to be seen as an isolated event. Other surrounding technologies would work in consonance with it. AI works heavily on data that could be fed into it, so a foundation of clean, relevant and structured data is necessary. For this a flexible culture open to changes and risks would be necessary, along with talented professionals that could understand the AI system.
So, the first barriers law firms are going to face are creation of clean and reliable data.Fortunately, technological innovations that help in collection of such data and support its management are improving day by day. 
Why is AI a Better Option?
Companies these days are collecting large amount of data that allows them to cater to the needs of their clients better, tailor their products, develop marketing strategies in such a way that both their profits and customer satisfaction increases.Defined technically as “the information assets characterized by such a high volume, velocity and variety to require specific technology and analytical methods for its transformation into value”. In simplest of words, Big Data describes large volume of data which is both structured and unstructured, that due to its massive size cannot be processed using traditional databases and software techniques. This is where AI would play its important role. AI would be able to analyse this Big Data efficiently and quickly.
Role of AI in Insolvency Resolution
To understand this, we would first have to understand , how the process of Insolvency resolution takes place . A corporate insolvency resolution process (CIRP) can be initiated by filing an application before the NCLT once a corporate debtor makes a default of Rupees 1 lakh or more. This application can be filed by a financial creditor, an operational creditor or the corporate debtor itself. The Code allows a maximum 270 days for resolution.
After such application is admitted, a moratorium order is passed which prohibits the institution of suits or continuation of pending suits or proceedings against the corporate debtor or any action to foreclose, recover or enforce any security interest created by the corporate debtor in respect of its property. The moratorium order also prohibits transferring of assets by the corporate debtor and remains in effect till the completion of the CIRP or earlier if NCLT approves a resolution plan or passes an order for liquidation of the corporate debtor.
Appointment of Resolution Professional
NCLT appoints an interim resolution professional (IRP) who continues to manage the resolution process till the appointment of a resolution professional (RP). Once the committee of creditors is formed, a majority vote of 66% or more of the voting share of the financial creditors appoints the IRP as the resolution professional or substitutes IRP with another resolution professional.
Committee of Creditors
Once all the claims against the corporate debtor are collated, the interim resolution professional constitutes a committee of creditors. This committee comprises of all financial creditors of the corporate debtor. Every financial creditor in the committee of creditors (COC) is endowed with certain voting rights which are determined on the basis of financial debt owed to them. When there are no financial creditors or when all financial creditors are related parties of the corporate debtor, COC is comprised of the 18 largest operational creditors by value.
Role of the Resolution Professional
Resolution Professional is central to the CIRP and has a wide variety of tasks to perform. Due diligence becomes a crucial practice in the resolution process as unlike usual transactions, resolution applicant is denied from benefit of representations and warranties from the promoters. Such applicant, to a large extent, depends on Resolution Professional to provide all relevant information.
Further, since the whole process is strictly timed bounded, there is limited time frame to finish the due diligence process. Although Resolution Professional is responsible for protecting and preserving the value of the property of the corporate debtor, COC has a vital role to play through its voting rights. Resolution Professional is also responsible for providing the liquidation value to every member of the COC and is required to maintain the confidentiality of such value. A liquidation value is the estimated possible value of the assets of the corporate debtor if the corporate debtor were to be liquidated on the insolvency commencement date. Along with liquidation value, fair value of the assets is also determined. ‘Fair value’ has been defined as the “estimated realisable value of the assets of the corporate debtor, if they were to be exchanged on the insolvency commencement date between a willing buyer and a willing seller in an arm’s length transaction, after proper marketing and where the parties had acted knowledgeably, prudently and without compulsion”. Resolution Professional is likewise required to provide fair value to the COC after the receipt of the resolution plans.
How AI is going to help in this?
Due to advent of Big Data Insolvency professionals would have access to more data than ever before.This would allow the advisor to identify strategies, factors, and issues that will impact on business performance.More digitised data means the professional won’t have to spend days physically searching for relevant documents. Using data analytics AI systems to analyse this big chunk of data would help the professional to reach quicker conclusions confidently about what are the drivers of performance in a specific business (Key performance indicators)and what needs to be changed in the business. These systems could conduct file scans of key storage repositories and email servers to discover documents. AI algorithm would help the insolvency practitioners to discover compliances and non-compliances easily. For instance, what forms have to be complied with and when they are due.
Real Time Data Access
Such information and the Key performance indicators of a business which get updated from time to time can then be shared with the creditors on their smartphones, which can help them take better decision regarding insolvency. Such real time data access can ensure that interests of creditors is maintained and leads to creditor empowerment, as they will be able to take better decisions.
Industry specific database
Due to creation of industry specific databases with regards to insolvency eventually AI would be able to come up with correlations with regards to performance measures and risk of insolvency, which could be used to provide advance warning signs to businesses before their business goes into the red.The ability of such AI systems to conduct file discovery scans of key storage repositories and email servers would help them identify anomalies and make it easier to point out who is liable. Example of Big Data for insolvency profession could be analysing actions of Directors using Director Identification Numbers to find fraud, misrepresentation, or negligent behaviour. This all would help increase the opportunity for successful rescue or restructure.
AI Complimenting Professionals
Researchers believe that due to AI people rather than relying upon works of professional could come up with their own problem solving strategies. They believe such professionals should become either highly specialized or collaborate with AI service providers to take large amount of work that could be automated while keeping their margins less for individual cases.
Researchers predict that such advent of technology may have two fold impact on the legal profession.
- By replacement of traditional technologies and tools the work efficiency of professionals would increase while costs would decrease.
- Some traditional professionals might be replaced by such advanced technologies.They predict emergence of ‘para-professionals’ i.e., those who equipped with such technology would be able to perform tasks that previously required expert professionals, that too at much lower cost.
The Silver Lining
Despite this threat, the key thing to remember is that embracing these technologies is not an option but necessity both for the sake of legal professionals, IPs, and clients. Appropriate and timely implementation of Artificial intelligence will not replace lawyers, but rather act as an augmentation tool to improve legal service industry.
If you have any queries relation to this, feel free to revert back to me at www.linkedin.com/in/shubhamborkar.
Author: Mr. Shubham Borkar, Senior Associate – Litigation and Business Development and Nitish Daniel, P.H.D Candidate NLU Delhi, Intern at Khurana & Khurana, Advocates and IP Attorneys. In case of any queries please contact/write back to us at firstname.lastname@example.org.
Artificial Intelligence, Merriam-Webster.com. Merriam-Webster, n.d. Web. 23 Oct. 2018
Artificial Intelligence, Oxford Dictionary (3rd edn, 2010).
Bruce G. Buchanan, ‘ A (Very) Brief History of Artificial Intelligence’, AI Magazine Volume 26 Number Number 4 (2006).
Moore’s law was a prediction made by American engineer Gordon Moore in 1965 which states that the number of transistors per silicon chip doubles every year. Hence, resulting in exponential growth in computational power.
 Technoligical Innovations that would work in consonance with AI
Aerial inspection via Drone technology could help topographic survey of large land assets from the air.
Cloud storage is form of computer data storage where digital data instead of being stored in local hard drive(memory) of the user’s computer is saved on remote data servers of cloud storage service providers. Same data could be stored in multiple servers of such service provider and these servers could be present in multiple locations across the globe. So, if one server goes down the data is still safe in other servers.
Cloud storage ensures that key company documentation on insolvency cases is easily accessible and stored at low cost without fearing the chance of it getting destroyed or lost. As data generated by company could be huge, instead of needing separate infrastructure on business premises, they could take the service of cloud service providers. This could ensure data is not destroyed or tampered with when company gets into financial trouble.Availability of such data would facilitate its processing by AI.
Blockchain is often defined in complex terms as distributed, decentralized, public ledger. Use of Blockchain technology can ensure that such data isn’t manipulated or tampered within simple word this means is that Blockchain is chain of blocks that contain information. Each block has data, ‘Hash’, and the Hash of previous block.
A Hash can be assumed to be fingerprint of a block, which is unique for a block just like a fingerprint. Changing any information in the block changes the Hash. Each time a new information/data is added in the Blockchain it adds new block, such a new block would contain the Hash of the previous block. So, tampering with a block will invalidate all the subsequent blocks, as the hash of tampered block would change and will not match with the subsequent blocks.
Further, Block chain has a security functionality called ‘proof of work’, which is a mechanism that slows down the creation of new blocks.Another security mechanism of Blockchain is being distributed. What’s special about blockchain is that instead of a centralised authority validating the transaction, transactions are validated by Person to Person(P2P) networks which is open to all. When someone joins this P2P network they get the full copy of blockchain. If someone tries to change data in a Blockchain, it is verified with each node(the participants in P2P network). Only if it checks out in the nodes it is added to the Blockchain.
To successfully tamper with data in Blockchain you will need to tamper with all the blocks in the chain, redo the proofing for each block, and take control of more than 50% of P2P network. This is considered almost impossible to do. Use of such technology can ensure that data is not manipulated and all creditors are on the same page.
 De Mauro et al., “A Formal definition of Big Data based on its essential Features”. Library Review 65 122–135 (2016).(Available at doi:10.1108/LR-06-2015-0061).
Insolvency and Bankruptcy Code 2016, s 4(1).
Insolvency and Bankruptcy Code 2016, ss 14(1)(a), 14(1)(c).
Insolvency and Bankruptcy Code 2016, s 14(1)(b)
Insolvency and Bankruptcy Code 2016, s 14(4).
 R Susskind and D Susskind, “The Future of the Professions: How Technology Will Transform the Work of Human Experts”, Oxford University Press, 2016.
 R Susskind and D Susskind, “The Future of the Professions: How Technology Will Transform the Work of Human Experts”, Oxford University Press, 2016.