Description:FORM 2
THE PATENTS ACT,1970
(39 of 1970)
&
THE PATENT RULES, 2003
Complete Specification
(See section10 and rule13)
1. Title of the Invention: ARTIFICIAL INTELLIGENCE TECHNIQUES AS A TOOL OF HUMAN RESOURCE MANAGEMENT

2.Applicants
Name Nationality Address
Dr. Prashant Amin
Indian Assistant Professor, Department of Commerce and Business Management, The Maharaja Sayajirao University of Baroda, Pratapgunj, Vadodara – 390002, Gujarat, India.
Dr. John E P
Indian Assistant Professor, Department of Management, SRM Institute of Science and Technology, Vadapalani Campus, Chennai – 600026, Tamil Nadu, India.
C. R. Vijay
Indian Assistant Professor, Department of MBA, DR. N. G. P. Institute of Technology, Coimbatore-641048, Tamil Nadu, India.
Syed Rizwan Naqvi
Indian Research Scholar, Department of Human Resource and Organizational Behaviour, Amity Business School, Amity University, AUUP, Sector 125, Noida, Gautam Buddha Nagar-201313, Uttar Pradesh, India.
Anuradha
Indian Assistant Professor, Department of Management, Pt Deen Dayal Upadhyaya Management College, Mall Road Meerut-250001, Uttar Pradesh, India.
Dr. C. Meera
Indian Associate Professor, Department of MBA, Dr. NGP Institute of Technology (Autonomous), Kalapatti Main Road, Sharp Nagar, Nehru Nagar West, Coimbatore-641035, Tamil Nadu, India.
Dr. Devpriya Dey
Indian Assistant Professor, Department of School of Business, Alliance University, Anekal, Chandapura Road, Bangalore-562106, Karnataka, India.
K. K. S. R. Deepti
Indian Degree Lecturer, Department of Physics, Spaces Degree College, Payakaraopeta, Visakhapatnam, Andhra Paredesh, India.
3.Preamble to the description:
The following specification particularly describes the invention and the manner in which it is to be performed.

4. DESCRIPTION
FIELD OF THE INVENTION
The present invention relates to the field of Human Resource Management. The main aim of this invention is to show the Artificial Intelligence techniques as a tool of HRM.
BACKGROUND OF THE INVENTION
In computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. AI as “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation”. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving". The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, "AI is whatever hasn't been done yet." For instance, optical character recognition is frequently excluded from "artificial intelligence", having become a routine technology. Modern machine capabilities generally classified as AI include successfully understanding human speech, competing at the highest level in strategic game systems (such as chess and Go), autonomously operating cars, and intelligent routing in content delivery networks and military simulations, artificial intelligence into three different types of AI systems: analytical, human inspired, and humanized artificial intelligence. Analytical AI has only characteristics consistent with cognitive intelligence generating cognitive representation of the world and using learning based on past experience to inform future decisions. Human-inspired AI has elements from cognitive as well as emotional intelligence, understanding, in addition to cognitive elements, also human emotions considering them in their decision making. Humanized AI shows characteristics of all types of competencies (i.e., cognitive, emotional, and social intelligence), able to be self-conscious and self-aware in interactions with others. AI and automation might replace roles, it’s easy to forget that these very same technologies have a huge role to play in finding, securing and retaining employees”. “In this era of constant change and digital skills shortages, finding the right talent is more challenging than ever. By using AI and automation, businesses can identify a diverse range of top candidates quickly and easily, and at a pace that keeps stride with the frenzied speed of modern business.”
SUMMARY OF THE INVENTION
As much as the HR technology landscape continues to be disrupted by AI. HR teams need to balance these cognitive tech advancements with transparency. HR leaders and practitioners need to have a clear understanding of how decisions are being made to mitigate unknowingly injecting bias into their programs, This transparency will be essential in making sure that employees trust the new technology. As you've gathered by now, there are multiple advantages to utilizing AI technology for your human resources and recruiting needs, but nothing is perfect in life, certainly not a budding form of technology that has yet to reach its maximum potential. Many services and programs offered could lack different aspects one might be accustomed to in manual the non AI world, such as the ability to leave feedback to a candidate after a video interview, or specific CV search criteria. One major aspect that AI technology lacks is empathy and human interaction or the opportunity to handpick a candidate and get to know them personally during the recruitment process which simply cannot be done at this time while relying on AI technology to do all the work for your company. AI sees data whereas humans sense emotion and this is something that will not be changing in the foreseeable future. Therefore, it is up to you to decide if AI technology is the right solution for your businesses' needs. Are you a corporation with thousands of employees, spending big bucks on recruitment annually and desperately need a way to streamline the process and cut costs? Are you a mom-and-pop shop that has less than 15 employees and takes pride in getting to know each employee like family? Every business has different goals, budgets, and desires, but the beauty of the AI industry is that there is a solution for everyone, no matter how big or how small. It is up to you to decide what works for your business, whether that is adapting to the constant growing AI industry or keeping things as they are or just introducing small changes over time. Either way, AI technology is only going to keep growing and at some point in the future AI will be the norm and the old-fashioned ways of recruiting and human resource processes will seem like the stone ages.
BRIEF DESCRIPTION OF THE DRAWINGS
Fig.1: depicts Artificial Intelligence in HRM.
Fig.2: depicts the impact of AI on HRM.
Fig.3: depicts AI application frame work in HRM.

BRIEF DESCRIPTION OF THE INVENTION
In computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. AI as “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation”. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".
The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, "AI is whatever hasn't been done yet." For instance, optical character recognition is frequently excluded from "artificial intelligence", having become a routine technology. Modern machine capabilities generally classified as AI include successfully understanding human speech, competing at the highest level in strategic game systems (such as chess and Go), autonomously operating cars, and intelligent routing in content delivery networks and military simulations, artificial intelligence into three different types of AI systems: analytical, human inspired, and humanized artificial intelligence. Analytical AI has only characteristics consistent with cognitive intelligence generating cognitive representation of the world and using learning based on past experience to inform future decisions. Human-inspired AI has elements from cognitive as well as emotional intelligence, understanding, in addition to cognitive elements, also human emotions considering them in their decision making. Humanized AI shows characteristics of all types of competencies (i.e., cognitive, emotional, and social intelligence), able to be self-conscious and self-aware in interactions with others. AI and automation might replace roles, it’s easy to forget that these very same technologies have a huge role to play in finding, securing and retaining employees”. “In this era of constant change and digital skills shortages, finding the right talent is more challenging than ever. By using AI and automation, businesses can identify a diverse range of top candidates quickly and easily, and at a pace that keeps stride with the frenzied speed of modern business.”
Basic artificial intelligence programs that can help recruiters with the sourcing and screening processes include screening chatbots and automated social media scraping tools. These tools are designed to provide weak or average indicators about an applicant’s likelihood of success with the company. Mya, an AI recruiting assistant created by First Job, is one such chatbot that interacts with applicants to verify they meet job requirements, answer questions and keep them informed on their application’s status, according to the Society for Human Resource Management. This bot provides 24/7 support through chat, text message, Skype or e-mail, and will contact a human when it can’t complete a task. Social media scraping tools are another type of artificial intelligence recruiting tool.
These bots can collect vast amounts of data through an applicant’s social media profiles and use this data to predict certain behaviors like future engagement levels. Intermediate artificial intelligence applications that are used in the hiring process include things like tests, gamification or simulations that collect data from the applicant directly. Unilever is one company that has utilized an effective artificial intelligence screening process designed with the help of their partners Pymetrics. Hiring strategy requires applicants to spend around twenty minutes playing some neuroscience-based Pymetrics games. These scientific games sneakily measure a candidate’s qualities like memory, relationship to risk, ability to read contextual cues and ability to focus. These intermediate AI applications usually give hiring managers a fairly good indication of whether a candidate is a good fit for the position or not, but these predictors usually don’t focus on specific job metrics. Advanced artificial intelligence solutions, however, utilize custom algorithms that are created specifically to link unique job performance measures to potential candidates that best exhibit these qualities. Hire Vue is a company that focuses on developing these advanced AI human resource solutions. Currently, their most successful program involves a video interview that develops questions “specifically designed to elicit responses predictive of job success and find the right behaviors.” The Hire Vue artificial intelligence program analyzes each applicant’s answers, body language, tone, emotional state and keywords. Affective has also recently produced emotion recognition software that helps judge a candidate’s honesty and emotional intelligence. These types of AI software programs are so incredibly advanced that they can literally “detect the flash of contempt that passes over an applicant’s face when he discusses his ex-boss,”.
ARTIFICIAL INTELLIGENCE AND HR FUNCTIONS
Personalized employee experiences: IBM officials in their study discussed how AI can effectively be woven into an employee’s on boarding program. New employees who typically want to meet people and acquire information typically may not know where to go. They may ask their desk neighbor. But what if she works in a different department? “What if Joe had been welcomed with new hire information on his mobile device that was tailored to his first assignment?” IBM officials wrote in the report on transforming HR with AI. IBM is looking to create a system that will answer a new employee's most pressing or job critical questions to help get them up to speed fast. An AI, for example, could provide training suggestions or provide the names, locations and contact info for people he/she should look to connect with on his first day or so. That same employee could also be advised by AI engines that a new hire webpage contains a lot of useful information. Cognitive-supporting decision-making: IBM officials, who naturally are promoting their own AI capabilities through IBM Watson, also demonstrated ways cognitive engines could help employees arrive at key day-to-day decisions in the workplace.
Usually, HR team members would have to handle these tasks:
Vacation requests - Employees that want to put in for vacation days are informed that it is unlikely to be approved as many others have already booked vacation in that time frame. Determining your mood - An employee takes a client call. After the call, the employee receives feedback that he seems anxious and should take a break before his meeting. Team training - When an organization wants to take a more systematic approach to employee training, team managers are provided a list of training opportunities for team members. Hiring processes - A hiring manager is presented with information that the company’s recruitment approach falls short because it interviews too few candidates. Cognitive solutions can help organizations tap into multiple data sources and reveal new insights to help companies develop candidate profiles, among other things.
Automation of ‘Repetitive, Low-Value Add Tasks’: AI presents an opportunity for HR to automate “repetitive, low-value add tasks” and increase the focus on more strategic work. HR spending time processing the steps of onboarding a new employee (allocating space, provisioning a laptop, etc.), saving time in those arenas can help HR teams pivot to making sure they focus on “value-add work like mentoring and continuous feedback.” AI tools automate away common HR tasks like benefits management and triaging common questions and requests, HR teams will be “free to do more of the creative and strategic work that has a bigger impact on the success of their companies.” Smarter people analytics: For years, companies have been collecting data on their customers to gain insights to predict future behavior. HR teams have a lot of catching up to do in leveraging these people analytics.
Determining what data to track, analyze, manage and protect will enable AI to play a larger role within HR. “In the never-ending war for talent, companies will look to find innovative ways to attract top talent. Technologies that enhance the candidate experience and meet the candidate’s digital expectations will help distinguish companies from one another.” Removing biases: In the survey by the Human Resources Professional Association, researchers found that even when employers strive to be inclusive, they may subconsciously lean toward candidates who are most like them, or what they call “unconscious bias.” Another bias, language bias, has been discovered by a psychological tool called the Implicit Association Test (IAT) that shows that people’s subconscious word associations indicate bias. “These biases find their way into job descriptions, as well as resume selections. Now, thanks to AI, algorithms can be designed to help employers identify and remove these bias patterns in language they use to improve their hiring communications and welcome diverse applicants,” HRPA researchers noted. AI could also present managers with candidates who may have been screened out due to human tendency to favor candidates with similar traits or competencies.
HRPA researchers algorithms are free of those tendencies, which allows managers to go beyond gut feelings and rely on data-driven assessments instead. Identifying employees on the way out: AI platforms are designed to single out employees that may be heading for the exit door. It tracks employee computer activity — emails, keystrokes, internet browsing, etc. — and stores it for one month and implements an AI system that analyzes the data to determine a baseline of normal activity patterns in the organization. “Based on that knowledge,” HRPA researchers noted, “it flags outliers and reports them to the employer and also detects changes in the overall tone of employees’ communications to predict when employees might be thinking of leaving.” Litigation strategy: Employment-related lawsuits tend to be fact-driven, which makes gathering documents and other information critical. However, only 5 percent of respondents to Littler's survey are using advanced analytics to guide their litigation strategy. Employers may not be aware of the benefits to using analytics in this context, Crews said.
"The ability to leverage data early in a case, to tease out insights before you ever take a deposition or begin evaluating the credibility of witnesses, is revolutionary." Having the ability to find key documents lets the employer see what people were actually doing at a certain time and can help build a story, he noted. Imagine that a repair technician who travels to residences to work on refrigerators files a wage and hour class action claiming that technicians weren't paid for all hours worked. The complaint and subsequent depositions will reveal the workers' version of what their days looked like, but analytics can be used to verify or refute their story. "The more information you have, the better the decision-making process you can engage in," Crews said. The employer could gather GPS data from work trucks, routing instructions, communications about the technicians' assignments, invoices, and cellphone and login information. These data will paint a picture.
The data may indicate that the technicians didn't work off the clock and were appropriately compensated for all hours—then the employer has some solid evidence on its side. But if the data reveals that the workers' claims have merit, it is better to review the data and know about it on the front end before going through lengthy and costly litigation, Crews said. Pay Equity: Data analytics can also be used to assess pay equity. Legislation in this area is changing rapidly at the state and local level. For example, at least 12 jurisdictions have passed laws prohibiting employers from asking job applicants about their prior compensation. The idea behind such laws is to stop perpetuating historic discriminatory pay practices based on gender, race and ethnicity. Technology can be particularly helpful to monitor employee compensation for discrepancies based on protected categories, Crews said, noting that some jurisdictions with pay equity laws have a safe harbor for employers that conduct audits and attempt to eliminate gaps. There are tools available that make it easy to build a user-friendly experience and to analyze, understand and communicate data, he added. "You no longer have to rely on just an Excel spreadsheet full of math." Getting a picture of what is actually happening in the organization is powerful, Crews noted. "When advanced technology is paired with good storytelling and visualization, it empowers HR professionals to have the conversation with the compensation team, executives and other decision-makers."
Chatbots: Certain technology, such as chatbots, can help employees access important information about policies and procedures from anywhere and at any time. Chatbots communicate by text and can be useful for answering common employee questions. Two-thirds of respondents said that they believe employees are more comfortable using chatbots than other forms of contact for transactional inquiries about paid-time-off policies, open enrollment and leaves of absence, according to a 2017 ServiceNow survey of 350 HR leaders. ServiceNow is a cloud computing company based in Santa Clara, Calif. Employers that use chatbots need to ensure that they are complying with data security, disability and other federal and state employment laws. Legal pitfalls: When using AI to drive human resources strategy, HR professionals must monitor systems for bias. They need to look out for disparate impact—which happens when a seemingly fair or neutral standard is actually discriminatory in practice. For example, a recruiting tool may weed out candidates that are more than 10 miles away from the worksite. What if the neighborhoods surrounding the worksite are predominantly made up of affluent white families? This hiring criteria could have a disparate impact based on race and ethnicity (Nicastro, 2018). Recruiting: We make many decisions on gut feel. One study showed that most hiring managers make a decision on a candidate within the first 60 seconds of meeting a candidate, often based on look, handshake, attire, or speech.
Does we really know what characteristics, experiences, education, and personality traits guarantee success in a given role? No we don’t. Managers and HR professionals use billions of dollars of assessment, tests, simulations, and games to hire people – yet many tell me they still get 30-40% of their candidates wrong. Algorithms based on AI can weed through resumes, find good internal candidates, profile high performers, and even decode video interviews and give us signals about who is likely to succeed. One organization uses Pymetrics’ AI-based gamified assessment to screen candidates for its marketing and sales roles and their success rate has gone up by over 30%, while eliminating all the “interview bias” and “educational pedigree bias” inherent in the current process. AI in recruitment will be huge. while we are all worried about job skills (software skills, sales skills, math skills, etc.) most research shows that technical skills make up a small part of a person’s success. In one of the most recent on High-Impact Talent Acquisition, study found that the level 4 maturity companies, those with the highest financial return from hiring, allocate almost 40% of their hiring criteria to emotional and psychological traits like ambition, learning agility, passion, and sense of purpose. Will AI uncover this too? Perhaps The global L&D industry is over $200 billion and most learning professionals tell us that at least half this is wasted (forgotten, inappropriately applied, or just wasting peoples’ time). But we don’t know which half this is! Do you as an individual know what you “need to learn” to be better at your job? We all have a pretty good idea, but what if we had algorithms that monitored and studied the skills, behaviors, and activities of the highest performers in our teams and then just told us how to be more like them? These kinds of “Netflix-like” algorithms are now entering the world of learning platforms, making learning as useful and fun as watching cable TV. Again the market is young, but the opportunity is massive. Research shows that the average employee has less than 25 minutes a week to train and learn; if we make that time more relevant everyone will perform better.
Management and leadership: We operate like Zen masters. We read books, we go to workshops, we copy the bosses we admire, and we glorify the successful leaders of the day. Do we really know the science of leadership? I’d suggest it’s a fleeting topic. This year we are focused on purpose, mission, and followership. Only a few years ago it was “servant leadership” and when I was young it was “execution and financial acumen.” Most studies find that there are dozens of management and leadership traits that define success, and each of us brings a slightly different and unique combination of them. AI can now help decode this. Three vendors who have built “AI-based” coaching tools, systems that request feedback, read comments, and intuit sentiment from employees and teams. They use this data to match these individual and teams’ issues against higher performing teams, and use that data to give managers and supervisors “nudges” on how to do better. One client told that within only 3 months of using this tool their leadership teams showed a 25% improvement in corporate values just based on small behavioral nudges.

, Claims:We Claim:
1. AI enables HR teams to extract insights from data and give recommendations in real-time.
2. AI also removes many of the common human biases and inconsistencies in a function that is as sensitive and crucial as Human Capital Management.
3. An HR manager might use an AI-enabled tool like Workable as part of their talent acquisition strategy by automating the recruitment process.
4. For example, automated screening frees up time and resources spent on interviewing candidates who aren't qualified for open positions at their company.
5. AI techniques are those procedures which are used to enable computers to show human like intelligent activities such as visual perception, speech recognition, decision-making, natural language understanding etc.
6. One of the most significant applications of AI in HRM is in recruiting and hiring. AI-powered tools can help automate the process of screening resumes, scheduling interviews, and even conducting initial interviews.
7. HRD is a process that involves both the employee and the organization working together to achieve mutual goals. It includes a variety of methods such as training, mentoring, coaching, job rotation, and career development.

Dated this the 30th June 2023.

Senthil Kumar B
Agent for the applicant
IN/PA-1549