Annotated Bibliography

ARTIFICIAL INTELLIGENCE: THE GOOD, THE BAD AND THE PRACTICAL

Artificial Intelligence: The Good, the Bad and the Practical

Institute of Management & Research

* Disha Bhatia, Anushka Patgaonkar, Ankeeta Mane and Sumit Dhyani

Abstract HR is primarily concerned with people management within organizations, with a major focus on policies and systems, designed to maximize employee performance. AI is intelligence demonstrated by machines, in con- trast to the natural intelligence displayed by humans. The purpose of this research is to study the impact of Artificial Intelligence on Employee Relations and the Human Resources spectrum as a whole, to understand the employee perspectives regarding Industry 4.0 and how millennial perceive this transformation. The tech- nology driven approach through AI tools have transformed various HR functions such as candidate sourcing, recruitment and selection, compensation and payroll, employee engagement etc. It is redesigning the func- tions of an organization to eliminate human errors and give accurate data at a faster pace. However in the current scenario, adaption to AI tools still remains a challenge to organisations and employees. Irrespective of their domains, employees find the smart technologies challenging, are concerned about these technologies replacing them and therefore are apprehensive while adopting the same. The major focus is also on how HR can enable people for the future of augmented work.

Every organization is affected by the environment it operates in and needs to modify itself on the basis of the changing demands in this environment. Another conflicting paradigm is that computer algorithms can never replace human empathy and intuition. AI would automate middle skilled employee functions however strate- gic decisions should be left to employees’ discretion presently. The paper studies these diverse perspectives, their positive and negative influence on the organisations, expectations of millennial from work and how HR can enrich an employee’s professional life with AI into picture, direct them with better career planning thus giving HR an edge over other organisational functions and create highly productive and efficient employees.

Keywords: Industry 4.0, Artificial Intelligence, Human Resources, Career planning, Employee Relations.

INTRODUCTION

Artificial Intelligence is an area which contains wide range of algorithms and machine learning tools that

can rapidly ingest data, identify patterns, optimize and predict trends. Due to its high potential, its adoption is being treated as the fourth industrial revolution which is commonly referred to as In-

* Disha Bhatia, Anushka Patgaonkar, Ankeeta Mane and Sumit Dhyani Chetana’s Institute of Management & Research, Mumbai.

36 Volume XI Issue 1  March 2019  C.I.M.R. ISSN – 0976-0628

ISSN – 0976-0628 Chetana’s Vol XI Issue 1 : pp 36 - 45

ARTIFICIAL INTELLIGENCE: THE GOOD, THE BAD AND THE PRACTICAL

37 Volume XI Issue 1  March 2019  C.I.M.R. ISSN – 0976-0628

dustry 4.0. The current trend of automation and data exchange, cyber-physical systems, the Internet of things, cloud computing and cognitive comput- ing all together amalgamates into the Industry 4.0. Speaking of the significance of AI in the industrial domain, it is revolutionizing how businesses work and has a massive impact on the current corporate scenario.

This paper majorly focuses on how HR can bring a difference in an Employee’s life through AI. Human Resources is an organizational function dealing with the biggest asset of an organization which is the Employees. From their well-being to managing various functions such as employee per- formance, development and culture, understanding employee ROI is crucial and helps to evaluate their impact on any organization. AI would be replacing many traditional human tasks that are mundane and time-consuming. Although it may be a little too early to sound the alarm, AI in HR is definitely gaining its momentum.

Coming to Millennial, it is a modern term broadly given to a group of people which are of two types Generation Y (people born between1981-1991) and Generation Z (born between1991-2001) who are often at odds with each other. They require a de- fined career path. They also want the tools neces- sary to exceed expectations. Millennial and auto- mation are hardwired with the same core character traits - efficiency, speed and connectivity. Research shows that Millennial are largely optimistic about the role automation could play in their future, Millennial digital know-how and passion for “the next best thing” make them the perfect candidates to drive automation forward. (Wheeler, S. A. (2017)).

Now with such a huge potential, AI would tend to

replace decision making and so would the decision makers. Therefore there is a massive need to have an appropriate career plan so as to reduce the fear of being replaced. Our future with AI in it is one where the professionals have to improve their abili- ties to produce value, think strategically and cre- atively, not just tactically only then will they be- come the power rangers of tomorrow.

However as exciting as it seems there is also a downside to this revolution due to the risks asso- ciated with it. AI cannot work without “Training data”. All the AI algorithms and need past data to function effectively. In case the current organiza- tional practices are not up to the mark, the result- ing solutions through AI would also be either bi- ased, punitive or overly hierarchical. AI applica- tions need to be transparent and tunable and need constant examination and up gradation. Also the risk of data security prevails in addition to which the hardware and infrastructure needs are not al- ways reasonable for all types of firms in the busi- ness eco systems

Business executives admit they have not imple- mented AI because they are not exactly sure what it can do for them, how it can help their organiza- tion, how they can integrate it into their company or how to assess the ROI in the technology. In order to be very clear about what business problem can be solved using AI technology, HR should take the lead in shepherding AI software into the work- place, transforming the human resources function and enhancing the employee experience.

For instance, through predictive analytics a man- ager might discover that a highly efficient employee might tend to leave the organization and therefore his behaviour towards the employee would be af- fected but this information can also be used to

ARTIFICIAL INTELLIGENCE: THE GOOD, THE BAD AND THE PRACTICAL

Volume XI Issue 1  March 2019  C.I.M.R. ISSN – 0976-062838

understand the consequences of this decision of the employee and thus help him change current practices so as to retain such talent. Therefore, it is crucial to learn the applications of behavioural economics so AI is used to the best of an organization’s benefits.

LITERATURE REVIEW

The New Year will bring in more challenges to the human resources professionals. New laws, new technologies, and the growing gig economy are all set to change the face of human resources. (McGrath, D., & Damodaran, D. (2017, 12)) In- deed, even the label “human resources” and today’s most advanced HR competency models, operating structures, and deliverables will fail to capture the necessary evolution. (Boudreau, J. W. (2015)), The group foresaw that by 2025, HR will exist in a world of boundary-less work, detached from tradi- tional employment. There will be a tsunami of big data on virtually every facet of work and the work- place. Workers will engage with work through a globally interconnected and democratized ecosys- tem that will have unprecedented ability to connect and share their views. (Boudreau, J. W. (2015)) Though the field of AI has been an area of exten- sive research since the term was coined in 1956, it has recently only led to large-scale deployment of intelligent applications for different domains and tasks. (Srivastava, S. K. (2018)).Over the last two decades, technology has drastically changed the way organizations operate. (Spahic, J. (2015)). The fu- ture requires a profession that seamlessly integrates disciplines such as procurement, marketing risk based options, global supply chains, and man– machine collaborative analytics.(Boudreau, J. W. (2015)) While significant advancements have been made in positioning HR to become more strategi- cally oriented, companies spend millions on HR

research and analytics practices. (Falletta, 2008a). AI is at the peak of the hype curve right now. A lot of people are talking about it, but there’s not a lot of understanding on how to really implement and deploy artificial intelligence to enhance people practices in the workplace. AI has the potential to offer personalization at scale, beginning with the hiring and onboarding processes. The first area we are seeing early traction in using artificial intelli- gence is in screening and interviewing new hires. One of the areas HR is struggling with is how to offer internal mobility to employees. As employees stay in their roles longer, companies are looking for easy ways provide employees with recommen- dations for new job roles to pursue within the com- pany and the relevant training needed for these. Artificial-intelligence-powered platforms are being explored as the optimal solution for internal talent mobility.

The technology will predict how likely an indi- vidual is to leave the organization. Then it’s the job of the people analytics team to identify em- ployee groups in key job roles at risk of finding new opportunities outside of the company and to propose a program of manager intervention to pre- vent departures. (Alexandria (Aug 10, 2018)).

Administrative tasks such as basic HR metrics, compensation, and staffing can now be streamlined, which allow HR professionals to move toward more sophisticated HR functions like gathering complex data and information, enabling benchmarking of HR metrics, and capitalizing on the unrealized potential of strategic use of human capital. As a result, HR professionals have the ability to signifi- cantly contribute to the bottom line through better human capital management (Spahic, J. (2015)).

Nonetheless, little is known about the extent to

ARTIFICIAL INTELLIGENCE: THE GOOD, THE BAD AND THE PRACTICAL

39 Volume XI Issue 1  March 2019  C.I.M.R. ISSN – 0976-0628

which global firms perform HR research and analytics activities and how these disparate data collection efforts inform HR strategy, decision making, and execution (Falletta, 2008a).

Considering the Millennial perspective, One of the most vocal frustrations expressed by them was that employers too often overpromise and under deliver with regard to benchmarks and expectations. Ca- reer paths are often based on timing matrices, rather than results. Successful younger professionals want assurance that if they appear well on the path to success, but that the process is taking slightly longer than expected, that the opportunity for advance- ment will still be there. (Aurora (March 2018)). Employee loyalty is best achieved when expecta- tions are clearly defined, when the work environ- ment is conducive to career advancement, and when the employer provides the necessary tools to allow them to succeed. Conversely, employers are loyal to their employees when the employees embrace the culture of the company; use the tools made available by the employer, work to advance the organization as well as their personal goals; and contribute to the well-being of the entire organiza- tion. The path to success is mutual and should be communicated upfront, without any ambiguity, in the interviewing process and during employment. Young professionals aspire to be well trained, knowledgeable, and strong participants in the in- dustry. One of the challenges for the industry is the means to expedite education and training. Millennial in the industry want immediate gratification and success. Although the equipment leasing and fi- nance industry is not difficult to learn, it often takes hands-on experience and time to fully understand the many nuances involved in originating, under- writing, funding, and collecting strong, well-per- forming assets. (Scott A. Wheeler)

STARA awareness captures the extent to which an employee views the likelihood of Smart Technol- ogy, Artificial Intelligence, Robotics and Algorithms impacting on their future career prospects. This approach, developed for this study, is positioned within the career-planning literature with Greenhaus and Kopelman (1981), suggests that career plan- ning has several key and sequential parts. These parts are based on the information surrounding: (1) one’s interests, values, and talents, (2) the work- place opportunities, and (3) work—fami1y/leisure interests. The individual may also have their own goals and strategies to achieve their desired career outcomes. Overall, career planning refers to indi- viduals outlining future career developments and to their setting and pursuing career goals’ (Zikic & Klehe, 2006: 393). It is important to note that ca- reer planning is an ongoing process that is assessed and carried out over one’s lifetime. Early career- planning research by Gould (1979) suggested that employees with higher levels of career planning had more effective careers.

The impact from STARA is also likely to increase the prominence of the boundary less career. Inkson summarized what is happening to careers by stat- ing that ‘the old picture of stable employment and associated organizational careers is fading’ (2006: 297). The way we view careers needs to be dy- namic, ever changing, and unexpected. However, we can see these changes to careers as opportuni- ties that can be capitalized on (Krumboltz, 2009).

Given that STARA is likely to change employment in a profound way, it is expected that the very nature of career planning is at a pivotal time. For ex- ample, if we take the future predictions from Frey and Osborne (2013) and look at them based on the traditional model of career planning (Greenhaus & Kopelman, 1981; i.e., assessing values, talents,

ARTIFICIAL INTELLIGENCE: THE GOOD, THE BAD AND THE PRACTICAL

Volume XI Issue 1  March 2019  C.I.M.R. ISSN – 0976-062840

workplace opportunities, and work—family/leisure interests), there is a large disconnect. This is im- portant because Baruch discussed the rate of change with technology, and how these changes ‘have wide implications for the management of people at work, and in particular the planning and managing of careers’ (2004: 58).

If the predictions of Frey and Osborne (2013) are even partly correct, workplace opportunities could be reduced significantly, making it harder to plan one’s career. This in part makes an employee’s values and talents, as well as work—family/1eisure interests, irrelevant to the career-planning process. For example, an employee with a personal love of vehicles and a talent for driving long periods can still be replaced by driverless vehicles. Within the career-planning process, we consider STARA awareness to be an extension or a part of how an employee considers their future career prospects within their current job, workplace and industry.

In addition, several ethical issues have emerged with respect to the use and application of predic- tive analytics in terms of HR decision making (Bassi, 2011). Therefore, this research investigates the extent to which global firms perform HR re- search and analytics and how the resultant data are applied. By comparing these practices across in- dustries, best practices can be identified and shared among participating companies. This will also al- low the researcher to build a practical framework to advance HR research and analytics practices in organizational settings. Spahic, J. (2015)

OBJECTIVES OF THE STUDY

To study: 1. The penetration of Artificial Intelligence in HR

functions

2. How career planning can be enhanced with the advent of AI

3. The Millennial perspective of AI 4. How HR can enable people for the future of aug-

mented work 5. And recommend a model for effective implemen-

tation of Artificial Intelligence in organisations. RESEARCH METHODOLOGY

It is a descriptive research where the questionnaire consisted of 16 different questions wherein 200 HR professionals were asked to give feedback and thoughts about AI in HR functions, out of which only 35 responded. The questions included various advantages and disadvantages of HR functions (re- cruitment, on boarding, employee engagement, payroll and compensation, training and develop- ment, attendance, employee retention, performance management, emotional quotient, individual biases, also to know if AI is better than HRIS).

The impact of AI on middle skilled functions of HR and whether it is going to enhance or empower the human aspect of human resources or overpower it up to a point where HR employees fear losing their jobs.

Despite these challenges and risks, the upside is enormous. As AI systems in HR get smarter, more proven, and more focused on specific problems, we will see dramatic improvements in productiv- ity, performance, and employee wellbeing. We just have to be patient, vigilant, and willing to invest and plan professional career path accordingly.

ARTIFICIAL INTELLIGENCE: THE GOOD, THE BAD AND THE PRACTICAL

41 Volume XI Issue 1  March 2019  C.I.M.R. ISSN – 0976-0628

Analysis

Fig 1.1 From a formal survey procured from 35 HR employees from the age group of 22-45 years, we conclude that 57% of respondents AGREE, 28% of respondents DISAGREE, 9% of respondents STRONGLY AGREE and 6% of respondents STRONGLY DISAGREE wherein our 2nd objective was fulfilled as AI entered that middle skilled jobs will be replaced due to AI.

Fig 1.2 From a formal survey procured from 35 HR employees from the age group of 22-45 years, we conclude that 60% of respondents AGREE, 31% of respondents STRONGLY AGREE, 9% of respondents DISAGREE that there is lack of emotional touch with the employees due to AI.

Fig 1.5 From a formal survey procured from 35 HR employees from the age group of 22-45 years, we conclude that 37% of respondents AGREE, 20% of respondents STRONGLY AGREE, 43% of respondents DISAGREE that recruitment of candidates has become smooth due to AI implementation.

Fig 1.3 From a formal survey procured from 35 HR employees from the age group of 22-45 years, we conclude that 68% of respondents AGREE, 26% of respondents STRONGLY AGREE, 6% of respondents DISAGREE that AI tools help to fulfil the objective of HR Functions.

Fig 1.4 From a formal survey procured from 35 HR employees from the age group of 22-45 years, we conclude that 52% of respondents AGREE, 14% of respondents STRONGLY AGREE, 34% of respondents DISAGREE that On boarding process has eased with the AI tools in your organisation.

ARTIFICIAL INTELLIGENCE: THE GOOD, THE BAD AND THE PRACTICAL

Volume XI Issue 1  March 2019  C.I.M.R. ISSN – 0976-062842

Fig 1.6 From a formal survey procured from 35 HR employees from the age group of 22-45 years, we conclude that 52% of respondents AGREE, 34% of respondents DISAGREE and 14% of respondents STRONGLY AGREE that Payroll and compensation process is quicker due to AI implementation.

ASSUMPTIONS

1. It was believed that respondents would respond openly and honestly to the survey.

2. It was anticipated that the survey instrument was a valid measure of HR research and analytics practices in terms of content validity.

3. It was presumed that the survey instrument would be easily understood by all the participants (e.g., those who perform HR research and analytics as well as HR generalists, HR business partners, and other HR leaders).

LIMITATIONS

The study was limited to surveying HR practitio- ners within various organizations. Additionally, the sample of participants for the study was selected from an external database of over 400 HR practi- tioners; hence, the sample is considered to be a convenience sample since it may accurately repre- sent all HR practitioners currently employed in the organizations.

Another potential limitation is the number of re- spondents who chose to participate in the study. As

such, the results may not be generalizable to the entire sample population. Further, potential bias may be present in that participants might have responded to survey items in a socially desirable manner, particularly with regard to questions related to eth- ics. However, given the current interest on the topic, the social desirability effect is not expected to be a significant limitation. Participants were assured confidentiality and anonymity in the pooled results to mitigate such bias. Lastly, a web-based survey instrument was used as the data collection method.

DELIMITATIONS

The study was limited to the research questions posed and bounded by the conceptual framework, streams of research described earlier, variables of interest, and the comprehensiveness of the survey instrument used in the study.

NEW KNOWLEDGE FROM THE FINDINGS OF THE STUDY

1. Align HR with Value Creation for Organizations

that Win. Articulate a new HR charter and con- tribution model that describes the essential con- tributions companies will need from our field to successfully compete in the future.

2. Improve the Expectations of HR’s Key Constitu- ents. Define what is needed to move beyond today’s constituent expectations of HR, then im- prove those expectations with evidence that this role leads to improved value creation.

3. Rewire the Work and Tools of HR. Define the processes, practices, systems, and operating mod- els that drive HR’s deliverables and outcomes.

4. Ensure the HR Talent Pipeline. Crystalize a new set of professional requirements based on cur- rent research that explores the needs and gaps in the HR profession.

ARTIFICIAL INTELLIGENCE: THE GOOD, THE BAD AND THE PRACTICAL

43 Volume XI Issue 1  March 2019  C.I.M.R. ISSN – 0976-0628

Suggested Model

The model aims at identifying gaps between cur- rently existing Artificial Intelligence tools and prac- tices and expected requirements in the current sce- nario.

Step 1: Transitioning from traditional approach in the administrative space and at middle skilled HR level to an automation approach is the basic need of the hour. HRIS systems implementation by firms

at all sizes is the first step towards building a digi- tal Indian ecosystem. All the traditional HR Func- tions such as managing leave and attendance, re- cruitment, sourcing candidates has to be completely automated through HRIS software.

Step 2: The biggest threat to the millennial is tech- nology taking over. The result of this would be loss of jobs therefore cognitive flexibility should be deep

ARTIFICIAL INTELLIGENCE: THE GOOD, THE BAD AND THE PRACTICAL

Volume XI Issue 1  March 2019  C.I.M.R. ISSN – 0976-062844

seated in the academic stages not just restricted towards courses pertaining to analytical studies. Aspiring HR students should undertake live projects where they can analyse how to improve employee motivation of someone who wants to quit or the parameters impacting employee high or low pro- ductivity, studying emotional quotient etc. They need to be initially trained to gather relevant data and infer logical problem questions.

Step 3: Many companies use AI to automate pro- cesses, but those that deploy it mainly to displace employees will see only short-term productivity gains. Firms achieve most significant performance improvements when humans and machines work together. AI can give certain characteristics for HR functions such as job evaluation and performance appraisal but the final decision of whether to ap- praise someone basis of performance plus charac- ter should be left to humans. What comes naturally to people (for example sarcasm) can be wily for machines, and what’s up - front for machines (like analysing gigabytes of data) would be ideally im- possible for humans. Thus there needs to be aug- mentation of all the systems through collaboration of the strengths of Human and AI such as team work, creativity, speed and agility and not one re- placing the other.

Step 4: The major short comings of AI is the costs associated with it along with the complex infra- structure. A ‘One Intelligent’ software should be available to accomplish end to end HR functions thus saving the time and recurring cost supplemen- tary to those.

Step 5: In order to reduce the fear it is the need of the day to make the employees strategically inde- pendent which can be done by implementing ana- lytical tools and functions at all levels. The main

aim is to improve employee personal productivity So that they can solve a business problem using AI technology.

REFERENCES

1. Bersin, J. (2018). AI in HR: a real killer app.

Retrieved from https://joshbersin.com/2018/06/ ai-in-hr-a-real-killer-app/

2. Boudreau, J. W. (2015). HR at the tipping point: The paradoxical future of our profession. People and Strategy, 38(4), 46-54. Retrieved from https:/ / s e a r c h . p r o q u e s t . c o m / d o c v i e w / 1758647789?accountid=185290

3. Brougham, D., & Haar, J. (2018). Smart tech- nology, artificial intelligence, robotics, and al- gorithms (STARA): Employees’ perceptions of our future workplace. Journal of Management and Organization, 24(2), 239-257. doi:http:// dx.doi.org/

4. Burton, E., Goldsmith, J., Koenig, S., Kuipers, B., Mattei, N., & Walsh, T. (2017). Ethical con- siderations in artificial intelligence courses. AI Magazine, 38(2), 22-34. Retrieved from https:// search.proquest.com/docview/1916149652? accountid=185290

5. Caudron, S. (2003). HR is dead long live HR. Workforce, 82(1), 26-30. Retrieved from ht tps : / / search .proques t .com/docview/ 219765701?accountid=185290

6. Greenlaw, P. S., & Valonis, W. R. (1994). Appli- cations of expert systems in human resource management. HR.Human Resource Plan- ning, 17(1), 27. Retrieved from https://search. proquest.com/docview/224593171? accountid =185290

ARTIFICIAL INTELLIGENCE: THE GOOD, THE BAD AND THE PRACTICAL

45 Volume XI Issue 1  March 2019  C.I.M.R. ISSN – 0976-0628

7. Haijian, L., & Fangfang, Z. (2018). Employee transition and future outlook: Evolution from em- ployee 1.0 to employee 4.0. China Econo- mist, 13(3), 78-87. doi:http://dx.doi.org/10. 19602/j.chinaeconomist.2018.05.07

8. McGrath, D., & Damodaran, D. (2017, 12). Editor’s note. Workforce Management (Time and Attendance) Excellence Essentials, Retrieved from https://search.proquest.com/docview/ 2043365455?accountid=185290

9. Robbins, B. R., Jr. (2000). Application of intel- ligent systems techniques to problems in career planning under a marketing paradigm (Order No. 1400422). Available from ABI/INFORM Collec- tion. (230852261). Retrieved from https:// search.proquest.com/docview/230852261? accountid=185290

10. Spahic, J. (2015). Exploring HR intelligence practices in fortune 1000 and select global firms (Order No. 10010853). Available from ABI/ INFORM Collection. (1765193112). Retrieved from https://search.proquest.com/docview/ 1765193112?accountid=185290

11. Srivastava, S. K. (2018). ARTIFICIAL INTEL- LIGENCE: WAY FORWARD FOR INDIA.Journal of Information Systems and Tech- nology Management : JISTEM, 15, 1-23. do i :h t tp : / /dx .do i .o rg /10 .4301 /S1807- 1775201815004

12. Zielinski, D. (2017). Artificial intelligence can free HR professionals to focus on strategy. HRNews, Retrieved from https:// search.proquest.com/docview/2023413688? accountid=185290

Reproduced with permission of copyright owner. Further reproduction

prohibited without permission.