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TRANSCRIPT
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Artificial Intelligence As An Antidote For Managing People In Organizations: An Unrealistic
Perspective?
by
Chaudhuri, Kaushik ; Varma, Arup; Malik, Ashish
Abstract
The advent of Artificial Intelligence (AI) has created numerous opportunities for
organizations to increase their profits by employing AI in various aspects of their work processes,
but especially as it relates to their human resources. As a result of this hype around AI, the
nature of jobs available and existing employment relationship will transform. Employers
implementing AI in managing people in workplaces have to be more accountable for improving
worker-experience, increase investment on their skill development, building organizational
competency, and enhance transparency in responsible usage of AI. But is at all possible to
sustain this hype of AI especially in the context of managing people in organizations? We argue
that the misuse of AI algorithms could have an adverse impact on people management if not
devised and implemented with caution. Noble intentions of the corporate leaders with purposeful
management philosophy and genuine willingness on how they want to utilize AI on employee
wellbeing will moderate positive impacts on their employees in organizations. This may be
possible only when organizations will reorient their corporate philosophies and honor their
obligations to fulfill their social contract of business, through the common good of trust,
transparency by implementing responsible HR practices and management policies.
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Artificial Intelligence (AI) refers to computer systems and algorithms that can dispose
conclusions without direct human intervention. They may be capable of equaling—and often
exceeding—human cognitive capacities with regard to specific tasks. AI and emerging
technologies such as virtual personal assistants and chatbots are rapidly making headway into
our workplaces AI is system that is super-intelligent and being smarter than the best human
brains in practically every field" could have an enormous impact upon humanity (Haenlein, &
Kaplan , 2019). It is estimated that these technologies will replace almost 69 % of the manager's
workload and that their role will change drastically. Organizations will spend less time managing
business transactions and will possibly invest more time on learning, performance management
and goal setting. AI and emerging technologies will undeniably change the role of the manager
and will possibly allow employees to extend their degree of responsibility and influence, without
taking on much management tasks and blame on themselves. Experts on innovation and AI are
now accountable for improving worker experience, developing new worker skills and building
organizational competency in use of AI and digital technologies. A gradual transition to
increased automation of management tasks is evident as this functionality becomes increasingly
available across more enterprise applications (First Post, 2020).
A recent study on AI at Work conducted by Oracle and Future Workplace (AI @work,
2019) suggests that employees have more trust in robots than their managers. A study of 8,370
employees, managers and HR leaders across 10 countries, found that AI has changed the
relationship between people and technology at work and is reshaping the role HR teams and
managers need to play in attracting, retaining and developing talent. Moreover AI is becoming
more prominent with 50 % of employees currently using some form of AI at work compared to
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only 32 % last year. 77% of employees in China and 78 % Indians have adopted AI over more
than twice than those in France (32%) and Japan (29%). Almost 65 % of the workers feel they
are optimistic, excited and grateful about having robot co-workers and nearly a quarter reports
having a loving and gratifying relationship with AI at work. Interesting an estimated 64 % of
workers would trust a robot more than their manager and half have turned to a robot instead of
their manager for advice. Alarming when 82% of the respondents think robots can do things
better than their managers. Respondents said robots are better at providing unbiased information
(26 %), maintaining work schedules (34%), problem solving (29 %) and managing a budget
(26 %) than their reporting managers. Truly AI is already revolutionizing industry.
Companies namely NVidia Corp., Alphabet, Salesforce, Amazon.com, Microsoft Corp.,
Baidu, Intel Corp. Twilit, Facebook, and Tencent are some of the top ten most prominent
money-making stocks at USA. Millions of consumers interact with AI directly or indirectly
on a day-to-day basis via virtual assistants, facial-recognition technology, mapping
applications and a host of other software. The potential of earning profit is too huge to
actually estimate their volume (US News, 2020). According to Accenture (2017), AI has the
potential to add US$957 billion, or 15 % of current gross value added, to India’s economy in
2035. Developing economies such as India is not fully prepared to seize the enormous
opportunities AI presents. AI spend in India has increased at 109.6% during 2018 to reach
US$ 665 million (Global Newswire, 2020).
Unequivocally AI is having a dramatic impact on the workplaces. Extensive growth in
the use of AI and robotics to automate simple and repetitive tasks such as factory work and many
back-office duties; and to make complex decisions, such as medical diagnostics, quickly and
more accurately via predictive algorithms. There are also enormous financial incentives for
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employers to increasingly automate their currently human processes and that advances in
automation could dramatically change the nature of jobs available (PWC, 2017). Automation is
increasingly being used in areas that require the storing or access of information (Frey &
Osbourne, 2017), such as in fraud detection, medical diagnosis (Wolcott, 2018). In addition, the
automation of manual tasks is increasingly widespread, including tasks such as driving cargo
handling and mining (Frey & Osbourne, 2017).
The speed with which the business rhetoric in management moved from big data to
machine learning and AI is astonishing. However some reports also claim that companies are
actually struggling to make progress building data analytics capabilities. A recent IBM study
(2018) suggest 41% of CEOs are not at all prepared to make use of new data analytic tools, and
only 4% of them say that they are “to a large extent” prepared well to avail this opportunity.
Research also suggests the types of knowledge, skills, and abilities required by organisations will
change as the need for routine cognitive and manual skills will decreasing. Organisations will
need a workforce with increased skill variety, autonomy, and interdependence, as well as
increased cognitive, creative, technical and social skills (Wegman et al., 2018), to complement
machines (MacCrory et al., 2014). They will engage to perform the remaining tasks that are not
automated (Makridakis, 2017). The challenge remains as how to manage people in organization
in this context, with a refined balanced nexus of humans and machines (Frey & Osborne, 2017).
Increasing trend towards workers undertaking jobs using AI platforms via the gig
economy based on self-employment contracts, subcontracts, and various forms of ‘gig-work’ is
staggering (Deloitte, 2018). Approximately 2.8 million workers in the UK alone are involved in
the gig economy to some extent and that this is contributing to a decrease in demand for
permanent employees, allowing organizations to reduce overhead costs and increase their
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numerical flexibility (Berg, 2016). Lack of institutional connectedness (Fitzgerald et al., 2012)
due to this in turn is said to be leading to precarious work conditions (Moisander et al., 2018) and
inefficacy of individuals to be able to influence their working environment (CIPD, 2017). In
addition, the gig economy has been linked to growing economic insecurity, low productivity,
diminished autonomy and increased levels of personal debt (Fleming, 2017). Globally working
suggest workplaces are become close to 24/7 (Deloitte, 2018). Employees are increasingly
susceptible to overwork and compromising their wellbeing (Schlacter et al., 2018). Digital
technologies propound potentials, but they can be used for different purposes, may be adding
inadvertent or intentional malice. This depends on the intentions of the employing organizations,
“organizational voluntarism” (Strohmeier, 2009). AI will lead to job losses (Frey & Osborne
(2017) but on the contrary there are also reports that expect job gains due to technological
developments by Federal Ministry of Labour and Social Affairs (2015 ) and current estimates of
Oracle in AI @work (2019) .
How can the employees sustain themselves in digital engagement in today’s organization
(Jesuthasan, 2017). In this paper we attempt to critique AI and its policy implementation in
managing people in organizations and posit a question if it is at all possible to sustain this hype
of AI especially in the context of managing people in organization? Is it a bigger ploy to justify a
rigged corporate decision in the veil of machines outputs through AI? Is there any hidden agenda
of the corporates to manipulate people using AI. We have critiqued implementations AI
algorithms and argued that it could impact adversely to people management, if not adequately
devised, monitored and implemented in organizations with extreme cautions. In the following
sections we have delved into some unpleasant truth- inadvertent anomalies on the organizational
intention to create and implement algorithms in AI with respect to management decisions. Our
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arguments could appear to be provocative and cynical however should be seen as opinion and
addendum to solicit further contemplations of scholars and practitioners.
Managers need to be aware that many employees will be scared of being replaced by AI,
independent of whether this fear is justified or not. This requires strong skills in leading an open
dialogue, resolving conflict, and ethical, open, and transparent leadership style. Managers may
need to identify the skills of their human employees and find a place for them in an ecosystem in
which humans and machines will work hand in hand (Pfeffer ,2018). This will include a stronger
focus on emotional or feeling tasks for humans, for which they have an inherent advantage over
machines (Huang et al., 2019). Involving employees in the process of developing and
implementing AI systems makes such systems more successful Cappelli and Tavis ( 2017),
Tambe, Cappelli, and Yacubovich, (2019). In short, managers will need to act as empathetic
mentors and data driven decision makers (Kaplan & Haenlein, 2019). When used together
correctly, human intellect and machine efficiency have the power to bring positive change to
your business over time. In introducing AI to organizational decision making, managers must
build internal capabilities to decide on the inputs to the algorithm, the algorithms themselves, and
the interpretation of predictions. Because AI technologies advance rapidly, organizations must
remain vigilant to the strengths and limitations of AI in fully delegated and hybrid human–AI
decision-making structures (Shreshtha et al, 2019).
We have proposed our arguments based on some evidence on how algorithm and coding
can be purposefully manipulated (Kosinski, et al., 2013) and wrongfully exploited for unknown,
either good or evil intentions. See for examples in Table 1, IA and IB, illustrations of a coding in
Python shows how purposeful bias in the process of hiring students from University could be
manipulated. Table 2, 2A and 2B show how promotion system can also be manipulated by a bug.
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Similarly gaming the system is also possible and should not be entertained, under estimated and
ignored by blaming the AI s or machines algorithm. The root cause of the problems may dwell
with the management philosophy with goodwill and intentions to use AI enabled machine
outputs for employee wellbeing, relationship and organizational growth. The policy framework
integrating AI in management may need to be revisited periodically and expect to be able to
balance both ethical and legal compliances of society, please refer to Table 3. Aim should be on
building noble partnership, cooperation between machines (AI) and people which will resonate
societal well-being and social identity of all employees. Please refer to Figure (1) with our
conceptual framework. AI definitely has the potential to reshape skill-demands, career
opportunities, and the distribution of job among industries and occupations in the developed and
developing countries. However, we are still underequipped to forecast the labor trends resulting
from specific cognitive technologies, such as in AI. This is possible only when organizations will
reorient and redirect their management philosophies and frame objectives not blatantly pursuing
after interests of profit maximizations and share-holders’ prosperity but actually by going back to
the basics of HR. The basics of people management are to treat employees as their important
source of capital and competitive advantage and not merely as costs and economic resources. It
is about being respectful to their obligations of fulfilling social contract through the common
good of trust, transparency and by implementing responsible HR practices. It is up to the
intentions of the corporate leaders and their willingness on how they want to utilize AI to
moderate positive impacts on their employees in organizations and thereby to the society.
**Acknowledgement: Our sincere thanks to Mr. Raman Dutt, a Computer Science Major student
of Shiv Nadar University for his valuable inputs in the illustrations of coding in Python for this
paper.
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Figure (1) Conceptual framework of AI in HRM
BUSINESS /SOCIAL CONTEXT
ETHICAL FRAMEWORK
(NON COMPLIANCE)
(NON COMPLIANCE)
LEGAL FRAMEWORK
WEAK MANAGEMENT
PHILOSOPHY (noble
intentions, obligation)
IRRESPONSIBLE HR PRACTICES
SUSTAINABILITY CRISIS,
SHAME, STIGMA, ISOLATION,
MARGINALIZATION,
FEAR,
PHYSICAL AND MENTAL
STRESS,
PERSECUTION,
WORK LIFE IMBALANCE
PSYCHOLOGICAL TRAUMA,
PASSIVE ECONOMICAL AND
DEVELOPMENT GROWTH
ABUSED Artificial
Intelligent SYSTEM
TERMINATION
OF PSYCHOLICAL
CONTRACT
CREDIBILITY CRISIS/
TERMINATION OF
ORGANIZATION’S OF
SOCIAL CONTRACT
OF BUSINESS
Demeaning
working
conditions
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Table 1 : Specimen Subset of Dataset for Hiring ( hypothetical)
Table 1 (A): The coding when the bias has been introduced by using on the feature ‘University
Type’ for our decision.
Table 1(B): The coding when the bias has been introduced by using the feature “10th marks” for
our decision
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Table 2 Specimen Data sub set for promotion (hypothetical)
Table 2 (A) Original Algorithm for Promotion without bug
Table 2(B) Algorithm after bug being introduced
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Table 3: Ethical Principles of different stake holders
Source: Field et al., (2020) in The Berkman Klein Center for Internet & Society Research .
Asilomar AI Principles
Shared Benefit: AI technologies should benefit and
empower as many people as possible
Microsoft’s AI principles
Inclusiveness – AI systems should empower everyone
and engage people. If we are to ensure that AI
technologies benefit and empower everyone, they must
incorporate and address a broad range of human needs
and experiences. Inclusive design practices will help
system developers understand and address potential
barriers in a product or environment that could
unintentionally exclude people. This means that AI
systems should be designed to understand the context,
needs and expectations of the people who use them
Partnership on AI Tenets
Seek to ensure that AI technologies benefit and
empower as many people as possible
Smart Dubai AI principles
share the benefits of AI throughout society: AI should
improve society, and society should be consulted in a
representative fashion to inform the development of
AI
T20 report on the future of work and education
Benefits should be shared: AI should benefit as many
people as possible. Access to AI technologies should be
open to all countries. The wealth created by AI should
benefit workers and society as a whole as well as the
innovators
UNI Global Union’s AI principles
Share the Benefits of AI Systems: AI technologies
should benefit and empower as many people as possible.
The economic prosperity created by AI should be
distributed broadly and equally, to benefit all of
humanity