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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