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HOW HUMANS PLAY A VITAL ROLE IN AN A.I.-POWERED WORKPLACE: MIT PROFESSOR


IN MANY AREAS, HUMAN CAPABILITIES WILL REMAIN IRREPLACEABLE IN THE WORKPLACE FOR
THE FORESEEABLE FUTURE.

By Yossi Sheffi • 08/31/23 11:38am
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 * 
 * 
 * 

A.I. will create new job opportunities like previous waves of innovation that
bring extreme changes to the workplace. Chip Somodevilla/Getty Images

As A.I.-driven changes in the workplace increase in number and scope, there is
growing concern over the technology’s impact on employment. However, these
concerns can be addressed if we prepare for future changes. While A.I. is
eliminating many jobs traditionally filled by humans, history shows that, in the
long term, it will create countless new employment opportunities. Moreover,
although algorithms outperform people in many areas, human capabilities will
remain irreplaceable in the workplace for the foreseeable future.

Waves of innovation that bring extreme changes to the workplace are by no means
new. Consider, for example, the introduction of containerization in the 1950s.
Transporting goods in standardized steel boxes revolutionized international
trade. It also eliminated many jobs associated with the manual loading and
unloading of cargo. However, containerization also spawned new industries, such
as the construction, maintenance, and handling of freight containers, and the
development of technology that optimizes how each unit is loaded and tracks the
global movement of containers.




Similarly, A.I. will create new types of enterprises and job opportunities that
we can only imagine today.

Also, humans will be an integral part of these future workplaces. Although
algorithms are far superior when it comes to performing repetitive tasks,
processing vast amounts of data, and identifying key trends and patterns, people
will continue to excel in a number of areas. Here are some examples:

1) REAL-WORLD EXPERIENCE

A lifetime of experience in the physical world allows people to detect changes
or discrepancies between normal and abnormal situations. For example, during the
financial crisis of 2008, companies worried about the financial health of their
suppliers. Many companies asked for economic data from suppliers, but these
numbers could be manipulated and only provided a lagging, infrequently updated
view of conditions at the supplier. To augment the data, companies sent people
to spot-check critical suppliers’ production of parts or materials on behalf of
the company.

2) A MORAL PERSPECTIVE 

Many work tasks involve value judgments and subjective elements based on the
system designer’s or manager’s preferences. However, objectives, moral
understandings, and preferences change over time. While machines may be able, if
appropriately trained, to sift through large amounts of data and present options
for actions, people must make the ultimate decisions in cases where the
implications matter. This is especially true when the context changes and
decisions must be made in a different environment. For example, when
prioritizing the response to a disaster, should preference be given to
customers, employees, suppliers, shareholders, or the community? The honest
answer is “it depends” on the nature of the event and the context, which makes
it difficult to program or train a model.




3) ADAPTABILITY AND COORDINATION

People are more adaptable than robots when faced with unstructured conditions
and environments. Robotic software systems are built and optimized for specific
tasks or domains. However, change (disruptions, new knowledge, new products,
competitors’ actions, economic cycles, etc.) can render the machine’s
appropriateness moot, requiring a person to take over the task. Also, social
networks are adept at creating new corporate organizational structures to manage
change. This has happened in response to numerous disruptions over recent years,
such as the 2011 earthquake in Japan and the Covid-19 pandemic.

4) AN IN-BUILT CREATIVE DRIVE 

Change that requires adaptation is built into many consumer and technology
supply chains, such as fast fashion. These fast-moving supply chains search
ceaselessly for differentiation that can spur demand for any new product or
service. People, not machines, are part of a cultural milieu that stimulates
creativity. Also, humans understand the vagaries of everyday life, and this
hands-on experience creates possibilities for new products and services.

5) EMPATHY AND COMMUNICATION 

While a growing number of A.I. applications are used in health care, computers
cannot show the empathy required of a nurse while treating a patient. Likewise,
a machine cannot replace the smile of a service worker, such as a cashier in a
local supermarket. Similarly, procurement contract negotiations cannot occur
without both sides understanding each other, developing rapport, and
appreciating each other’s points of view.

Even though algorithms that mimic these qualities are becoming increasingly
sophisticated, it isn’t easy to imagine absolute acceptance of
machine-generated, simulated emotions and empathy.




6) NUANCED RISK MANAGEMENT

While rules can be programmed based on different contexts, the most appropriate
choice in a situation that requires a company to select a way forward may differ
from the one suggested by the rules. For example, if the company suspects a
recession is on the horizon, it may prefer the safer course of action rather
than the high-risk/high-reward path. Humans are used to taking such nuances into
account when making decisions.


BALANCING HUMAN AND MACHINE INTELLIGENCE

The vital challenge for societies as A.I. advances is how to create workplaces
that enable humans and machines to work alongside each other—not in competition.

This can be achieved in various ways. For example, data analyzed by A.I.-based
models can be sent to human decision-makers for action. Chipmaker Intel uses
this approach in its procurement operations. Its A.I. system provides a mass of
data, such as supplier performance reports, that help procurement managers make
sourcing decisions.

Another method is to deploy A.I.-infused automation technology to carry out most
of the work. Humans intervene when a machine fails or cannot recognize that the
context has changed (e.g., a system has been hacked or a pandemic has erupted,
requiring the mode of operation to change). The flexibility of human employees
is needed to pivot quickly when such changes occur.




Anxieties over the rise of A.I. are legitimate, and the technology will
transform the world of work. However, it is vitally important that we take a
balanced view of A.I.’s potential and its impact on employment.

Dr. Yossi Sheffi is the Elisha Gray II Professor of Engineering Systems at the
Massachusetts Institute of Technology and Director of the MIT Center for
Transportation and Logistics (MIT CTL). His recent book is “The Magic Conveyor
Belt: Supply Chains, A.I., and the Future of Work.”




Filed Under: Business, Technology, Artificial Intelligence, Intel
 * SEE ALSO: Biographer Walter Isaacson Dissects Why Elon Musk Is So Difficult

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