Man-Machine enabled Garry Kasparov to become a chess master

Collaboration-Transform Even the Highest Levels of Work


It is said that Man-Machine
Collaboration will take the work to the next development state because
cognitive technologies are capable of processing so much more data so much more
quickly than humans, the ways researchers and analysts conduct their work is going
to transform. Already, administrative and office tasks are being automated at a
rapid pace, and cognitive technologies are ready to automate more complex
assignments. Take the work of mortgage organisation, If the process
traditionally involves three separate groups of employees that have to work
with 15 systems in consecutive order, making for an obtuse and training-heavy
operation. Using robotic process automation to enter and review captured data,
Forrester details how managers only needed two groups working with just seven
systems, which both streamlined the entire process and expedited the training
required for new team members. Intelligent machines could even start changing
the way we dress. There is website called ‘Wired’ which reports that a software
program developed at the University of Toronto is capable of recognizing
fashion flaws and suggesting corrective clothing adjustments. With the customer
service aspect of the fashion industry being handed off to robots, human
workers can turn their attention to creating new lines and changing tastes,
tasks that their non-human counterparts simply aren’t capable of. This is the
next phase of the industry. This is not only started in Market and banking
industry but also started in customer service, finance, research, and many
other field. Ultimately, this collaboration between man and machine frees up
humans for higher-value work such as delivering content unique and personalized
to each and every individual customer and consumer. Not only will this maximize
productivity, but it will also lead to happier employees, which in turn leads
to happier customers and better businesses.

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Collaboration of Human and Computers

The creation of Man-Machine
Collaboration applications in medicine will likely alter the mix of skills that
characterize the most successful physicians and health care workers. Just as
the skills that enabled Garry Kasparov to become a chess master did not
guarantee dominance at freestyle chess, it is likely that the best doctors of the
future will combine the ability to use AI tools to make better diagnoses with
the ability to empathetically advise and comfort patients. Machine learning
algorithms will enable physicians to devote fewer mental cycles to the
“spadework” tasks computers are good at (memorizing the Physicians’ Desk
Reference, continually scanning new journal articles) and more to such
characteristically human tasks as handling ambiguity, strategizing treatment
and wellness regimens, and providing empathetic counsel. There is also evidence
that big data and AI can help with both verbal and nonverbal communications
between patients and health care workers.

Similar comments about job loss
to AI can be made about fraud investigators, hiring managers, university
admissions officers, public sector case workers, judges making parole
decisions, and physicians making medical diagnoses. In each domain, cases fall
on a spectrum. When the cases are frequent, unambiguous, and similar across
time and context and if the downside costs of a false prediction are acceptable
algorithms can presumably automate the decision. On the other hand, when the
cases are more complex, novel, exceptional, or ambiguous in other words, not
fully represented by historical cases in the available data human-computer
collaboration is a more plausible and desirable goal than complete automation.

Man and Machine are
winning team in the workplace

The human-machine combination is
total intelligence, and can significantly raise both productivity
and quality. Thousands of new positions have been and will continue to be
created elsewhere in the technological and creative spheres, professional and
management areas and caring professions. They are at low risk of automation as
they require high levels of manual skill and social or cognitive skills such as
problem-solving and decision-making. There are two opposing viewpoints
on the ongoing robotic revolution. Those who think that the glass is
half-full, say humans will have more time for creativity. The pessimists,
however, warn that soon smart machines will make thousands of lawyers,
librarians, policy analysts and professors jobless. But the combination of
human and machine can do greater things and helps to attain excellence in

Human Plus Machine

we think about smart machines or robots entering many domains of our lives,
several visions come to mind: robots taking over the world, jobs disappearing,
and machines running amok and reproducing themselves. But a look at what’s
being developed today, and the potential of these new powerful machines, yields
an optimistic view of the future. We are on the cusp of a major transformation
in our relationships with our tools, analogous to the transformation humanity
went through during the agricultural revolution. As agricultural production
became mechanized, many farming jobs disappeared and farming families moved to
cities, where they became responsible for building bridges and skyscrapers,
producing things in factories, and creating new kinds of services. This collaboration
is Man Plus Machine and when both comes in collaboration it will make a better
environment to live.


Interaction – Critical Issues for Human Environment


Machines exist since
the period of Ancient times and man did not cease to improve them in terms of
utility, efficiency and safety. This process has accelerated in the last
century and particularly rapid for some decades. A consequence, at present
time, is exhibited through the significant complexity and some autonomy
capacity of machines. These
new features have consequences on humans: some distance, sometimes a true separation between the designer and the
user, and a confusion of user in
the presence of machine. The natural trend of engineer or researcher is to go
toward fully automatic machines with autonomous decision making. That is
possible only accepting strong limitations in the tasks. In fact numerous
mental and physical tasks needed or useful in daily life, very easily performed
by man, are not performable with a fully automated machine. That is the reason
why an association of man with machine is often