Man-MachineCollaboration-Transform Even the Highest Levels of Work It is said that Man-MachineCollaboration will take the work to the next development state becausecognitive technologies are capable of processing so much more data so much morequickly than humans, the ways researchers and analysts conduct their work is goingto transform. Already, administrative and office tasks are being automated at arapid pace, and cognitive technologies are ready to automate more complexassignments. Take the work of mortgage organisation, If the processtraditionally involves three separate groups of employees that have to workwith 15 systems in consecutive order, making for an obtuse and training-heavyoperation. Using robotic process automation to enter and review captured data,Forrester details how managers only needed two groups working with just sevensystems, which both streamlined the entire process and expedited the trainingrequired for new team members.
Intelligent machines could even start changingthe way we dress. There is website called ‘Wired’ which reports that a softwareprogram developed at the University of Toronto is capable of recognizingfashion flaws and suggesting corrective clothing adjustments. With the customerservice aspect of the fashion industry being handed off to robots, humanworkers can turn their attention to creating new lines and changing tastes,tasks that their non-human counterparts simply aren’t capable of.
This is thenext phase of the industry. This is not only started in Market and bankingindustry but also started in customer service, finance, research, and manyother field. Ultimately, this collaboration between man and machine frees uphumans for higher-value work such as delivering content unique and personalizedto each and every individual customer and consumer.
Not only will this maximizeproductivity, but it will also lead to happier employees, which in turn leadsto happier customers and better businesses. CognitiveCollaboration of Human and ComputersThe creation of Man-MachineCollaboration applications in medicine will likely alter the mix of skills thatcharacterize the most successful physicians and health care workers. Just asthe skills that enabled Garry Kasparov to become a chess master did notguarantee dominance at freestyle chess, it is likely that the best doctors of thefuture will combine the ability to use AI tools to make better diagnoses withthe ability to empathetically advise and comfort patients.
Machine learningalgorithms will enable physicians to devote fewer mental cycles to the”spadework” tasks computers are good at (memorizing the Physicians’ DeskReference, continually scanning new journal articles) and more to suchcharacteristically human tasks as handling ambiguity, strategizing treatmentand wellness regimens, and providing empathetic counsel. There is also evidencethat big data and AI can help with both verbal and nonverbal communicationsbetween patients and health care workers. Similar comments about job lossto AI can be made about fraud investigators, hiring managers, universityadmissions officers, public sector case workers, judges making paroledecisions, and physicians making medical diagnoses. In each domain, cases fallon a spectrum. When the cases are frequent, unambiguous, and similar acrosstime and context and if the downside costs of a false prediction are acceptablealgorithms can presumably automate the decision. On the other hand, when thecases are more complex, novel, exceptional, or ambiguous in other words, notfully represented by historical cases in the available data human-computercollaboration is a more plausible and desirable goal than complete automation.
Man and Machine arewinning team in the workplace The human-machine combination istotal intelligence, and can significantly raise both productivityand quality. Thousands of new positions have been and will continue to becreated elsewhere in the technological and creative spheres, professional andmanagement areas and caring professions. They are at low risk of automation asthey require high levels of manual skill and social or cognitive skills such asproblem-solving and decision-making. There are two opposing viewpointson the ongoing robotic revolution. Those who think that the glass ishalf-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 ofhuman and machine can do greater things and helps to attain excellence inworkplace.Human Plus MachineWhenwe 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’sbeing developed today, and the potential of these new powerful machines, yieldsan optimistic view of the future. We are on the cusp of a major transformationin our relationships with our tools, analogous to the transformation humanitywent through during the agricultural revolution. As agricultural productionbecame mechanized, many farming jobs disappeared and farming families moved tocities, where they became responsible for building bridges and skyscrapers,producing things in factories, and creating new kinds of services. This collaborationis Man Plus Machine and when both comes in collaboration it will make a betterenvironment to live.
Man-MachineInteraction – Critical Issues for Human Environment Machines exist sincethe period of Ancient times and man did not cease to improve them in terms ofutility, efficiency and safety. This process has accelerated in the lastcentury and particularly rapid for some decades. A consequence, at presenttime, is exhibited through the significant complexity and some autonomycapacity of machines. Thesenew features have consequences on humans: some distance, sometimes a true separation between the designer and theuser, and a confusion of user inthe presence of machine. The natural trend of engineer or researcher is to gotoward fully automatic machines with autonomous decision making.
That ispossible only accepting strong limitations in the tasks. In fact numerousmental and physical tasks needed or useful in daily life, very easily performedby man, are not performable with a fully automated machine. That is the reasonwhy an association of man with machine is often