Regional News

How collaborative intelligence works and what company benefits it generates

By Silvia Castro Betancourt 0 Comments NEWS, Regional News

This article was written and published in Spanish and has been translated into English via Google Translate. Click here to read the original article.

The improvements that artificial intelligence is introducing both in companies and at a social level are unquestionable. In addition to speeding up certain mechanical processes, it is allowing communication even when the language is unknown, as well as diagnosing diseases or improving the services that companies provide. In this sense, although artificial intelligence will radically alter the way in which work is done and who does it, the greatest challenge will be to complement and increase human capabilities and not replace them.

Harvard Business Review has carried out a study that involved 1,500 companies, to find out how artificial intelligence is being implemented and the effects it has at the human level. As the media reveals in a report, "companies achieve more significant performance improvements when people and machines work together," which underscores that collaboration between technology and the workforce is key.

In this way, collaborative intelligence is a model that works on the idea of ​​the exchange of knowledge and the reinforcement of the strengths that distinguish people - leadership, teamwork, creativity and social skills - and machines: speed, scalability and quantitative capabilities.

Also, according to the report, people play three crucial roles in companies: "They must program the machines to perform certain tasks; explain the results of those tasks, especially when they are contradictory or controversial; and carry out its maintenance and responsible use."

Thus, regarding the first question, HBR emphasizes that "machine learning algorithms must learn to perform the work for which they were designed" and train themselves to "interact better with humans". After that, as artificial intelligence generates conclusions through opaque processes, experts who know how to explain their behavior to inexperienced users begin to be required. "These professionals are particularly important in evidence-based industries, such as law and medicine," says the report.

Another example of this is seen in the new General Regulation of Data Protection (GDPR) of the European Union, which gives consumers the right to receive an explanation on any decision based on algorithms, such as the rate offer on a card of credit or mortgage.

In addition, in addition to having people who can explain the results, companies need employees to work to ensure that AI systems work properly, safely and responsibly, as is the case with cybersecurity experts or industrial robot developers.

But not only people have their role in this new way of working, also machines. In this way, the first of its three main functions is to "amplify our cognitive strengths, analytical and decision-making capabilities by providing the right information at the right time".

In second place is the interaction with clients and employees to free them from tasks. For example, tools such as Cortana can facilitate communication between people or on their behalf, such as transcribing a meeting.

Finally, machines can include human skills to expand people's capabilities. This is the case of those tools and programs that include facial and voice recognition, and which, in the field of human resources, are already being used to recruit talent with the aim of hiring the most appropriate professionals and avoiding biases.

"To obtain the maximum value of AI, operations must be redesigned. To do this, companies must discover and describe an operational area that can be improved, "and then "develop a solution through joint creation."

"The third step for companies is to scale and maintain the proposed solution," they say. From HBR, which has also identified the five characteristics of business processes that companies usually want to improve: flexibility, speed, scale, decision making and customization, while exposing how these challenges faced companies such as Mercedes-Benz, which have replaced some robots with AI-enabled ones and redesigned his processes around human-machine collaborations; HSBC, which developed a solution that improves speed and accuracy in detecting fraud; Unilever, which applied an AI system in its recruitment processes; General Electric, which introduced virtual models of physical equipment; Starbucks, which uses AI to recognize its customers' mobile devices and retrieve its order history; or The Carnival Corporation, which is applying it to personalize their cruise experiences.

This article was written and published in Spanish and has been translated into English via Google Translate. Click here to read the original article.

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