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Artificial Intelligence vs Emotional Intelligence




The term "Artificial Intelligence" is frequently used to describe machines that mimic "cognitive" functions related to the human mind, like "learning" and "problem-solving. The system's ability to properly interpret external data, to find out from such data, and to use those learnings to realize specific goals and tasks through flexible adaptation. With multiple AI functions built into an equivalent package AI systems achieve better, and faster performance thanks to the synergies between the systems. This permits AI to accomplish reasoning, allowing machines to execute sophisticated, non-intuitive actions that bring them a step closer to us.


AI was founded as a tutorial discipline in 1955. The sector was founded on the idea that "Human Intelligence" or "Emotional Intelligence" might be so precisely described, that a machine might be made to simulate it on the idea of the two activities which the human brain performs in daily life: prediction (what will happen or what it is) and decision (what should we do). This raised philosophical arguments about the character of the mind and therefore the ethics of making artificial beings endowed with human-like intelligence.

Technological evolution is always a neutral phenomenon. It’s us who make the phenomena positive or negative. In the 19th century, we tried to develop machines that could mimic the physical strengths of humans or animals whereas, in the 21st century, we are trying to develop the decision-making capability of humans. AI is adept at identifying patterns from big data, and this piece elucidates how it has become one of humanity’s ace cards in handling crises.


AI in healthcare is largely being used to assist doctors as it offers interactive visualizations of the connections among diseases, symptoms, and biological processes sourced from databases and algorithms. Disease Surveillance AI, Virtual Healthcare Assistants (Chatbots), Diagnostic AI, Facial Recognition and Fever Detector AI, Curative Research AI, and Information Verification AI are providing wide-ranging support to healthcare professionals. Microsoft is operating on a project to develop a machine called "Hanover". Its goal is to memorize all the papers necessary to cancer treatment and help predict which combinations of drugs will be most effective for each patient. AI is playing a big role in fighting against global pandemic COVID-19 by contributing to early warning alerts, tracking and prediction, diagnosis and prognosis, treatments, and social control.


Advertising and Marketing industry uses data to predict or generalize the behavior of customers from their digital footprints in order to target them with personalized promotions or build customer personas automatically. A documented case reports that online gambling companies were using AI to enhance customer targeting. Moreover, the application of personality computing AI models can help to reduce the cost of advertising campaigns by adding psychological targeting to more traditional sociodemographic or behavioral targeting.


Banks use artificial intelligence systems today to organize operations, maintain the database, invest in stocks, and manage properties. AI can react to changes overnight or when business is not happening. In August 2001, robots beat humans during a simulated financial trading competition. AI has also reduced fraud and financial crimes by monitoring the behavioral pattern of users for any abnormal changes or anomalies.


Advancements in AI have contributed to the expansion of the automotive industry through the creation and evolution of self-driving vehicles. As of 2016, there are over 30 companies utilizing AI into the creation of self-driving cars. A few companies entailed with AI include Tesla, Google, and Apple.

Artificial Intelligence has inspired numerous creative applications including its usage to create visual art. The exhibition "Thinking Machines: Art and Design in the Computer Age, 1959–1989" at MoMA, provides a good overview of the historical applications of AI for art, architecture, and design. Recent exhibitions showcasing the usage of AI to create art at the Gray Area Foundation in San Francisco, where artists experimented with the "Deep Dream" algorithm. The Ars Electronica's 2019 festival "Out of the Box" extensively thematized the role of arts for a sustainable societal transformation with AI.


Military AI enhances communications, sensors, integration, and interoperability. It helps in the detection and identification of threats, marking of enemy positions, target acquisition, and deconfliction of distributed Join Fires between networked combat vehicles and tanks. The worldwide annual military spends on robotics ranges in billions. Military drones with the potential to autonomous action, are considered a useful asset.


The widespread use of AI could have unintended consequences

that are dangerous or undesirable. Irakli Beridze, Head of the Centre for Artificial Intelligence and Robotics at UNICRI, United Nations, has expressed that "I think the dangerous applications for AI, from my point of view, would be, criminals or large terrorist organizations using it to disrupt large processes or simply do pure harm via digital warfare, or it could be a combination of robotics, drones, with AI and other things as well that could be really dangerous". Scientists from the Future of Life Institute, among others, have described short-term research goals to see how AI influences the economy, the laws, the ethics, and the way to attenuate AI security risks. The development of public sector policies for promoting and regulating AI is considered necessary to both encourage it and manage associated risks. In 2017, Elon Musk convoluted regulation of AI development. In February 2020, the European Union published its draft strategy paper for promoting and regulating AI.


So far in the job market, AI will replace those jobs easily which are more predictive in nature with data for example Illness Diagnosis, Financial Anomaly Detection, Intruder Detection from video sequences, etc. But for mimicking the decision-making capabilities of the human brain, there is still a need for much advancement in the existing AI algorithms. AI will remain more assistive in nature as in the current form. The first and most important requirement of AI is "data". Data is as important for AI as the mortar is important for bricks. In the near future, data collection is going to become more difficult, with users becoming more aware and possessive about sharing their data.


We humans do not learn just from cold hard facts. Instead, we process information at a much complex level with the ability to break patterns and change our opinions for the best results with decision making that is influenced by an infinite number of parameters. With the current set of algorithms, it’s a bit tough for AI to perform likewise. Self-awareness, self-regulation, intuition, social skill, and empathy remain reserved for humans and here Emotional Intelligence (EI) beats Artificial Intelligence (AI)!


Source: Multiple sources via Google

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