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Creativity in the Age of Artificial Intelligence (Essay Sample)


Creativity in the Age of AI


Creativity in the Age of AI
Academic Institution
Author Note
TIME \@ "MMMM d, yyyy" July 2, 2021Introduction
Whether or not people are prepared, AI creativity will make decisions for them. While this concept is positive, it is frightening and complex. Artificial intelligence (AI) has been widely used in organizations, resulting in increased concerns that technological systems would replace critical human decision-making practices. A major drawback and concern about AI is its relationship to our creativity. AI will facilitate human creativity if used properly (Boden, 2005). It can help people understand creativity and become inspired on command when we are stuck. This collaborative approach to AI can shape future minds. However, as humans, creativity makes us distinct from other species and is an important part of life. People should be creative to solve problems and have a fuller experience of life. That has not been the case, in a highly artificial intelligent environment, where creative decision making has been made obsolete, and a reliance on technology has increased. As a result, AI has limited creative decision making.
Decision Making in Uncertain Environments
In an uncertain environment, there lacks sufficient information about the consequences of an action or the available alternative decisions (Choo, 1991). This makes interpreting situations and making decisions more difficult. The uncertainty stems from the lack of information about both the external and internal business environment, including new government policies, new competitors, and the emergence of disruptive technologies. Creative decision making is not useful in uncertain environments because AI and several intelligent technologies can be used to generate ideas through data-driven and probabilistic statistical approaches (Jarrahi, 2018). AI ability to identify relationships between several factors and act upon different data sets at once has made human creativity unnecessary. For example, predictive analytics tools are now used to generate new information and offer predictions about business operations, customers, and assets, compared to the traditional need for creative decision making.
According to Jarrahi (2018), consulting firms including McKinsey and Deloitte have integrated intelligent tools which can monitor organizations external environments, thereby boosting the automated strategy articulation. Such systems have reduced the need for humans in strategy formulation and decision making. Besides, these systems detect irregularities and provide real-time data about the functionalities of businesses and processes. As a result, AI offers timely corrective actions which is far much more efficient than the traditional human decisions. Moreover, Moore (2016) proposes that thorough maintenance of the F-16 fighter jet fleet was effective because of the use of AI algorithms, which identified the failure patterns that affected the aircraft, and developed models to resolve those problems. Therefore, AI improves performance and fast-tracks effective decision-making processes.
When uncertainty is overwhelming as experienced majorly in creative decision making, or when organizations encounter scenarios with no precedence, AI offers an instinctive style of decision making (French, 2013). AI will continue to symbolize organizational decisions, in situations where the ratio of examples of previous related decisions on issues that are important to those decisions is low. AI continues to offer solutions to problems like technical glitches, which disrupt strategies and decision that had previously been made by humans. As a result, the cognitive technologies analyze probability-based decision frameworks in ways that have made creative decision making inessential.
Decision Making in Complex Environments
In complex environments, the variables or elements of decision making are in abundance. Besides, the constant change in data analysis and information processing is above the reach of traditional human comprehension. Data analysis has become more complex because it no longer involves analysis of transactions only, but the interactions of different variables at the same time. As analysts check data and develop innovative business solutions, they are required to extract tens of thousands of variables compared to the few variables they used in the past. Creative decision making, therefore, has become a complex process that requires more than the limited human processing abilities.
One of creativity’s worst enemies is human limitations. The creative capability is reduced when the amount of memory in human working memory, known as a cognitive load, is overwhelmed. Gigerenzer and Gaissmaier (2011) suggest that humans with high cognitive load are less creative compared to those with low cognitive loads. When several tasks overload human minds, their functionality and ability to think critically and creatively are reduced. Stankov (2010) suggest that creativity requires a breeding ground, and cannot be forced. AI has surpassed this limitation and can handle deterministic and repetitive activities, and at the same time create models to handle future scenarios. AI has liberated humans from engaging in creative pursuits.
Decision making in complex environments requires processing of information swiftly beyond the cognitive abilities of human decision makers. However, AI with outstanding analytical qualifications and computation competencies have outdone humans and can analyze these variables and develop situation-based decisions. Algorithm-based decision making presents effective ways of problem-solving compared to the contemporary human decision-making process, which is considered to be time-consuming and ineffective (Marwala, 2015). Creative decision making is not used nowadays because AI is a rigorous instrument for analyzing and retrieving large data sets, and restructuring the complexity of decision making. For example, creativity in decision making is not required because AI can decrease the difficulties of problems by pinpointing fundamental relations and affirming the best course of actions among the several available possibilities.

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