Philosophy
Descartes on Humans and Machines
Descartes focused on the discourse of the ‘very certain’ tests that define the differences between humans and machines in respect to the theory of mind. The concern is on the veracity and authenticity of the two tests in creating context of machine learning and the abilities that the innovative interventions can influence. For instance, can the machines completely replace humans in the routines such as workplace, games, reasoning, and forecasting? Descartes had the two clear tests that defined the essence of machines and the overarching differences to influence the understanding of the core outcomes (Franco, 2018). In this regards, the context of argument on the importance or relevance of Descartes’ arguments is pinned on concepts of machine learning, communication, and the understanding of machines in relation to animals and humans. The theory of mind focuses on the ability to achieve comparative assessment of the philosophical discussions on the subject and how Descartes’ arguments and tests can be right or wrong in the wake of increased assessment and understanding of the outcomes (Marchetti et al., 2018). Consequently, despite the innovative and technological breakthroughs in various fields, the human factors and their influence on the machines are still crucial. There cannot be a complete automation that delinks human factors from the machines, hence the suitability and relevance of Descartes arguments and tests on the differences between the two concepts.
Descartes’s first test on the differences between machines and humans relate to the dependability of the machines to produce certain outcomes. Humans are known for the communication prowess, which socializes and relates to others to advance the general outcomes and shared values (Marchetti et al., 2018). The production of words and signs for the machines are based on the preprogrammed or automated concepts, which cannot move beyond the defined areas of influence. These concepts underscore and confirm the arguments tests that Descartes fronted to distinguish humans and machines. A typical sector that has witnessed increased automation and machine learning is the aviation, in which more human factors tend to be reduced. The flights depend more on software interventions compared to the flight crews. However, even with these innovations and interventions, the roles of human factors such as pilots still remain crucial and relevance in advancing safety and communication needs of the flights (Brödner, 2019). Operating within the concept of comparative cognition and the causal or associative learning define the need for human factors and creating an environment where the machines complement or ease the roles of humans and not to completely eradicate their significance.
Descartes’ argument as framed in the first test defines the things that machines cannot do, which are only limited to humans and their models of operation. The theory of mind underscores the superiority of the human mentality, cognition, and associate learning that discredit the authenticity of the presence of minding machines (Franco, 2018). Despite the breakthroughs in learning and other historical elements and concepts, the outcomes still remain discontinued on whether the minding machines can be created to completely eradicate the influences, roles, and impacts of humans across various sectors. As evident in the aviation industry, other sectors such as health, education, and sales and marketing have invented lots of interventions that continue to ease the operations of humans. These include automated learning, communication through the bots and the block-chain logistics management to advance the supply chain interventions. These frameworks are crucial in shaping the long-term outcomes and framing the anticipated outcomes, including the ideological and technological elements. However, part of the discussion is on the presence of the minding machines and their significance (Grzeliński & Łagosz, 2019). The argument is that despite their evidence of effectiveness, the machines cannot work in isolation and complete independence of the factors such as human’s operation models.
Programmers use the human reasoning and models of the mind to effectively highlight the roles of the computers and other machines across various sectors. The focus is to limit the influence of human factors, including errors of judgment through a programmed intervention of inventions and automation. In this regard, the focus is on the metrics and frameworks that shape the understanding of the mentality and the minding machines (Isaac, 2018). Descartes argument is crucial in defining the increased human influence in the machines, but in ability to completely remove them in the discourse of operations. The innovations in this century have focused on the models that shape the understanding of minds and how the machines have revolutionized several interfaces and discourses. Consequently, it is a question of the metrics and frameworks that underscore the brains and their models of operation (Milici, 2020). Machines, according to the first test in Descartes argument, do not have the potential to automate the relevant signals or reduce accompanying words. There have been innovative robots that highlight the essence of communication and sharing with the individuals regarding series of their needs, including the shared prosperity and attempting to replace humans.
The rationale, cognition, and the learning contexts underscore the essence of learning from the structured arguments. The essence of causal learning means the machines depend on the discourse of creating a human mind whose mode of operation is confined to the essence of memory, number discrimination, and metacognition. Moreover, the second test focus on the machines and their inability to achieve the status of the minding machines from the understanding of the core attributes (Brödner, 2019). The essence of minding machines cannot initiate the complex changes on the machines, which need regular maintenance and understanding to adapt to the changes in the environment. These contexts underpin the structural and contextual understanding of the machines and the human factors and how the two are distinguished despite the overlaying arguments on the replacement. Studies have suggested how certain machines can do tasks and activities even better than humans. However, these cannot be independence of their potential or organs. In this regard, there have been instances of the organ failure and how it impacts the understanding of the core arguments and discourses. Machines operate based on the distinct organs and are independent of the rest of their bodies, which highlight the discourse of argument and create the necessity for comparative assessment.
The second test appreciates the existence of efficiency in operation of the machines and how they influence the general outcomes. However, the challenge is on how they can work in isolation to do certain tasks without the intervention of their organs and human influence (Isaac, 2018). Descartes is right in highlighting the mechanisms and strategies for long-term engagement and creating the needed outcomes and discourses. Such things define the differences related to machine learning and the application of various elements in the long run. It is therefore a true manifestation that Descartes is right based on the theory of mind and how the evolution of the minding machines is still a mirage (Cave & Dihal, 2018). The context of the argument is on the structured understanding of metacognition that the machines are subjected to by the innovators, who attempt to replace their own imaginations and contextualize the outcomes and outcomes (Franco, 2018). Machines in the context of the second tests do not work in coordination of its organs, but in isolation and hence the discontinuity of one of the segments is a negative influence on the rest.
A typical case is on the aviation industry, where the high profile aircraft crashes have been attributed to overarching challenges, including the mechanisms for software failure. The human factors have been reduced in terms of their influence, hence the insistence that the machines cannot completely replace them even in the era of safety concerns (Martins, 2018). The machines have organs, which cannot be automated and coordinated to reduce the metacognition as human, which depict Descartes second reason for the differences between the machines and humans. A crucial context of the argument is on cognition and its relevance across many areas, including the mechanisms and strategies for long-term engagements. Human factors and bodily and organ composition are based on complex reasoning to appreciate a situation and come up with strategic interventions to reduce the chances of potential dangers (Grzeliński & Łagosz, 2019). However, the machines are spontaneous and do not have the critical assessment and metacognition elements that reduce the needed signal and forecast on the identifiable dangers that lurk.
The definite challenge is the problem of animal consciousness, which shapes the overarching differences between machines and humans and creates the context for distinguishing them. Descartes focused on words, signals, and operation of the organs to influence the long-term goals and objectives. These metrics underscore the relevance of the needed perspectives and instill the needed goals, through the demystification of the conspicuousness and how machines come into play (Isaac, 2018). The challenge of consciousness underpins the needed interventions and the Descartes argument in many discourses, including essence of inner order theory and higher thought theories. The understanding is that mentalities and cognition of the humans are superior to the machines and create the relevant framework for machine learning, which is embedded in the strategic interventions and contexts (Grzeliński & Łagosz, 2019). Moreover, it is a situation of the overarching outcomes and instilling the metrics and measures to influence change in reasoning and cognition. Machines and humans have differences, which includes attempts by the innovators to resemble human rationale and learning perspectives. These frameworks fail to match the essence of machines and their credited outcomes.
Despite the arguments fronted by Descartes, there are concerns on the veracity of such arguments in the current dispensation. The current machines have become more sophisticated, which highlight the possible obsoleteness of the thoughts, especially in health, communication, and aviation industries. The machines have become significant in reducing signals and words, which were not art of the discourse during the times of Descartes (Cave & Dihal, 2018). Thus, the current innovations, including software and other interventions, have overcome the initial notion about the expected outcomes and the frameworks for comparative assessment in the long run. In such scenarios, the focus is on the associative elements and discourses, including how the current innovations and automations have replaced or replicated the human minds. These contexts are relevant in sharpening the arguments and creating the major concerns about the mind and mentality. Machines have consistently done better in the current dispensation compared to humans, including reprogrammed activities and interventions. In this regard, the arguments by Descartes become obsolete as it has been overtaken by the sophistication (Brödner, 2019). The machines can now produce the signals, words, and other elements that define change and its resultant outcomes. Thus, the counterargument can be true in ascertaining whether machines can be humans, or even replace them in the models of operations.
Descartes understood the importance of cognition and how it underpins the relevant outcomes, including the frameworks for distinguishing the machine machines from other human interventions. The theories of mind define these concepts and reduce the ambiguities associated with the overarching outcomes and frameworks. Moreover, it is a context of the needed interventions and strategies, hence suitable for the long-term outcomes. The concern is on how individuals can identify that a machine, despite the effectiveness in operations and thinking, are not actually real men. Descartes two tests underscore the foundation based on words, signals, and organs as the basis of these elements. However, the contemporary innovations underscore the needed outcomes, including how the human mind operates in anticipation of an event and how to respond to such instances in the long run. Ideologically, the humans have the necessary frameworks and interventions that instill the relevant values different from the machines. Descartes underscored the different mechanisms that machines can never match humans in cognition, rationale, and learning propensity. Thus, the context is on the measured metrics and comparative assessment of the machines and their relevance to the learning and cognition attributes of the mind and body.
References
Brödner, P. (2019). Coping with Descartes’ error in information systems. AI & SOCIETY, 34(2), 203-213.
Cave, S., & Dihal, K. (2018). Ancient dreams of intelligent machines: 3,000 years of robots. Nature, 559(7715), 473-475.
Franco, A. B. (2018). Descartes’ Dog: a Clock with Passions?. Philosophia, 46(1), 101-130.
Grzeliński, A., & Łagosz, M. (2019). The animal-machine concept in Descartes and Berkeley. The attempt at comparison. Вісник Національного авіаційного університету. Філософія. Культурологія, (1), 5-10.
Isaac, A. M. (2018). Computational thought from Descartes to Lovelace. The Routledge Handbook of the Computational Mind, 9-22.
Marchetti, A., Manzi, F., Itakura, S., & Massaro, D. (2018). Theory of mind and humanoid robots from a lifespan perspective. Zeitschrift für Psychologie.
Martins, P. N. (2018). Descartes and the paradigm of Western medicine: An essay. International Journal of Recent Advances in science and technology, 5(3), 32-34.
Milici, P. (2020). A differential extension of Descartes’ foundational approach: A new balance between symbolic and analog computation. Computability, 9(1), 51-83.
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