Techno animism versus Replacement Theory: A comparison of cultural attitudes towards AI, Automation, and Robotics in Japan versus the U.S. (Part 2))
Perhaps then it isn’t Christianity (alone) but Americas peculiar relationship to Christianity, vis-à-vis the transatlantic slavery, that informs American attitudes towards AI, automation, and robotization. Shaped by unique social circumstances in their interaction with non-European, and non-Christian population, Christian doctrine indeed took a different turn when it came to the shores of the Americas.
In “Stamped from the Beginning”, Ibrahim Kendi X, points out the distinctly American historical phenomena of debating whether enslaved Africans should have spirits or souls “conferred” onto them by being “allowed” to accept Christianity. This polemical discussion had no parallel within Shintoism or Buddhism, which already accepted that all creatures had souls.
Thus, the private societal discourse over whether a ‘soulless’ workforce was capable of developing a ‘soul’, and subsequently whether they should be granted access to information reserved for soul carrying creatures (humans) was the essence of the American justification of native American genocide and African chattel slavery.
Within this discussion was the very public claim that enslaved Africans (as pseudo humans) were: 1) not oppressed; and 2) content with their lot as human chattel. However, these public declarations were contradicted by the society’s obsessive fear that these, contented ‘non-humans’ might engage in the very human practice of reprisal, a reprisal inspired by a discontent that was ostensibly not present, and against a system of oppression that purportedly did not exist.
As American society became moved to secularism, religious debates gave way to scientific theories or race and racial superiority. Debates over whether enslaved Africans possessed a ‘soul’ drifted whether enslaved Africans, and their offspring, were capable of intelligence or other human sentiments.
The American fear of robots and AI exist on a spectrum of three main points. The basic fear is that robots will replace humans, further down the line is the fear that AI will continue to increase its intelligence until it becomes sentient. The fringe of the spectrum is what AI-related blockbuster films are made of. The typically plot centers around AI robots, who immediate upon becoming sentient, set out to revolt against, imprison, enslave, or commit genocide against humans.
Replacement theory is a subset of a larger “white genocide conspiracy theory” which posits that there is a deliberate plot to render the white race extinct through miscegenation, interracial marriage, or non-white immigration. In the post Trump world this fringe theory has gained more mainstream acceptance in the U.S. and Europe. A variation of this theory is the commonly expressed allegation that non-whites have come to take jobs and resources away from whites. This theory is typically cited in initiatives to curb immigration from non-western countries.
In pre-Civil war America, in many places throughout the U.S. Southern States, enslaved Africans outnumbered whites over 9 to 1. And between 1526 and 1864 the U.S. saw over 313 documented slave revolts. Just as slavery provided the backdrop to the founding documents and norms of the U.S. legal system, fear of slavery revolts shaped the laws, social mores, and cultural sensibilities of Americans. Long after the abolition of slavery, these societal obsessions inform our fear of AI
Atlantic Slavery engendered a pathology of fear, addition, and dependency in its perpetrators and beneficiaries. On the one hand they feared revolt from this ‘subhuman’ population. Nonetheless the addiction to, and dependency on their labor induced society to continue to breed them. The result were societies in which the ‘subhuman’, outnumbered the humans. Mainstream American thought denied the idea that enslaved people possessed intelligence or the ability for higher order thinking, yet the same proponents of this thought rushed to create laws which prevented them from access to literacy and learning. Proponents of slavery, and their enablers, publicly declared that the enslaved Africans were happy with there lot as slaves, yet despite their professed belief in this idea, they also obsessively feared slave revolts.
At the time of this writing, there are twice the number of smart devices than humans on earth. By 2030 IoT devices will outnumber humans over 4 to 1. Despite our awareness of these devices and the popular fear that these devices will replace our labor, we promote or facilitate their continued production partially because of our learned dependence on them.
We continue to express our fear of AI’s ability to learn from the unsupervised data from the open internet and our collective imagination concocts elaborate scenarios in which machines will use this data to enslave and control us. A common correlate of the fear of AI across cultures, is the general fear of hyper capitalism unchecked by ethical standards. In the U.S. the discussion centers around the intuitive knowledge that AI will become more efficient executioners of our way of life, and our fear of this phenomena, more than anything, speaks volumes about what we subconsciously think about our current way of life.
However, there are ways for us to come to terms with this reality. AI, and technology in general, tends to replace human labor but not necessarily humans. Doomsday prophets often overlook the fact that trending technology typically replaces jobs that were, once upon a time, created by a previous emerging technology.
An important goal is to remove the silos born out of our preference for niche expertise. This can be accomplished by disrupting the monopoly of experts who currently dominate the field and increase access to a wide watch of learners.
If we are to classify career fields using Gardens Multiple Intelligence theories, we will find that those who currently dominate the fields of AI and robotics are generally experts in the fields of Logical and Mathematical intelligences, namely Data Scientists, Engineers, Computer Scientists, Mathematicians, and Statisticians. A great portion of their expertise is used to serve the business sector.
Statistics, is currently changing from a field which focused strictly on mathematical methods, to one which is based on an entire problem solving cycle. Similarly Data sets, and Data science platforms are becoming more available to non-experts. Finally, the Machine Learning behind AI models is migrating towards a no-code learning environment. This atmosphere is the perfect time for those with domain knowledge in the linguistic and intrapersonal fields to enter into the field of AI. Should a core of Anthropologists, Sociologists, Political Scientists, Information Specialists, Legal experts, and Historians learn the fundamentals of Machine Learning and Data Science, not only will the field be enhanced with their domain expertise, this enhancement will aid in setting forth the necessary social and ethical structures that the people fear AI currently lacks.