AI cheerleaders treat everything as a technical problem that can be quantified- this is the root cause of algorithmic violence

(Abeba, CompSci@Dublin, Jelle, Management@Twente, Robot Rights? Let’s Talk about Human Welfare Instead https://arxiv.org/pdf/2001.05046.pdf)

It has become trivial to point out how decision-making processes in various social, political and economical sphere are assisted by automated systems. AI solutions pervade most spheres of life from screening potential employees to interviewing them, to predicting where criminal activity might occur (in some cases who might commit a crime) to diagnosing illnesses. These are highly contested and inherently political and moral issues that the technology industry is nonetheless treating as “technical problems” that can be quantified and automated. The automation of complex social, political and cultural issues requires that these complex, multivalent and contextual and continually moving concepts be quantified, measured, classified and captured through data [29]. Extrapolations, inferences and predictive models are then built often with real life actionable applications with grave consequences on society’s most vulnerable. Machine learning systems that infer and predict individual behaviour and action, based on superficial extrapolations, are then deployed into the social world resulting in the emergence of various problems. These systems pick up social and historical stereotypes more than any deep fundamental causal explanations. In the process, individuals and groups, often at the margins of society that fail to fit stereotypical boxes suffer the undesirable consequences [25]. A recurring theme within algorithmic bias, for example, shows that individuals and groups that have historically been marginalized are disproportionately impacted. This includes, for example, bias in detecting skin tones in pedestrians [42]; bias in predictive policing systems [32]; gender bias and discriminations in the display of STEM career ads [27]; racial bias in recidivism algorithms [1]; bias in the politics of search engines [24]; bias and discrimination in medicine [20, 30]. AI, far from a future phenomenon waiting to happen, is here operating ubiquitously and with a disastrous impact on socially and historically marginalized groups. As Weiser remarks: “The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it.” Ubiquitous AI is inextricably intertwined with what it means to be a human being [11]. Yet the question is, how to best frame this intertwining conceptually? The typical narrative seems to conceive of AI technologies as some type of social partner that we will communicate and live with in ways comparable to the ways other human beings are bound up with our lives. In reality, no robot today is anywhere near that future vision. The actual situation we have today shows machine learning algorithms as embedded in seemingly mundane tools, supporting everyday tasks. These algorithms are influencing our basic ’being in the world’ - the way we perceive and categorise the world, the agency we ourselves have in acting on it, in a more invisible, Weiserian sense, which makes it all the more insidious. For example, the humanoid robot known as Sophia, epitomizes an image that sits well with widely held conception of “intelligent robots” but whereas in fact, it has rudimentary engine and capabilities in reality. In comparison, iRobot’s Roomba, while portrayed as a harmless household machine, exerts much more impact on our lives, and the dark side of it, is that it serves as a surveillance tool that continually harvests data about our homes. It is easy to overlook the dangers that the Roomba pauses to our privacy as the machine fades into the background and becomes silently incorporated into our day-to-day life. iRobot’s Roomba “autonomous” vacuum cleaner is fitted with a camera, sensors and software enabling it to build maps of the private sanctuary of our home, while tracking its own location[43]. In combination with other IoT devices, the Roomba can be used to supposedly map our habits,behavours, activities. Most AI companies boost on capabilities to be able to provide insights into the human psyche. Financial interests of companies and engineers that collect, evaluate data and algorithmically interpret and predict behaviors drive AI research and development. As such “smart” systems infiltrate day-to-day life from the IoT devices to “smart home” all designed to render all corners of lived experience as behavioral data [43]. Envisioning a future humanlike intelligent system while putting aside such ubiquitous and invasive systems which are a thereat to privacy and human welfare, shows misplaced concern, to say the least. The integration of machinic systems into social and human affairs poses immediate danger, especially to disfranchised people that need the most protection (O’Neil, 2016). Taking ethical concerns seriously means, we argue, prioritizing welfare of people, especially those often disproportionally impacted by the integration of machinic systems into daily life.