as a woman in america
What is the ‘American Dream’ for women? For most, it is set of ideals promising prosperity and access to social mobility, and it has been evolving alongside the country – and now it will be doing so with technology configured to catalyze the reinvention of the concept. Exploring the notion through the lens of a young American woman, there needs to be a deeper understanding of the role women have played in the cultural fabric of the nation. In summation of Rosen’s work on the book Popcorn Venus, the decades have defined stages of social feminine revolution in the USA. She studied the characterization of women through the form of reflection theory and emphasizes their portrayal and its direct relationship to the social climates through cinematic archetypes. Originating at the extreme Vamp and Eternal Child tropes, women were still subject to Victorian values of domesticity which crafted both overly sexual depictions and unrealistically childlike personas. Over time this evolved into the Femme Fatale trope where women were subliminally punished as promiscuous behavior was metaphorically rewarded with death in films, and the dual role developed a Sacrificial Lamb trope which displayed a sense of disposability and justified discarding or emotional mistreatment of seemingly meek women. Following this, the Mysterious Woman was developed as a form of escapism during the Depression which weaponized sexuality, which was then followed by the trope of Bombshells who used sexual behavior as economic tools onscreen but were simultaneously psychologically damaged to the point of hysteria. Finally, she ends with a description of the Fatal Woman in the 60s, victims of violence who were displayed alongside educational atmospheres emphasized as backdrops to pursue romantic aspirations. This enlightened me towards the perception of American women and how it has grown over time – however it only provides sufficient detailing up until the 70’s which is right at the cusp of the electronic revolution. Not only that, but it lacked theoretical depth towards non-white women. However, it primed me for the current conversation on technology as an insightful factor for shaping this era for female citizens in the country. AI can be used as a neutral tool designed for the underprivileged or underrepresented, such as American women who have multifaceted underlying limitations and inequity within current conditions. Today, we have expanded new horizons that foremothers had rarely dared to envision such as a feminist American dream no longer hinged upon factors of wealth, sex, or race. The forging of new frontiers and prosperous identity was not readily available to women at the birth of America who were not taken into consideration either professionally or socially – but have been fighting against this narrative since the dawn of the nation. The “woman question” arose in 1845 where there was argument on the importance of future roles for women and the need for speculation on “every path laid open to woman as to man”. Written in an article section that glosses over Chopin’s novel The Awakening – the protagonist Edna explores the deceiving concept of purity and rejection of bodily sensation; worded as the expansion beyond “colorless existence” and “blind contentment” meant to speak to the cohort of metaphorically caged woman who may “see the possibility of empowerment” but “not see the reality of it”. A formerly enslaved woman, Sojourner Truth, also provided a powerful perspective on the denied privileges of women and drew parallels to the roots of slavery and highlighted the significance of a universal female identity. The advancement of intelligent technologies will positively alter the fabric of the American dream for the female demographic via increased career equality, reduced domestic role segregation, incentivized inclusion of feminism within STEM curriculum, and amplified significance of currently women dominated industries.
The American Dream for women is currently tainted by the legacy of unequal representation, however technological solutions could include motivation for increased efforts in involving women in STEM and equal educational opportunity and access. An increasingly automated future is derived from technologies developed by non-diverse technical teams, risking the construction of machine learning instruments influenced by subconsciously biased algorithms; this provides further motivation to integrate an immense proportion of female researchers within the STEM population as a preventative route. Selection bias will grow in machine learning technologies if there is no diversity behind the enterprise endeavors ranging from research to product launch and currently the World Economic Forum claims only 8% of women take engineering coursework and only 5% pursue math and statistics while only 13.8% of AI related research papers are authored by women. Women have need to break the virtual glass ceiling most now since they face an 11% risk of job loss in comparison to 9% for male counterparts due to automation which is translated to globally 180 million women – as only 22% of AI jobs in 2018 were held by women so those experimenting and implementing the technology for organizations will leak unconscious bias into it. An example of where this has already occurred includes an incident occurring within the well-known corporation Amazon. Amazon abandoned its AI recruitment tool once they discovered it shows male preference since the algorithms that sift through resumes and spot performance problems are more objective than human based decision making; therefore, it penalized women as it utilized date culled from 10 years of resumes that were mostly of males. Other examples worth emphasizing include the yielding of high-level technology being directed into the creation of highly sexually explicit content or deep fakes of existing women, as well as the female characterizing of all digital assistive services such as Siri, Cortana, and Alexa and the underlying messages of default usage of female voices and titling. Media like Hidden Figures and Rise of the Rocket Girls may offer glimpse towards the pains of professional development for working women post World War II and the Cold War (gender specific positions were externally enforced and supervised) and how that legacy has lived on. Existing institutional histories of NASA facilities has given insight into the gender barriers within educational resources even today. This concludes my first subpoint. Denser online networks and big data cloud computing can effectively be introduced as a tool purposed to bridge the digital gender divide of infrastructure access and proposing inaccessible instructional content and resources to those with restrictive means to cultivate higher quality skills. This can especially be implemented within subsocieties where women are somewhat culturally prohibited from achieving higher and more modern standards of separate education. Equal accessibility to advanced curriculum allows for high skill cultivation among the demographic as well. Social and technological factors can alter the time it takes for someone to become a professional expert from novice as the knowledge is embedded in the software instead and no longer are required to be an engineer. With proactive efforts companies can make AI a net benefit to females instead – the current issue is women being unaware since they are uninvolved in the digital revolution to the same extent. Upskilling/reskilling can flip these odds for up to 77% of this working force with limited retraining. As proof of the impact of education for American women, there has been much media meant to raise awareness. The American Nightmare is a theatrical showing crafted to address income and education inequality through a documentary on women who fought the stereotypical plaques such as “welfare queens” and could only support themselves through proper education and 4-year degrees, supporting their argument upon statistics such as that 90% of women provided with proper college education move away from welfare plans. Alongside this, many organizations are attempting to better equip the next generation of women by addressing the roots of certain issues with technology itself. Critical components of emotional development are specifically focused on to help young girls confidently navigate social terrains sophisticatedly and apply appropriate assessment towards financial literacy and stability amongst complex choices. They are provided with a sense of self-reliance and drive for mandatory professional representation – but many still experience a self-convicted liability rooted in generations of deep anxiety and insecurity towards career or financial independence. To address such topics, the same groups of girls were tasked to design apps to benefit themselves and provide tools or resources that are applicable in the modern world. Apps such as mirrors with subliminal messages aiming for promotion of self-assurance in professional environment were designed, as well as anonymous apps made for cultivating mentorship relationships. This correlates to the narrow networks many working women deal with which limit essential anchors that may provide critical sources of motivation and criticism and serves as a solution.
The American Dream for women is currently influenced by imbalanced gender education and employment, and technology can offer automated performance and resume reviewal as well as intentional balancing of preexisting workforce demographics. Preexisting power imbalances within technology startups and corporations can be mitigated with the usage of computer programs utilized for unprejudiced employee recruitment, intervention, and performance evaluation in substitution to candidate reporting and screening via naturally biased human networks. Reutilizing a previously mentioned example: FAANG/MAANG big tech companies such as Amazon utilized self-developed AI for resume review which adopted male bias utilizing prior data analytics and preference. Algorithmic creep has presented itself in other examples as well. STEM career ads meant to be explicitly gendered neutral were disproportionately displayed to potential male applicants as advertising to younger females is higher and cost-efficiency was optimized within the technology. However, if altered, the same technology is capable of conducting demography analysis and prioritizing equal gender hires. As an analogy to better understand how algorithmic bias operates, consider a software programmed to select astronautical candidates for a mission to the moon. Based on the nature of the computer, it will be wired to analyze prior candidates and make a selection based off that information. But what if all the prior candidates were men, seeing as no women have been to the moon yet? The software’s likelihood of selecting a woman has now significantly decreased based on its previous data set – this will exacerbate the inequality observed and noted. This same software can also feature a skill, if properly implemented, to do the opposite. AI, if implemented correctly, can be used to instead aim to hire those who are underrepresented in current company employee demographic information and spotting candidates that could be overlooked through traditional recruiting means. There has also been a notable reported 16% increase in diversity hires after adopting digital hiring. AI can now also propose solutions and in the future identify the most effective interventions at key career junctures by analyzing internal workforce data to make performance review recommendations, substantial job redesign, etc. An interesting sidetrack to this argument is also to explore how this may depend on subcategories within the demographic of woman as well. An error in the Gender Shades project by MIT has proven its AI to be systematically worse at analyzing darker skinned women specifically, and some interview software are coded to analyze facial muscle movements and decipher expressions – a culturally influenced feature that is highly variable across the world marking this as an unintentionally discriminatory process. Algorithmic bias can be implemented intentionally with the objective of recognizing disproportionate industrial/social skews, and actively opposing any significant reflection of discriminatory processes by performing selectively in favor of factions who are statistically unfavored by the preexisting systems.
The American Dream for women is currently threatened by targeted unemployment risk and career insecurity; advancement of technology can provide a solution to this by instead taking the direct opposite course naturally in the long term. To begin, I would need to address the argument consisting of speculation that female dominated industries will be the most vigorously impacted victim to the automation and technologically based displacement of work, on the premise of speculative exacerbation of preceding gender disparities in higher value employment and careers. I, however, would like to assert a nuanced counterargument: in future years female dominated industries will acquire stronger security/stability as a direct net benefit of the introduction of AI due to the psychologically challenging nature to replicate of these career paths, restricting computers from acting as an appropriate replacement - at least with the current predictive trajectory of AI/ML. Emotional intelligence and advanced empathy work careers are primarily held by females (ex: therapists, secretaries, youth education, nursing, etc.) and such human interaction based + socially hardwired skillsets will become increasingly valuable in an era of inefficient routine work being transferred to technology; current algorithms are incapable of sufficiently portraying or understanding emotional needs to a necessary extent and likely won’t reach such a level of advancement in the discernable future. Complex problem-solving, creativity, fine-tuned upper-level social emotional skills, and organizational settings are areas where AI can’t be effectively introduced yet/certain jobs in traditionally female sectors such as medical or social services require cognitive and interpersonal skills and are less prone to automation. It is important to consider that underrepresentation of women in science and technology roles is supplemented with overrepresentation of women in emotional intelligence and advanced communication skills (therapists, secretaries, therapists, etc.) and empathy is difficult to recreate in AI, so they are in fact safer from disruption theoretically than the male demographic for whom the majority actually conducts more automated physical or mental labor.
The American Dream for women is currently restricted by traditional role norms and outdated expectations, and technology can resolve this via reduced household responsibility factors (domestic equity) and an increased variety of career paths to adopt for women.