• Brock Scott

To Thine Own Self Be Artificially Intelligent

This essay explores how emerging technologies in the form of artificial intelligence (Ai) and data analytics tools will impact social dynamics and identity concepts within emerging social systems. We will need to redefine our social norms, how we value interpersonal relationships and the ways in which we assess and define our own identities. (1) Ai and data analytics will provide quantifiable metrics to personalize these new norms, values and identities. (2) Furthermore, as rapid technological progress hurdles us into a new era known as the digital revolution, we must monitor how we use these new technologies by learning from the historical mistakes our predecessors made during the industrial revolution. (3) Our rulemaking actions and regulatory monitoring should focus on eliminating traditional biases while creating a social system and a marketplace that promotes fairness and equality. Regulating rapid technological innovations without deterring creative progress is no easy task. As T.S. Eliot states, “Most of the evil in this world is done by people with good intentions.” (4) Therefore, we will discuss the inherent problems that arise when creating a new social system and the creation of a digital economy.

To examine how emerging Ai and data analytics technologies will impact identity concepts within an evolving social system, let’s examine the popular episode “Nosedive” of the television series “Black Mirror.” The story illustrates a seemingly utopian society where everyone is hyper-connected within a ubiquitous social credit system powered by artificial intelligence and data analytics (everyone uses an app to rate anyone whom they encounter in-person or on social media). As the plot unfolds, Lacie, the protagonist, pursues achieving a social rating of 4.5 out of 5, which allows her to be regarded by her peers as an esteemed influencer.

Influencers are allowed special privileges such as access to luxury housing, priority seating on airplanes, the nicest car rentals and employment at the best companies. Lacie spends much of her time exercising a concept known as impression management, which is an activity people do to control the presentation of their personal information and influence how others see them. Lacie posts staged photos of herself on social media and oozes flattery to everyone she encounters in public.

Impression management becomes more difficult when Lacie loses the ability to control the initial impression others have of her identity. Lacie experiences the negative effects of an incongruent identity when her life spirals out of control on her way to attend her friend, Naomi’s, wedding. While at the airport Lacie’s flight is delayed. However she notices that for anyone rated 4.3 or higher has the privilege of accepting a seat on the next flight. Lacie identifies with being rated a 4.3 because that had been her rating earlier that same day. However, due to the effects of dynamic construction, which regards identity as being malleable, Lacie received a couple poor ratings. Now Lacie was rated below a 4.3. The airline attendant points out the incongruous nature of Lacie’s self-identity and causes Lacie to lose her temper. Lacie curses at the airline attendant and as a result her social rating crashes to unprecedented low levels. She loses all her privileges and is subjected to a barrage of prejudices and biases from anonymous people because of her low rating.

There is a stark dichotomy of living standards and social value between those with a rating in excess of 4 and those with a rating below 4. Experiencing the unjust prejudices and biases that people of lower socio-economic demographics encounter each day forces Lacie to shift her self-perceptions and how she perceives other people, which is evident by her acceptance of the lowly-rated truck driver who drove Lacie to the wedding--and Lacie’s own behavior while attending the wedding. Instead of flattering Naomi while delivering her speech, Lacie criticized her. Perhaps, after enduring embarrassing public ridicule and criticisms, Lacie realized the ubiquitous social credit system that aimed to provide fairness for everyone may have its own inherent hidden flaws.

Therefore, it is important to understand the implications a ubiquitous social credit system will have upon fundamental psychological principles regarding social dynamics and identity concepts. Currently, in China, a similar social credit system is emerging. Facebook has also patented a social credit system that ranks your credit score based off your friends and their associated credit scores. The social credit system in China, known as Zhima Credit, is creating radical social change. The changes will affect identity concepts surrounding self-knowledge and self-presentation and the chief social dynamics affected will be those surrounding interpersonal relationships and peer groups.

Self-knowledge, which involves the self-enhancement motive, accuracy motive, consistency motive, is assessed within the physical, social, and inner-psychological worlds.According to psychologist Roy F. Baumeister, to a great extent, our identity (and who we think we are) is determined by the physical world--i.e. the time and place we are raised and live. The social world involves social comparisons within interpersonal relationships and between peer groups. Because of the emergence of social credit systems, anything within the physical and social worlds can be measured with quantifiable metrics, which directly support people’s need for accuracy motives and consistency motives to verify both their social rating and their identity. And thus, the way we seek self-knowledge within the physical and social worlds will change because of the emergence of Ai and data analytics.

The way we seek self-knowledge will change beginning with the self-enhancement motive and its correlation with positivity bias: people desire to seek positive emotional states and avoid feeling negative emotional states. Positivity bias research by Dunning, Leuenberger and Sherman asserts “that people use self-serving trait definitions after they receive negative feedback about themselves, suggesting that the tendency is motivated by a desire to enhance feelings of self-worth.” But in a ubiquitous social credit system, is it even possible to avoid feeling negative states and the impact of a negative rating? I argue that it is impossible. In a social credit system there is no way to hide from your negative ratings and diminish accepting negative criticism from your peers.

Therefore, positivity biases become obsolete within a social credit system. Consequently, since no one can run from their negative states, self-enhancement motives become more important as they provide motivation to posture oneself as grandiose and gain social value. Along with positivity biases, the influence of reflected-appraisals is negated by the emergence of social credit systems. Having direct knowledge of the ratings your peers provide you lessens the legitimacy of the concept of reflected appraisals and with it Charles Cooley’s discussion of the looking-glass self (which proposes imagined judgments by your peers to gauge your self-worth). The emergence of social credit systems also negates the importance of psychologist Richard Felson’s assertions. Felson believed "people are not very good at knowing what any particular individual thinks of them” (Felson, 1993). That's untrue with a ubiquitous social credit system. Social credit systems remove the communication barriers and social norms that limit the information we exchange with others.

The physical world becomes more important in a social credit system. Actions are measured and define one’s value in society. Unlike the social credit system in “Nosedive,” the real social credit system in China supports the consistency motive for individuals and promotes long-term healthy behaviors. Self-presentation and its correlation with self-regulation becomes of chief importance to anyone aiming to live a prosperous life in China. While failing to stop at crosswalks may result in a fine and dinged a couple credit points, committing a heinous crime will result in social ostracism and, just as Lacie suffered in “Nosedive,” the loss of social and personal privileges.

For those people who are committed to maintaining a healthy lifestyle and a good credit rating, they must consider not only their own behaviors and self-presentation skills but also the behaviors of their friends. Zhima Credit, China’s leading social credit rating, people’s credit scores are adversely impacted by their friends whom have poor credit ratings. Social rating experts advise people using Zhima Credit to disassociate themselves with their friends (or lovers) if their credit ratings fall below a certain threshold.

If the use of Ai and data analytics within a social credit system has such an immense impact on our interpersonal relationships and peer groups, how will it affect our identity concepts about employment and the nature of work? The biggest impact won’t be the number of jobs lost or job displacement but rather companies and employees will have to reimagine the nature of work and the job content. In the digital economy, traditional job roles will become obsolete; however, this is a positive idea because humans will be asked to add value using creativity and thought-leadership instead of performing menial tasks and manual labor. For instance, according to recent Accenture research:

“...explored the nature of some new [job] roles and uncovered three new categories of AI-driven jobs: the “trainers,” “explainers” and “sustainers.” Trainers, for example, will help computers learn to recognize faces. Explainers will interpret the results of algorithms to improve transparency and accountability for their decisions, helping to strengthen the confidence of both customers and workers in AI-powered processes. Sustainers will ensure intelligent systems stay true to their original goals without crossing ethical lines or reinforcing bias.”

Speaking of biases, Ai will impact the nature of jobs but what is the impact Ai and data analytics will have on hiring practices? The goal of eliminating biases within Ai algorithms is at the forefront of emerging employee assessment programs. For instance, and Entelo are companies that use machine learning to detect skill prerequisites for job types.’s algorithm is programmed to only search for job candidates based on a certain set of skills needed for a certain job. Entelo focuses on eliminating personal physical attributes from a recruiters decision-making process. According to a recent Bloomberg Law news article, Entelo’s software “...allows recruiters to hide to hide names, photos, school, employment gaps and markers of someone's age, as well as to replace gender-specific pronouns—all in the service of reducing various forms of discrimination.”

Another company committed to creating Ai programs that assist companies in creating fair, unbiased employment practices is Pymetrics. There exists a crucial need for assessing the risk-management skills of job candidates at financial firms such as JP Morgan. Pymetrics has created interactive video games that predict future job performance. Candidates can click on a balloon to earn money and risk overfilling the balloon until it bursts in the hopes of collecting the most money or the candidate can stop filling the balloon and risk collecting less than a maximum return. Pymetrics hopes their games create a fair playing field for job candidates to assert their skills while allowing companies to diversify their workforce.

The innovative Ai tools available to companies and job recruiters is growing and is designed to help eliminate traditional human biases. According to Solon Borocas, an assistant professor in Cornell’s Information Science department, “Human decision-making is pretty awful. But we shouldn’t overestimate the neutrality of technology, either.” Implicit biases can exist in algorithms because of unintentional biases included by the programmer, such as favoring particular skills within a given data set. Programmers and executives within corporations can implement procedures to attenuate programming biases. Pymetrics’ team of programmers perform audits to discover if their algorithms create biases for any gender or ethnicity. If a programming error is realized it can be corrected.

As we progress into a digital economy, more problems than discrimination will confront us. The main issue that we will face is that of people feeling like they’re living without purpose. How can we avoid a society that delves into nihilism? We must focus on the nature of work as jobs become more reliant on artificial intelligence and machines. We gain meaningful relationships through engaging with our co-workers. How do we ensure we will stay connected with others and sustain our shared sense of purpose? According to Ryan Avent in his book, The Wealth of Humans, “When work works, we understand it provides a basis of social order. It gives people something to do. It gives workers the sense that they are contributing to society and to the welfare of their families.”

This sense of purpose and social belonging has sustained America’s economy since the Industrial Revolution. However, we would be wise as a society to prevent the same problems that arose during the Industrial Revolution. As we transition into a digital economy and the nature of work evolves we need to rely on human connection to sustain a creative workforce that focuses on promoting fair wages and avoiding an egregious income inequality so everyone can experience a shared higher quality of living.

There is no doubt our economy is becoming digitized and redefining the role of humans to work alongside artificially intelligent machines. Our identities will be defined for us by data analytics and social credit systems. Everything but our deepest inner thoughts will be quantifiable and measured, influencing everything from our interactions with our peers and intimate relationships to our career achievements. Our goal as a society must be to promote fairness and instill purpose within each of us. As Norman Vincent Peale states, “People want to feel important.”


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