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Behavioral Economics and Big Tech:
Curse and Blessing

By Daniel Naumov

November 2020

          The New York Times reported on two Nobel Prize winners in economics back in 2002: Daniel Kahneman and Vernon L. Smith, who observed and documented the differences between economic theory and how people actually behave. This was the foundation of the subject of behavioral economics, which, by 2002, was already prominent in economics graduate circles. Nowadays, with far more advanced technology and an ever more digital world, the topic is more important than ever. Behavioral Economics combined with Big Tech and constantly evolving machine learning algorithms have opened up a Pandora's box of possibilities, ranging from better outcomes in cardio-oncology cases and improved health habits to swelling monopolies and invasion of privacy.

          Facebook and Google have been building up their monopoly empires, and some of their purchases are telling of their current and future strategies. In a 2019 NYT Opinion article, Tim Wu and Stuart A. Thompson took a deep dive into the acquisitions made by Google and Facebook, and briefly discussed some of the more important ones. Onavo Data, a mobile company purchased by Facebook in 2013, surveyed usage patterns of millions of users, and used the data to guide the future acquisition pattern of Facebook. The Wall Street Journal reported in 2017 that data from Onavo helped guide Facebook to their largest acquisition ever: Whatsapp. Onavo was shut down by Facebook in 2019, after Apple removed their VPN app from the app store due to data collection policies that violated the company’s policy.

          While not discussed in the NYT article (but acquired by Google in 2012), Incentive Targeting partnered with retail chains and provided a targeted marketing service. Many of the Big Tech giants’ acquisitions are either data-oriented or meant to remove competition. The former gives the companies valuable information about consumers - which is where behavioral economics comes into play. Acquisitions worth mentioning here are DoubleClick, acquired by Google in 2007, and AdMeld, in 2011. DoubleClick was Google’s main advertising competitor at the time. After the acquisitions, these two companies revolutionized advertising on Google. Not only was their advertising targeted, but it also set up a bidding system, where advertisers would try to win an auction in order to display their ad. Furthermore, user interactions with the ads gave information to Google on what sorts of ads the user would click on.

          Facebook’s acquisition of Onavo Data allowed them to better understand the behavior of their consumer, and thus guide them to make other acquisitions based on intelligent assumptions. Google’s acquisitions of target advertising companies allowed them to streamline the ad-placement system, as well as understand how users reacted to different ads (allowing ads to become more effective.)

          “Nudging a user” is mildly influencing their behavior by motivating them to change it. Made prominent by Richard Thaler and Cass Sunstein, two behavioral economists, it gained a following in the US and UK public health sector. One such case of behavioral economic principles in medicine was a University of Pennsylvania cardio-oncology study. The university used a nudge ladder: a step-by-step process that ideally significantly changes the behavior of the user for a better end result. In the article, the ladder consists of four primary portions: framing information, prompting implementation intentions, enabling choice, and setting default options.  It promotes patient participation in an app that would help detect and treat cases of cardiotoxicity much earlier than would be normally possible. The program implements many principles of behavioral economics, mainly to circumvent irrational decision making and cognitive biases.

          “For example, individuals are motivated by immediate compared with delayed gratification, motivated more by avoiding losses than receiving equivalent gains, and often overestimate the probability of positive events while underestimating the probability of negative events.”

          Essentially, the cognitive biases present in us may have a serious negative impact on our health. The nudge ladder makes the system more streamlined and effective. U-Pennsylvania’s paper shows that the principles of behavioral economics (in the form of nudges) can be used in the medicinal field in order to change our behavior such that cardiovascular diseases are easier to detect and treat. Perhaps this system will spread to other sectors of the medical field, and cause mortality rates from dangerous, long-term diseases to drop.

          “Nudging” goes beyond medicine too. A Harvard Business Review article from 2019 likened the current AI revolution to the behavioral economics one: both are centered on irrational behavior. Bob Suh, the author of the article and CEO of OnCorps, states that “The key to better outcomes is to boost AI’s emotional quotient — its EQ… to mimic the way people behave in constructive relationships.” By making interactions between AI centered applications and humans constructive, the AI can “nudge” the human towards better behavior. Behavioral science and machine learning developed several techniques in order to produce better outcomes. Some of the tactics include encouraging self awareness with benchmarks, and choosing the right time for insight and action. While I wasn’t able to find any articles that talked about applications that used nudging in such a way, aside from the U-Penn one, it could be a game changer in this new era of social media. Suh concludes on an optimistic note: “Could higher-EQ AI help bring more civility to the internet? Social media companies might do well to consider a distinction Western business people soon learn when negotiating with their Japanese counterparts — “honne” (what one feels inside) versus “tatemae” (what one publicly expresses)...The challenges of developing such emotionally charged, high-EQ AI are daunting, but instead of simply weeding out individual posts it might ultimately be more beneficial to change online behavior for the better.”

          Hopefully, in the future, his vision of a more civil society aided by machine learning AI and gradual nudging in the right direction will come to ahead. 


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Behavioral Economics and Big Tech: Curse and Blessing: Services
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