解説/Review

特集：Society5.0，超スマート社会に向けた新しい価値を創造する

Behavioral Economics of Addiction in the Age of aSuper Smart Society: Society 5.0
Taiki TAKAHASHI∗

Abstract– In behavioral economics, violation of rationality in human judgment and decision making
has been investigated. In neoclassical economics, on the contrary, almost all human behavior (including addiction) has been assumed to be rational. Recent developments in Neuroeconomics haverevealed neural foundations for human judgment and decision making. Cyber technologies offer newrisks for new types of addiction (e.g., internet addiction, online video game addiction, and smartphoneaddiction); while these technologies can potentially offer new intervention methods for the treatmentof addiction. In this review, current findings in the studies of addiction in the age of “super smartsociety” (i.e., societies highly digitized and connected via SNSs) are introduced and future directions
are discussed.
Keywords– Neuroeconomics, Behavioral economics, Addiction, Smart society

1. Introduction
According to the Japanese governmental official website (https://www.gov-online.go.jp/cam/s5/eng/index.html ), “Society 5.0 represents the 5th formof society in our human history, chronologically following
hunting, farming, industry, and information. The Fourth Industrial Revolution is creating new values and services one
after another, bringing a richer life to all.” The key technologies of the super smart societies include telemedicine,AI nursing, drone deliveries, and so on. The Transdisciplinary Federation of Science and Technology (“横幹連合” Oukan Rengo, in Japanese) has a number of opportunities to contribute to this innovative changes in our societies
by collaborating with diverse academic societies including
the Association for Behavioral Economics and Finance inJapan.
In this review article, potential risks and opportunities
emerging from new technologies in the super smart societies which are related to addiction are introduced and analyzed by means of quantitative models developed in behavioral economics. Future directions in academic researchand social applications of the behavioral economics of addiction with new cyber-technologies are discussed. There∗ Hokkaido University, Center for Experimental Research in SocialSciences, N10 W7 Kita-ku, Sapporo, Hokkaido
Received: 13 July 2018, Accepted: 2018.

are several reasons for our focus on addiction. First, ascybertechnologies penetrate into our daily life, new typesof addiction, e.g., “Facebook addiction” and “Smartphoneaddiction” have begun to draw much attention [Pontes etal., 2018]. Second, owing to developments in new technologies, novel methods to assess and intervene in individual health problems (including addictive behaviors) havebeen introduced [Ferreri et al., 2018)] Third, addiction has
been extensively investigated in the discipline of behavioral
and neural economics [Takahashi, 2009], since addiction is,seemingly, one of the most irrational behavior. It is to be
noted that the Association for Behavioral Economics andFinance has been tackling the problems of addiction via theeconomic theory of addiction and self-control problems.

2. Empirical findings in addiction in theSmart Society
Problematic Internet use and Internet addiction, the excessive use of information and communication technologies
have been recognized as problematic behaviors for nearly
two decades [Young, 1998]. The concept of Internet addiction was originally proposed by Ivan Goldberg in 1995 ona chat forum for psychiatrists. Recently, it has been proposed that excessive use of video games and Facebook aremarkers of cyber addiction [Suissa, 2015]. The author proposed a psychosocial approach to Internet addiction such asOukan Vol.12, No.2

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Facebook addiction, since Individualism and the emptinessof social ties may be potential risk factors for Facebook addiction. Facebook addiction Disorder can be defined [Nadkarni & Hofmann, 2012] as follows: “When people areafraid to disconnect from Facebook because they think they
are going to miss something important.”
In terms of neurobiological foundations for Facebookaddiction, Montag et al. [Montag et al., 2017] utilized
functional Magnetic Resonance Imaging to examine neuralcorrelates of Facebook addiction. They observed that thenucleus accumbens, a brain region, has an important rolein Facebook addiction. Regarding molecular mechanisms
of Internet addiction, a neurotransmitter Dopamine [Hanet al., 2007] and a neuropeptide Oxytocin [Insel, 2010]
may have important mediating roles. Recently, Kuss et al.
[Kuss et al., 2018] reviewed studies of neurobiological correlates in Internet Gaming Disorder. They concluded that“(Internet) gaming addicts have poorer response-inhibitionand emotion regulation, impaired prefrontal cortex (PFC)functioning and cognitive control, poorer working memoryand decision-making capabilities, decreased visual and auditory functioning, and a deficiency in their neuronal reward system, similar to those found in individuals withsubstance-related addictions.” Therefore, it is recommended that Internet addiction is studied in a manner whichis common to other more conventional addictions such as
alcoholism [Nicols & Martin, 1993] and habitual smoking [Ohmura, Takahashi, Kitamura, 2005]. Notably, timediscount rate, an economic parameter indicating impulsivity, has been shown to mediate the relationship between
posterior insular cortex volume and social media addiction
symptoms [Turel et al., 2018]. This finding suggests that
economic approaches may be beneficial for a better understanding of social media addiction.

3. Treatment of addiction in a Super Smart
Society
New cybertechnologies can profoundly change the manner we understand and treat health problems and addictive disorders. Importantly, novel means of collecting live
individual data, computerized questionnaires, and the useof passive (i.e., not actively intervened or controlled, justobservatory) data, in the Big Data age. Furthermore, applications of artificial intelligence, e.g., machine learning
may improve the diagnosis and classification of individual patients based on data patterns which have not consciously been considered by clinicians in the past. Ad-120

ditionally, remote and automated medical interventions(web/smartphone-based applications) with the help of virtual reality and neurofeedback are or at least will be, available in a future Super Smart Society. We now introduce
several future concepts of technological innovations potentially useful for assessing and intervening in addictive behaviors, following Ferreri and colleagues recent reviewing
article [Ferreri et al., 2018].
3.1 e-health
The combined use of electronic communications information technology in the health sector has been
defined as “e-health”. The representative examples
are “telehealth” (health mediated by telecommunications tools such as mobile phones) and robotics (a setof techniques using automatic machines and medicalrobots).
3.2 Clinical Decision Support System
Computer-based tools supporting the decision-making
process, to facilitate organizational processes and provide clinicians with information about patients clinical status may be effective. The US Food andDrug Administration (FDA) recently authorized asmartphone-based e-health program.
3.3 Machine LearningThis is the subdiscipline of artificial intelligence thatgives computers the abilities to learn without explicit
pre-program. Machine learning may help accurateclassification and diagnosis of patients patterns.
3.4 Computerized adaptive testing (CAT)This system automatically adapt questionnaire items
to the answers provided by the patient to previous
items, using a big data. In psychiatry, “embodied conversational agents” have been developed.
3.5 Ecologically momentum assessment
The use of smartphone apps allows patients to maintain an accurate diary of their clinical status. Alcohol
use and PTSD (post-traumatic stress disorder) havebeen treated with this methodology.
3.6 Digital phenotyping
This technique can capture specific characteristics ofpsychiatric disorders by computerized measurement
tools. Also, the characteristics can be objectified
and quantified by computer tools, constituting an “esemiotics”.

横幹 第 12 巻 第 2 号Behavioral Economics of Addiction in the Age of a Super Smart Society:
Society5.0

3.7 Biofeedback or neurofeedback
Painless, non-invasive methods including the capturebiometric data (EEG, ECG, SCR, body temperatureetc.) and feeding them back to patients themselves ina real time manner so that they learn how to promote
or inhibit brain activities have been developed. This
computerized methods may enhance patients selfcontrol.
Overall, active and real time data obtained in a continuous manner (via smartphone, biosensors or connected objects, i.e., IoT) in a Super Smart Society may help assessment of addictive behaviors and other problematic behaviors. However, important ethical issues (e.g., individuals
privacy and data piracy) should be resolved before wide acceptance of these innovations in the future societies.

dysfunction of the prefrontal activation in the brain [Wanget al., 2017]. This recent study in neuroeconomics of addiction suggests that neuroeconomic investigations into addictions to cyber-technologies are important.
As stated earlier, recent technological innovations developed Ecological Momentum Assessment methodology
with CAT technique. One of the promising directions isthat real-time and simultaneous measurements of economic
parameters related to addictions and other health problem
behaviors (e.g., time-discount rates) and biometric parameters such as stress levels and heart rates for monitoring therisks of the initiation of illicit drug use and relapse in potentially risky populations. Accumulated findings in healtheconomics and behavioral economics may help analysis ofthese issues in terms of cost-effectiveness and social welfare.

4. Behavioral economic approaches to addiction in a Super Smart SocietyAddiction has also been studied in economics. For instance, Gary Becker, a Nobel prize-winning economist,
proposed a theory of rational addiction [Becker, 1988]. In
the (neoclassical) economic theory of addiction, Becker
and Murphy modeled addictions as the implementation of
a forward-looking consumption plan made under rational
considerations of tradeoff between immediate pleasure due
to drug intake and delayed health problems due to the past
drug consumptions, where the individual is entirely committed toward maximizing utility with exponential time discounting (devaluation of future rewards as delay until its
receipt increases). In exponential discounting, even drug
intake might be rational, since the preference for drug use
over future health does not change over time.
However, later studies in behavioral economics have revealed that human behavior in time discounting is not exponential [Thaler, 1981]. In actual human behavior, time
discounting is “hyperbolic”, in other words, people s time
preference reverses over time (referred to as “dynamic inconsistency”). Therefore, in neuroeconomic studies ofaddictions, neurobiological correlates of time discounting
have extensively been investigated.
In people with Internet Gaming Disorder (defined as thepersistent use of online games in spite of adverse consequences), a neuroimaging study demonstrated deficientability in evaluating tradeoffs between delayed reward fromabstinence from Internet Gaming and immediate satisfaction from persistent online gaming, and the impaired ability in impulse inhibition, which may be associated with theReferences[Pontes et al., 2018] Pontes HM, Taylor M, Stavropoulos V.; Beyond “Facebook Addiction”: The Role of Cognitive-Related
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Taiki TAKAHASHI（高橋 泰城）

横幹 第 12 巻 第 2 号

1996 年，東京大学理学部物理学科卒業．2001 年，
東京大学理学系大学院物理学 専攻修了，博士（理学）．2001 年 4 月〜2001 年 12 月，理研 BSI．2002
年 1 月〜2003 年 7 月，東大 CREST．2003 年 8 月〜
2006 年 2 月，北大 21COE．2006 年 3 月〜2007 年 12月，東大 21COE．2008 年 1 月〜2008 年 11 月，北大GCOE．2008 年 12 月，北大准教授 (文学研究科、脳科学研究センター)．行動経済学会理事．