Behavioral measurement is the hallmark of research in the field of computational social science. We are witnessing innovative as well as clever use of existing and novel, commercial, or research-grade “sensors” to measure various aspects of human behavior and well-being. Passive sensing, a version of measurement where data is gathered and tracked unobtrusively using pervasive and ubiquitous sensors, is increasingly recognized and utilized in organizational science research. This chapter presents an overview of where passive sensing has been successful in workplace measurement, ranging from assessing worker personality and productivity, to their well-being, and understanding the overall organizational pulse. A range of passive sensing infrastructures are described (e.g., smartphones, wearable devices, social media) and several machine-learning-based predictive approaches are noted in this body of research. The chapter then highlights outstanding challenges as this field matures, which include issues of limited generalizability in computational measurement of workplace behaviors, gaps and limitations of gold standard assessment, model simplicity and sophistication tradeoffs, and, importantly, privacy risks. The chapter concludes with recommendations on important areas that need further or altogether new investments, so as to fully realize the potential of passive sensing technologies in more accurate, actionable, and ethical workplace measurement.

Substance use, aggression/violence, delinquency, and risky sexual behaviors emerge and peak during adolescence, as teens enter new social and digital ecologies. This chapter reviews the literature on the co-occurrence and mutual influences between adolescent digital media use and engagement in online and offline health risk behaviors, with attentions to the mechanisms underlying these associations. Research suggests the quantity of time adolescents spend online is less important than the quality of how they spend that time, and that many well-documented peer influence processes (first studied in face-to-face peer interactions) are also emerging in online spaces. Shared vulnerabilities, peer selection, peer socialization, and identity development are important mechanisms helping us understand why adolescents engage in online and offline risk taking (and thus potential targets of interventions to reduce risk processes). This chapter highlights directions for future research, emphasizing longitudinal and experimental designs to improve causal inference and testing directionality of effects.

Although lay participation has long been a feature of scientific research, the past decades have seen an explosion in the number of citizen science projects. Simultaneously, the number of low-cost network connected devices collectively known as Internet of Things devices has proliferated. The increased use of Internet of Things devices in citizen science exists has coincided with a reconsideration of the right to science under international law. Specifically, the Universal Declaration of Human Rights and the International Covenant on Economic Social and Cultural Rights both recognise a right to benefit and participate in the scientific process. Whilst it is unclear whether this right protects participation by citizen scientists, it provides a useful framework to help chart the ethical issues raised by citizen science. In this chapter, we first describe the origins and boundaries of the right to science, as well as its relevance to citizen science. We then use the findings of a scoping review to examine three main ethical and legal issues for using Internet of Things devices in citizen science.

Mobile learning is learning across multiple contexts using smartphones and tablets, digital watches and fitness bands, wearable tags, and other more specialized devices. In educational applications, these devices are often linked together through the Internet or Bluetooth wireless technology, supporting collaboration and interaction. Mobile devices support seamless learning by extending learning beyond the classroom into everyday real-world experience. Mobile devices support the blending of the “formal learning” of the classroom with “informal learning” that takes place at home, in museums, or with peers. Mobile devices support personalized learning, and yet when networked together they can at the same time support collaboration and group learning. Many mobile devices generate large volumes of data from each student’s device, supporting learning analytics applications.

Digital technologies show great promise for moving clinical trials from using in-person approaches that have perpetuated long drug trial timelines, biased sampling and high costs. A review of the current state, however, reveals that technology use has been largely limited to replicating known methods and/or applied to small study samples. Full realization of the potential will require significant investment in validating digital signals into novel metrics fueled by advanced computational methods. These steps, however, will require regulatory guidance, as well as considerations regarding data security and future proofing against rapid technology obsolescence. Despite these challenges, the end-to-end virtual clinical trial is possible today.

This chapter looks at the future of people assessment. Like many other areas of business there have been many, and rapid, technology-led changes. There are questions about who are or should be assessed; when and how they are assessed; the cost and legal changes in assessment; and how data is stored. The quiet world of academic-led assessment and testing has been ‘invaded’ by people in business eager to sell psychological testing and assessment to a much larger market. Inevitably there are enthusiasts and sceptics: the former claiming how AI computer and neuro-science technology will revolutionise the ease, cost and accuracy of assessment, while the sceptics argue there is still very little evidence for these claims. It certainly is a ‘good time to be alive’ for those interested in people assessment.

This chapter focuses on the international extension of modern intellectual property, highlighting America's place in a regime of intellectual property that today is global. We trace the foundations for this global regime in international treaty frameworks, focusing on the legal parallels between treaties and contracts, as instruments of legal power. We briefly sketch the twentieth century developments of intellectual property law in the U.S., highlighting the juristic "solicitude" that is shown to intellectual property in U.S. lawmaking and international diplomacy. In the wake of World War II, the U.S. has used its position of global economic power to solidify commitments to intellectual property in a legal framework for trade relations that constitutes a super-national organization, the World Trade Organization, one that has facilitated global convergence in intellectual property law. New dangers and challenges are facing us today, in this globalized legal order, with the rise of artificial intelligence, and with patent claims extending very deeply into the social dimensions of human life, through computer-implemented inventions.

Progress to date has varied between different sub-disciplines and this final chapter will touch on common themes throughout. Psychology as a discipline has much to gain from the digital age, especially following the mass adoption of smartphohes. Software development is an entire discipline within itself, but even comparatively simple smartphone apps that collect minimal data can be highly revealing of everyday behaviour. However, we face numerous challenges that go beyond technological development. Some of these issues pretain to theorising and replication, while others concern the scientific climate in which we operate. Most of these issues are not unique to research involving new technology, but they become more apparent as the speed of innovation accelerates. As a result, we appear to carry very little understanding forward to the next mass-adopted innovation.

By reflecting on past successes and failures, this chapter provides guidance on how psychological research can become more productive and break free from tired cycles of research. More importantly, if psychological science can re-align existing priorities and embrace the digital age, it has nothing to lose and everything to gain.

Smartphones and associated wearable devices have gained a greater prominence directly within health psychology. Not only can such devices track health and answer a variety of research questions in relation to physical and mental health, but real-time feedback can also be augmented to support subsequent behaviour change interventions. There are literally 1000s of smartphone health apps that aim to change behaviour. Hence, health psychologists have been heavily involved with the design and testing of interventions (Ellis and Piwek, 2018). In addition, there are increasing numbers of interdisciplinary groups who focus on such interventions. However, while the research landscape is now littered with many well-publicised successes and failures, very little is known when it comes to understanding why such results are occurring even for users who engage with a long-term smartphone/wearable intervention. Despite having plenty of scope for development, progress has stalled because existing adaptations continue to be poorly designed from both a theoretical and patient perspective.

With these issues in mind, this chapter points towards where psychological research is using smartphone sensing methods that can quantify health related behaviours on a larger scale. It also considers how psychology can make a key contribution in the future. For example, while the process of behaviour change remains complex, additional research is urgently needed to understand how individuals, devices, and related technologies can be designed and implemented if interventions are to become widespread across healthcare systems in the future (Piwek et al., 2016; Ellis and Piwek, 2018)

Psychological concerns around the impact of smartphone use tends to overshadow all other threats and concerns around digital spaces. This chapter critically considers research that has associated smartphone use with negative traits and behavioural outcomes. In contrast to other areas of smartphone research, and while many prominent academics have argued that smartphone data have a great deal to offer as a research tool in psychology, comparatively little research utilises objective smartphone usage data in relation to potential harms (Andrews et al., 2015). For example, the majority of existing research tends to rely on self-report alone when to quantifying ‘addictive’ behaviour. A frank discussion regarding similar issues of measurement would help the field move forward more quickly, improve its visibility and generate additional impact from a policy and practitioner perspective.

This chapter provides a timely narrative and critically considers where smartphone research within psychology has advanced in a variety of innovative ways, but also where it is has been slower to innovate both theoretically and methodologically. While some progress has been made regarding the genuine impacts of general technology use, this chapter will conclude by reminding readers that smartphone addiction provides an excellent example of where the field has to embrace the abilities of other disciplines if it is to make additional progress.

Cognitive science has often considered the impact of new technology on childhood development and the ability of digital devices to disrupt attention and cognitive processes. In contrast, the same area has successfully implemented smartphones into existing research practices, which perhaps reflects the methodological training many psychologists working within cognition and perception receive as part of their doctoral studies. For example, standard psychophysical experiments and reaction time tasks have been ported to a variety of smartphones using their built-in web-browser. This has been extended to include the large-scale gamification of traditional cognitive tests (Wilmer, Sherman and Chein, 2017). Combining advanced graphical abilities, a number of cognitive tasks have been validated to assess working memory, attention and decision-making abilities (Paletta, 2014).

This chapter points towards a future whereby cognitive psychology could become the first sub-discipline within psychology to develop a complete portable laboratory. This would, in turn, reveal any casual links between technology use and cognitive functioning which continues to allude existing research paradigms

Social interaction and the subsequent generation of interpersonal relationships appear to be inherently linked to emotional well-being. Smartphones have increased an individual’s social footprint while remaining the primary way in which people communicate with each other via social media, phone calls and text messages. However, many researchers have questioned if the same technology is simultaneously preventing us from developing meaningful relationships?

At the same time, other research has started to focus on a variety of popular smartphone applications that have changed the way modern relationships are formed and maintained (e.g., Tinder, Snaphat). This work typically considers a participants’ own experience or data derived directly from applications themselves (Davidson, Joinson and Jones, 2018). However, it is also possible to explore real-wold social interaction via the variety of on-board sensors, which can also reveal group dynamics within the real-world (Piwek, Ellis and Andrews, 2016). For example, Bluetooth and location data derived from appropriate sensors can be used to infer when someone is meeting with others who are also running similar software of their device. This has also been referred to as Social fMRI whereby researchers can quantify social mechanisms in the real world (Aharony et al., 2011).

Smartphones can also generate data within other domains that psychology could take advantage of in the future including “smart cities.” For example, tracking and understanding individuals’ mobility using GPS location can allow for the forecasting of future movements. While smartphones have dramatically changed how large sections of society form and develop new relationships, this chapter points towards how the same technology can be leveraged further to understand how relationships and groups rapidly shift between offline and online contexts in the digital age.

Much of the research discussed previously will have relied on participants consenting to have data collected from their smartphone. However, smartphones continue to pose an inherent security risk within and beyond research. They also provide ways in which criminals can operate and communicate across larger networks. Despite the majority of devices holding large quantities of personal information, many people continue to ignore advice when it comes to securing their device. This is particularly problematic when it comes to carrying out tasks on unsecured networks. Malware can also gain access to a smartphone and compromise its function.

The popularity of smartphones provide another digital outlet for illegal data capture and this chapter will consider why, despite multiple security concerns, the majority of smartphone users and even large organisations are unable to recognise the importance of developing sound security practices. A second stand considers how psychologists and software developers are attempting to improve the security of existing devices and encourage security focused beahviours. While data in the digital age can be tremendously valuable for research purposes, developing good practice remains essential when developing software that collects sensitive data from smartphones and associated devices.

While psychologists agree that individuals differ from each other on a variety of traits (e.g., personality), the theoretical and methodological assumptions used to develop pen and paper psychometric tests have failed to keep pace with recent computational developments that utilise digital traces to infer information about individuals and the world around them. For example, while self-report assessments are designed to predict behaviour in the absence of any real-world measure, digital devices (e.g., smartphones) have facilitated the measurement of many real-world outcomes (Piwek et al., 2016). Even the purchase of a specific device can reveal something about the individual behind the screen (Shaw, Ellis and Ziegler, 2018). Smartphones could therefore lead to a step change in how we study and conceptualise a variety of individual differences. This is particularly pertinent when it comes to understanding personality traits (e.g., levels of extraversion – a measure of sociability) that are automatically deployed in new situations seamlessly and non-consciously (Roberts and Hill, 2017).

A number of studies using smartphones have correlated data from these devices with traditional psychometric tests. However, following a brief review of this work, this chapter will question how much progress has been made in this domain. There remains a general consensus among many social scientists that, while traditional psychometric measures are far from perfect, they are the only option available. This chapter will challenge that assumption however, data derived from smartphone sensing may ultimately support the notion that existing psychometric tools remain valuable and reinforce existing conceptualisations of standard personality models.