Research universities reside within a broader environment and are influenced by a host of external global factors that are beyond our control. These factors shape the topics, methods, funding, partnerships, and other resources important to conducting research.

The objective of this chapter is to identify these issues and how they might influence what we work on, how we work on it, and who we partner with. While these external forces may lie outside our control, by identifying these trends and potential future scenarios, we can proactively plan how we will engage, respond, and influence “The World Beyond.”

This chapter organizes these external forces through the following four forces and trends:

• Values: Normative sociopolitical factors that influence who we are and how we conduct research.
• Challenges: Systemic stressors that motivate responsive, real-world research.
• Innovation: Pivotal technologies that allow us to communicate and create new ways of doing research.
• Policy: Factors that influence the resource availability required for collective action.

This chapter also includes several “View from 2045” vignettes. These vignettes envisage future scenarios driven by the convergence or realization of these forces and trends.

2.2 Values

Value systems provide standards for evaluating actions, justifying opinions and conduct, planning behavior, selecting alternatives, engaging in social influence, and shaping how an individual or organization portrays itself to the world [Hebel 1998]. They vary across groups, from individuals to entire cultures, and present in hierarchies that may be dynamic in time. Such hierarchies arise from aspects of the human condition that are in natural tension, as indicated in Figure 2.1.

This figure depicts both a cluster analysis of different value categories from a values survey across 20 countries [Schwartz 1992], and these value categories are more compactly organized in a structure of hierarchies of competing tensions [Schwartz 2016]. For example, different societies and groups prioritize personal fulfillment and social unity differently, or have different propensities to accepting new ideas relative to conservatism.

These values become fundamental drivers in how research is prioritized, resourced, conducted, and evaluated. Values shape the economic and policy environment researchers compete within for funding, for example favoring near-term applications versus forward thinking discovery, or winner-take-all grand challenges versus broadly distributing resources. National security priorities are equally value driven, whether defensive in nature or for the projection of power. Tension around these questions is inevitable. Nonetheless, organizations typically develop a set of shared core values, which summarize these normative, foundational beliefs. For example, core values shared across university research enterprises include “we tackle complex societal challenges” and “we empower and support all researchers.” At Georgia Tech, these core values are further expanded to include “students are our top priority,” “we strive for excellence,” “we thrive on diversity,” “we celebrate collaboration,” “we champion innovation,” “we safeguard freedom of inquiry and expression,” and “we act ethically.” The rest of this section provides several examples of how values drive research trends.

Tackling Complex Societal Challenges

Universities are at the core of innovation, both through their generation of new knowledge and unique role in developing and deploying minds that can solve the complex issues facing the world today [NRC 2014]. Government and industry rely on the activities of universities as the emerging “innovation hubs” of science and technology in the U.S. [NASEM 2019]. This perception registers at every level of society, as citizens overwhelmingly see universities as the engines of discovery for strategies to solve the world’s most pressing concerns [UCA 2020].

Perhaps most saliently, universities exhibit reflexive interests in research that has a high positive impact on local, regional, and global communities. As seen recently, numerous universities mobilized research around the containment and mitigation of the coronavirus pandemic [GIT 2020]. Students themselves are demanding interdisciplinary training in support of “Public Interest Technology,” defined as technology that “adopts best practices in human-centered design, product development, process re-engineering, and data science to solve public problems in an inclusive, iterative manner — continuously learning, improving, and aiming to deliver better outcomes to the public.” [Doran 2020] In all, university values reflect accelerating momentum toward research that positively influences an increasingly interconnected world.

Sustainability

A broad concept of sustainability for global development is outlined in the United Nations Sustainable Development Goals [SDG]. Research driven by sustainable development includes an analytical framework to understand our planetary challenges, as well as frameworks to translate values into action. As Jeffrey Sachs argues: “Sustainable development is a way to understand the world as a complex interaction of economic, social, environmental, and political systems. Yet it is also a normative or ethical view of the world, a way to define the objectives of a well-functioning society, one that delivers well-being for its citizens today and for future generations.” [Sachs 2015]

The fundamental role of normative values in driving approaches for sustainability has been emphasized by Charles Mann in “The Wizard and the Prophet,” [Mann 2018] who contrasts two competing value frameworks. One approach for sustainability emphasizes a societal response that seeks to preserve, reduce our impacts, and establish ourselves within a natural order that is imposed upon us. A different approach sees the solution lying in innovation, technology, clever management, and reshaping nature around human needs. These are not either/or questions but they are normative ones, where one’s fundamental approach is based upon deep-seated moral values about the world and how we should interact with it.

Social Impacts of Technology

Technology is not “neutral” and has a range of impacts on society. Emerging technologies have large societal impacts, whether they are gene editing, automation, artificial intelligence, or influence techniques. Digital and networked technologies, from personal to assistive, and even medical, are becoming pervasive; new algorithmic processes take advantage of both the massive data now available from such devices as well as the intimate relationship individuals have with these devices and services.

As highlighted in the documentary The Social Dilemma (2020) [Orlowski 2020], social media was originally imagined by developers as a force for the consolidation of community. But as we have seen, it is equally well suited to pervasive marketing, psychological manipulation, and digital surveillance, allowing like-minded individuals to self-segregate into isolated information environments, a phenomenon commonly referred to as “information bubbles.” The commercial advantage afforded by these technologies is provided through the hyper-specific personalization of content to each individual user, allowing for the monetization of targeted, behavior-changing content. This same specificity allows for previously unavailable inroads into changing values and behavior around commercial and political matters.

Equity and Social Justice

Technology can either mitigate or promote inequity, as well as rectify or amplify historical injustices. Understanding these influences is both a research topic itself, as well as one where research institutions will face value-centric organizational challenges due to the tensions that arise from the categories in Figure 2.1 in order to sustain the modern research enterprise that upholds core values, particularly diversity and empowering and supporting all researchers. (See Chapters 3 and 5 for more detailed discussions.)

A variety of challenges at the local, national, and global levels will profoundly influence the research university environment and motivate research that is done and how it is done. While our list is far from exhaustive, we describe a few of these issues here to provide context.

Climate Change/Sustainability

Climate change is leading to a variety of challenges, including rising sea levels affecting coastal areas, desertification, and changes in local temperature and water patterns. Population growth, deforestation and biodiversity loss are other stressors that challenge sustainability of the planet. In addition, global decarbonization initiatives are changing the geopolitical landscape and international relations as oil and gas become less connected to the power of countries and regions, as well as sources of jobs.

Aging

Fertility and mortality rates tend to decline as countries develop economically, causing a shift in populations toward older people. This affects the direction of innovation, research workforce, and how public funds are distributed, which diseases government and corporate agencies focus on, housing, and healthcare. For example, a health research agenda increasingly focused on aging-related illnesses, fewer people of working age, and the increasing need to care for the elderly will influence new research and technologies in robotics, telemedicine, and artificial intelligence.

Sociopolitical Factors

Demographic shifts, the rise of new economic players, and increasing environmental pressures will continue to influence how regions, nations, ethnic groups, age groups, cultural affinity groups, or a range of other groups will self-identify and organize. The rise of nationalism could make global research collaborations more difficult and local research more burdened with oversight and process. Simultaneously, world leaders are also recognizing the need to come together to solve common global challenges, such as climate change and sustainability.

Political, Urban/Rural, and Regional Differences

Notable differences exist in how some key social trends are playing out across urban and rural communities [PEW 2018]. For example, urban and suburban counties are gaining in population and diversity while people leaving rural areas outpaced the number of those moving in. There are significant gaps in measures of economic well-being and resource allocations across urban/rural counties. Those differences extend to politics and perspectives. And these factors influence consensual democratic decision-making, views of our national identity, and the role of science and other expert knowledge in decision making and prioritization of research.

Epidemics and Pandemics

Large-scale outbreaks of disease, with accompanying societal disruptions, have occurred globally throughout history. However, new viruses continue to emerge, and whether the next pandemic occurs in a few years or a century, the repercussions of Covid-19 on globalization, research, and other areas will persist for many years to come.

Security

Security threats put at risk the fundamental bases upon which individuals and societies rely. The development of nuclear weapons in the 1940s profoundly altered the global security landscape. Since then, a host of additional, similarly global challenges provide a backdrop for national security and research, including cybersecurity and biological security.

Public Opinion

Recent events have shown how rapidly public opinion can be energized for or against an idea on a global scale. The fact that there is no central control of information means that vast populations can be reached immediately with specific messaging to cause rapid and extreme public response. In the coming years the desire by various groups to leverage this power will create more instability, which will in turn drive different research directions within two extremes: exploiting this power to cause instability versus responsible research to prevent such exploitation.

Technological advances will continue to drive important changes to the way in which research is done, the research topics that are investigated, the future workforce, and societal structures as a whole. Below are several illustrative examples.

Artificial Intelligence and Machine Learning

Artificial intelligence and machine learning are increasingly used in a wide array of applications, including scientific discoveries, biomedical technologies, construction, industrial control and assembly, transportation, and information and communications technologies. Artificial intelligence is capable of guiding self-driving cars, performing automatic translation, identifying images, exploring massive sets of data, and automating a host of other activities. To a large extent, recent advances in machine learning have improved the ability to gather and process massive data sets rather than creating breakthroughs in understanding the nature of human intelligence. Nonetheless, artificial intelligence will continue to influence nearly all disciplines, including healthcare, transportation, and manufacturing, and has the potential to spur the development of entirely new industries.

Data Science and Engineering

Broad deployment of data and image collection devices, alongside the 5G networks enabling rapid data collection, will continue to increase the amount of raw information gathered by society. Privacy concerns may lead to regulation that could impose burdens on those seeking to use data for research, as has already happened with HIPAA restrictions on healthcare data, the use of data involving minors, and so on.

Research in data collection, storage, and manipulation will become increasingly important to a broad family of research categories. Policies around archival storage, remote access, cross-institutional sharing, data retention, and related issues will need to evolve rapidly, and coordinating those processes across various levels of control (institution, university system, city, state, federal, and sovereign nations) is likely to be challenging.

Virtual Labs and Online Collaboration

Collaboration tools and connectivity have matured enough so that it is possible to be effective in a remote environment for many job types. These tools and processes will improve, making remote collaboration even more efficient. As more research is done with data and computers, the physical presence of a lab becomes less important for a growing family of research topics. This will drive laboratories that can configure remote access to lab equipment and make it available to a wider group of researchers, exemplified by Georgia Tech’s Robotarium.

Once researchers can access labs remotely, research social networks with prearranged access to specific distributed equipment might emerge as more valuable than any physical campus location.

A potential benefit to the broader deployment of remote access and online collaboration tools is one of accessibility for researchers who otherwise would not be able to access them, such as those in developing countries, or who have disabilities or are caregivers. Moreover, increased digitization of resources, including automatically generated transcripts of conferences or conversations, would improve accessibility.

Simulation

Practical considerations impose limits on what kinds of experiments a researcher can run safely or within cost, but new simulation technologies, offering higher fidelity at reduced costs, are rapidly mitigating many of those concerns. For example, research on the effects of distractions while driving in traffic would be dangerously impractical in the real world. Using a realistic driving simulator, however, a variety of experiments can be carried out at minimal risk, and in a much wider range of scenarios.

Virtual and augmented reality (VR/AR) technologies may also play a related role. If VR/AR hardware continues to decrease in price and increase in fidelity, and consumer adoption of the technology ramps up, the next generation of researchers may be as comfortable working in virtual environments and with other VR/AR-based tools as the current generation is with email or spreadsheets.

Computing

The speed and size of high-performance computing continues to grow, enabling realistic calculations of a host of phenomena. Computational methods are increasingly shifting the nature of the research from reductionist methods to data exemplified representations. Several other technologies have the potential to reach breakthrough status soon.

For example, as quantum computing and communications mature, they will push hardware performance into an entirely new realm governed by the rules of quantum mechanics and creating new concepts for algorithm development. Algorithms and hardware that properly leverage quantum advantages will outperform previous methods in some domains, potentially allowing for detailed design processes that are currently impossible with classical computing models, as in molecular and biological engineering and large-scale simulation.

National and global politics play a pivotal role in defining the research environment. International research projects and initiatives will drive large-scale science and engineering programs and affect priorities at the national level. These will create a category of drivers that will create opportunities and challenges for university research programs.

Government Research Investments and Industrial Policy

Over the last two decades, global R&D investment has tripled, surpassing $2 trillion in 2018 [Flagg 2020]. The U.S. share of this investment has diminished from 69% to 28% since the 1960s, as increasing global investment has outpaced U.S. investment. The U.S. and China together account for more than 50% of these expenditures. The remainder of the R&D funding comes from other countries shown in Figure 2.2.

Globalization and proliferation of technology to peer, non-peer, and non-state actors means the U.S. can no longer rely on having and keeping the technological advantage.

In recent years, consolidation within the research and development industry has led to a winner-take-all model. As an example, in the aerospace and defense industry, four contractors — Lockheed Martin, Boeing, Northrop Grumman, and Raytheon — were formed from 51 companies in just a couple of decades. Historically, the concentration of companies reduces competition, which in turn leads to further concentration [GAO 2019]. Similar examples occur across the tech industry, including Facebook acquiring Instagram, and others. This principle maps to funding profiles as well, which drives funding toward a smaller number of larger contracts. This trend is difficult to reverse; innovation builds intellectual capital and establishes relationships that further perpetuate it.

Human and Capital Resources

The concepts and skills associated with a STEM-trained workforce are central to competitive positioning in applied research and technology-driven industries. As such, there is a positive correlation between economic activities around technological innovation, the promotion of STEM fields, and pursuit of advanced research capabilities.

U.S. and European research centers have depended on international graduate students as part of the innovation engine. Asian economies are undergoing major growth and may disrupt the supply chain of top-tier researchers who otherwise might have come to the U.S.

In the past 30 years, several Asian countries, including China, South Korea, and India, have followed the examples of Japan and Taiwan to move to the forefront of research innovation and technology development. Many of the leading scientists and engineers in this cohort were educated in, and developed groundbreaking research results under, the U.S. research enterprise. They have created a number of intellectually fertile and technologically productive innovation centers around the globe. These centers already attract world-class talent and can compete with the best U.S. research institutions for top-tier researchers.

As the local research environments mature in these countries, the demand for education and research from U.S. universities may decline, and lead to a fundamental shift in the relative distribution of global research resources. The U.S., for instance, has fewer STEM graduates than China, which had 4.7 million graduates, and India, with 2.6 million, in 2016. The U.S. had 600,000 [WEF 2016]. One driver of this trend is the so-called “youth bulge” in which “nine out of 10 people between the ages of 10 and 24 live in less developed countries” [Modley 2016]. This means the market of new students, engineers, and researchers will primarily come from less developed countries.

This could cause a pull of corporate research and recruiting dollars away from more developed countries.

Geopolitical Tensions

Geopolitical tensions and competition profoundly affect research priorities, such as the space race in the 1960s or artificial intelligence today. Moreover, there are inherent conflicts with the open and free development of ideas and innovation, and efforts of countries to restrict those innovations to in-country. The U.S. has implemented policies to protect federally funded and commercial research from information extraction attempts. The cooperative international research process is strongly influenced by covert and overt espionage activities [Wray 2020]. One example is China’s talent and recruitment program called the “Thousand Talents Program” [Portman 2019], through which China encourages researchers in STEM fields to extract knowledge and innovation from other countries [Wray 2020].

Resource models that enable research and development for technology innovation are evolving. For example, the U.S. relies more heavily on commercial interests and decentralized processes to drive research, especially in artificial intelligence and quantum systems, while European and Asian nations favor different balances between public and commercial interests [Lee 2018], such as the role of public and private institutions in funding research or managing privacy.