Learning & Working in 2030

LEARNING & WORKING IN 2030

Southern New Hampshire University FUTURES PLANNING STRATEGY

We see futures forecasting as A systematic, participatory, and multidisciplinary approach to explore mid-to long-term futures and drivers of change.

PREPARING FOR THE FOURTH INDUSTRIAL REVOLUTION

At Southern New Hampshire University (SNHU), we strive to transform the lives of our learners through affordable, high-quality, and innovative pathways to education. In order to begin strategically planning and building for the learner of 2030, we must create a shared vision of what that future might look like. As a university, we will continue to challenge the higher education status quo as we work to serve the learner of 2030. This is a function of the fifth commitment in the SNHU 2018-2023 Strategic Plan, which conveys our strong determination to create the capacity and foundation on which to build the 2030 learning ecosystem.

Looking to the future, we believe it is critical to rethink our approach to learning and learner success by placing bets on future scenarios. Building toward scenarios allows us to imagine multiple futures that the University might find itself a part of. By analyzing observed market signals, macro-trends, and insights from emerging technologies, we can begin to plan for the possibilities our learners might face. Through partnerships, foresight training, and extensive research, the University has selected five future forces and six challenges that we believe will shape the scenarios in which we may be asked operate and serve our learners in the future. The rest of this book will describe these forces and challenges, how our learners might navigate this new future, and how the University is preparing to support, or already supporting, these learners. This forecast is to provide a blueprint for SNHU and higher education in the Fourth Industrial Age that inspires, instigates, and encourages conversations about the future of learning and working.

Why did we select the year 2030? A central component of this work is the development of a futures planning strategy for the 2020-2030 time period. We benchmarked the year 2030 as the “over the horizon” date for this work. The critical technology that will impact the future of learning and working in the next 1015 years has already been invented but is not equally distributed. Only one or two major revisions to the Higher Education Reauthorization Act could occur during this time, and while being far enough away to not disrupt our operating model tomorrow, 2030 is close enough that we must pay attention to the current signals, forces, and trends at hand.

Through three years of internal and external research across diverse industries, attending scenario- and persona-building trainings, collaborating with foresight practitioners and targeted focus groups, we have developed our 2030 Forecast to inspire, instigate, and drive conversations at SNHU about the future of learning and working for our learners, staff, and faculty.

The Fourth Industrial Revolution refers to how technologies (artificial intelligence, internet of things, etc.) will merge with humans’ physical lives. The Fourth Industrial Age comes out of the Digital Age and describes the imminent next stage of human civilization.

CURRENT CHALLENGES OUR LEARNERS FACE

Learners pursue education with the hope of improving their lives, but are faced with obstacles, both direct and indirect, that often appear insurmountable. Since our success is defined by our learners’ success, the challenges they face are also our challenges. In our 2018-2023 Strategic Plan, we identified the following as primary challenges our current and prospective learners face.

Challenges facing our current and prospective learners today include:

Shifting Regulations

Changes in regulations around financial aid, loan forgiveness, and immigration visas create hesitation for enrollment as learners may wonder if they will qualify for enough aid each year, if their immigration status will be approved each year, and if their federal loan forgiveness program will still exist when they are finally eligible for forgiveness.

As our learners are wondering whether their visa status will remain valid or if their budgets will make it out of the red, these regulatory shifts hit our learners at the most personal level.

Economic Barriers to Entry

The cost of higher education tuition has risen over 200% in the last 20 years with the cost of textbooks close behind, far outpacing the growth in cost for healthcare.1 This has led to an increase in graduates with extensive student loan debt, with 3,000 Americans defaulting on their loans on a daily basis.2 This is a barrier to self-actualization for our learners.

Need for Flexible Pathways

Numerous priorities compete for our learners’ time: school, work, family, hobbies, etc. Education adds to an already demanding schedule. For some, this provides seemingly immovable barriers to enrollment. However, higher education can rethink what is possible by offering flexible options for pursuing academic pathways. Learners have responded to this opportunity with increasing enrollment in distance education — over a million people in just four years.3

The continued exploration and permeation of flexible learning pathways will grow increasingly essential for higher education’s existence.

Disruption from Automation

While automation has created numerous new jobs, about half of existing jobs in the US will either be changed or fully replaced by automation and this will require a re-scoping of thousands of occupations.4 Institutions will need to prepare students for careers that require a creative mindset and the mental flexibility to reinvent or discover new ideas. Our learners will work alongside intelligent machines, often in jobs that do not exist today or jobs that have been thoroughly reinvented.

Public Trust in Higher Education

There is a gap between what education institutions and the public prioritize in higher education; More than 70 percent of institutions believe providing a well-rounded education is more important than developing designated career skills, while 50 percent of the public emphasizes learning specific tools and resources to succeed in a career as taking priority over having a well-rounded education.5 Public trust in higher education has eroded, which increases the number of prospective learners and their support systems who think that higher ed is not worth the time and monetary investment.

Climate Impacts

Large parts of our planet will not be inhabitable by humans if climate change impacts are not mitigated. Food production will be impacted, major cities will run out of water—or be under water, and the ecosystem will begin to break down. This will compromise a significant portion of our learners’ physiological needs for quality air, food, water, and shelter and make higher education truly an afterthought.

Throughout this document we use the term VUCA, which describes the volatile, uncertain, complex, and ambiguous world of today and tomorrow. Using a VUCA lens allows us to better imagine the challenges and opportunities facing both current learners and the learners of 2030.

TRENDS SHAPING THE HIGHER EDUCATION ENVIRONMENT OF 2030

Given these current challenges facing our students and in order to remain relevant in an uncertain future, SNHU must be agile enough to respond, adapt, and transform with the ebbs and flows of forces and challenges beyond our control in a “VUCA landscape.” US national security experts introduced the term “VUCA” to describe the volatile, uncertain, complex, and ambiguous world resulting from the end of the Cold War. The acronym was popularized following the terrorist attacks of September 11, 2001. VUCA is now used outside of the military to describe the new normal, where factors beyond one’s control lead to highly variable and irregularly timed changes that could be good or bad.

Internet. The global paradigm of the 21st century, though, is marked by niche and local economies; division and isolationism; and the rapid expansion of economies in developing nations in Asia, South America, and Sub-Saharan Africa.

Imagining the Challenges and Opportunities Facing Both Current Learners and the Learners of 2030

Full-time work will be available to fewer, while part-time “gigs” and entrepreneurial opportunities will balloon, creating both higher job flexibility and insecurity. With a global population increase of a billion people, innovation will spring from places outside the usual suspects of San Francisco, Tel Aviv, Shenzhen, and Bangalore—and from less commonly expected places like rural communities and refugee camps. The dire impacts of human and natural disasters, such as the 2019-2020 Australian bush fire season and the COVID-19 pandemic, will only expedite this process.

Pivotal events shape the future and world outlook for each generation, consider the following:

• Gen X – Cold War

• Gen Y – 9/11/2001 Terrorist Attacks on US Soil

• Gen Z – Financial Crisis of 2008

• Gen Alpha – COVID-19 Pandemic

We are using the VUCA lens to better imagine the challenges and opportunities facing both current learners and the learners of 2030. We are imagining what higher education will need to be in order to serve the learners of 2030 ranging from Generation Alpha to Baby Boomers. More than any generation before them in modern history, Gen Alpha learners—the children of Millennials born from 2007 to 2025—are living in a historically unprecedented world. We must strategize and prepare for teaching them in a world dissimilar from the existing higher education landscape.

The globalism of the late 20th century led to unprecedented degrees of open access, free trade agreements, global supply chains, and interconnectivity through the

Across all industries, the time-frame between the conception of an idea and its implementation will shrink, simultaneously creating new opportunities and opportunities to be “left behind.” The world of learning, then, will increasingly shift to address the “iterative” model of its surrounding environment. Successful institutions will evolve into hubs of ongoing learning and evaluation, treating themselves as largescale collaborations that include students, professors, and faculty. SNHU will need to establish clear, ongoing avenues to generate, gather, and integrate insights across its entire population. This will involve an attitude that regards the work (and friction) of innovation as opportunities to best serve learners. By carefully embracing emerging practices (peer-to-peer learning) and technologies (synthetic colleagues), SNHU stands to offer the learners of 2030—be they 16 or 80—educational experiences that meet them in the VUCA world where they live.

MAPPING FUTURE FORCES

MAPPING FUTURE FORCES

We worked with Institute for the Future (IFTF) to analyze current and historical trends and signals of innovations and disruptions occurring today. We worked with IFTF to apply foresight techniques toward the creation of five “future forces” for the world of learning and working in 2030. With each future force, we also identified a corresponding “zone of innovation” that is embedded with opportunities and challenges, as well as a fictitious persona of a person in 2030 experiencing the impacts of the future force in a “day in the life” narrative.

In order to ultimately produce robust and holistic possible future narratives, we examined signals and future forces through the STEEP framework, which analyzes the social, technological, economic, environmental, and political factors we believe will be significant to workers and learners in 2030.

We then conducted a series of focus groups with different stakeholders across the SNHU ecosystem to ensure a “user-centric” approach to writing about the future. The focus groups allowed us to deduce which signals resonated with each group by understanding what emotion (i.e. anxiety, excitement) the signals elicited in participants, develop an understanding of how they felt their work would or would not be impacted by future forces, and test the language that most effectively built connections and understanding of the future forces.

How do you have the courage as an organization to divert resources to what’s new?

How do we let people know that they should do that in the name of improving EX and CX?

— Dave Carter, Director, Academic

Advising

FUTURE FORCES & ZONES OF INNOVATION

In order to build our portfolio of possible futures, we derived five future forces by scanning current and historical trends in the world of learning and working, describing the key zones of innovation corresponding to each future force, and then identified signals that exist currently that indicate how those challenges are being addressed today or may be addressed in the future. Through this process, we present the following five Future Forces and Zones of Innovation which may transform the future world of working and learning.

Future Force:

A Future Force is a pattern of change that is likely to disrupt today’s way of doing things

Intelligent Systems

Technological systems that can perceive, respond to, and learn from the world around them

Distributed Computing

Use of information management systems to manage disparate content, often through decentralized networks that allow for collective ownership rather than centralized systems that rely on intermediaries

International Markets

Evolution of how we define demographics on a global scale

Platform Economies

Digital market environments as a location for individuals to buy, sell, and trade goods and services

Personal Economies

Human-Machine Collaboration

Human beings working alongside intelligent machines

Zone of Innovation:

Shapeshifting Organizations

Business organizational structure where classic hierarchies are replaced by projects and priorities that rise and fall in importance across the organization; requiring data to be held on an accessible, distributable network

Market environment where individuals can offer their own goods and services in the ondemand marketplace

Spectrum Demographics

Range of classifications and communities for individuals and groups outside of traditional binary classifications or categorizations

Futures Literacy

Competency in using digital simulations of the current environment

Areas of potential challenges and opportunities for the future as a result of the corresponding future force

Masterminds of Reality

Applying futures literacy simulation tools to reimagine reality and the future through forecasting

Terms to know

For each future force and corresponding zone of innovation, we apply a possible scenario indicated by signals that exist today to build a Day in the Life narrative of a persona encountering the challenge and/or opportunity from the Zone of Innovation.

FUTURE FORCE: A Future Force is a pattern of change that is likely to disrupt today’s way of doing things

ZONE OF INNOVATION: Areas of potential challenges and opportunities of future as a result of the corresponding future force

SIGNAL: A present-day innovation or disruption that has the potential to grow in scale or geographic reach

PERSONA: Personas are tools we use to make observations and insights about individuals and groups vivid, testable, and durable so that we can think more clearly and expansively about those we serve and how to serve them

DAY IN THE LIFE STORY: A coherent description of a persona encountering a scenario highlighting its main characteristics and dynamics, the relationships between key driving forces, and their related outcomes in a routine, average moment of time in the future

For a full list see Handy Guide to Futures Terminology on p.37

It’s really easy to identify trends; it is really hard to come to the table and place your bet.

INTELLIGENT SYSTEMS at SNHU in 2020

• SNHU’s Global Campus is using Sense, an AI software solution, to help students in introductory coding courses. By uploading a dataset of student submissions, SNHU is training Sense to be able to provide instant feedback that helps students identify errors in their code. In turn, this process allows instructors to identify key coaching areas and the University to identify additional learning supports for students.

• SNHU is exploring uncharted territory by applying AI technology to learn and mimic an instructor’s unique grading and feedback styles to increase engagement and enhance learner-faculty interactions. By automating the scoring mechanism while still giving instructors the option to have a final review of the proposed grade, faculty will be able to allocate more time to meaningful, uniquely human interactions with their learners.

INTELLIGENT SYSTEMS Deployment of

Intelligent systems refers to the widespread deployment of tools such as artificial intelligence (AI) to increase efficiency within companies and enhance consumer goods and services. This will require our learners to prepare for human-machine collaboration, which describes working alongside intelligent machines in the workplace. Humanmachine collaboration will enable individuals to hone their uniquely human skills such as creativity while increasing productivity in the workplace through human augmentation via technology, allowing workers to focus on less repetitive tasks. By relying upon augmentation (instead of replacement), human workers are projected to increase both productivity and earnings as workers become more efficient, effective, and drive the work through new capabilities.

As MIT observes in “The Work of the Future: Shaping Technology and Institutions” (2019), the world is on the brink of a technological revolution in AI that is projected to transform our lives at a level similar to electronification, mass production, and telecommunications.6 This will change how we interact with the technology around us, and how the technology around us works for us. AI will redefine work, how we relate to each other, and how we relate

to ourselves. “Intelligent systems,” or systems that rely on AI, will weave themselves even more tightly into the fabric of daily life. Even though you might not think about it, AI and the subfield “Machine Learning” (ML), already power much of your routine, from Spotify playlists to recommended Google search results to recommended friends and romantic partners on apps. ML becomes an ever more integral part of our lives every day; it’s making its way into our homes, cars, hospitals, governments, educational institutions, and more. This will require a higher level of collaboration with humans and machines.

The rapid inclusion of AI technologies into our lives means that the workforce of the 2030s will involve a high degree of human-machine collaboration. This will bring about sweeping change to the notion of work and career. In some cases, whole jobs or industries will become automated, in others, whole new classes of jobs and industries will emerge—but what will be most common is that the interaction between human and machine will come to define many roles. This emerging relationship will reinvent the way we learn, the way we create value, and the way we build the world around us.

Digital agents like synthetic colleagues, virtual assistants, bots, and avatars will act on our behalf. Algorithms will make judgments, recommendations, and decisions about how we spend our time, money, knowledge, and social capital. Robots will perform both conceptual and physical tasks, often in partnership with humans. As the warehouse model of Amazon and Alibaba continues to drive the growth of ecommerce, we will see physical robots entering into the workforce that speed up logistics, production, assembly lines, and more.

Artificial Intelligence vs Automation

You’ve probably seen Artificial Intelligence “AI” and “Automation” used interchangeably. While they are similar there is an important difference between them.

For more information on AI and Automation see Handy Guide to Futures Terminology on p.37

2020 Signals of INTELLIGENT SYSTEMS

These signals are signs of future innovation and disruption for the trend of increased use of intelligent machines in the workplace and at home

Facebook begins using AI for suicide detection and prevention

A new chair in the dentist’s office gathers biometric data to communicate pain for patients

A new desk can identify stress and adjust lighting, imagery, and sound to improve mood ‘

Automated job screening systems force job seekers to learn new tricks to have resumes seen by real people

XAVIER

Looking to 2030, we see signals of Intelligent Systems and Human Machine Collaboration happening today. Using these 2020 signals, we applied foresight techniques to construct personas of 2030 who encounter mature versions of these emerging signals in a typical, daily life scenario in 2030.

MEET XAVIER, A LEARNER IN 2030

Name: Xavier

Generation: Alpha

Identifies As: Go-getter, Athlete, Vegan

Education: Just completed online bachelor’s degree in marketing

Work: Seeking entry-level employment

Challenge/Opportunity in Zone of Innovation: Finding meaningful employment

A Day in the Life of Xavier in 2030

Xavier is playing a video game that has access to not only his resume and relevant experience via platforms like LinkedIn and Upwork, but to games that serve to identify Xavier’s strengths in soft skills such as interpersonal communication, collaboration, and conflict resolution. This bot uses artificial intelligence technologies such as natural language processing and computer vision to gather vital data about Xavier, which will be used to align his skills and interests with relevant opportunities. In rare cases, his performances can even unlock a video interview with a prospective employer looking for a specific combination of skills and experience that Xavier matches.

At this particular moment in the game, Xavier is running into a roadblock that’s frustrating him. A notification pops up in his augmented reality glasses alerting him that his smart watch is sensing a surge in stress levels. His synthetic assistant, Zo, chides him and reminds him to drink a glass of water, meditate, or take a walk. Xavier’s willingness to address his stress levels in real time will also be logged for employers to evaluate.

Xavier has already built up a powerful knowledge base for employers to see his strength as a leader in groups of 3-6, notably his ability to develop and clearly articulate his goals—as well as growth areas when dealing with frustration when unexpected events disrupt his plans. Instead of having to tell employers what he believes his greatest weakness to be, he has voluntarily allowed them to access this information in specific detail through his participation in the game, as well as steps he may have taken to improve weak areas, demonstrated through data the bot gathers.

This “opt-in” view of his gameplay allows Xavier to not only demonstrate ideas, but to receive badges for achievements that live in his professional portfolio. Today Xavier is able to indicate that he is able to keep stress levels low during a surprise disruption in the game, earning him an improvement badge. Feeling satisfied with this accomplishment, he powers down the game. Having wrapped up a full day of job-seeking work, he decides to take a 15-minute walk around the block before getting to work on the market research gig he just landed yesterday. He’s hoping that getting some sunlight will energize him to knock it out faster than the projected 17 hours on the listing.

DISTRIBUTED COMPUTING

at SNHU in 2020

• SNHU’s Digital Credentials Lab (DCL) is clarifying, testing, and validating market demand for microcredentials to inform the University-wide strategy and business model. Microcredentials, also known as micros, are certified units of learning, short of a degree, that attest to learners’ knowledge, skills, and abilities. Instead of validating learning with a degree, learners will maintain their microcredentials on the blockchain, allowing learners to own their credentials without the intermediary of a traditional registrar.

• SNHU’s FEATuring You program, funded by a Google.org grant, connects opportunity youth with an employment opportunity through soft skills assessments and University-powered digital badges. Opportunity youth are typically 16-24 years old and are marginally engaged with school or work. There are over 4 million opportunity youth in the United States today. Connecting opportunity youth with badges demonstrating soft skills improves their likelihood to be hired, as 77% of employers believe soft skills are as or more important than technical skills for entry-level work.

Expansion of

DISTRIBUTED COMPUTING

Distributed computing refers to the use of information management systems such as blockchain to manage disparate content worldwide. This will require our learners to prepare for employment in shapeshifting organizations where classic hierarchical organizational charts are replaced by projects that rise and fall in importance across the organization, changing priorities on a regular basis. Shape-shifting organizations will secure more data on a distributed network and enable workers and organizations to refocus efforts toward more meaningful work.

Distributed computing, like Intelligent Systems, is driven by an increase in connectivity. For every 100 people globally, there are 106.4 mobile subscriptions, an increase from just 12 mobile subscriptions per 100 people in 2000.7 This global connectivity has already massively changed our world and society as we know it, and this will only continue as we look out 10, 20 years into the future. New ideas will continue to emerge from tech hubs like Silicon Valley, Tel Aviv, Shenzhen, and Bangalore, but with new communities able to participate on a global scale, we’ll also witness innovation springing

up from less commonly expected places, from rural communities to refugee camps.8

This increase in connectivity supports a more dispersed infrastructure and fosters the ability for distributed computing through the dissemination of information and data across multiple locations but with the ability to signal each other. For example, blockchain is an example of distributed computing that allows power and value to be stored across an entire network, rather than in one single server, and provides the technological foundation for most cryptocurrencies today.

Some blockchain networks enable “smart contracts,” which are contracts automated in advance based on agreed-upon conditions. Smart contracts minimize the need for intermediary professionals and services and could build into “distributed autonomous organizations.” These smart contracts could interact with an individual’s collection of “tokens” representing pieces of information about them using blockchain technology. As learners enter the workplace, both during and after the completion of

relevant degrees, certifications, and competencies, they will need to continue managing these “wallets” as an evolving portfolio of smart contracts. This will allow the wallets to operate on their behalf across the job marketplace while concurrently enabling organizations to shift from having set organizational structures to an endless network of contracts based on unique specializations and recommendations generated by the interconnected system.

THIS EMERGING RELATIONSHIP WILL REINVENT THE WAY WE LEARN, THE WAY WE CREATE VALUE, AND THE WAY WE

BUILD THE WORLD AROUND US.

2020 Signals of DISTRIBUTED COMPUTING

These signals are signs of future innovation and disruption for the trend of expansion of distributed computing across industries.

Norwegian Air accepts cryptocurrency for payments and opens its own crypto-exchange

A new fund in Cleveland acquires businesses then sells them back to workers in co-op format

The We Company launches “future cities” initiative to create products and partnerships that address globalization, urbanization, and climate change

Amazon recruits entrepreneurs to run small-scale delivery services

Looking to 2030, we see signals of Distributed Computing and Shapeshifting Organizations happening today. Using these 2020 signals, we applied foresight techniques to construct personas of 2030 who encounter mature versions of these emerging signals in a typical, daily life scenario in 2030.

MEET DONNA, A LEARNER IN 2030

Name: Donna

Generation: Millennial

Identifies As: Multitasker, Grit, Trivia Ace

Education: High school, pursuing BS through CBE

Work: Variety of roles at local bakery

Challenge/Opportunity in Zone of Innovation: Gain qualifications to become “Product Owner” of the bakery

A Day in the Life of Donna in 2030

Donna is working her first shift at The Bread Box, the bakery/café in the bottom floor of the building—the same one where, a few floors up, she lives. It’s wild to imagine it used to be one of those old-timey ’80s shopping malls. Now it’s an autonomous community, with affordable housing units and all kinds of local businesses, from boutique smart fashion to law offices to VR gyms. All of them are employee-owned…or at least they will be when they’ve bought them “back” from the R3vita Fund, a venture capital firm that invests in local micro-communities all over the nation.

Donna found the co-op after the Next Recession, when her service-industry work dried up (for the second time, after the COVID-19 Depression) in the late 2020s. Her story mirrors that of many who weathered the ’20s, a decade rocked by upheaval. She’d always planned to get her bachelor’s degree, but has been too focused on earning money. Without a safety net, she looked for the most efficient housing solution, and landed on the co-op, a blend of capsule hostel and apartment. Rent and utilities are deducted as a revenue share for work done in one of the businesses. Her paycheck is distributed each night, with rent costs distributed automatically through a smart contract.

When Donna arrived a few years ago, she took a familiar job at The Bread Box as a barista. She was so relieved to get something steady that she put everything into the business, and in the process has shown her versatility. She’s now behind much of the bakery’s day-to-day operations—from social media to bookkeeping. After all, bakeries aren’t just places to get coffee and a baguette now. Successful bakeries generate income through everything from virtual howto’s to data analysis of buyer behavior. Synthetic agents do a lot of the work, but it’s still vital to get human clearance.

Before, Donna worked for the paycheck, but she’s begun to realize she’s passionate about taking The Bread Box to the next level, using learnings from data to establish new work streams. In other words, she’s hoping to position herself to one day become the “Product Owner,” and building the pathway to become qualified for the role. Notably, she needs to formally establish her data science abilities. After her partner encouraged her to look into competencybased education online, Donna begun amassing microcredentials based on skills demonstrated at work and through courses she takes online. All of that information is stored safely in her digital wallet, as well as her reputation scores in different work offerings. She can send these to prospective employers at any time, with blockchain identification eliminating the need for background checks. Her wallet also keeps track of possible gigs and learning opportunities that sync with her calendars to make sure she reaches her goal of getting her degree as quickly as possible.

Speaking of which, she just got an alert that her favorite peer-to-peer job interview service is offering a 2% discount. She’s been needing to log more hours, and every penny counts, so she decides to hop in and push her Bread Box tasks later into the afternoon. Hopefully it doesn’t mess up her trivia date night with her partner—but if it does, she’ll understand. It’s a busy life, but hey, she’s used to it! Only now, for the first time in years, Donna feels energized with purpose.

PLATFORM ECONOMIES at

SNHU in 2020

• SNHU’s School of Business on campus is implementing Team Academy, an entrepreneurial pedagogy and philosophy. This model replaces a traditional lecturebased faculty role with just-in-time coaching that helps learners master business competencies to succeed in a VUCA world.

• SNHU’s Income Sharing Agreements (ISA) pilot tests the viability of a contract under which a borrower agrees to pay a fixed percentage of their income for a fixed period of time to an equity lender (in this case SNHU). It also protects learners against unemployment and crippling debt, making credentials more affordable in an economy of gig work.

Proliferation of PLATFORM ECONOMIES

Platform economies refers to the proliferation of digital market environments such as Etsy, Uber, and Airbnb as a location for individuals to buy, sell, and trade goods and services. This gives our learners the ability to pursue personal economies on such platforms, similar to the gig economy and “side-hustles,” where entrepreneurial individuals will offer goods and services in the on-demand marketplace. Personal economies will increase the ability of workers to pursue flexible career pathways oriented around their own interests and skills.

Platform economies are marketplaces organized around digital platforms such as artists selling work on Etsy, gamers livestreaming on Twitch, or influencers monetizing posts through advertising on social media. These income formats have been steadily evolving over the past decade, and they’ve facilitated a new kind of relationship with buying and selling services, becoming a driving force in commerce today. We believe platform economies will give rise to a proliferation of “personal economies,” which individuals will create for themselves based on their specific skill-sets and preferred platforms. Rather than conceiving of themselves as one type of worker with one career path,

participants in the platform economy marketplace will develop complex portfolios of their skills, resources, and public identities. How personal economies are developed will be unique to each individual. For some, they might develop complementary skill-sets they can offer as “gigs” with a continuous (or changing) roster of employers. Others might seek to monetize their hobbies by building up an online presence around their social media accounts. Others still might find ways to share their resources such as guest rooms, cars, parking spots, even personal data.

We will need to help learners develop meta-skills, personal branding, and strong communication skills to lead personal economies. As the marketplace morphs, these “soft skills” will become invaluable in securing desired jobs across a wide range of industries in addition to the widespread opportunities of building their own personal economies. Concurrently, we will need to help promote a literacy of positive platform design for learners who will go on to become the builders of these platforms, so another service higher education provides is promoting a literacy of “positive platform design.”

How to Build a Personal Economy

PERSONAL BROADCASTING: using live streaming platforms to engage a public audience

LIVE TEACHING: using similar platforms to demonstrate skills, crafts, and expertise in real time, often with paying subscribers

GIG-ASSISTED ENTREPRENEURSHIP: creating services that use gig platforms to recruit a small or large workforce

DIGITAL BROKERING: using platforms to connect diverse people and objects into trusted ecosystems with distinctive identities for offering products or services— or becoming markets for products or services

PERSONAL CROWDSOURCING: using crowdsourcing platforms to secure individual support—often to accomplish personal goals or survive catastrophic personal events

These signals are signs of future innovation and disruption for the trend of proliferating digital market environments.

A cottage industry of chicken diapers has sprung up alongside a surge in urban chicken keeping, allowing for boutique sellers to make six-figure yearly incomes selling across Etsy and Instagram

James Dean will be “resurrected” as a digital character to star in his fourth film, indicating how public personalities might license their representation during and even after their lives

2020 Signals of PLATFORM ECONOMIES NADIA

Half a million people are “clickworkers” on Amazon’s Mechanical Turk platform

Looking to 2030, we see signals of Platform Economies and Personal Economies happening today. Using these 2020 signals, we applied foresight techniques to construct personas of 2030 who encounter mature versions of these emerging signals in a typical, daily life scenario in 2030.

MEET NADIA, A LEARNER IN 2030

Name: Nadia

Generation: X

Identifies As: Tinkerer, Techie, Skydiver

Education: BA, now upskilling

Work: Position as software developer was recently eliminated, now self-employed

Challenge/Opportunity in Zone of

Innovation: Shifting from full-time employment to building a personal economy through upskilling

A Day in the Life of NADIA in 2030

Nadia is just about to wrap up her latest instructional video on best practices for training holograms to sound more empathetic—if only she could stop flubbing the final line! Just five months ago, this type of work with holograms was her day job. But the latest round of layoffs among senior developers found her with a modest severance and a ton of experience that had just been deemed non-essential.

She may be near classical retirement age, but Nadia is nowhere near ready to stop working—and anyway, nobody exactly trusts their retirement accounts anymore. So Nadia decided she’d follow her son’s lead and try her hand at producing content. Since then, she’s gotten hooked on “the hustle.”

It started with her instructional video series. While corporations may have found a solution in algorithms with the guidance of low-paid human facilitators, indie creators are thrilled at the chance to learn from her skills. She hates going back and looking at those early videos—so poorly produced! She’s clearly reading off a script, there’s obviously no attention to lighting, and her editing skills leave…a lot to be desired. At least she had the wherewithal to realize it early on. She entered into a revenue share arrangement with a remote video editor, though their contract renegotiation is coming up and he’s been making a killing because she struck a weak deal before she knew better. More importantly, she enrolled in online courses that would let her quickly establish her skills in content production and entrepreneurship.

Now she’s amassed 15,000 subscribers; not enough to make ends meet on its own yet, but still something to feel proud of. And from there, other opportunities have sprung up. License her likeness to a video game on a revenue share? Sounds kind of cool. Opt-in to a research study examining her brainwave data while producing her videos? Well, sure. She’s even attracted the attention of a few bigger virtual instructors in related fields, who have told her they’re going to start looping her into some of their gig work when they need a hologram specialist. She’s also produced a few bespoke reality filters for clients—including her most recent one for the local museum, which gave her unprecedented access to their archives and upcoming schedule.

Every job is a possibility—to learn, to drive new business, or both. As such, she’s already put together a pitch for a creative campaign she could conduct to drive foot traffic during the coming winter months, when things tend to slow down for businesses that rely on attendance because of the general precaution around possible viruses. She gets a notification that her pitch meeting with them is only 7 minutes away. Okay, time move on. Deep breath, back straight. She looks into the camera, gestures with her hand to kick off the 5-second recorder countdown, and gets ready to nail this line.

INTERNATIONAL MARKETS

at SNHU in 2020

• Through the Global Education Movement (GEM) program, SNHU provides access to online degrees to learners in five different countries by working with local on-the-ground partners. This credentialing allows displaced or vulnerable students to take advantage of an internationally recognized American degree, which affords them the opportunity, if desired, to participate in a global marketplace.

• SNHU’s Project Atlas integrates CBE and the coming of age experience on campus to explore efficacy and suitability of CBE oncampus for traditional-age students. In the first year, SNHU measured similar learning efficacy scores and coming of age experiences for the Atlas student cohort and comparable learner cohorts on campus.

• LRNG is enabling opportunity youth to participate in global markets by building “Learn x Work” ecosystems that create nontraditional pathways by leveraging technology, in-person experiences based on learner passions, and collaborations with public institutions and cities. Learners unlock educational and career opportunities by engaging with “playlists” that drive them toward LRNG badges, shareable digital credentials that certify evidence of learning.

INTERNATIONAL MARKETS Reinvention of

International markets refers to the changing methodology of how we define ourselves. Traditional market lines on age, race, gender, and nationality begin to erode into a spectrum that gives our learners the ability to identify, create, and understand themselves as part of new communities such as gamers, e-sports, and political groupings outside the traditional two-party system. Spectrum demographics will give individuals a greater sense of community while changing how industries such as marketing do business.

Existing international markets will continue to be impacted by migrations from conflict and global crises; emerging trends in the nature of work will transform and lead to a blurring of the traditional demographic categories that have served as the basis for organizing groups of people. Traditional demographics include factors such as age, ethnicity, and income which are the principal categories by which we organize ourselves (and are how we’re grouped when studied or marketed to), and are hard lines and typically either-or questions. With this blurring of populations, human and machine, work and life means that we won’t be able to draw

such clear distinctions. Add to that new ideas about identity, such as virtual citizenship and gender fluidity, and we find ourselves in a world driven by spectrum demographics, a way of describing the characteristics of an individual or group of individuals along a spectrum.

Such spectrum approaches lift the burden of some categorical identities and, in general, suggest more fluid—and individually unique—identities.

Categories to Spectrums

GENDER: The mapping of the human genome has demonstrated that a spectrum of gender markers actually underlies such seemingly unambiguous distinctions as male-female. Society has already begun to embrace ungendered fashions, ungendered facilities, and a growing array of new gender identities.

ETHNICITY: The National Geographic Society’s Genographic Project has shown that most humans are a complex mix of genetic racial markers rather than the discrete racial categories that have defined and isolated some groups. Ethnic identities are a complex combination of positions on several different ethnic spectrums.

MENTAL HEALTH: Most recently, the Physicians’ Desk Reference has dropped the traditional diagnostic categories of mental illness, replacing them with a spectrum of mental health.

N EW POPULATIONS WILL BE CONSIDERED IN THE HIGHER EDUCATION CONVERSATION, AND, HOPEFULLY, DESIGNED FOR APPROPRIATELY AND GIVEN A PATHWAY TOWARDS SOCIOECONOMIC MOBILITY.

— SNHU Employee in 2030 Focus Group

These signals are signs of future innovation and disruption for the trend of shifting demographic and market categorization.

Trans athletes spur debate over the future of gendered competition

“OK Boomer” trend marks end of friendly relations between Boomers and Zoomers (Gen Z)

Study finds that Millennials sleep and work more than previous generations

Tension surrounding age is driving many to seek a new understanding of “Life”

Mattel redefines Barbie by launching genderinclusive dolls

Giant consumer startups are emerging without needing venture capital

2020 Signals of INTERNATIONAL MARKETS ALEX

Looking to 2030, we see signals of International Markets and Spectrum Demographics happening today. Using these 2020 signals, we applied foresight techniques to construct personas of 2030 who encounter mature versions of these emerging signals in a typical, daily life scenario in 2030.

MEET ALEX, A LEARNER IN 2030

Name: Alex

Generation: Z

Identifies As: Strategist, Competitor, Goofball

Education: Recently enrolled in on-campus BA on eSports scholarship

Work: Pro Gamer

Challenge/Opportunity in Zone of

Innovation: Figure out the next phase of her career

A Day in the Life of ALEX in 2030

Alex is at a “speed dating” event in VR, where users are randomly paired based on algorithmic matching. But this isn’t a typical speed dating event—for starters, it’s not even about dating. It’s about finding a gaming partner.

As video games have become increasingly social, duo- and team-based play options have overtaken solo gaming in eSports. With the ubiquity of streaming, it’s often just more fun to watch buddies banter back and forth with each other while playing than it is to watch lone players. And while so much of 2030 is different than 2020, one thing remains the same: Everybody loves a good story.

The initial pairing process is based on data that the algorithm has gathered about each player’s gaming style; your age, race, and gender aren’t important because you’ll be able to take on whatever avatar identity you want. When matched, players have 4 minutes to chat with each other before being switched to the next. The primary focus in those few minutes is for Alex to gauge if the person across from her is somebody she could see herself spending hours upon hours gaming with, and whether she thinks their dynamic would make for good “TV.” After each “date,” Alex logs initial thoughts and impressions she can revisit later. But there’s a little more to it than that.

Alex’s situation is a little unique. She’s known since she was young that she wanted to be a pro gamer. Recently, she caught the attention of a college recruiter, who ultimately offered her an eSports scholarship, which she’s accepted. While this might have seemed like a strange thing to happen 10 years prior, collegiate eSports leagues in 2030 don’t impose age limits, and often, players in their twenties are at the peak of their capabilities. But Alex is aware that, like any talent, her gaming chops will fade. She wants to make the most of her career while she’s able, but also set herself up to have another career she’ll enjoy when she’s no longer a serious competitor.

Gaming has been her life, and she can’t imagine wanting to do anything that would take her out of that sphere. Coaching would be one path, but she’s not sure that’s the right followup career for her...though she’s leaving her options open. One thing she’s been toying with is launching a niche fashion line for androgynous gamers—though she knows nothing about fashion or business. Her undergraduate studies may be where she acquires the formal training in service of these goals, but being the strategist she is, she’s not going to hedge her bets. With the help of a synthetic agent, she has filtered her search parameters at the speed dating event to optimize for partners with strong entrepreneurial and aesthetic capacities. She’s hoping that whoever she finds will not only help her find success in the short term, but help teach her invaluable content along the way.

Alex isn’t wasting a moment of any of it; she’s documenting every step of the process on her channel. By rolling it all into her personal narrative, she creates a living document of her journey—and invites the participation of her viewers in the process. These days, you never know where you’re going to find what you’re looking for. The best strategy she can see is to keep her options open.

FUTURE LITERACIES

at SNHU in 2020

• SNHU is investigating the use of extended reality (XR) technologies in traditional instruction. By building and testing the efficacy of immersive experiences, the work is leading to an understanding of how to best leverage these technologies to drive student engagement and learning.

• The game design and development studio, Inkwell Interactive, on SNHU’s campus delivers an innovative model for competency-driven project-based experience for the 21st century learner. Learners at Inkwell deliver products to real clients, get feedback, and iterate. Clients who have worked with Inkwell include the Veterans Administration, Boston Children’s Hospital, and Make-A-Wish Foundation.

• SNHU’s Little Fish Lagoon tool, funded by the Hewlett Foundation, is an online multiplayer simulation that puts players in charge of their own fishing company in the North Atlantic. The digital experience provides an extension that enables teachers to visualize, analyze, and discuss how their learners approach collaboration in group projects and better prepare their learners with 21st Century soft skills. These skills will prepare learners for the future of work.”

Application of FUTURE LITERACIES

Future literacies refers to the competency of using digital simulations of our current environment powered by software tools such as virtual reality (VR) and augmented reality (AR). Our learners will be challenged to become masterminds of reality by acquiring knowledge about these types of forecasting tools, which will allow them to better utilize technology in their career. Using simulations to reimagine reality and the future will enable individuals to prepare for an increasingly VUCA world.

The world of the present is caught between two curves. The first curve is all our existing beliefs, practices, and institutions. The second curve is what has not yet come into being—the future. In the gap between the two is the volatility and uncertainty we experience today. There is no certainty in this gap. There are only urgent futures, ranging from climate change to income inequality. These futures will shape everything that tomorrow’s learners and workers do. At the same time, the continued build out of the world’s digital backbone will make it possible to simulate possible versions of these futures with ever higher resolution. These urgent futures and the tools for understanding them will challenge

the world to build a widespread simulation literacy designed to empower everyone to participate in these control systems of the future in order to become masterminds of reality. Critical tools, competencies, and technologies will include:

Hyper-Connected Data: Mobile devices, cheap sensors, and social networks create orders of magnitude more data than ever before.

Artificial Intelligence (AI): AI will leverage the hyper-connected data to form artificial neural networks that can act more efficiently and more predictively than we can—even if we can’t always understand them or explain how they’re doing it.

Extended Reality (XR): XR refers to a spectrum of technologies that includes Augmented Reality (AR), Mixed Reality (MR), Virtual Reality (VR), and other immersive technologies like haptics and projection mapping. These new spatial mediums will translate the knowledge and workings of AI systems into experiences for humans—including simulations of the future.

If we want a more equitable future, it’s imperative that workers, learners, and organizations all grasp the power of simulations and integrate them into their daily practices like we do with calendars and spreadsheets today.

Being masterminds of reality literacy will help our learners:

• Model complex systems that have previously evaded our understanding

• Enable new capacities for large-scale collaboration, prototyping, and interaction that build on the simulation models we create

• Use the digital twins of our physical environment to learn about the systems and optimize them in new workplace settings—for everyone’s economic and social good

These signals are signs of future innovation and disruption for the trend of applying digital simulations of our current environment in the future.

Mojo Vision announces augmented reality contact lenses in development

Adobe launches Aero, its augmented reality authoring and publishing tool

Startup uses deepfakes to anonymize videos and protect privacy

Epson Drone Soar is the first glassesoptimized app to help pilot users pilot DJI drones

2020 Signals of FUTURE LITERACIES RICKY

YUR launches virtual smart watch, letting users track health information in virtual reality

Looking to 2030, we see signals of Future Literacies and Masterminds of Reality happening today. Using these 2020 signals, we applied foresight techniques to construct personas of 2030 who encounter mature versions of these emerging signals in a typical, daily life scenario in 2030.

MEET RICKY, A LEARNER IN 2030

Name: Ricky

Generation: Z

Identifies As: Family first, Sci-Fi geek, Environmentalist

Education: BS in electrical engineering

Work: Field Service Engineer for Wind Turbines

Challenge/Opportunity in Zone of

Innovation: Pursue a passion

A Day in the Life of RICKY in 2030

It’s 9 p.m. and Ricky is heading into his second shift of work after putting his kids to bed. As a field engineer, his job sends him to different companies to install parts, train and supervise workers, develop safety measures and protocols, and most importantly, to monitor those already in place to ensure everything is working functionally. His focus is wind turbines, but he’s been in the industry for over a decade, so he has familiarity with a variety of other equipment in the green energy sector.

Ricky does all of this work from the comfort of home through his extended reality (XR) headset, which has the ability to shift seamlessly between virtual and augmented reality. In some cases, he supervises on-site humans or robots in the installation of new equipment (generally speaking, robots handle the more dangerous installations). In others, he hosts meetings with team members all over the world to develop new products and protocols. By collaborating on 3D prototypes in real time, the team is able to develop solutions at speeds and an efficiency never before possible.

He gets a call from his wife, Maria, a touring musician who is constantly on the road. He only has a minute, but he misses her, so they hop into a private VR chat. They check in quickly before he has to shift back to the task at hand. Family is of the utmost importance to him, so he’s worked out his schedule to where he can see the most of his 5 year old daughter and 2 year old son. He works his first shift while they are at school, and then gets back to work a few hours after they go to sleep.

Ricky is regarded by his peers as a domain expert, and with the growing presence of climate-related events, the need for his work isn’t going anywhere. All things considered, Ricky is set. But in this world of the future, Ricky has discovered a surprising desire: He wants to write a novel. His work at the front lines of green energy has given him a keen understanding of how vital story can be to share messages that could save lives, which activates his environmentalist impulse…but it goes deeper than that. He just feels drawn to express his creativity in a way that, as a pragmatic person, he never really made space for himself to do.

Last month, he enrolled in an online MFA in creative writing, which has already pushed him in completely different ways than what he experienced pursuing his undergraduate degree in electrical engineering. Turns out this writing thing isn’t going to be easy, but he’s energized by the challenge—and it has changed how he sees his day job. All of a sudden, he’s finding himself taking notes after conversations and thinking in terms of how certain coworkers would make great characters.

It’s clear from his workshops that he has a long way to go before his writing will be ready for the public, but he’s happy to have a virtual community to help him get it there.

Building Toward The world OF 2030

BUILDING TOWARD THE WORLD OF 2030

Through SNHU’s current pilots, projects, and futures planning efforts, we are building toward the world of learning and working in 2030. IFTF encourages us to create the future we desire. We see the range of possible futures as scenarios that may come to pass, but charge ourselves with boldly moving towards the future that will enable us to continue delivering our mission and vision to deliver life-transforming education to our learners. We continue to develop concepts and pilot programs to test emerging technologies, new learning models, creative financial structures, and alternative assessments and credentials. The results of these pilots will inform our future investment and business modeling at the university as we build towards our desired future for learning and working in service of our mission and vision in 2030.

The combined impact of the future forces and zones of innovation for the future of American higher education will transform how we create and deliver experiences that interconnect working and learning. In our vision of a new American higher education landscape, traditional institutions of higher education (IHEs) will likely remain critical to the greater education landscape (and they are terribly hard to kill off anyway) and traditional degrees are likely to remain key credentials and learning milestones. Residential colleges serving traditional-age students persist, though four years of the “coming of age” campus experience will likely come to be seen as excessive and a luxury if costs models remain intact. Those other “jobs” that higher education does—research, economic and cultural roles,

professional preparation for doctors and graduate-level learning, the military academies—will remain important. If the most important thing our industry is being asked to do today is to educate a larger and more diverse student population for a rapidly changing world of work and to create social mobility and well-being, we need a dramatically different system of higher education.

LearnerCentered Ecosystems

Focus on Real-world learning skills

A shift from Curriculum to Curation

Personalization & tech empower

Human skills

We envision the future of higher education among these future forces and challenges as having these critical components:

• Learners must be at the center of the learning ecosystem, rather than the institution. Learners might dip in and out of a learning platform, getting just the right learning at just the right time in just the right amount in a manner that best suits them, at a price they can afford.

• There will be a reduction of dependency on credit hours and more focus on real-world competencies where technology will become an enabler of strategic and transformational change.

• The work of faculty will become unbundled so that courses aren’t designed, developed, and delivered by the same person. As content becomes ubiquitous and increasingly free, it may very well be that universities will shift from an emphasis on curriculum and delivery of content to curation, assessment, and certification of learning.

•

This new system of higher education will be no less human and humane.

Through personalization and the use of technology to empower and amplify the most important human interactions, higher education can be more responsive to the emotional and psychological needs of students.

While this is a radically different form of higher education than the one we have today, it is not a fantasy. The component parts of what is needed exist today, and to some extent it’s happening in pockets of innovation within the industry. Realizing this vision is incredibly hard. Higher education is deeply resistant to change, a resistance deeply situated in long-held traditions, governance models, how we organize ourselves in terms of knowledge, departments, and who does what, and our own self-regard. Moreover, like healthcare, higher education is a regulated industry, and our ability to realize a new vision for higher education means a new vision for quality assurance, one more fully focused on outcomes, accountability, and transparency. Regulatory frameworks can either be a barrier to or an enabler of success—right now, they are more of the former.

Reinvention, just like in the corporate world, means dramatic changes to business systems, financial models, roles, understanding of who one serves and how. In all of that chaos, there are perceived winners and losers. Faculty roles will change. Institutions unable to change will fall away. New providers will emerge. Old disciplinary boundaries might shift, as might institutional boundaries. This will be hard, and is already proving to be hard. The key will be the willingness and ability to change, which invokes a quote attributed to Darwin, “It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is most adaptable to change.”

To be relevant in a changing future, we must continue to provide meaningful education and the tools to transform lives and we also provide hope and social mobility. This is our most important work.

Handy guide to Futures Terminology

HANDY GUIDE TO FUTURES TERMINOLOGY

4K and 8K

The term 8K Ultra High Definition, or just 8K, refers to the highest available form of Ultra High Definition video. 8K resolution has 4 times the number of pixels of 4K (33 millions pixels vs just over 8 million). 8K also has about 16 times the number of pixels as 2K (HD).

5G

Fifth-generation wireless (5G) is the latest iteration of cellular technology, engineered to greatly increase the speed and responsiveness of wireless networks. 5G will also enable a sharp increase in the amount of data transmitted over wireless systems due to more available bandwidth and advanced antenna technology.

Anticipation

The sense of expectation of an occurrence, predicting it, and occasionally the act of preparing for it.

Artificial Intelligence (AI)

AI is a broad category including many different technologies, but the important aspect to note is that AI learns by analyzing massive quantities of data. Through further human input, an AI algorithm can teach itself based on specified goals.

Automation

The replacement of previously human-run tasks with algorithms or machines. Although in the past, automation referred primarily to simple or menial tasks, some more complex knowledge work roles are now vulnerable to replacement by automation.

Autonomous Technology

Complex tools or functions (such as vehicles, appliances, or hiring processes) that use automation and artificial intelligence to function with minimal or no human guidance.

Avatar

An icon or figure representing a particular person in video games, internet forums, virtual realities, or other digital environments.

Backcasting

The process of working backwards from the definition of a possible future, in order to determine what needs to happen to make this future unfold and connect to the present.

Baseline

A set of reference data used as a basis for comparison.

Black swan

A metaphor describing an extremely low-probability /unforeseen, high impact event that takes everyone by surprise.

Blockchain

A distributed computing protocol that can track the status of autonomous virtual objects and provide security without a central authority. Blockchain is a new kind of distributed computing infrastructure that makes it easier to build secure and trustworthy distributed systems.

Bot

A device or piece of software that can execute commands, respond to messages, or perform routine tasks such as online searches, either automatically or with minimal human intervention. Bots often function as digital robots, as opposed to mechanical robots.

Breaks, Ruptures, Disruptions, Discontinuities

Abrupt, major changes in the nature or direction of a trend.

Business as Usual

A path towards a future considered as the continuation of the current path.

Causality

A logical link between events where a cause precedes an effect and altering the cause alters the effect.

Complex systems

Systems which are made up of multiple interacting components exhibiting emergent macro-behavior and interact dynamically with their wider contexts.

Cryptocurrency

A digital currency in which encryption techniques are used to regulate the generation of units of currency and verify the transfer of funds, usually operating independently of a central bank.

DAO (Distributed Autonomous Organization)

A set of blockchain or similar digital code, protocols, and contracts that function as an organization without any central governance. No successful DAO exists at present, but many experiments have attempted to demonstrate the theory of an organization without traditional human-defined hierarchies and structures.

DAPP (Decentralized Application)

An application that does not rely on the central server-to-client communication that is typical of most of today’s software applications. Usually implemented in blockchain-style code, DAPPs do not require an owner or administrator to provide their services.

Delphi

An anonymous survey method using iterative structured feedback to pool expert opinion on the future.

Digital Twin

A representation of a physical-world object in digital space that a user can interact with in a virtual environment.

Drivers

Factors causing change, affecting or shaping the future.

Emergent Learning Community

A community of learners with shared interests, learning objectives, and learning styles, created from a process of mutual discovery. Digital platforms that use machine learning and massive data stores about learners could automate the creation of such communities, possibly displaying typical topdown courses and classes.

Emerging Pattern

A novel situation/new trend created by unforeseen recurrent events.

Expert

A person who has a special skill, knowledge, insight, or ability in a particular domain based on research, experience, judgment, or occupation.

Exploration

An anticipatory inquiry that investigates a wide range of possible future developments, considered from a variety of perspectives.

Extrapolation

Application of a method or conclusion to a new situation assuming that existing trends will continue or similar methods will be applicable.

Forecast

A statement that something is going to happen in the future, often based on current knowledge and trends.

Foresight

A systematic, participatory, and multi-disciplinary approach to explore mid- to long-term futures and drivers of change.

Fungible Currency

A currency that can be easily exchanged, at a standard rate, with a variety of other currencies and commodities. For example, Bitcoin is a fungible currency that can be traded for most fiat currencies of nations—as is the U.S. dollar.

Future

The time yet to come.

Futures Studies

A field of studies, focusing on a methodical exploration of what the future might be like.

Gig Economy

A labor market characterized by short-term contracts or freelance work, often brokered by software platforms, as opposed to a labor market composed primarily of permanent jobs and corporate employers.

Horizon Scanning

A systematic method for gathering new insights on issues which may impact the future.

IoT

(Internet of Things)

The network of objects, typically without screens, that are connected electronically to the Internet. The connected objects may be anything from simple sensors to complex appliances and even entire buildings.

Knowledge

Information about what the future could be before it exists, acquired through the practice of Futures Studies.

Mapping

A process seeking to display how factors that have created the present and/or can create the future are inter-connected.

Meme

An element of a culture that can be passed from one individual to another by nongenetic means, especially by imitation. Many expressions and beliefs can be considered to be memes. Social and cultural groups often aggregate around sets of memes.

Meta-Skill

A set of behaviors or insights that enable a wider subset of skills. For example, creativity is a meta-skill that may enable—and be a prerequisite for—everything from composing a musical score to engineering a new kind of space rocket.

Model

A simplified representation of an object, an event, or a process.

Narrative

A coherent description of a scenario (or a family of scenarios), highlighting its main characteristics and dynamics, the relationships between key driving forces and their related outcomes.

Normative

Describes a preferred scenario, or future.

Outlook

A description of a future state or development that is considered likely (or at least plausible) given clearly defined logic and assumptions.

Pathway

A trajectory in time, reflecting a particular sequence of actions and consequences against a background of autonomous developments, leading to a specific future situation.

Platform Economy

A marketplace organized around digital interfaces to goods and services as opposed to brick-and-mortar institutions. These interfaces are typically branded and serve as hubs for various kinds of commerce.

Plausible

Judged to be reasonable because of its underlying assumptions, internal consistency, and logical connection to reality.

Predictability

The degree of confidence in a forecasting system based either on law derived from observations and experience or on scientific reasoning and structural modeling.

Proactive

Oriented towards acting in advance of a future situation, averting undesirable futures and working towards the realization of desirable futures.

Probability

The likelihood of something happening or changing.

Projection

An expected value of one or more indicators at particular points in the future, based on the understanding of selected initial conditions and drivers.

Prospective

Refers to the French foresight method “La Prospective,” which is based on the principle that the future is not written, but is to be built as a collective endeavor.

Qualitative

Characterizes something that can be observed but not measured numerically.

Quantitative

Characterizes something that can be observed and measured in magnitude and multitude.

Roadmap

Roadmaps and road mapping in futures studies are often related with technological foresight.

Scenario

A description of how the future may unfold according to an explicit, coherent, and internally consistent set of assumptions about key relationships and driving forces.

Shapeshifting Organization

An organization that is designed a priori to change its structure in response to demands of the environment. Typically, shapeshifting organizations rely on a flexible network structure in which many different nodes can take the lead in executing an evolving set of goals and objectives. This flexibility allows them to rapidly adapt to a changing environment.

Simulation (Foresight)

Assessment of system behavior undertaken by building and using models that are designed to behave in a manner analogous to a real system.

Smart Contract

Computer code, typically in a blockchain system, that uses artificial intelligence to initiate transactions, test whether those transactions meet conditions set by the code (or learned by the code in the case of machine learning), and confirm when the transaction has been accomplished according to conditions.

Spectrum Demographics

A way of describing the characteristics of an individual or group of individuals along a spectrum of difference, typically between two poles. For example, on a male-female spectrum, any given individual may identify with a broad set of characteristics that are more or less male or female.

Strategic Planning

Preparing for, or achieving, some future state.

System

A set of interconnected elements that is coherently organized in a pattern or structure.

Systems Modeling

A way of representing a system from multiple points of view as a way to understand how the system changes and how it can be changed. For example, an economy is a system that can be explained from the point of view of labor and productivity, of financial value, and of commercial activity, among other things. Typically, a system includes many dependent and independent variables, whose values can be changed to understand how to change the system as a whole.

Time horizon

The farthest point in the future that one will consider in a Futures Study. The time frame refers to the complete period (past-tofuture) considered in a Futures Study.

Token

A representation of value in physical or digital form. In a cryptocurrency like Bitcoin or Ether, a token is equivalent to a coin in a fiat currency—a fungible unit of exchange in the global marketplace.

Transition (Foresight)

A shift of a system from one state to another.

Trend

General tendency or direction of a movement/change over time. A megatrend is a major trend, at global or large scale.

Uncertainty

A state of having limited knowledge about the future.

Virtual Assistant

A digital application, often with a voice interface and some level of artificial intelligence, that performs a variety of tasks typical of an assistant in the physical world. Some virtual assistants are highly specialized, helping citizens navigate a government website, for example. Others, like Apple’s Siri or Amazon’s Alexa, are more general interfaces to the digital devices and web services that are integral to daily life today. All virtual assistants attempt to simplify the digital tasks that people need to accomplish to be successful.

Vision

A compelling image of a (usually preferred) future. Visioning is the process of creating a series of images or visions of the future.

Weak Signal

An early indication of a potentially important new event or emerging phenomenon that could become an emerging pattern, a major driver, or the source of a new trend.

Wild Card

A surprising and unpredictable event, that would result in considerable impacts (or consequences) that could change the course of the future.

Worldview

How people see the world, with an emphasis on their unconscious assumptions and the principles that they do not call into question.

END NOTES

1 https://www.bls.gov/cpi/factsheets/college-tuition.htm

1 https://www.cnbc.com/2017/11/29/how-much-collegetuition-has-increased-from-1988-to-2018.html

2 https://www.cnbc.com/2017/03/14/more-than-11million-borrowers-defaulted-on-their-federal-student-loanslast-year.html

3 https://nces.ed.gov/fastfacts/display.asp?id=80

4 https://www.oxfordmartin.ox.ac.uk/downloads/academic/ The_Future_of_Employment.pdf

5 https://www.edelman.com/post/university-reputationstruths-not-all-self-evident

6 https://workofthefuture.mit.edu/sites/default/ files/2019-09/WorkoftheFuture_Report_Shaping_ Technology_and_Institutions.pdf

7 https://data.worldbank.org/indicator/IT.CEL.SETS.P2

8 https://www.epi.org/publication/usa-lags-peer-countriesmobility/

SPECIAL THANKS

• Friends at Work

• Games and Learning

• Gartner

• Institute for the Future

• Kairos Future

• Pearson Education

• PwC

• University of Houston

• Google.org

• Hewlett Foundation