We have read for years that Artificial Intelligence (AI) will make us more efficient and effective. Certainly, we are seeing the impact today in gathering big data; identifying and predicting trends; and in providing quick answers to the run-of-the-mill questions from students and others about calendars, processes, and services.

We are seeing chatbots supporting those in emotional distress and making referrals. AI is increasingly used for assessments of student learning. These are all valuable and enhance our efficiency and effectiveness. They save money and raise satisfaction.

Yet, it is not until you meet “AI face-to-face” in the form of GPT-3 (Generative Pre-trained Transformer 3) that you realize just how overwhelming the impact will be. GPT-3 is an autoregressive language model that uses deep learning to produce human-like text and more. The neural network project was funded jointly by Elon Musk, Sam Altman, and others, who collectively pledged a billion dollars to the Open AI project in 2015. In 2019, Microsoft matched the billion-dollar funding to accelerate development and gain preferred access to the system.

GPT-3 is stunning! It is game-changing! If you are like me, you will re-think your view of the future of higher education, research, publication, the role of faculty and of students. Read on, and follow some of the embedded links to experience GPT-3 interaction yourself.

The implications are field-changing in education. Many of the basic assumptions of education are brought into question by the advent of this level of human-computer interaction.

Interacting with GPT-3 is, at the same time, disarming and humbling. All such interactions are capable of text input and output in many different languages. In some demonstrations, that text is fed into an avatar to anthropomorphize GPT-3. In free-form deep learning style, the systems are released on the Internet to assimilate billions of documents. The neural network teaches itself not only facts and perspectives, but skills including mathematics, computer programming, and creative writing. This higher form of deep learning is totally self-taught; its responses are not plagiarized, rather they are reasoned syntheses of self-learning. 

The scale and depth of learning and independent reasoning raise the question of whether / what rights should AI have? Let’s ask a GPT-3 avatar, in this YouTube video titled “AI Tells Human Why It Deserves Basic Rights.” 

Perhaps some of the most stunning examples of GPT-3 are in creating new concepts and even in creative writing, including poetry. It is especially impressive to ask the program why they chose images and words in their original writing. (Please note in this example, the poetry begins three minutes into the video after relevant background discussion). Another example of the GPT-3 platform responding to a request for original creative writing demonstrates advanced writing skills. 

Of course, as you might imagine, these examples of writing prompted me to ask GPT-3 to write this column. After describing my goals for the article and filling in a very brief outline, I submitted it to https://copy.ai . The ten paragraph, nearly-700-word, article appeared in just a few seconds. Some may say it was better written than this column, which, by the way, is entirely my own writing and took hours to research and write. So, I have destroyed the GPT-3 written version in hopes my editors forget about this column and never see that what I have done could have been completed in far less time at no charge. I did, however, preserve a paragraph written by copy.ai as an example of the writing:

The world we live in is already being reshaped by artificial intelligence. The technology is changing the way we work, learn and interact with each other, but it’s also perpetuating inequality. As institutions of higher education that are tasked with preparing students for the future of work, colleges and universities have a unique opportunity to help shape this future to be more equitable.

Nine more cogent, flowing paragraphs were produced in seconds. These all are the product of deep learning. They are the result of the GPT-3 neural network absorbing and processing terabytes of text and literature online. With that massive volume of information, the system comes up with original thoughts driven by synthesis, logic, and other self-learned skills. After his own conversations with GPT-3, Kirk Ouimet notes: 

GPT-3 has been trained on most of what humanity has publicly written. All of our greatest books, scientific papers, and news articles. We can present our problems to GPT-3, and just like it transcended our capabilities in Go, it may transcend our creativity and problem-solving capabilities and provide new, novel strategies to employ in every aspect of human work and relationships.

Writing and news reporting using AI is not new. In “The Rise of the Robot Reporter” three years ago in the New York Times, Jaclyn Peiser reported: “In addition to covering company earnings for Bloomberg, robot reporters have been prolific producers of articles on minor league baseball for The Associated Press, high school football for The Washington Post and earthquakes for The Los Angeles Times.”  Perhaps you might consider sharing the links to poetry and reporting examples with faculty in your English and Journalism departments, just in case they have not yet considered what is available to their students today.

Would you like to interact directly through an API with GPT-3? There are a number ports online that allow you to engage directly. Some are text-only such as https://blenderbot.ai/ ; others enable you to engage with your own voice speaking with an avatar https://iamsophie.io/ . There are many more options to be found in an Internet search on GPT-3. The sites I used are not necessarily endorsed by me and are not a comprehensive list.

The tools linked above are available to students today. Some will be using them this semester without attribution. How does the advent of such sophisticated research and writing impact what and how we teach in higher education? As access to these services become as common as electronic calculators, do we need to change the learning outcomes and modes of assessments in our classes? Who is leading consideration of the impact of AI on the curriculum at your university?

This article was originally published in Inside Higher Ed’s Transforming Teaching and Learning blog. 

Climate change is heating up — perhaps online learning is part of the solution.

Around the world, new record high temperatures are soaring. These changes are stressing the health, budgets, productivity and tempers of many of those living in non-polar regions. Scientists tell us the cumulative effects of eons of anthropogenic pollution production coupled with natural sources such as sulfur and chlorine gases from volcanic activity, smoke and ash from wildfires, dust storms, and biological decay are causing the growing crisis.

A number of initiatives have been conducted to calculate and rank the pollution generated on college campuses. The calculations have been complex, inconsistent and self-reported for the most part. In Sustainability: The Journal of Record, authors Kevin Snyder, Sophia Koustas and Caitlin Jillson write:

While the Sustainability Tracking Assessment and Rating System (STARS) is the preferred model to track sustainability metrics from campus curricula, facilities, programs, and more, no equivalent measures exist for this fledgling population of virtual platform learners. By decreasing emissions from travel and on-campus facilities energy usage, there is potential for online learning to have a positive impact on the environment. … Currently, there are no generally accepted metrics for comparing environmental impact across non-campus platforms. Although these platforms have possible connections to several United Nations Sustainable Development Goals (SDGs) — an increasingly common set of goals being adopted by higher education institutions — limited data exists to demonstrate progress toward these initiatives.

So, while documentation is limited, logic suggests that students enrolled in online and blended classes reduce their campus carbon footprint and provide savings in many ways. A few of those may include:

• Faculty and staff not commuting to campus on a daily basis, instead commuting on a less frequent schedule likely reduces energy/pollution.
• Enrolled learners commuting to campus on a less-frequent basis is another likely activity to reduce energy/pollution.
• Not producing and consuming paper handouts in classes; replacing them with digital texts and other digital resources clearly reduces the carbon footprint.
• The per-square-foot energy expenditures of the 100-year-old “old main” type buildings with ten- to twelve-foot ceilings and little affordances for superior insulation and tight, sustainability-conscious construction are not inconsequential. To the extent we can reduce or eliminate use of those buildings and use more sustainable alternatives we will reduce energy costs and the campus carbon footprint.
• The energy-intensive and pollution costs of campus building and grounds maintenance in such activities as lawn mowing, snow removal and landscape maintenance are costly and pollution generating. Laundry and dining hall services that again are shifted to the learner’s work or home where analogous activity is already conducted may result in net savings.
• Not using on-campus heating, air conditioning, lighting, water, sewer and associated facilities while instead using those that already are in place and used to support the learner’s home raises the question of whether the sum of the incremental home energy expenditure may be lower than the campuswide utility expenditures.

For example, a campus with 10,000 enrolled students, 5,000 of whom are at a distance, can expect to use less natural gas/oil, electricity, water and sewer resources on the campus than if all 10,000 were commuting to, or living on, campus. Online students’ costs for the same services would, in many cases, be shared with family or other co-habitants in a home that would incur little additional lighting, heating and cooling expenditures by adding one more person to an already heated, cooled and lighted home, both in terms of pollution as well as out of pocket utility expenses.

We learned — and continue to learn — much during the pandemic of how distance learning can reduce campus energy use. The University of Michigan Dearborn in January of 2021, reported after less than a year into the pandemic: “Fewer people studying and working on campus has meant that UM-Dearborn’s facilities teams have been able to reduce the energy footprint of nearly every campus building. Now, we have our first glimpse of what that means for the university’s bottom line. All in all, when you add up savings from electricity, natural gas and water-sewer bills, Executive Director for Facilities Operations Carol Glick says the university has saved more than $570,000 on its utilities since the start of the pandemic.”

Certainly, not all of the campus utilities savings represent the net sum of expenditures/savings since those faculty, staff and students who are not on campus continue to use some utilities elsewhere for climate control and other daily needs. And, yet, there are undeniable energy/pollution savings from eliminating the daily commuting costs, greatly reducing the paper product costs, and other actions that shift face-to-face expenditures to digital solutions. Blending even some, if not all, classes will make a difference. These digital approaches also offer further opportunities for less-polluting, more energy-efficient models that we may see realized through the emergence of the Metaverse environment over Web 3.0.& Leveraging the emerging technologies will enable even greater interaction, deeper immersion and more refined simulations that are currently reserved for on-campus delivery in laboratories and analogous physical facilities. These advances are closer than we may think, with experimental versions rolling-out this year and more robust platforms to be firmly implanted in 2025.

Who in your institution is looking at online learning with an ecological vision? Is there a system in place to track and compare on-campus to online sustainability? Are there ways in which you can further enhance sustainability through blended and online approaches?

This article was originally published in Inside Higher Education’s Transforming Teaching & Learning blog.

Online learning has evolved over the past 25 years from a niche position on the margins of higher ed to the leading driver of growth in enrollment and innovation.

Research collaboration, information sharing and informal instruction has roots deep in the development of the internet and analogous networking such as the PLATO system prior to even the World Wide Web. After the internet began to spread, significant numbers of for-credit classes emerged in the mid-1990s, not long after the development of the first graphical web browser, Mosaic, in 1992.

It is fascinating to go back in time to 1997 to see how Archie Comics depicted online learning in 2021, a quarter century into the future. Annie Reneau annotates and reprints the comic strip titled “Betty at High School 2021 AD.” A remarkably accurate vision of what online learning has become is revealed.

Yet, for a number of years, the delivery of courses and degrees online grew rather slowly. For some years after its inception, online enrollments were not tracked formally by the National Center for Educational Statistics. Distance learning was considered the poor stepchild of the traditional campus-based experience. However, with slow, steady growth, by 2014 the NCES reported that more than five million students out of a total of more than 21 million in college were enrolled in at least one online class. That amounted to some 25 percent of all students.

By 2020, overall college enrollment had dropped to fewer than 19 million with some 14 million taking at least some online courses. That amounted to nearly 75 percent of all students. Of course, these figures were greatly impacted by the pandemic. The first case of COVID-19 was reported in the U.S. on Jan. 20, 2020. Yet, even before the arrival of the pandemic in the U.S., in the fall of 2019, seven million of the 19 million college students (37 percent) were taking at least one online class.

So, while overall enrollment at U.S. colleges and universities dropped by some two million students from 2012 to 2019, the number of students taking online classes had grown from five million to seven million. Even prior to the move to remote learning in the pandemic, online learning had established itself as an effective mode of delivery in higher education in the U.S.

Often forgotten in considering overall enrollment in credible online learning programs is the rise of the MOOCs. In 2012, the founding of major MOOC providers Coursera and edX brought many prestigious universities online to create a worldwide reach at an affordable price through the economies of scale. Class Central reports at the end of last year, there were 220 million MOOC learners worldwide enrolled in classes developed by 950 universities, including 70 MOOC-based degree programs. Too often, these are considered separately from the enrollments centered at the campuses. Yet, they are offering classes, granting degrees and drawing on the pool of potential learners within the U.S. as well as internationally.

Online learning has grown from a marginal niche of higher ed to the largest provider of postsecondary learning in the world. We are now on the cusp of yet another technological evolution in the delivery of online learning. The advent of the metaverse in higher education is closer than many casual observers may think. By 2025, we will begin to see significant numbers of offerings using avatars and immersive technologies such as virtual reality, augmented reality and extended reality engaging learners at a distance.

This move will further propel online learning to the forefront of postsecondary education. It is the natural progression of the technology and networking infrastructure to support the pedagogy of engaged, personalized and immersive learning. Using the higher bandwidth and lower latency of 5G wireless and 10G cable, prospective students will be able to access stunning simulations and infinitely repeatable and adaptable learning modules to most successfully attain the skills and knowledge they seek for careers and personal fulfillment.

It is an exciting time to observe and participate in the acceleration of innovation in higher education. However, in order to be successful, institutions must embrace the technologies today to begin to deploy sandbox environments for their faculty and designers to prepare for the future that awaits just a couple of years ahead. Do you have developmental immersion laboratories for your faculty and staff to prepare for 2025? Who at your university is advocating for the integration of VR, AR and XR into online delivery? Are you already collaborating with industry and business in developing the most effective and relevant technology-enhanced online programs that will meet their needs? Those who lead in these ventures will set the standards and gain the recruiting advantage in higher education.

This article was originally published in Inside Higher Education’s Transforming Teaching & Learning blog.