Reed's Ruminations: A Blog by Dan Reed

Higher Education in the 21st Century

N.B. In rapidly changing, global knowledge economy, social, cultural, and economic advantage accrues to those societies that cultivate, nurture, and empower all of their citizens via advanced education, freeing each person to pursue their individual dreams, to the mutual betterment of all. 

On May 12, 1780, John Adams, then in France as part of a diplomatic delegation for the still nascent United States, penned a poignant letter to his wife, Abigail, in which he described the manifold and beguiling beauties of Paris.  Anyone who has strolled down the Champs-Élysées or visited the Palace of Versailles knows instinctively and immediately why Adams was so impressed.  (Mind you, that other modern wonder, the Louvre Museum, did not open until 1793, long after Adams had sailed home.) 

In a forward nod to Abraham Maslow’s hierarchy of needs, Adams resignedly acknowledges that his duty and commitment to an aborning country then struggling for its very existence must take precedence over his personal interests and desires. No matter how much he might yearn for different circumstances, immediate necessity must triumph over the desired:

I must study politics and war that my sons may have liberty to study mathematics and philosophy. My sons ought to study mathematics and philosophy, geography, natural history, naval architecture, navigation, commerce and agriculture, in order to give their children a right to study painting, poetry, music, architecture, statuary, tapestry and porcelain.

Across more than two centuries, Adams’ lament still rings true, albeit with amendments to embrace equity for all. The luxuries of time and resources, made possible by the successes of previous generations, afford their blessed progeny to pursue intellectually and emotionally rewarding endeavors of all kinds – art, music, literature, science, engineering, medicine, business – beyond those dedicated to immediate sustenance and survival.

Adams elegant characterization of the seeming dichotomy between present exigencies and an imagined, better future is now manifestly and explicitly visible in our debates about higher education as a public good accessible to all or a private benefit to only those willing and able to pay, as a birthing place for thoughtful and discriminating citizens of a democratic society or a workforce training and skills delivery system in a globally competitive world.

In a perfect world, each child would be educationally empowered and free to live a life defined by the content of their character, the scope of their talent, the reach of their dreams, and their willingness to work. Sadly, we do not live in that perfect world.  We must do better and do so now.

The circumstances of birth, gender, ethnicity, socioeconomic status, and a host of other factors all too often circumscribe a child’s future, with opportunity crushed and dreams stillborn. In theory, there is no difference between theory and practice. But in practice, there is.  We must do better and do so now.

Life’s Challenges and Exigencies

The students of our public research universities are neither socioeconomically, culturally, nor ethnically homogeneous. In that diversity lies both our strength – we all better when we both learn from others and respect and value our differences – and our educational challenge, for not all begin their educational journey on an equal footing.

For the sons and daughters of the rich and powerful, college is a place for maturation, exploration, and education. They have the freedom to stumble and recover, secure in the safety that societal status and money provide. The path for others is more narrow and difficult, even for the increasingly financially challenged middle class. Whether first generation, immigrant, underrepresented, or poor, college can be both a rare chance and a desperate struggle. As poor, first generation college student, on this I speak from some personal experience. (See Transforming Lives Via Public Higher Education and A Taste of Sherbet.)

Far greater than my own, students of color face compounded challenges alien to most and unimaginable to many. Biases – implicit and explicit – can and do make them feel marginalized and unwelcome, carrying social and cultural burdens that majority students neither see nor feel but sometimes themselves foster, whether intentionally or unintentionally. First generation students, regardless of background, often experience imposter syndrome and lack the social support networks common in families for whom college has been a multigenerational experience, with no familiar place to seek counsel and support when challenges arise.

Finally, life has a way of intruding in expected and unexpected ways. Despite our national angst over student debt and graduation rates, many students who fervently hope to finish a college degree never do, and an even larger fraction lack the opportunity to try. The reasons are myriad and diverse, including poor educational preparation from underfunded primary and secondary schools, lack of finances to pay tuition and housing, a multigenerational family needing support, feeling unwelcome and out of place, or simply not seeing curricular relevance to their personal objectives and needs. 

The American Dream was built on the shared principles of economic opportunity and upward mobility. The idea that everyone deserves a fair shot – not a guarantee, but a fair shot – to better their socioeconomic circumstances through hard work and determination is a central tenet of the American social contract.  Today, the lifeline of higher education and successful pursuit of the American Dream is increasingly out of reach for a growing fraction of the U.S. population.

Recognition of higher education’s importance to our nation’s future is not a partisan issue.  Multiple U.S. President’s from both parties have repeatedly convened august bodies to recommend ways to improve K-12 and post-secondary education, beginning with the 1946 Commission on Higher Education for American Democracy, commonly known as the Truman Report.  That report recommended expansion of federal financial aid for college students and the creation of a community college system, noting

If college opportunities are restricted to those in the higher income brackets, the way is open to the creation and perpetuation of a class society which has no place in the American way of life.

Despite these stentorian calls for action, a large fraction of children born in poverty still remain there, and less than 15 percent of students from the lowest socioeconomic bracket earn a bachelor’s degree by age twenty-four. No euphemistic intellectual legerdemain can hide the ugly truth of our current situation. It is neither unfortunate nor regrettable; it is morally and ethically wrong. Beyond educational opportunity as an ethical imperative, it has deep and profound justifications on economic and competitiveness grounds.  (See The Hopes of Parents and the Dreams of Children on the importance of giving every child a chance.)

Change in the Wind

Public research universities are in the business of helping people. This is especially true in times of accelerating and disruptive change.  Compounded by the consilience of globalization, each year now brings disruptions that once defined generations. In an earlier time of rapid change, the land-grant universities, authorized by the 1862 Morrill Act, were created to spread new agricultural and mechanical knowledge and “promote the liberal and practical education of the industrial classes in the several pursuits and professions in life.”  In modern parlance, the objective was to educate an underserved population, one whom extant higher education neither welcomed nor served.

Similarly, the Servicemen’s Readjustment Act of 1944 – the G.I. Bill – brought millions of veterans to college and university campuses, and it firmly rooted the graduates in the expanding middle class when many feared a post-war slide into recession. The G.I. Bill, along with post-World War II government investment in academic research, further expanded during the Cold War via the National Defense Education Act of 1958, reshaped academia and created the modern research university. Finally, the Civil Rights Act of 1964, the Higher Education Act of 1965, and Title IX of the Education Amendments of 1972 broke down further legal and economic barriers to educational access, though we have by no means eliminated those impediments.

Today, urbanization, global communications, artificial intelligence, talent mobility, and the global knowledge economy are reshaping social expectations. These changes are disrupting the historical web of interconnected economic sectors, while rendering some professions superfluous and creating demands for new skills in others.  A recent McKinsey report, The Future of Work in America, discusses regional economic stratification and the anticipated changes in workforce needs in the next decades.

The National Science Board, of which I am a member, recently issued two reports raising similar concerns.  The first of these, on The Skilled Technical Workforce, emphasizes the need for greater investment in community college technical training. The second, on The State of U.S. Science and Engineering, paints a worrisome picture of the position of the United States relative to its international competitors.

Our world is changing rapidly, and public higher education must adapt and engage as active and honest participants in renegotiating the societal compact.  Any compact reification begins with identifying the irreducible core – the essential values that define public research universities. Quite clearly, these are unfettered discovery (original scholarship and research), transference (student education and training) and fulfillment (societal engagement and services). Put another way, public research universities create new knowledge, transfer insights and ideas, and deliver solutions to societal problems. 

How universities do those things and in what measure are the subject of debate and negotiation. After all, the practices of a modern public research university span less than a single human lifetime. Some of the options will be new, and some will undoubtedly be philosophically challenging. (Remember that many feared the G.I. Bill would destroy U.S. higher education by bringing battle hardened veterans into academe.)

While protecting the irreducible core – the defining verities of academia – I believe we must be more organizationally nimble and flexible, more financially accountable and economically savvy, more societally engaged and responsive, more collaborative and transdisciplinary, and more team oriented. 

We face deep societal challenges – poverty, inequality, injustice, health and wellness, environmental sustainability, and economic uncertainty – and it is tempting to embrace a psychology of diminished expectations. But we also have unprecedented opportunities to unleash the creativity and talent of our citizens.  A university frees successive generations of human minds to realize their potential. We must not waiver in our commitment to the future of our students and our society.

Educational Futures: Beyond Degrees

The intellectual dichotomy between lifelong knowledge and near term skills is a canard, patently and demonstrably false, but the economic and social dilemma is very real. Our students arrive with manifestly different constraints and needs, and we must meet each of them where they are and respond accordingly. Put another way, one educational model and approach does not fit all.

I believe we must move beyond undergraduate degree completion as the sole, simplistic, and arbitrary metric of educational success. Degrees matter, but all education is valuable. It is neither a simple, linear process with a single terminus nor is it synonymous with an immediate continuation beyond secondary school. Degrees matter, but only insofar as they are talismans – social currency and indicators of our true objective, which is bettering the lives of our students.

If a student completes a single course and comes away with a deeper perspective on our world, we have added value to their life.  If another completes a certificate, gains a demonstrated competence, and achieves meaningful new employment, we have changed their economic circumstances for the better.  If we have informed and enlightened a community group, we have enriched our society, even if it were just a weekend seminar and discussion.

I believe we in academia must step back, and live up to our intellectual principals and ideals, remembering that no matter how high the academic ivory tower, its foundation and that of all public higher education, rest on a repeatedly renegotiated societal compact. The history of U.S. higher education is one of punctuated equilibria, with long periods of stability separated by brief interregna of extraordinary change, each coincident with shifting societal norms and expectations for broader access.

We must be more flexible in responding to the heterogeneity of student expectations and needs, while concurrently disintermediating knowledge delivery, certification of completion, and socialization across time and space. (See Pinball, War Games, and Universities.) I believe this means offering a smorgasbord of educational delivery modalities, content packages, and success models, each tailored to differing needs and constraints:

• Traditional degrees. The traditional undergraduate degree is the sine qua non of higher education, tested and proven, but adapting and adaptable to a rapidly changing world, preparing students for careers that do not yet exist, and educating them as critical thinkers and thoughtful communicators steeped in knowledge and wisdom.

• Stackable certificates. Not all students learn the same way, nor do they have similar motivations and objectives. Certificates, both credit and non-credit, organize a coherent body of knowledge with a demonstrable applicability and outcome, ranging from perspective on one of the liberal arts to concrete technical skills. If organized wisely, a combination of credit-bearing certificates can lead to a degree, though the certificates need not be completed sequentially, and they may be delivered either online or via traditional classroom modalities.

• Credit, non-credit, and convertible credit. The goal of educational delivery is the transfer of knowledge and recognized certification of that knowledge. Traditional credit with a transcript grade, earned on completion of an academic course, is the internationally recognized metric of accomplishment. It need not be and increasingly is not the only one. What matters is trusted validation of knowledge and competence. Non-credit certificates and badges are rising in importance as alternative validations.  Today, non-credit programs are often viewed as ancillary, second class activities on most campus; this must change. More importantly, students who acquire skills via non-credit mechanisms and later decide to pursue certificates or degrees may want to convert those accomplishments into academic credit.  We need more flexible mechanisms to establish knowledge and recognize that knowledge as credit.

• Competency certification. Not all knowledge is acquired in the virtual or physical classroom, nor is course completion fully synonymous with demonstrated competence. Life and work are themselves valued teachers. There are a variety of ways to prove and accept competence in lieu of course credit, ranging from academic and professional service testing through probationary credit to work experience

• Mixed online and placed-based education. Synchronous cohort learning on academic campuses will remain part of the educational ecosystem, both for student socialization and access to specific facilities and instrumentation, but it will be complemented by and in some cases replaced by online content delivery that is asynchronous from academic calendars. Online, asynchronous content delivery both allows students to participate based on personal schedules and also allows them to begin classes when the need arises. (See Online Higher Education for some lessons from the history of technology mediated education.)

• Lifelong/lifewide and just-in-time education. The time has long past when the knowledge and skills acquired before age twenty-five could serve one for a lifetime. Today’s worker can expect technological and economic shifts to render many of their skills obsolete every few years. The persistent skills are reasoning and communication, coupled with a desire to learn and relearn throughout life. We must move from a model of “education then life” to lifelong and just-in-time education that delivers new knowledge and skills as needed, via a variety of modalities and mechanisms, recognizing that many will be unable study in situ on an academic campus. For a few, this education will result in new degrees, but for most it will be by securing new credentials, badges, and certificates.

Some might say many of these educational roles and responsibilities are the proper function of community colleges and comprehensive universities.  That is true, in part.  Higher education is a system, with differentiated and overlapping, but complementary roles for community and technical colleges, comprehensive universities, and public research universities. 

However, in a rapidly changing world, public research universities are the critical incubators of intellectual discovery and translation, with national and international stature and partnerships.  They also attract a faculty and student talent base in part distinct from all others. As such, they bear unique responsibility as educational thought leaders and innovators, with the resources and capability to conduct educational experiments at scale. They are also charged with ensuring the economic competitiveness of our citizens and industry in a global knowledge economy.

University of Utah Analysis and Actions

As a flagship public research university and a member of the Association of American Universities (AAU), the University of Utah is a leader in basic research, knowledge creation, and scholarship.  It is also unwaveringly committed to educational access, broad-based liberal arts education, workforce skills training, and economic development.  

A University of Utah Student Success and Educational Futures Taskforce, composed of seventy five students, faculty, and staff members, assessed the current state and future needs of higher education in Utah, based on a charge to consider our changing world and the needs of Utah’s citizens.  Composed of six working groups – facilities and infrastructure; financial analysis; enrollment management, marketing and communications; student success and services; educational delivery and partnerships; and graduate student success – the taskforce outlined a series of recommendations intended to reduce student costs, expand educational access, and deliver targeted, just-in-time training. Common themes from the recommendations include:

• Diversifying pathways to student success by developing alternative credentialing options, improved pathways for transfer students, expanding undergraduate student experience roadmaps, improving support for graduate students and programs, and developing strategic partnerships with employers.
• Expanding online offerings and, where appropriate, using technology to increase educational accessibility, affordability, and inclusiveness.
• Utilizing the University’s physical infrastructure to its fullest by increasing student and mixed-use housing, improving transportation options, and optimizing the allocation of classrooms and teaching facilities.
• Ensuring students have a sense of belonging through individualized attention and support, deeply engaged learning experiences, a robust and inclusive campus community, on-campus career opportunities, and coordinated health and wellness programs.
• Continually revising and adapting initiatives to ensure consistency with the University’s core values: student success and engagement, research and teaching excellence, diversity, sustainability, global vision and strategy, community, and leadership.

In response to the taskforce recommendations, the University is launching several initiatives, including:

• For Utah The For Utah Scholarship creates a fully funded path to a University of Utah degree by covering four years of tuition and fees for Pell Grant-eligible Utah residents. As a result, the fall 2020 entering class was the most diverse in the University’s history, though we still have far to go to ensure broad access.

• Inexpensive all online degree completion. The University of Utah offers lower cost tuition for students taking all classes online as part of a qualifying online undergraduate degree program. This special all-online tuition rate help students who have started college finish their degrees and graduate, even if they cannot return to the campus. (Sadly, we were forced to temporarily defer this program during the COVID-19 pandemic.)

• Expanded credit and non-credit certificates. The University is rapidly expanding its suite of both non-credit and for credit certificates, targeting domains with where there are critical job shortages across Utah. Examples include software development, data science, and entrepreneurship.

• Integrating continuing education and online learning. Reflecting the continuum of learning objectives and the need for fluid transition between non-credit and for credit learning processes, this integration is enabling coordinated management of all aspects of non-traditional education, under the supervision of an Assistant Vice President/Dean.

• Predictive intervention and support. The best time to help students is before they fail, allowing time for recovery from early academic missteps. While protecting and respecting privacy, data can support powerful analytic and predictive interventions, allowing advisors and instructors to work with students while there is still time to recover, both in individual courses and in certificates and majors. This will rely on a combination of commercial software (e.g., Civitas) and local software and data.

• Storefront and electronic services. A large and growing fraction of students are “non-traditional” – they have lives, jobs, and families outside academe, and many lack the flexibility to visit academic support offices during normal business officers. Moreover, the born digital generation expects anywhere, anytime access.  The University of Utah plans to offer advising and consulting services at multiple sites.

• Skill and aptitude assessment. Accurate assessment of student knowledge and skills, via leading edge measurement tools can help students understand their aptitudes and preparations for study emphases and reduce the time needed to complete degrees and certificates by validating extant competencies. The University seeks to adopt and adapt assessment tools that can maximize student success.

• Enhanced student support. A sense of community and belonging is key to student success, enabling students persevere in the face the inevitable challenges students face.  Among many other programs, the University of Utah has created Student Ambassadors who share their experiences with prospective students and parents, Student Success Advocates who serve as peer mentors and advisors, Living Learning and Theme Communities where students share common courses and deeply engaged learning experiences that offer practical and collaborative opportunities to engage communities and the world.

• Faculty mentoring and inclusion. Expanded faculty onboarding and training are essential to preparing new faculty and new administrators to respond effectively to shifting student needs.  These services include (a) training search committees in best practices for recruiting and hiring a diverse faculty, (b) sharing best practices for student mentoring and advising, (c) and support and training for new faculty and new administrators in culture and processes – leadership, education, research and scholarship, and service.

• Corporate and business partnerships. Regularly upgrading the skills and degrees of employees is in the best interests of employers, as it provides the insights, training, and perspectives that allows employees to grow and adapt to changing business circumstances. The University seeks to partner with Utah and national companies on certificate and degree programs for employee and corporate benefit.

Coda

In the Christian tradition, the New Testament (Acts 16:9-10) says a vision appeared to the Apostle Paul  in the night, “A man of Macedonia stood and pleaded with him, saying, ‘Come over to Macedonia and help us.’ Now after he had seen the vision, immediately we sought to go to Macedonia, concluding that the Lord had called us to preach the gospel to them.”

The world gospel is an Old English translation of the original Greek word, εὐαγγέλιον, meaning “good news.” The preservation, creation, and transmission of knowledge are defining attributes of our civilization, and our educational system is an embodiment of the ever-expanding 21^st century “good news.” Education transforms lives, lifts generations out of poverty, nurtures our democracy, fuels innovation, and creates our future.

Our citizens are pleading; we must come help them, without judgment and in partnership. All education, regardless of scale or scope, is valuable. There is no dichotomy between knowledge and skills, but the guilt of our dilemma and our failure to act are very real.

Understanding and Explaining: The Feynman Technique

Richard Feynman, the late Caltech physicist and Nobel Laureate, perhaps best known for his work on quantum electrodynamics, was also a thoughtful explainer of science.  Already a physics rock star, his 1961-1963 Caltech undergraduate lectures, designed to reinvigorate the undergraduate educational experience, arguably became his most famous work. Compiled as The Feynman Lectures on Physics, they have sold over 1.5 million paper copies and are now available online as well. Anyone reading the compiled lectures or viewing the recordings will immediately recognize the contents as brilliant, complex, and subtle, pitched perhaps even above the high intellectual level of Caltech undergraduates, where being “just an average genius” could well mark you as an underperforming student.

Alas, I never met Feynman, though I had hoped I would. As a young whippersnapper assistant professor at the University of Illinois in the 1980s, I was pursuing parallel computing projects related to the Caltech Cosmic Cube and ongoing work at the Jet Propulsion Laboratory (JPL). (My Ph.D. dissertation was on the then crazy idea that we might build supercomputers using large numbers of microprocessors.) I agreed to serve on a panel at JPL simply because Feynman had agreed to serve as well. I wanted to discover for myself if even a portion of the oft-repeated stories were true.  Unfortunately, by then, Feynman was too sick to participate, and he died soon thereafter from the effects of cancer.

Just a few years before this, my friend and later Microsoft colleague, Tony Hey, had worked with Feynman to convert a second lecture series, on computation, into another book, the Feynman Lectures on Computation. However, this essay is about neither Feynman’s physics or computation insights, but about how to first learn and understand deeply, then explain simply and clearly. 

Feynman was unparalleled in identifying the irreducible core of any scientific topic and elucidating it with clear and simple language. If you doubt me, remember his iconic ice water demonstration of O-ring failures during the Rogers Commission investigation of the space shuttle Challenger explosion. As he later opined on the dangers of go fever, “The first principle is that you must not fool yourself, and you are the easiest person to fool." (See Nature Cannot Be Fooled.) 

Feynman’s simple, yet powerful four step approach to understanding a topic and sharing it with others has been codified in the now eponymously named, Feynman Technique:

• Choose a topic, study it and the interrelations among its components
• Explain what you have learned, simply and clearly, to a child
• Identify and fill the knowledge gaps exposed by your explanation
• Refine and simplify your explanation and repeat as necessary

It seems simple, and it is, but as Leonardo da Vinci reputedly said, “Simplicity is the ultimate sophistication.” Let’s deconstruct each of these four ideas, with a few personal detours along the way.

Choosing and Learning a Topic

Entire forests have been decimated by pundits and experts, all pontificating on the art of learning. Yes, you learn faster and more efficiently if you have had a good night’s sleep, have eaten breakfast, and (hear me, college students) are not hungover. Nor is a yellow highlighter required, though it can help. Learning is not a black art, it simply requires patience, diligence, and some paper and pencils.

Pick a topic you want to understand, something not so broad as to be an abstraction. The Theory of Everything is not the place to start, unless you are a theologian or cosmologist.  Instead, choose something clear and specific (e.g., Why is grass green?) that can be understood in terms of simpler concepts, then write down everything you know about the topic.

The act of writing will undoubtedly raise some questions; find the answers, and write them down too.  Finally, organize and reorganize what you now know into a coherent story.  Throughout, look for missing elements and contradictions. Ask yourself questions and see if you can derive the answers from what you now know.

I wasn’t joking about the pencils. Writing (or typing) is a powerful way to force oneself to think about ideas and to internalize their relationships as a coherent narrative.  For these reasons, good teachers, whether in secondary schools or universities, always tell students to take their own notes, even if the textbook or course materials contain the same information. 

Learning is not a passive process; it is an active one that requires questioning how and why the jigsaw puzzle pieces fit together, and if what you have been told is internally consistent. If you exhaust the pile of known pieces, and the puzzle is still incomplete, congratulations, you have identified the need for original research.

In his biography of Feynman, James Gleick relates a story about Feynman studying for his qualifying examinations, one of those life altering transition points for every putative PhD student. In Gleick’s telling, Feynman created a book of study notes:

On the title page he wrote: Notebook Of Things I Don’t Know About. For the first but not the last time he reorganized his knowledge. He worked for weeks at disassembling each branch of physics, oiling the parts, and putting them back together, looking all the while for the raw edges and inconsistencies. He tried to find the essential kernels of each subject.

As Feynman knew well, even as a graduate student, rather than rote memorization or blind acceptance of textbook statements, you must assemble the pieces yourself. Only by peering behind the wizard’s magic curtain, studying the theme park ride’s engineering, repeatedly asking yourself how and why, then reproducing what you have seen, can you truly be confident you understand.

 If you cannot recreate an idea from its elementary components, you do not really understand it -- knowing something is not the same as knowing the name of something.  It is why teachers always tell students not to memorize formulas, but to understand the principles. From that, one can derive the formulas.  I agree, but it is best to do both.

Now about that green grass; it is a scientific and biological marvel. Understanding how it functions in the biological ecosystem and why it is green requires internalizing several key topics, among them the electromagnetic spectrum, differential absorption, photosynthesis, chlorophyll (itself worthy of a deep dive), quantum efficiency, ATP, optics, visual perception, and cognition.  (For extra credit, consider whether grass would be green if the sun were not a G-type main-sequence star.)

There’s a lot to assemble and connect before one can thoughtfully and clearly answer a child’s question, “Mommy, why is the grass green?” Doing so while not hiding behind jargon is even harder.

Explain What You Have Learned To A Child

Feynman himself said that the best way to know if you have well and truly understood a concept is to explain it to someone else. There is no better litmus test of one’s own understanding than explaining something to someone young. A child has a shorter attention span, a smaller vocabulary, and far fewer emotional filters than most adults. Moreover, a child will ask excited, impertinent, and repeated questions in ways that the social conditioning of adults would prevent.

Nothing can humble an adult more quickly than a child’s persistent questions. Therein lies the beauty of explaining ideas to children.  They have neither the social filters to prevent themselves from asking uncomfortable questions, nor the shame in admitting ignorance.  They expect clear, simple answers, all consistent with their own experience.  Using unnecessarily complex technical jargon is also a sign of, at best, intellectual laziness, and at worse, one’s own shallow understanding. 

Let me be clear. I believe every child is born a scientist, innately inquisitive and curious how the world works. They embody the essence of science, doggedly asking questions, being unsatisfied with answers that will not withstand scrutiny, and being utterly unimpressed by intellectual stature or pedigree. A resigned and frustrated appeal to authority – “because I said so” – is an indicator of elucidative failure. Though the incessant, “But why?” may seem like an infinite regress, fear not.  It’s not turtles all the way down, and the Münchhausen trilemma lives to fight another day.

The classic xkcd Up Goer Five cartoon about the Saturn V rocket, which uses only the ten one hundred most common words (thousand not being among them), illustrates how challenging it can be to explain complexity via only simple words.  If you doubt me, try explaining why the grass is green using a text editor that limits you to just those one thousand (uh, ten one hundred) most common words.  (Grass is not among them; you’d best start with “green sticks that grow toward the sky” instead. This might also be a good time to think about explaining phototropism and the rabbit hole of multicellular biology.)

In a televised lecture, Feynman himself talked about the egalitarian nature of scientific exploration, noting, “It doesn't make any difference how beautiful your guess is, it doesn't matter how smart you are, who made the guess, or what his name is… If it disagrees with experiment, it's wrong. That's all there is to it.”  (See The Epistemology of Science.) 

Quantum Confusion and Uncertainty

Years ago, when I was a corporate vice-president at Microsoft, the company’s quantum computing project, Station Q, which was then located at UC Santa Barbara, reported to me as part of the eXtreme Computing Group.  Station Q was headed by Michael Freedman, himself a Fields Medal winner, in recognition of his work on the generalized Poincaré conjecture.

As part of our computing research, we regularly brought leading experimentalists and theoreticians together for a multiday workshop, all of whom were working on topological approaches to quantum computing.  The intellectual throw-weight of the invitees was a highly skewed sample of the smart kids club; everyone in the room had won their school’s fifth grade spelling bee.

Although I can impress unsuspecting undergraduates with a whiteboard discussion of quantum computing, superposition, Hilbert spaces, and Bloch spheres, I am by no means a quantum computing expert. Hence, I fully anticipated to become intellectually lost at some point during the workshop presentations, though I expected to understand the gist of each. As the first theoretician began speaking, I was dismayed, however, at just how quickly I was overwhelmed.  After just a few minutes, as complex and subtle mathematics danced and whirled, juxtaposed with “as you can clearly see” phrasings, I realized I had no idea what the speaker was discussing, or even the point he was trying to make. 

Just as I was about to sigh with resignation, open my laptop, and begin responding to my denumerable but enervating steam of backlogged email, an equally accomplished experimentalist spoke up, saying, “Excuse me, but I have no idea what you are trying to say! Can we go back to the beginning, please?  I have some basic questions.”  As I looked around the room, gratified that I was not the only lost soul, the puzzled but relieved expressions revealed everyone – theoreticians and experimentalists alike – felt the same way.

All of the very smart, highly educated people in the room were confused, and not in the way Niels Bohr meant when, in a mashup of a Zen koan, a physics superposition joke, and Dadaist wordplay, he had commented, ““If you are not confused by quantum mechanics, you do not understand it.” Rather, we were confused due to inadequate and opaque explanation.

The speaker responded quickly and with good humor, asking where people had become lost.  What then followed was a lively give-and-take of questions and answers that led to mutual understanding, a pattern that continued throughout the day.  None of that would have happened had one person not evinced the intellectual courage to profess total confusion and an utter lack of understanding.

Although I was just a bit player in this quantum play, regrettably, I had starred in my own production.  As a senior graduate student, I had given a colloquium on my research, where I had excitedly derived all the queueing theory formulas underlying my work.  It was a disaster, leaving everyone else confused and me flustered and disheartened.  Afterward, my advisor pulled me aside and offered some sage advice, reminding me that the goal of a colloquium is to tell the audience what you have done, why it matters, and why they should care.  As he put it, “If you excite people with clear rationales and explanations, they will want to read the paper later to understand the details.”  Wisdom that.

Linguistic castles of idiosyncratic academic buzzwords frequently isolate individuals and disciplines, preventing collaboration and shared understanding. It is an unfortunate academic disease, and too few seek the Strunk and White treatment. (See Renaissance Teams: Reifying the School at Athens.) As anyone who has read (or tried to read) research papers or academic books knows all too well, we in academia often hide behind turgid, meandering prose.  In the name of intellectual precision, we seek to impress and sometimes to obfuscate, rather than elucidate and explain. Perhaps driven by intellectual insecurity, we fear clear explanation might imply our ideas are simple and obvious – and sometimes they are.   I have been guilty of this myself.

Remember, the primary purpose of communicating is not to impress others with one’s intellectual prowess and academic stature, it is to share ideas and invite discourse. A research colloquium, paper, or poster is a not a denouement, but a prelude to conversation, one where inevitable knowledge gaps are identified and rectified, the third step in the Feynman technique.

Identify and Fill Knowledge Gaps

If you have ever spoken to a grade school class, whether as a practicing scientist or as a part of a “take a parent to school” day, you know the questions can be far more challenging than those experienced during either a venture capital startup pitch or a research colloquium.  You need to know your stuff, because you will be asked, and you may discover that you are, in fact, not smarter than a fifth grader.

Humbled by such experiences, any teacher will readily confess that when teaching a class for the first time, even one in an intellectual area where they are an acknowledged expert, perhaps even the world’s leading authority, the teacher learns far more than any of the students.  Whether from the unexpected questions that reveal poor explanations, or in an advanced graduate class, questions with no currently known answers, the act of explaining is a test of one’s own understanding. Explaining anything shows others what you truly know and do not know, exposing the gaps in your own knowledge, and it makes you ask yourself questions.

Occasionally during lectures, most often during a graduate class, I have had a student ask me a question that truly made me pause and think, “Why is that really so?” only to realize I was not sure myself. At point, honesty is the only approach, “I do not know, but I will answer your question in detail at the start of the next class.” At that point, it is time for some faculty homework, or maybe some original research.

Why is that so?  How does this relate to that?  I was told this, but why is it true?  Is it actually true? Such questions are one of the purposes of PhD qualifying examinations, to assess a student’s knowledge base and readiness to conduct independent research. Do the student understand – at a deep level – or is the student merely parroting words, phrases, and concepts? 

They may be using a CRISPR to edit genes and polymerase chain reactions (PCR) to amplify DNA, or deep neural networks to classify Seyfert galaxies, but can they explain mitosis, stellar evolution, and the convergence properties of stochastic gradient descent? Mastery of the known is a prerequisite to exploration of the unknown. (See Research: When There Are No Answers in the Back of the Book.)

Refine and Simplify

Sadly, not all initial attempts at explanation succeed, as anyone who has taught or attempted to explain something to others will ruefully acknowledge. During their educational journey, each student develops a finely tuned sense of teacher quality and explanatory skill.  Within minutes, seasoned students can separate experienced and effective explainers from those less adept.  However, recognizing is not the same as doing, as more than one inexperienced teacher has learned to their chagrin.  Explaining something clearly and accurately takes both skill and practice, though there are best practices.

Good teachers watch their students while speaking, seeking non-verbal cues for explanatory clarity.  Confused faces trigger alternative explanations, additional decompositions, and new analogies.  Recognizing that it takes courage to admit ignorance, good teachers encourage and welcome questions, for they provide additional educational opportunities. If one student is confused, others almost always are as well. 

A teacher who is dismissive of questions is rarely an expert, but more often fears having their inadequacies exposed. Conversely, true experts have a deep reservoir of background knowledge on tap for interactions and clarifications. A willingness, even an eagerness, to entertain questions is a hallmark of someone who truly understands their subject and takes joy in sharing that understanding with others. Indeed, the joy of explaining something well is its own reward, reflected in enlightened faces.

Coda

There you have it – the Feynman technique for learning:

• Choose a topic, study it and the interrelations among its components
• Explain what you have learned, simply and clearly, to a child
• Identify and fill the knowledge gaps exposed by your explanation
• Refine and simplify your explanation and repeat as necessary

The next time a child asks why the sky is blue, do not send them to the encyclopedia. Embrace the curiosity and wide-eyed wonder, sit down and begin explaining, using words they understand. Share the passion and the joy! Few things in this world are more fun and exciting than science, if explained well and correctly.  (See Science: It’s About the Wide-Eyed Wonder.)  Under no circumstances should you consider saying – Rayleigh scattering.  Though true, it is an obfuscation, not a clarification. Hiding behind big words and technical phrases is a “baffle them with B.S.” parlor trick to hid one’s own lack of understanding and intellectual depth.

Study the camber of the wings, twist the ailerons, move the rudder, work the pistons, spin the propeller, oil and assemble the parts.  Build a model yourself. Then, when the intellectual airplane takes flight, you will understand how it flies, and you will not need fancy phrases like laminar flow or Bernoulli principle to explain how and why to others.  (And for the record, that grade school demonstration, where the teacher blows over the paper, watches it rise, and exclaims, “This is how airplanes fly!” is not quite the correct explanation of lift.)

Finally, remember Feynman’s admonition, “Nearly everything is really interesting if you go into it deeply enough.”   Go, learn, explore, explain, celebrate!

Missing Talent, Missing Opportunities, and Losing Ground

Growing businesses and economies depend critically on a pool of educated people, leading edge ideas and technologies, robust investment, and growing market opportunities.  Whether advanced manufacturing, information technology, energy, medicine and healthcare, or a host of domains, in an increasingly competitive global economy, continued innovation, fueled by a judicious combination of private and public sector actions, is key to success. Implicit in this model is an educational system that attracts and trains the talented individuals needed by businesses and a research and development environment that continually catalyzes new products and services. 

Every two years, the National Science Board (NSB) assesses the state of the U.S. research and development enterprise, issuing a Congressionally mandated report on science, technology, engineering, and mathematics (STEM) education and U.S. investment in research and development. How is the U.S. faring in education and innovation relative to the rest of the world?  Simply put, not nearly as well as in the past.

The NSB is a group of twenty-four scientific experts, appointed by the U.S. President for six-year terms.  The NSB has two statutory responsibilities. First, it provides strategic, policy, and budgetary oversight for the National Science Foundation.  In its second role, most relevant here, it provides advice to the White House and Congress on science and technology issues, STEM education, and workforce concerns. I am honored to serve as a member of the NSB.

This year’s NSB report, The State of U.S. Science and Engineering 2022, shows that other countries have learned from the historical successes of the U.S., and they are dramatically increasing their investment in STEM education and research and development.  Even as U.S. intellectual output has grown, China has surpassed the U.S. on several key metrics, including the number of science and engineering research publications and the number of issued patents, and it is at near parity on the number of science and engineering doctoral degrees awarded. Overall, the U.S. still leads, but not by nearly as large a margin as in the past.

Let’s begin by examining STEM workers in the U.S., which now comprise 23% of the total U.S. workforce. These STEM workers include a wide spectrum of occupations, ranging from scientists, engineers, and healthcare workers through technicians and workers in production and construction.  About 16 million of these STEM workers hold a bachelor’s degree or higher, with the remaining 20 million comprising the skilled technical workforce (i.e., with associate degrees, certificates, and other technical training).  Reflecting their criticality to the U.S. economy, throughout the COVID-19 pandemic, these high paying STEM jobs were resilient, with STEM workers employed at a higher rate than their non-STEM counterparts – at all education levels.

Sadly, U.S. STEM education leaves many students behind in our K-12 schools. U.S. 15-year-olds rank between Hungary and Turkey in national mathematics proficiency, behind the large majority of industrialized economies. However, the challenges begin even earlier. On average, U.S. 8^th grade students of all ethnicities who are eligible for free or reduced school lunches fail to achieve mathematics proficiency, but the disparity is most pronounced for Black, Hispanic, Native Hawaiian or Pacific Islander, and American Indian or Alaska Native students.  If a student is fortunate to be in a higher socioeconomic status (SES), the mathematics news is not much better.

Moreover, K-12 STEM teachers with fewer than 3 years of experience are more prevalent at schools with high-minority or high-poverty populations, perpetuating generational inequities. Nor does this inequitable state of affairs improve in college and post-graduate studies, where women and individuals of color are substantially underrepresented in STEM fields. 

Why is it culturally acceptable in the U.S. to say, “I’m bad at math and science” when few would willingly confess to semi-literacy by saying “I don’t read very well.”  Unless we reward and remunerate STEM teachers, celebrate student STEM accomplishments, and value scientific and mathematics literacy, the U.S. is likely to continue falling further behind its global competitors.

In a previous life, I was a Microsoft corporate officer, and met I often with government leaders from around the world. In my travels, I consistently emphasized the importance of a country’s people as its only truly renewable resource. I also reminded leaders that talent comes from everywhere – from all ethnic groups and socioeconomic strata.  Wise leaders nurture and cultivate talent everywhere, without exception.  The U.S. needs to heed that lesson.

If the U.S. STEM workforce were truly representative of the U.S. population, millions of additional skilled workers would be inventing the future and supercharging the U.S. economy. These “missing millions” are a huge lost opportunity for the U.S., all at a time when an increasing fraction of jobs require critical thinking, technical knowledge, and mathematical reasoning.

To meet a portion of this shortfall, the U.S., has historically imported talent, particularly at advanced levels. In my own discipline, computer science, over 60 percent of Ph.D.’s. working in the U.S. are foreign born. Many of them came here because U.S. research universities remain the envy of the world, attracting some of the world’s best and brightest.

However, the numbers of immigrant graduate students have declined recently due to COVID-19, shifting U.S. immigration policies, and rising opportunities in their home countries. U.S. academic preeminence is also increasingly at risk, as state support for public higher education declines, tuition rises, and competition for limited research funding intensifies, making it harder for domestic students to attend college, continue graduate studies, and pursue faculty careers.

Continued U.S. scientific and engineering leadership, with its manifest economic benefits, is not a birthright.  Every business person instinctively knows the truth of the aphorism from Intel’s Andrew Grove:

Success breeds complacency. Complacency breeds failure. Only the paranoid survive.

Leadership is built on sustained and strategic investment in education and critical workforce skills, as well as a collaborative industry and government research and development investment engine that fuels new businesses. The U.S. is now at a critical inflection point.  It is time to up our game by investing in our people and infrastructure to compete more effectively in the 21^st century.

Academia: Who We Are and Why It Matters

N.B.  In my role as Senior Vice President for Academic Affairs (SVPAA) at the University of Utah, I recently reiterated the university’s dedication to and unwavering support for academic freedom – the right to pursue intellectual directions freely and unfettered, along with the associated societal responsibilities – as the bedrock principle of our scholarly enterprise. The following message was part of that statement.

In the midst of uncertain times – a pandemic, cultural and political divisions, persistent social inequities, and evolving environmental change – it is also important to pause and remember who and what we are and why open intellectual inquiry is so fundamental to our democracy.  That is especially true in times of Sturm und Drang, though such times seem to be with us always. All too often, the prosaic exigencies of publication deadlines, course schedules, and research proposals can overwhelm us and cause us to lose sight of foundational principles.

We have the great privilege and high honor to be members of the scholarly community at one of this country’s great public research universities.  As such, we are curators of the storehouse of human knowledge, one built, sustained, and expanded across generations at great cost and sacrifice, a shared birthright preserved for the benefit of all of humanity. 

As researchers and scholars, we are not mere custodians of the past. We are active explorers of the great unknown, asking penetrating questions, and seeking answers to difficult questions. In so doing, we expand humanity’s understanding, for the benefit of current and future generations. Each of us has known the joy of scholarly insight, when first seeing new connections, elucidating a phenomenon, or understanding relationships and principles. That joy is extraordinary and transcendent – in that moment of discovery, one can live a lifetime, and a thousand lifetimes would not be enough.  Make no mistake, this insatiable desire to know and understand is a defining attribute of our humanity; it is an urge older than history, a siren that calls us to the future.

Powerful though that impulse is, it does not solely define us, for we do so much more than steward and expand the great mosaic of human knowledge.  We joyously share that knowledge and those newly won insights with inquisitive minds, young and old.  Even more importantly, we teach our students the one truly enduring life skill – not only how to learn what is known, but how to seek new knowledge and create new insights from the unknown. And in so doing, we teach them to understand and evaluate subtilty, nuance, conflict, and complexity; and how to think deeply, critically, and holistically about it all.  This is the quintessence of the active and engaged scholarly education that only a great research university can impart.

Most of all, we seek to live the words of Plutarch, the Greek philosopher, believing, “The mind is not a vessel to be filled, but a fire to be kindled.”  A mind set on fire with knowledge and kindled with critical thinking blazes for a lifetime, as a thoughtful citizen of our state, our country, and our world.  In the transgenerational trust, we are the midwife of student futures, one mind at a time.  We owe each and every parent and child the opportunity and our support to pursue those dreams, regardless of their background, their ethnicity, their gender, their creed, their economic status, or the circumstances of their birth.  As Chaucer said, gladly would we learn, and gladly teach.

Finally, we engage our communities, our state, our country, and our world, sharing the benefits and bounty that accrue from their support and our unfettered intellectual explorations.  Whether in science, technology, engineering, and mathematics (STEM) disciplines, health and medicine, the social and behavioral sciences, the humanities, or the creative arts, we share our insights and our ideas for the common good. We work to solve the world’s most pressing problems, partnering in the spirit of humility, and marshalling the diverse disciplinary resources of our institution in a collaborative way.

I conclude as I began. Society has vouchsafed in us an extraordinary privilege, as scholarly stewards and explorers, individually and institutionally entrusted with the hopes of parents and dreams of children, united in our ardent desire to create a bright and beckoning future. It is a deep and sacred trust, a principled compact embodying mutual expectations and shared responsibilities.  We must honor it each day with our words and deeds.  This is who we are and why it matters, now more than ever.

Coda

In the words of Tolkien, himself an Oxford scholar,

All that is gold does not glitter;

Not all who wander are lost.

The old that is strong does not wither.

Deep roots are not reached by the frost.

The knowledge and wisdom we seek are the enduring gold that does not glitter. As we wander in search of new knowledge, we are inveterate, peripatetic explorers, but we are not lost. The deep truths and open questions about our world and the human condition endure, untouched by transient vicissitudes, but illuminated and expanded by new insights and ideas.

My Balm in Gilead

COVID-19 has disrupted our lives in so many ways – commerce and trade, personal livelihoods and economic vitality, family and social interactions, health and wellness (obviously), mobility and travel, and education, to name just a few. This global pandemic has also exposed deep social inequities in new ways, convolved with political disarray and often dysfunctional government processes.  (See On the Etiology of Heroes for a few thoughts on a way forward that calls on our best to address the challenges before us.)

Meanwhile, cue theme music over a video montage of transformed academia – grassy quadrangles devoid of human activity, sparsely populated classrooms denuded of desks, and research laboratories accessible only by those in personal protective equipment (PPE).  As the music fades, the final cut shows me sitting in my home office, dressed in stereotypical Zoom attire – a business shirt and tie, visible on camera, complemented by off-camera sweatpants and slippers.

In this morality play, my character is a balding, myopic, astigmatic university provost navigating the ship of academe through the iceberg filled waters of these uncertain times, seeking to ensure fair and equal access, facilitate student academic success, promote faculty research and scholarship productivity, and safeguard staff wellness. It’s not an easy thing, and I have lain awake many nights, agonizing over decisions and their unexpected consequences.

About that balding thing; it’s neither an appellation nor a sobriquet, simply an attribute. A few years ago, I sent a saliva sample to 23andMe, curious what I might learn from my SNPs and the company’s database of expressed traits. Like Captain Renault, I was shocked, shocked, I say, when the report showed there was some ever so slightly elevated probability that my genetic profile might be consistent with male pattern baldness.  LOL, who knew?  It’s a cogent warning to consider carefully insights a modern GWAS can sometimes reveal. But I digress, lest I also pontificate on my childhood surprise, when glasses first let me see leaves on trees, rather than just a green blur atop a gray one.  Now back to the scene of the balding provost …

In my provost role, I regularly counsel faculty, staff, and students that successfully navigating this pandemic requires constant vigilance, determined collaboration, committed partnerships, and mutual support. A yearlong pandemic is an emotional and logistical marathon, not a sprint, and in the midst of unremitting stress, each of us must allocate some time and space to focus on our individual mental health and engage in activities that bring happiness and serenity.  In the spirit of “physician, heal thyself” where have I sought my own balm in Gilead?

So Many Books, So Little Time

In differing times and places, I have, unlike Poe, found books to provide a surcease for sorrow. Books can teleport one into the mind of another’s memories and knowledge (non-fiction) or imagination and fancy (fiction). That a string of stylized symbols can record the thoughts of another, sometimes long dead, whose insights and ideas reach across time and space to illuminate and inspire, is itself an extraordinary thing, one that still fills me with unabashed wonder.

Arguably among humanity’s greatest inventions, these things we call language and writing are perhaps rivaled only by fire, agriculture, and science in their importance. In their embodiment via books and libraries, ideas and knowledge accumulate and set ready for transmission and uptake by successive generations of willing and malleable minds.

It’s no surprise then, that books were one of my first and most joyous childhood discoveries, a precursor to that other abiding love, science. (See Libraries: Arms Too Short to Feed the Mind.) With a good book, I could, then and now, sit transfixed for six, twelve, or even eighteen hours, oblivious to my surroundings, transported into worlds unknown and challenged by ideas beyond the reach of my experience and current understanding, each page crackling with enlightenment.

Emboldened, seeking meaning in an oft-confusing world, I sometimes try my own, feeble hand at the mystic art of writing, finding comfort and refuge in the feel of words and their juxtaposition to ruminate and communicate ideas. (Yes, I was a geeky kid who read dictionaries for pleasure, savoring both the etymology and the denotation. No surprise – myopia and astigmatism came early; baldness reared its sunburned head somewhat later.)

In a world of eight second sound bites and enervating ad hominem social media attacks, when Warhol’s fifteen minutes of fame seems like the imprimatur of immortality, meditative reflection and long-form written discourse now seem like lost arts. (See Contemplative Reflection and Instantaneous Communication and Just the Facts, Ma’am: Reasoning is Not Dead, Jim.)

At its best, writing is a contemplative Zen state where words and phrases spring unbidden from the recesses of your mind, bound by a set of unspoken rules and imagined mores and shaped by a lifetime of intellectual and emotional milieu. Part puppeteer, part curious observer, you are a transcriber of events in real and imagined worlds seen only through the uncertain lens of your mind. It is an exhilarating and sometimes frustrating art, at its best, informed by experience, wisdom, and passions. (See Eudora, You Got the Love?)

Some of my writing samples are archived on this website (www.hpcdan.org), and some others are shared only with select friends. You now hold one such weak musing in your digital hands. Those writers with the greatest gifts can touch our naked souls, but none of us can ever truly master the form. I know I never will, though I continue to try, and perhaps that is, in the end, enough. 

Pure Thought Stuff

Of late, I have returned to one of my other teenaged and lasting loves, the art of software.  (See A Feeling for the Code.)  As in any creative medium, there are hacks, artisans, and artists of the highest gift. Hence, I use the word art with thoughtful intent, for well-written software has an austere and ethereal beauty all its own, and like writing, it can bring joys unknown to all but the most committed and talented acolytes.

In his wonderful book, The Mythical Man Month, my friend and former colleague, Fred Brooks, writes elegantly of the joy of software and why it is so enthralling:

The Programmer, like the poet, works only slightly removed from pure thought-stuff. He builds his castles in the air, from air, creating by exertion of the imagination. ... The magic of myth and legend has come true in our time. One types the correct incantation on a keyboard, and a display screen comes to life, showing things that never were nor could be.

When fully immersed in the code, you hold in your mind an abstract world of your own creation, defined by the rules of logic, but mutable and capable of evolving in complex and unexpected ways, just as an author’s fully formed characters can take on lives of their own, sometimes surprising even their creator. In these moments, pure thought-stuff becomes incarnate and nested causal chains glisten with beauty like raindrops on a spring flower.

Reconciling the perfect world as imagined and the inevitably flawed creation then becomes an exhilarating and encompassing quest. Why did this happen?  How can that be true?  Inspired and chagrined by unexpected behaviors and sometimes subtle clues, the creator becomes detective, seeking insights and remediations that return the code to a state of grace.  The magic of myth and legend, indeed.

It can take hours to load one’s working memory with such a virtual world of software, and doing so necessarily pushes all other concerns from one’s mind. As Morpheus tells Neo in The Matrix, you must “free your mind” from all other thoughts, perspectives, and assumptions and follow the code. During that oneness, there are no other actors, no other concerns, and one can abide in the bliss of total immersion.  It is intellectual joy that unexpectedly changed our world. (See Reluctant Revolutionaries, the Trolley Paradox, and Ender’s Game.)

Such creativity and full cognitive loading brooks no exceptions and tolerates no distractions.  It can be broken by such mundane events as an unexpected telephone call, a colleague’s doorway interrogative, or an unwelcomed text message. In that momentary interruption, connections can disappear, insights can fade, and perspectives can be lost. That too is a fall from grace. (See On Cognitive Loading and Intellectual Hierophany.)

In the past few months, I have sought solace in the beauty and logic of such software, incarnated as the end-to-end development of a wireless environmental sensor network. As a potential extension to the SAGE research project of which I am a part, it offers a path to citizen science empowerment and real-time response to environmental change. The terms of art – ESP32, Raspberry Pi, Jetson, JSON, MQTT, InfluxDB, Grafana, LoRaWAN, TensorFlow – matter only to those in the discipline.  For me, the beauty and the cognitive load can, for just a few hours of the nights and weekends, free my mind, and in the midst of the COVID-19 pandemic, that too brings me peace.

Coda

Our culture and our future rest on mutual respect, sharing insights, ideas, and knowledge, and the empowerment of human minds and their ingenuity.  In the crucible of the pandemic, we must support and draw strength from one another. As I have noted before, these simple things matter most of all. (See The Simple Things Matter, Most of All Now.) Ultimately, that is humanity’s sustainable balm in Gilead.

Geek Gifts for the Holidays

The holiday season is here, with lights and festive celebrations of all kinds. Normally, I am loathe to offer holiday product endorsements, perhaps because, like you, I’ve been jaded by too many marketing campaigns and late night infomercials. (See The Ghosts of Holiday Shopping: Past, Present and Future.) Other than filing my taxes on time, acting before midnight tonight has never changed my life.  However, in a spirit of beneficence, I do make one exception to aid two connected, but suffering groups. I speak of course of geeks and their gift giving friends and family.

Let’s be honest; it’s hard to buy for geeks. Few would know that a signed copy of The Art of Computer Programming is a rare and precious thing, perhaps exceeded in value only by a Knuth reward check.  A copy of a Big Bang Theory DVD or a word of the day calendar just isn’t the same, though it helps if it is Klingon. 

So what’s a friend or family member to do when your geek smiles wanly and says thank you – for the socks? Fear not; even though the holidays are here, it’s not too late to trade those socks for a gift that will bring a delighted grin to your geek’s face, whatever their age.

Turing Tumble: Logic Is Child’s Play

Maybe you have a young geek, one interested in all things science related, and computing in particular. They may be too young for “the talk,” where you explain the dangers of unprotected ports, the subtleties of functors and futures, or the central dogma of the Church-Turing thesis, but they are still old enough to avoid specious logic, develop algorithms, and create working code.  (See Just the Facts, Ma’am: Reasoning is Not Dead, Jim.)

Turing Tumble ($69.95, ages 8+) is a game where players can build mechanical computers powered by marbles to solve logic puzzles.  In the spirit of LEGO-powered Turing machines, Turing Tumble exposes the logic of computers in a tangible way.  Developed by University of Minnesota professor and backed by a Kickstarter campaign, Turing Tumble is the real deal, combining marbles, levers, gears, and bits to teach logic and algorithms in an accessible way.  Just don’t let the adults play with it, or your child geek may never get it back.  And yes, I’m playing with mine over the holidays.

AWS DeepRacer: Start Your Engines

If you have an adult geek, particularly one who writes code for a living, this is the gift for you. AWS DeepRacer is a bit pricey at $399, but it’s the only gift your adult geek will want or need. AWS DeepRacer is a 1/18^th scale model car and Amazon Web Services (AWS) reinforcement learning toolkit to train your car for competition in either a real or a virtual racing league.

The DeepRacer can be also be driven manually via a joystick, and with an Intel Atom processor, HDMI port, and Ubuntu Linux, it can double as a serviceable, albeit somewhat slow, desktop computer. (Pro tip: Your GPU-accelerated Jetson Nano ($89 from Nvidia) is a great offline reinforcement learning training tool.)

If your geek is throwing around words and phrases like TensorFlow and generative adversarial network, while railing about deep fakes and social responsibility, relax.  Even if you think Sagemaker is the nom de plume of the family matriarch and her secret stuffing recipe, your geek knows that a reward function is more than a second helping of gravy and stuffing.  I will be racing mine in the living room tomorrow.

PDP-11 Emulator: When Nostalgia Reigns

If your geek’s native language is FORTRAN and they speak wistfully of the days when toggling absolute binary into the computer front panel was a rite of passage, you have an aging geek. They are likely to grow pensive when someone mentions the Great Editor War, modality, and meta keys. Viva Emacs; viva vi; those were heady and difficult days, when friends were forced to choose sides, and flames filled the nascent Internet. (See You Might Be a Computing Old Timer If …)

The PIDP-11 ($250) is a Raspberry Pi emulation of the iconic PDP-11/70, complete with hardware front panel lights and switches. If you want to impress your geek friends, comment on the orthogonality and beauty of the PDP-11 instruction set and smile knowingly. Even better, tell them the simh software supports all the old PDP-11 operating systems your geek knew and loved – RT-11, RSTS/E (my favorite), and UNIX V5, V6, and V7.

With the PIDP-11, you can toggle in code, or boot your operating system of choice, play with all the old system software tools, and even write or run old code. TECO lives!  (Warning: Some soldering is required to assemble the front panel, or you can skip the kit and do everything in software, albeit without that heady joy of blinking lights and toggle switches.)  Mine is on order.

Save the Detritus

Now it is possible you live in one of those increasingly rare places where the gray fog of nothingness lurks in the distance and same day or overnight package delivery is not possible. However, you still have the raw materials in your possession needed to satiate the emotional and intellectual yearnings of a nascent Time Lord, Dungeons and Dragons role player, Skywalker acolyte, or wannabe Gandalf.

Wired’s 2011 review of the All Time Best Toy Ideas ($0) exposes the truth: the detritus of your gift wrapping, along with some yard debris, holds the key to happiness.  Stick (Glamdring), box (TARDIS), string, cardboard tube (lightsaber), and dirt, these are the enduring toys for geeks and the rest of you, though the purist might insist on the addition of rock, hole, and mud puddle.

I’d explain more, but a launch window has been posted for my LEGO Saturn V.  I need to finish the LEGO launch gantry before the Mobile Launcher Platform can roll out of the Vehicle Assembly Building to pad 39A. If you were a geek you would understand why that is important.

Business, AI, and the Future

N.B. You can watch a video of the panel here, along with another summary.

A few days ago, I had the opportunity and pleasure to chair a panel on AI as part of the David Eccles School of Business (DESB) Alumni forum at the University of Utah. The panel members were local innovators and entrepreneurs Bassam Salem (CEO, AtlasRTX), Glenn Colby (Founder, Invarius), and Keelan Johns (Senior Director of Engineering, Clearlink).  My sincere thanks to each of them for participating.

I began the panel by observing that AI researchers have long bemoaned that AI is often defined as what they do not know how to do, rather than what they have accomplished. By that definition, AI has always been an unsolved problem.

I also noted that despite the prominence of AI in the popular consciousness, whether because of its much discussed influence on social networks or its renderings in movies, we are very far from creating a general-purpose AI, a goal-directed entity capable of independent activity and reasoning.  Put another way, HAL in 2001: A Space Odyssey, Skynet in the Terminator movies, or, more recently, the Turing Test and Ex Machina and love and relationships in Her, are far from reality.

 I did note, however, that the human faces created via generative adversarial networks (GANs) were now indistinguishable from photographs.  This proliferation of deepfakes is raising a host of social, ethical and legal issues, as well as political and social sentiment influence.

Lest we sink into a miasma of AI ennui, I then turned to the panelists, and asked each of them what the term AI meant to them and how it was being used in each of their companies, stimulating a lively discussion. Bassam discussed the value and importance of realistic chatbots for improving the quality of human services management, allowing computer systems to adapt to the questions asked by humans, rather than forcing humans through a fixed decision tree.

As an aside, he remarked on how far they have come from the early, simplistic days of Eliza. Seeing a few puzzled faces, I quickly polled the audience to see how many people remembered Eliza.  When precisely zero people raised their hands, I realized Bassam and I, both with computer science PhDs, had unmistakably labeled ourselves as geeks.

Rather than press on deeper into the big muddy, I quickly pivoted to Glenn and Keelan, who highlighted the power of big data and deep learning systems to identify solutions and approaches that might not be obvious to humans, even domain experts. While discussing the AI advantages to businesses, we also touched on the importance of fairness and ethics in AI systems, and the risk that algorithms and learned behaviors might discriminate against particular individuals and certain groups.

Perhaps the liveliest panel discussion was around the utility, usability, and cost of AI for small businesses.   All of the panelists agreed that the AI water is great, and most small businesses could benefit from cloud-based AI services.

Near the end, audience questions turned to the future, with one questioner asking when AI systems would be more proficient than humans.  I took the opportunity to mention AlphaZero and the fact that it was both a much more powerful Go player than any human but that it also played Go in strikingly different ways than the approaches used by even the best human players.  

The last pensive question concerned our future in a world of powerful AI. I opined that the history of our society was replete with technology disruptions, each shaped by our sense of ethics, justice and law. Incumbent in that evolution is our need for informed debate and collaborative shaping of appropriate and acceptable uses.

 

Undergraduate Research and Scholarship

What motivates us to discover, to explore new frontiers?  What unbroken causal chain connects a child’s boundless curiosity to the focused, but equally insatiable questioning of a trained researcher at the peak of their intellectual prowess?

Why is the sky blue? Why is the grass green? How did it all begin?  How will it end? Why is there anything at all? Why, why, why? Why, indeed?

As the inimitable and ever quotable Richard Feynman once remarked in an interview, “Nearly everything is really interesting if you go into it deeply enough.” This omnivorous curiosity has driven us since the dawn of self-awareness, shaping our culture, our values, and our future. (See Science:  It’s About the Wide-Eyed Wonder and The (Scientific) Good News.) I worry, though, that all too often we reward conformity and punish curiosity, particularly in formal education; the deep and existential why deserves more than a superficial because.

Education and Research: An Unnecessary Division

I’ve spent over half a century in U.S. educational institutions. Some might say I am a very slow learner, others might say it is good that I’ve been institutionalized. Perhaps they are right in both assessments.

Nevertheless, I remain amazed that we spend so much of our educational energy on the transfer and regurgitation of knowledge, rather than nurturing the curiosity that fuels learning. Make no mistake, knowledge is essential, the whetstone of a sharpened mind able to ask insightful questions and understand nuanced answers. However, learning can and should be an inevitable consequence of fueled curiosity, for a curious mind is passionate, indeed desperate, to know and understand.

I speak, of course, of the bicameral separation of education and research. (Here, I use research as a catholic placeholder for discovery and creative works in the sciences, engineering, and medicine, as well as in the arts, humanities, and social sciences.) All too often, formal education is presumed isomorphic with (sometimes) trained performers in classrooms and lecture halls, the sage on the stage, lecturing to passive and often restive students who have been told repeatedly and emphatically this is important and will be on the exam but not why it is interesting or why it might matter. In some, more enlightened contexts, this public education lives in more lively flipped classrooms and the halfway house of experiential learning. 

Meanwhile, research thrives privately in laboratories, libraries, field stations, workshops, communities, and offices, largely isolated from public lecture halls and student habitudes. While our faculty members lead double lives – teachers in the classroom and seekers in the laboratory – many of our undergraduates see only an enervated and desiccated version of the vibrant life of the mind that so energizes and defines faculty.

Our students walk daily past buildings filled with research spaces, unaware of both the process and methods of research and scholarship, and of the passions that drive scholars to pursue answers to age-old questions.  Then, we wonder why the public does not understand why fact-based reasoning and investment in basic research are so important to our nation’s future. (See Just the Facts, Ma’am: Reasoning is Not Dead, Jim and The Epistemology of Science.)

No bright line divides education and research, the known and the unknown. The great mosaic of human knowledge is fractal, with intriguing questions large and small, lurking everywhere, and few answers in the back of the proverbial textbook. (See Research: When There Are No Answers in the Back of the Book.) 

What is now transmitted knowledge was once breakthrough research, and when we separate the passion of discovery from the joy of learning, we diminish both. We want our students to slip unawares across the fractal edge of the known and the unknown, as they ask and seek answers to both old and new questions.

Expanding Undergraduate Research

All research universities, public and private, have organized undergraduate research programs (URP), where selected students work with faculty members. During my years at both Iowa and Utah, I have been impressed by the URPs run by Iowa’s Center for Research by Undergraduates (ICRU) and Utah’s Office of Undergraduate Research (OUR). More to the point, I always found it an unbridled joy to discuss research with students, as they explain problems, methodologies, and insights. It always reminds me that research and education are truly one, driven by curiosity.

Many of these URPs involve thousands of students, but few, other than at smaller institutions, seek to involve all of their entering undergraduate students as a defining and distinguishing educational attribute of their research university experience. There are many reasons for this, some related to scalability, others to fiscal realities, and a few lost in the mists of institutional history, but we can and should do better.

Simply put, I believe every student should have the opportunity to experience the consilience of the known and the unknown, from the very first day on campus. Research universities not only transmit extant knowledge; they create new knowledge. We ask the whys, not just explain the answers. Given this, education at a research university can and should differ from that at even an elite college.

There are national exemplars of this integrative approach, notably the Freshman Research Initiative (FRI) at the University of Texas at Austin and Vertically Integrated Projects (VIP) at Georgia Tech. FRI currently enrolls over 900 first and second year students annually through 29 faculty-driven research “streams.” In contrast, VIP serves over 1,000 students at varying stages throughout their undergraduate careers in 70 faculty-drive multidisciplinary teams. These are scalable, highly successful programs with demonstrable outcomes.  Student retention and graduation rates rise, diversity and inclusion grow, and research awareness – informed curiosity – thrives.

At the University of Utah, the College of Science is building on these insights to create an Undergraduate Research Initiative, as a complement to our Office of Undergraduate Research, our Honors College, and our Office of Undergraduate Studies. I am excited about this future and its implications for our students.

Research is more than a metaphor for life.  It is life grounded in the knowledge and ability to ask and answer questions that shape our individual and collective futures.

Coda

Oh yes, I know you were wondering.  Why is the sky blue? Two words: Rayleigh scattering. Why is the grass green? Because chlorophyll, used in photosynthesis, absorbs red and blue wavelengths more efficiently, and the light reflected by plants is enriched in green wavelengths. How did it all begin?  How will it end? Those are among the deepest and most profound questions of cosmology.

The Magic behind the Curtain: Hardware and Software

The Wizard of Oz is a beloved and widely watched movie that brought us Technicolor, several memorable songs, and lasting cultural memes – “We’re not in Kansas anymore,” “There’s no place like home,” and “Somewhere over the rainbow.” In the movie, Dorothy’s dog, Toto, pulls aside the curtain, revealing the great and mighty Wizard as a mere mortal projecting the trappings of power through indirection and abstraction.  Attempting to continue the charade, Oz proclaims, “Pay no attention to that man behind the curtain!”

Deception once revealed, however well intentioned, is mere artifice.  Accordingly, magicians guard the secrets of their tricks assiduously. After all, it is how they earn a living. More importantly, a trick’s mystique makes it both alluring and intriguing. The legerdemain in a coin’s disappearance may still bring a smile to one’s face, but familiarity with the French drop lessens its mystery.

In my experience, a distinguishing feature of researchers and scholars is their interest in not just in the “trick,” but how the trick is created and performed. These are the people peering around the corner, dissecting the art and engineering beneath each Disney World^TM theme park ride

Hence, some seek the truth, whereas others treasure illusion and, sometimes, their own self-deception. As Morpheus says in The Matrix, “You take the blue pill - the story ends, you wake up in your bed and believe whatever you want to believe. You take the red pill – you stay in Wonderland and I show you how deep the rabbit hole goes.”

Segue alert! Every teacher wants his or her students to take the metaphorical red pill and explore the rabbit hole. It is about challenging beliefs, perspectives, and illusions with new ideas and approaches.  I have reflected on this dichotomy since my very first teaching experience, when I looked back at aspiring young students with both anticipation and trepidation.

As a teacher, there is no greater joy than seeing understanding in the eyes of students, when seeming magic is at last replaced by holistic insight. In short, it is about illumination and understanding, pulling back the curtain on apparent magic to reveal an unbroken chain of insights.

Architectural Magic

As a computer and computational scientist, I long ago realized that introductory computer architecture is the transformative place where computing prestidigitation becomes intellectual engineering. It is where varied computing insights unite in the big reveal – how an idea and the abstraction of an algorithm embodied in code becomes an instantiation in logic, hardware, and device physics.

Make no mistake, the rabbit hole runs unbroken from quantum mechanics through undecidability, the Church-Turing thesis and Turing machines to computability theory and formal language theory (Chomsky hierarchy). It touches the very nature of what it means to think.

First, let’s step back and remember how the intellectual puzzle pieces form the big reveal.

By the time most undergraduate students study basic computer architecture, they have often received an intellectual dose of electricity and magnetism (E&M), perhaps via the latest edition of the same Fundamentals of Physics by Halliday, Resnick (and now Walker) that I studied as an undergraduate over forty years ago. Conductance, capacitance, inductance, wave/particle duality, and quantum tunneling; it is all there. (I so treasured the joy of my E&M course that I have saved my lecture notes and worked problem sets across multiple moves and several decades.)

An introductory class in device physics, transistors, and digital logic often follows E&M. There, the rudiments of semiconductor devices and VLSI design include field effect transistors (FET) (See gate, source, and drain), MOSFET NAND gates, and flip-flops. From there, it is just a hop, skip, and jump to circuit design and logic minimization. At this point, students have architectural Lego^TM blocks and some vague notion these are intellectually sufficient, but microprocessor architecture remains as aspirational and unattainable as a Lego Empire State Building.

Meanwhile, most students have also been learning new programming language(s), efficient algorithms (quicksort), and associated data structures (balanced binary trees). Years ago, the programming languages of choice would have been C or FORTRAN. (I first learned FORTRAN in the 1970s, using WATFIV; see A Feeling for the Code). Today, most introductory computing courses teach Python, with its large sets of libraries, tools, and IDEs.

What really happens when one writes a loop or invokes a procedure? Is it just an incantation, an intellectual sacrifice offered to the machine? Therein lies the reification magic of compilers, which translate code in a high-level language such as C or FORTRAN into equivalent sequences of machine instructions. (The nuance of interpreted languages such as Python is a topic for another day.)

I have found manually translating a simple piece of code (e.g., a loop that sums a set of numbers) into a sequence of assembly language instructions small enough to fit on a single piece of paper is by far the best pedagogical technique. Those symbolic assembly language instructions then map directly and intuitively to individual machine language instructions, each defining a specific hardware behavior (add, read, write, branch), but whose collective describe the intent of the high-level language code.

Trust me; we are now nearing the French drop, but there is nothing up my sleeve …

Computer architecture is where code meets hardware, and the seemingly disparate Lego pieces become a dazzling whole. (It is not turtles all the way down.) Constructed using only those elementary logic gates (aka Lego blocks), the conceptual execution of machine instructions for a simple, non-pipelined stored program computer (superscalar, out-of-order, and parallel are topics for another day) can be traced easily using only pencil and paper. (Computer Organization and Design by my friends Dave Patterson and John Hennessy is as legendary in introductory computer architecture as Halliday and Resnick in physics.)

Simple, yet elegant, these designs embody the core ideas of the von Neumann architecture and its fetch-decode-execute instruction cycle. To test their designs, many a budding computer architect has also trekked to Radio Shack (RIP) or Fry’s (one stop shopping for potato and DRAM chips), or let their fingers do the walking online, for parts to breadboard simple computer components. The more ambitious and adventuresome also stuffed circuit boards and sported solder burns as a point of pride.

The great reveal, the denouement is now at hand. From electrons through transistors and gates to architecture, and from algorithms and code to machine instructions on architecture, it all comes together.  It is all there, the magic of ideas – the abstraction that is code – is now manifest in architecture, hardware, and physics. That is the “Aha!” moment, when students truly appreciate the intellectual construction, like Chartes, that both dazzles and inspires. The true wonder is that one can explain it all on a single whiteboard!

Deep and Open Questions: Not All Is Yet Revealed

The amazing construction that is modern computing rests on many scientific and engineering insights, a few of which are now feeling the strain of their age. The von Neumann model, for all of its elegance and simplicity, increasingly limits future innovation (See Nothing Lasts Forever), and the future of semiconductor technology – 7 nanometers and below – is economically and technologically uncertain. The Landauer principle and low energy (operations/joule) or even reversible computing beckon.  Quantum computing labors in an uncertain aborning, brain-inspired neuromorphic computing is in its infancy, and DNA-based storage and computing are nascent.

Perhaps, the most important intellectual question of all, one deeply related to the nature of computational complexity and the partial recursive functions lies open. Does P=NP? (i.e., is the class of problems where verifying a solution requires non-deterministic polynomial time (NP) the same as the class of problems where computing the solution requires polynomial time (P))? Put another way, if the solution to a problem can be verified in polynomial time, can it also always be found in polynomial time? Most think not, but resolving the question has bedeviled the some of the best mathematical minds of the last century. (If you think you have a proof, sketch it in the margin and claim mathematical immortality.)

Make no mistake, the rabbit hole goes deep, connecting two of the greatest intellectual edifices of the last hundred years – decidability, computability, and complexity united with quantum mechanics and the standard model – via algorithms, software, and computer architecture. The rabbit hole reaches to the very foundational question of what it means to think and share information. There is undeniable magic inside, and that magic continues to transform our perceptions and our world.

Given a choice, always follow the rabbit hole. Scrutinize the man behind the curtain. Seek the big reveal. See the whole whiteboard. Therein lies magic.

As Far as the Eye Can See

In 2016, while Vice President for Research and Economic Development (OVPR&ED) at the University of Iowa, I invited faculty from across the university campus to author essays, sharing what attracted them to their field, why they had devoted careers to exploring big questions, and what research and scholarship have contributed to the world. The indefatigable Stephen Pradarelli, communications director in the Iowa OVPR&ED, skillfully edited the faculty contributions. Last week, I was privileged to be back in Iowa City for the unveiling of the resulting book.  Stephen and I co-wrote the introduction, an abbreviated version of which I have reproduced below.

Few scientists in the history of the University of Iowa embody the American spirit of discovery and innovation as vividly as the late James Van Allen. Born on a small farm near Mount Pleasant, Iowa, Van Allen was fascinated by mechanical and electrical devices, and he was an avid reader of Popular Mechanics and Popular Science magazines. In the 1990 issue of the Annual Review of Earth and Planetary Sciences, Van Allen wrote that he loved to tinker as a child, building elementary electrical motors, crystal radios, and, once, to his mother’s horror, a Tesla coil that discharged foot-long electrical ribbons and “caused my hair to stand on end.”

That tinkering led, in time, to Van Allen making some of the most important 20^th century discoveries in space science while a researcher at the University of Iowa. A device he designed and helped build for Explorer I—America’s first satellite—enabled him to detect a zone of energetic charge particles that originated from the solar wind and were held around Earth by its magnetic field. The finding of what was later dubbed the Van Allen Radiation Belts landed him on the cover of Time magazine in 1959, when the United States badly needed a PR boost after the Soviet Union’s successfully launched Sputnik. It also led to the establishment of a new research domain, magnetospherical physics, and demonstrated that brilliant scholarship takes place in big cities and small, coastal Ivy League institutions and Midwest public universities. 

In the same way that the 31-pound Explorer I needed a rocket to reach space, researchers—scientists and scholars—depend on financial and public support to seek answers to the universe’s most intriguing questions and to explore and elucidate the human condition. With public and political backing, universities have blazed a path of discoveries over the past fifty years that have reshaped the world, translated basic research and scholarship into new cancer treatments and smartphones, life-changing public health policies and social science insights.

The universal human drive of curiosity—the thirst not just for information, but for deep understanding—has survived all manner of challenges over the centuries. That is certainly true at the University of Iowa, whose medical research, writing programs, and space exploration have been providing fresh insights into the nature of the universe and the human experience since the school’s founding in 1847, just 59 days after the state of Iowa was admitted to the Union.

This book highlights some of the current research and scholarship at the University of Iowa, not just from an academic perspective, but from a human one. We asked the contributors to write about their work in language accessible to a general audience, to help readers understand why such work is important to the public, and to share what attracted them to their chosen fields of study. Research is about the systematic exploration of the unknown. Of course, not every line of inquiry leads to a great breakthrough; in fact, there is value in having one’s expectations confounded. As James Van Allen has said about science, “pure investigation has enormous benefit. I can't tell you what this might be good for, but learning about nature is important. And lovely things turn up.”

My wish is that this collection of essays builds understanding about the value of academic inquiry and inspires hope for the future. If nothing else, you should take away a sense of the passion, dedication, and vision University of Iowa’s researchers and scholars bring to work each day.

Happily, for those of us who parlayed youthful curiosity about the world into a lifelong profession, there is no end of mysteries to solve. In her Pulitzer Prize-winning novel, Gilead, author and longtime Iowa Writers’ Workshop faculty member Marilynne Robinson wrote, “This is an interesting planet. It deserves all the attention you can give it.” Indeed.

To solve some of the most challenging mysteries and to better comprehend and celebrate what it means to be human—understand how the world works, explore how and why we respond to it in the ways we do, and express the fruit of those inquiries in bold and creative ways—we need public trust, support and vision for the role of public research universities like ours.

May this book help persuade you to join us on this journey of discovery.

A Feeling for the Code

Each individual’s professional path from past to present is defined by an oft-unexpected and uncertain trajectory.  As the Danish philosopher, Søren Kierkegaard once remarked, "Life can only be understood backwards; but it must be lived forwards." For some, the path is clear and straightforward – a simple gradient ascent, or more sadly, descent. Alas, life, like most multivariate functions, is rarely globally convex. Rather, it is filled with a seemingly random distribution of local minima, each of which can become an unwitting trap, and time rarely permits an exhaustive and deterministic global optimization. Instead, one must be satisfied with limited stochastic optimization. As best, life is a bounded simulated annealing, making each decision potentially transformative. (See One Life to Live.)

Canto One: Geek in a Small Town

Why might I ramble inanely about the dubious duality of life and optimization theory? Perhaps because my life path and its objective function were changed by a single experience.  As Peter Medawar wrote in his delightful book, Advice to a Young Scientist, “I cannot distinctly remember a time when I did not think that a scientist was the most exciting possible thing to be.” From an early age, I too felt that calling – my childhood dream was to be a scientist, and by my teenage years, more specifically, to be a physicist.

In my naiveté, I knew mathematics was the language of physics, but my small high school’s mathematics curriculum ended with plane geometry. Haltingly, with borrowed library books, I began teaching myself trigonometry and elementary differential calculus. (See Libraries: Arms Too Short to Feed the Mind.) By backing one of my high school classmates into the water fountain while expounding excitedly about limits, derivatives, and the slopes of tangent lines, I finally and irretrievably branded myself the left-handed, myopic geek I truly was, a seemingly singleton set in a small town.

Canto Two: Finding Others

Just after this, I was thrilled to spend a summer at the University of Arkansas in a science, technology, engineering, and math (STEM) program. As a term of art, STEM gained currency much later; I simply basked in the opportunity to do something amazing – stretch my talent and expand my limited knowledge with a group of likeminded physics students.

Ensconced in Fayetteville, I repeated the double slit experiment, which left me pondering wave-particle duality and the uncertain nature of reality. More importantly, in that small academic community nestled in the Ozark mountains, I met people who shared an academic passion to know and to discover. For the first time, I did not feel alone, and for that, I will be forever grateful.

During that summer, I also received a brief introduction to digital logic and a crash course in FORTRAN IV. Less powerful than today’s smartphones, computers were then multimillion-dollar behemoths, housed in secure facilities, their use limited to a select few. Now instructed in obscure, digital incantations, I was now privileged to offer subservience to the great machine. In the 1970s, this was heady stuff for a young boy from the backwoods.

Somewhat coincidentally, I was soon to read The Machine Stops, E. M. Forster’s chilling meditation on technological dependence, However. I was in no way sufficiently prescient to imagine our future dependence on these computing machines.  Excuse me; Alexa, set the temperature to 68 degrees. Siri, where is the nearest grocery store? Cortana, just who was E. M. Forster?  However, I digress, distracted by our digital surroundings.

Canto Three: Computing Life

At the time, the University of Arkansas had an IBM 360/50 system, and spira mirabilis, a Calcomp pen plotter that could generate graphs of computational outputs. Therein lies the second part of my transformative life experience.  Armed with rudimentary FORTRAN knowledge and a paperback copy of Waterloo’s WATFIV manual, I hastened to an IBM 029 cardpunch to write my first program. Of course, it did not initially work as expected, which then introduced me to the fine art of debugging, further honed when I foolishly attempted to write a chess program.

With ambition that exceeded my skills, that first program brought my simple mathematics to life in a wondrous way. It also forced me to think more deeply, as I built a mental model of its bifurcating execution paths. (See On Cognitive Loading and Intellectual Hierophany.)  I was rewarded when the static equations on my textbook pages took life; they danced and moved, revealing their secrets in rows of printed numbers and simple line plots. Deus ex machina!

Later, I learned of universal Turing machines, computability theory, and the Entscheidungsproblem, but with that first program, I knew immediately and instinctively that well-written code had an ethereal elegance and a haunting subtlety, and that breathtaking complexity – and beguiling beauty – could emerge from its simple rules and mathematical incantations. (Is there a computer scientist anywhere who has not been enthralled by Conway’s Game of Life and its cellular automata, fully Turing complete?)

Without doubt, I had found the calling of a lifetime, all that and more in a feeling for the code – the transfiguration of hypotheticals, the reification of concepts, and the instantiation of the imagination – code as both science and art.

Since then, I have marveled at intellectual haiku, brief code sketches that amused and illuminated. I have shuddered at abominable monstrosities, code assembled and then brutally modified by teams over decades, intellectual Frankensteins unleashed to sow destruction.  I have seen masterpieces of minimalist, yet surpassing beauty, where form inexorably illuminated function, crafted by artists of the first order. It is all there in the code.

Throughout, I have been privileged to collaborate with scientists across diverse disciplines, from astronomy and quantum physics though genetics and gene expression to weather analysis and severe storms, all via the universal intellectual amplifier that is computing.  (See Intellectual Amplification via Computing.) Each time there is excitement; there is wonder; there is discovery; there is insight, as ideas come to life.

A thing of transfixing beauty, the code pirouettes gracefully, dancing in my mind, conjuring the possible; it always will.

Finally, about that geek thing?  I have always been at peace with it.  Professional optimization complete; global maximum found.