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Graduate Programs
For Understanding and Managing Accelerating Change

A brief list of graduate programs helpful in Foresight and Futures Studies (FS), Acceleration Studies (AS), Acceleration Management (AM), and Evolutionary Development Theory (EDT)



Generalist and Specialist Programs

Some Generalist (Big Picture) Areas of Study

Some Specialist (Applied) Areas of Study

Foresight and Futures Studies (FS): Global Primary and Secondary Programs

Foresight and Futures Studies (FS) versus Science and Technology Studies (STS): A Career-Oriented Comparison for Semi-Technical Generalists


Acceleration Studies (AS). Programs: A List for Semi-Technical Generalists

Acceleration Management (AM) Programs: A List for Change Managers


Evolutionary Development Theory (EDT) Programs: A List for Technical Generalists

Finding Your Thesis Advisor / Principle Investigator: Some Advice


Understanding accelerating change can be done from a great variety of academic backgrounds. Here we briefly frame the challenge and outline some Generalist and Specialist approaches.

As most individuals who grapple with the topic of accelerating change are nontechnical generalists, we next briefly compare two potential career fields, Foresight and Futures Studies (FS) vs. Science and Technology Studies (STS).

We conclude with a list of Acceleration Studies (AS), Acceleration Management (AM), and Evolutionary Development Theory (EDT) Ph.D. programs that might be considered by semitechnical, application-oriented generalists, change managers, and technical, theory-oriented generalists respectively.

To explore the differences between Acceleration Studies and Universal Evolutionary Development Studies, see Intro to Acceleration Studies (AS) and Evolutionary Development Theory (EDT) .

Generalist and Specialist Degree Programs

Certain programs, which we've labeled "Big Picture" or "Generalist" areas of study, will inherently give you a more generalist, synthetic, and systems theoretic perspective. While these areas may require many specialization skills and duties of their own, they often provide an ability to generalize across a number of complex systems. Though profiling can be dangerous, these areas of study tend to reward those whose personal psychology seeks expertise in a multitude of systems, often in a more abstract, general, holistic, and harder to measure manner.

Other programs, which we've labeled "Specialist" areas of study, tend to provide the bulk of the original research, the infrastructure, and the many discrete, objective facts necessary for the Big Picture to emerge. These areas are often in more restricted, field-specific domains of investigation, and tend to reward those whose psychology prefers a narrower focus, and the ability to be highly concrete, specific, and reductionist in one's approach.

In both approaches hard work, discipline, and a deep understanding of the benefits and limits of the scientific method will serve you well, along with an appreciation of breadth of knowledge and the role of intuition when working on poorly understood problems. The more multi-disciplinary your perspective, the better you will be able to understand the fundamental mechanisms and language of the specialists, and at the same time employ them within the models and outlooks of the generalists. Such background will equip you to see the outlines of the Biggest Picture of all, the statistically inevitable developmental trajectories of the cosmos and the constrained future of local intelligence.

Just as developmental biology and ecology provide fundamental understanding of predictable futures on the human and global scales, the canonical example of predictable developmental trajectories on the universal scale is represented in the physical sciences. Celestial mechanics, thermodynamics, general relativity, physical, inorganic, and organic chemistry, and other domains of physical science all give breathtaking insights into the necessary future of many large and fundamental systems in our universe, over astronomical timescales. These are subjects every Big Picture futurist critically needs to understand, at least at the level of the college undergraduate. Those who are not familiar with the basic insights of these subjects are missing many of the fundamental constraints and forces shaping our future environment. As one consequence, their predictions for the future will often be biased more toward human creativity, without balancing that creativity with human discovery, including our increasing characterization of natural constraints on the human enterprise.

While the physical trajectories and dynamics of still-more-complex systems (life, the human species, our increasingly autonomous technology) operate over much shorter timescales, at much faster rates, and are certainly harder to discern and quantify today, the role of the Big Picture futurist and systems theorist is to progressively uncover the regularities, predictabilities, and constraints of such systems. This requires the development not only of basic physical sciences proficiency, but a general complex systems intuition, the ability to device crude indicators and measurement systems for one's predictions, the ability to use a language comfortable with probabilities, and the desire to test one's futures intuition wherever possible against reality.

Some Generalist (Big Picture) Areas of Study

The dark blue subject areas below are well suited to Big Picture generalists, to understanding accelerating change across a broad range of academic domains. Those underlined provide particularly good frameworks for dealing with all five of the fundamental UGNOI complex systems levels (Universal, Global, National, Organizational, and Personal) which humans commonly use to understand accelerating change. All the dark blue fields tend to be more theoretical, abstract, and holistic in their approach, although applications-oriented generalist programs are also becoming more common.

The light blue fields focus more on human-centric generalism. They may provide a big picture in the human sphere, but are "holons" (holistic systems that are part of a larger whole, in Ken Wilber's useful terminology) in the Big Picture of universal computational development.

(biogenesis, anthropic developmental models)
Cognitive Science (CogSci), Psychology, Behavioral Science,
and Consciousness Studies
Communication Studies
Complexity Studies, Complex Adaptive Systems
Computer Science, Theory (Artificial Intelligence, Agents and Autonomous Systems, Evolutionary and Biologically Inspired Computation, Neural Modelling, Computational Linguistics, IT metrics, Autonomy, Intelligence, and Growth Modelling)
Business Administration (general forecasting)
Business Administration (Technology Forecasting, Operations Research, Management Science)
Developmental and Evo Devo Biology (especially Comparative Biology and Convergence Studies)
Economics (most)
Economics (technology and productivity benchmarking, intangible assets, deflationary studies)
Evolutionary Psychology
Ecology (including Ecological Psychology)

Futures Studies (FS)
A current difficulty with the Futures Studies field, the one I have chosen for my own M.S., is that it does not yet incorporate evolutionary developmental (as opposed to purely evolutionary) models, or a mature understanding of the unique developmentalist nature of accelerating technological change. "The future is not inevitable or predictable" is a fundamental perspective of many practicing futurists. This is clearly only half true, as many aspects of the future are highly predictable, and certain futures seem overwhelmingly inevitable, barring highly improbable global developmental failure. While it is certainly true that evolutionary events are contingent and within our free choice, developmental ones are not. Developmental emergences seem to be universals—overwhelmingly statistically inevitable attractors and emergent constraints. We ignore them at the cost of our own individual and collective impoverishment, and discovering and better characterizing them is the role of the Evo Devo Futurist.
History of Law and Ethics Studies
History of Science/Technology (HoS/HoT)
Humanities (Art, Literature, Music, Classics)
Information Theory/Information Studies/Informatics (IS)
Immunology (especially Comparative Immunology)
Journalism (Science and Technology Writing)
Mathematics (Nonlinear and Dynamical Systems, Game Theory, Automata Theory, Self-Similarity)
Philosophy (most)
Philosophy of Science/Technology (PoS/PoT)
Physics (Astrophysics, Biophysics, Cosmology, Quantum Physics, Relativity, String Theory, M-Theory)
Religious Studies (most)
Science and Technology Studies (STS)
Social Sciences (most)
and Political Science
Systems Science (prev: Systems Theory, Cybernetics)
Technology Policy (most)
Technology Policy (IT, telecom, nano, and other technologies on the "current leading edge")

A number of generalist fields have suffered subtle conceptual problems in recent years as they have attempted to incorporate the phenomenon of ever-more-rapid technologic development within their traditional static or linear paradigms, often doing so in a conservative, human-subordinate and ultimately ineffective manner. As a result they systematically underestimate the current influence and future effects of accelerating technological change on their fields of study, in their lives, professions, and in the larger world, and contribute to a generalized technological illiteracy and lack of foresight development within their profession. Fortunately, revisionist thinkers are emerging within each of these disciplines to help us better consider the implications and effects of accelerating change on each field's models, practice and forecasts.

If a generalist academic path is one you plan to take, I urge you to be one of those revisionists. When we reflect on the accelerating succession of physical —> chemical —> biological —> technological evolutionary developmental emergences we have seen to date, it seems most reasonable to assume that the biological human era, though it presently serves a vitally important link in this progression, is about to be transcended by, and transition into, a system with far greater universal intelligence and autonomous capacity for change.

Some Specialist (Applied) Areas of Study

The dark red subject areas below are good examples of scientific specialization fields that are usually more fundamental and reductionist in their approach, and particularly useful for discovering the facts necessary for the Big Picture to emerge

The light red specialist areas are examples of humanistic or applied specialization that help to improve the infrastructure within which the Big Picture to continues to evolve and develop.

Architecture (Ecological/Sustainable Construction, Smart Buildings)

Biology (Evolutionary, Molecular, Genetic, Cellular, Physiology, Organismic, Population, Marine, and Biomedical Sciences)
Chemistry (Physical, Inorganic, Organic, and Biochemistry)
Computer Science, Applied (Artificial Intelligence, Agents and Autonomous Systems, Evolutionary and Biologically Inspired Computation, Neural Modelling, Computational Linguistics, IT metrics, Autonomy, Intelligence, and Growth Modelling)
Development Studies (Emerging Nations, Globalization, Democratization)

Earth Sciences, Oceanography, and Geography
Econometrics and Cliometrics
Engineering (Electrical, Mechanical, Chemical, Civil)
History (most)
Journalism (most)
Linguistics (Comparative)

Linguistics (most)
Materials Science
Mathematics (most)
Medicine and Health

Physics (most)
Space Science (most)
Urban Studies and Planning
Women's Studies

Do you see yourself as a big picture generalist? a human-centric generalist? A scientific or humanistic/applied specialist? Listen to your heart, and choose carefully. You could contribute to acceleration studies, universal evolutionary development studies, phase transition (singularity) studies, or predictive futures studies in any of these and other fields, as a generalist or specialist. If you choose to be a Big Picture generalist, you'll want a basic level of fluency in as many of these fields as possible.

Given the cost of our choices, whatever path you take may turn out to be a lifelong commitment. Remember to enjoy the process as much the progress you make (or don't) toward your goal!

Finally, when you choose a graduate discipline, try hard not to enter it because you presently conceive it as "most important" for improving the planet, as judged by some systematic or analytical perspective. For most of us, such judgments will be based on our own preliminary model of the Big Picture. But your model is likely to change significantly as you walk your path, particularly in your teens, twenties, and thirties, so this kind of "early optimization" can easily be a recipe for disappointment.

Instead, seek out a subject that feels best for you given the interests and aspirations you have personally expressed to date, a subject you personally feel passionate about, a profession you could love "warts and all," and one to which your skills and disposition seem well suited, both in your judgment and in the judgment of your friends. If you can find more than a few older mentors in this field, with similar personalities to you, who appear to enjoy the choice they have made, that is also an excellent sign.

Foresight and Futures Studies (FS): Global Primary and Secondary Programs

Please see ASF's web page, Foresight and Futures Studies - Programs and Resources for an extensive list of global primary and secondary FS educational programs to consider.

Foresight and Futures Studies (FS) vs. Science and Technology Studies (STS):
A Career-Oriented Comparison For Semi-Technical Generalists

Foresight and Futures Studies

Foresight and Futures Studies (FS), as presently developed in the few universities that offer it, explores long-term change using mostly qualitative tools, such as scenario planning, and a few quantitative ones, such as statistical analysis. While there are a number of academic programs that train students to think on 3-year, 5-year, and very occasionally even 10-year horizons, such as Strategic Planning in business, or Science and Technology Policy Studies (e.g., RAND graduate school), Futures Studies is presently unique in that it also considers 10, 20, and even 30 year time horizons, where all plausible scenarios include discontinuities or "wild cards" of various types. Scenario planning in this context is generally used with the assumption that risk management (careful consideration of possibilities) is its main benefit. Nevertheless, within a few of the more innovative business and engineering schools Technology Roadmapping is emerging as a subdiscipline (not yet a formal degree, unfortunately) which allows 10+ year futures work, and within the tech roadmapping community there are acceleration-aware scenario planners who assume certain inevitable (e.g., computational) developmental trends that must be common to all future scenarios we generate. A few of these special futurists, such as Ray Kurzweil, Nathan Mhyrvold, and Peter Schwartz, have even developed semi-technical research and predictive analyses to support trend inevitabilities.

As we discuss in our definition of a futurist, professional Futures Studies can be classified into five major types, characterized by five unique goals of the foresight practitioner: Exploration/Creativity, Agenda-Advancing, Consensus-Seeking, Prediction, and for a few, understanding and applying the paradigm of Evolutionary Development to all universal processes. Each is increasingly uncommonly seen, in practice.

1. Exploratory/Creative Futures Studies ("Possible" Futures)
Examples: Utopian studies, science fiction and speculative literature, futurist imagery.
2. Agenda-Driven Futures Studies ("Institutionally Preferred" Futures)
Examples: Any self-interested organization's long-range strategic goals and plan.
3. Consensus-Driven Futures Studies ("World's/Community's Preferred" Futures)
Examples: U.N. development projects, community visioning, democracy-promoting NGO's
4. Predictive Futures Studies ("Probable" or Statistically "Inevitable" Futures)
Examples: Any specific, falsifiable predictions about future conditions.
5. Evolutionary Developmental ("Evo Devo") Futures Studies
Examples: Discriminating evolutionary from developmental processes, at all physical scales.

Unfortunately for the careers of prospective acceleration students, predictive futures studies and its descendent, evolutionary developmental (evo-devo) futures studies, are the least developed of the above disciplines. Both involve attempts to generate falsifiable, scientifically-testable quantitative and qualitative predictions about a special subset of apparently developmentally inevitable future events, many of which have to do with accelerating growth rates in computational and physical capacity, power, miniaturization, etherealization, and autonomy in a small subset of Earth's complex systems. These and other emergent properties are definable and predictable by a variety of different but related metrics. An understanding of the primacy and statistical inevitability of this developmental progression is notoriously missing from most current futurist scenarios, which are, as Kurzweil would say, using intuitive linear rather than historically exponential models of change.

It appears that the majority of events we see on the local scale are unpredictable and evolutionary (e.g., highly chaotic and contingent). Hence, those futurists discussing typical (evolutionary) events, such as whether a particular company, nation, policy, or cultural feature will emerge at a particular time, have historically had a discouraging record of prediction within any average sample. Nevertheless, there are a special subset of computationally-related developmental trends (e.g., a generalized Moore's law over the last 110 years, independent of manufacturing paradigm, Dickerson's law for proteomics over the last 40 years, Poor's law of network node density, Cooper's law of wireless bandwidth, etc.) that have remained highly predictable over long spans of time.

Furthermore, studies in "convergent evolution" (e.g., convergent universal evolutionary development), are proposing an ever-growing number of physical structures and processes that appear to be inevitable emergent forms, which becomes particularly clear when we observe processes at the universal or global scale. The fields of Astrobiology, Cosmology, Evolutionary Developmental Biology, and Science and Technology Studies, for example, are helping predictive futurists to understand that there has been convergent evolutionary development in a long succession of chemical, biological and technological structures over time. See our introductory page on convergent evolution(ary development) for a better understanding of universal developmental processes.

Today, emergences such as carbon-based organic chemistry, proteins, nucleic acids, lipids, cells, cell nuclei, nervous systems, eyes, binocular vision, jointed limbs, wings, opposable thumbs, bilateral symmetry, humanoid forms, mathematics, wheels, internal combustion engines, automobiles, silicon-based computing systems, and the paradigm of scientific investigation are all among a large and growing class of events that many now suspect to be not simply evolutionary adaptations for particular niches, but rather universal developmental attractors for accelerating local computation, given the unvarying physical laws of the common universal environment that all these systems inhabit. Learning to discriminate between evolutionary and developmental events when considering the future is both a useful art and a nascent systems science.

Unfortunately, while there are tens of thousands of individuals who consider themselves practicing futurists, the state of futures studies is today still so underdeveloped that a majority of practitioners do not understand the difference between evolution and development on universal scales, and have not looked carefully at the universal record of computational acceleration.

At the same time, futures studies in the U.S has yet to gain traction within academia. There have been only two domestic academic programs created in the last 30 years, at the U. of Houston (M.S.), and U. of Hawaii (M.A. and Ph.D.) Both programs emerged back in the mid 1970's, during the optimistic Apollo-era heyday of the field. Each has so far been unable to expand their vision to other U.S. universities.

It is my belief that one of the reasons futures studies programs have had this long term difficulty because the field has to date largely neglected predictive futures studies, and has focused instead on the first three types, each of which, while certainly socially and politically important, are an incomplete set of futures tools, and can mire practitioners in normative disagreements. The lack of sufficient effort at prediction and falsification by students of the field has not allowed sufficient scientific credibility to emerge.

Futures studies, in every academic institution I have seen to date, does not even aspire to the modeling and empirical rigor of any of the hard social sciences, such as Econometrics or Cliometrics in Economics, or the more predictive branches of Psychology and Sociology. That, plus the lack of science, technology, and social sciences educational prerequisites in admitting students to the field, are significant and serious present blocks to its expansion.

Nevertheless futures studies has slowly gained ground on an international basis. Approximately ten primary and many more secondary academic programs are now available around the world (see Foresight and Futures Studies - Programs and Resources). Furthermore, a small group of successfully predictive futurists have produced a limited but growing collection of well-researched, exponentially-aware, long-term prediction studies, work which began at such institutions as the Stanford Research Institute (now SRI International) and the RAND corporation in the 1960's and 70's (e.g., Herman Kahn's excellent Long-Term Multifold Trend predictions), and continues today in a more subdued form at such locations as Kahn's Hudson Institute and the Cato Institute, where the famous futurist and accelerating technology prognosticator Julian Simon was a senior fellow.

Much of this modern applied futures work is considered policy analysis or business forecasting. Thus an advanced degree in Technology Policy, an M.B.A. or Engineering degree with an emphasis in strategic planning, technology forecasting, or technology roadmapping, a degree in Operations Research or Management Science, or a Computer Science or Information Science degree with an emphasis on technology benchmarking and measurement would be places from which to advance modern predictive future studies.

There are lingering image problems with the futures studies field, particularly at the lower lay and semi-professional end. Yet there are many good opportunities for students of acceleration to make progress in predictive futures studies, while recognizing the field's current challenges and shortcomings.

Science and Technology Studies

Science and Technology Studies (STS) is another field in which the acceleration scholar may engage in serious futures work. Unlike futures studies, which remains broadly underdeveloped, or science and technology policy programs, which are politicized and narrower in scope, STS comprises the fastest growing group of Big Picture futurists. STS practitioners may legitimately consider long-term trends in accelerating change within various domains of science and technology, including whether and how technology transcends limitations in human biology and culture.

STS is a very new field, yet has received significant academic support in recent years. There are now twenty four university Ph.D. programs available in the U.S., and many more worldwide. Most of these programs have emerged in just the last decade.

At this point we should mention that acceleration and phase transition studies, and the specific hypothesis of increasing human-independence and efficiency of accelerating computation would still be radical topics of discussion even within STS. Universities as institutions, for all the intellectual freedom of their students, do not have a great tradition of early service to future-important fields. In the Renaissance era, for example, almost all of the innovation that occurred in science, medicine, humanities and culture occurred in decentralized patronage-based work outside the intellectual and creative confines of "The Academy." In a more recent example, the first U.S. Ph.D. degree in Computer Science, was only awarded in 1961, a full two decades after the tremendously impressive computing innovations of the Second World War. Fittingly, John Holland, one of the fathers of genetic algorithms received this degree, and went on to train John Koza, a current leader in the nascent field of Evolutionary Computation.

Fortunately, through the vehicle of STS, academia has finally broadly realized that it needs to better study the phenomenal, accelerating progression of science and technology. Most promisingly, several of the better STS programs are today willing to explore such issues as artificial intelligence, philosophy of science and mind, human-machine convergence, and dialogs which consider science and technology as universal developmental phenomena.

As you investigate STS programs, you should also be aware that much of the work within this emerging field is constrained by a much less universal topic, the sociological and cultural issues of scientific research. In particular, some STS programs have fallen victim to the "cultural relativist" school of thinking, the dead-end narcisissm and nihilism of postmodernism. Cultural relativism/postmodernism is a world view that is unaware of the profound difference between socially constructed (subjective, evolutionary) and socially discovered (intersubjective, developmental) knowledge.

STS relativists such as Susan Cozzens and Edward Woodhouse characterize such discoveries as the scientific method, electricity, and digital computing as having "no privileged claim to truth," considering them simply manifestations of the particular accidental cultural choices we have made. Such models overlook the fundamental utility of particular tools and algorithms (e.g., the wheel, number theory, automation) to all cultures, and their rapid and irreversible spread after they have been discovered in any culture.

Cultural relativism, in my opinion, like ultra-Darwinist theory in Evolutionary Biology, is thus, half-formed, and "half-right" in its model of scientific and technological reality. It correctly understands that most knowledge is evolutionary, contingent, unpredictable and initially socially constructed and validated, and that there is great value in understanding the social context of most scientific and technological knowledge and processes. But at the same time relativism misleadingly ignores the special subset of knowledge that is developmental, convergent, and highly statistically likely to be discovered by all cultures, as a function of their complexity, given the unique laws, constraints, and boundary conditions of the particular universe that we inhabit. As one example, it appears that what we call STEM compression, a phenomenon of increasingly local universal computation, via migration to increasingly miniaturized and resource-efficient local substrates, is a developmental trend intrinsic to our physics that we ignore to our own detriment.

Cultural relativism exists in the Foresight and Futures Studies communities to some degree as well, but perhaps because current Foresight and Futures Studies programs tend to be less academic, it isn't as pervasive a problem in the futures field at the present time. Nevertheless, it does exist. I have had a practicing professional futurist tell me, for example, that my claim that women globally, on average, can be reliably predicted to continue to gain greater personal liberties, both in absolute terms and in closing their relative gap in relation to men, was a form of cultural imperialism and that, even when considering the network of cultures on the planet as a whole, it represented an unpredictable evolutionary choice, rather than an inevitable attractor for cultural development. Such differences of opinion are worth clarifiying and testing as we look for ways to advance the rigor and quality of work in the futures field.

While cultural relativism unfortunately dominates some of the more theoretical-sociological STS programs, there are several STS programs that are developing increasingly strong basic science knowledge prerequisites for their graduates, and are building strong ties to applied technical communities (engineering, computer and information sciences, and other specialties). Look especially for these qualities as you evaluate each program. In addition, some STS Ph.D. graduates, such as Alex Pang at the Institute for the Future, are practicing professional futurists, and are building bridges to the business strategy and business forecasting communities.

In addition to their scientific rigor and close ties to working science and technology communities, leading STS programs help their students to extensively consider the history, philosophy, conceptual foundations, and developmental trends of science and technology. These are domains where one may legitimately propose and analyze technological and developmental acceleration and phase transition (singularity) hypotheses, even though they should be conservatively advanced and are likely to be subject to parochialism and prejudice for several years to come.

Acceleration Studies (AS) PhD Programs: A List for Semi-Technical Generalists

STS is presently the primary candidate among U.S. programs for pursuing career academic (Ph.D.) work in acceleration studies (generalist, applications-oriented studies of accelerating change). In rough preference order, we recommend:

1. Cornell (STS). Well rounded, flexible. Good AI coverage.
2. VA Tech (STS). Flexible, large student body.
3. Rensselaer Polytechnic (STS). Broad ranging academics.
4. MIT (Science, Technology, and Society). A bit too conservative/rigid, at present.
5. RAND Graduate School (Policy Analysis). A strong tradition in acceleration studies, presently more policy oriented and restricted in scope. Also quite politically correct/restrained.
6. Chicago (Conceptual and Historical Studies of Science). Good rep, not quite as flexible.
7. GA Tech (History, Technology, and Society). Tending toward historical/sociological.
8. U. of South Carolina (Phil. and Social Dimensions of Nanoscale Research). Dogmatically humanist and somewhat relativist in its assumptions, but promising in its scope.
9. University of CA, Irvine (Logic and Philosophy of Science). More rigidly focused.

For students who seek to maintain a full time job, or to do interdisciplinary academic work of their own devising, it is also possible to do a nonresidency Ph.D. in acceleration studies. Several online Ph.D. programs are accredited in the U.S., but there are only two that we would recommend specifically for this purpose at present:

1. Union Institute and University. PhD in Interdisciplinary Studies (Interdisciplinary Arts and Sciences).
2. Fielding Graduate University. PhD in Human and Organizational Systems

Union (UI) in particular is a rarity in the academic freedom it provides. You are encouraged to propose your own thesis committee of international scholars (the lead must be Union faculty), and design your curriculum to achieve the academic goals you are personally seeking, such as writing an acceleration studies thesis that can be published as a book. This affordable program ($18K year x 3 years) is ideal for emerging disciplines (acceleration studies, universal evolutionary development studies, future studies) that do not yet fit well into traditional academic domains.

Union has been granting PhD's for 40 years, and its alum include teachers, heads of small colleges, congressmen, governmental and military employees, business leaders, writers, and others. One disadvantage of this Ph.D. is that it will not typically give you access to primary academic research or tenure teaching positions at major U.S. universities. You would, however, be able to use your Ph.D. to secure an adjunct, part-time teaching spot in a range of courses, including courses of your own design, anywhere but at the most prestigious of schools (and perhaps even there as a "lecturer"), which may be sufficient for many students. With a well-designed course of study you would also be equipped to publish, present papers, and serve on editorial boards in your relevant communities of interest.

The primary value of a research PhD is the quality of the work and the committee you are able to work with, and at UI you have broad control over both of these, unlike most conventional programs. As a Ph.D. graduate, you also have the opportunity to apply to be Union faculty afterward, or to serve as a thesis adviser for Ph.D. students who come after you at U.I. to do work with similar professional interests.

I am presently planning to start my Ph.D. at UI upon completing my Futures Studies M.S. (currently in process).

Until we have our own independent academic program, ASF will seek to attract other U.S. students with acceleration, evolutionary development, and futures studies interests to build a student and faculty tradition in these subjects at UI and other uniquely open-minded and flexible schools.

There are also excellent international programs in these subjects (acceleration studies, interdisciplinary studies, STS) that we have not as extensively researched. Here are several promising ones to consider:

1. Kyoto University (Informatics). (51pg PDF) Very interdisciplinary, future-aware program.
2. Free University of Brussels (Interdisciplinary Science). An outstanding small program.
3. University of Toronto (History and Philosophy of Science). Large, active student body.
4. University College, London (STS). Accessible and well-regarded program.
5. University of Wollongong, Australia (STS). Small, more sociological.
6. Goteborg University, Sweden (STS). Mostly sociological orientation.


Acceleration Management (AM) Programs: A List for Change Managers

Select M.B.A. programs with strong change management and trend tracking capabilities, and some Engineering programs with strategic and technological management and operations research focus are among the leading professional degrees that one might get for applied work understanding and guiding accelerating technological change.

The following are a few M.B.A. programs with particular competency in productivity measurement, trend tracking, forecasting, organizational development, innovation, strategic planning and other related change management skills. This is a very partial list. Engineering programs will also be reviewed and listed here later, as time allows.

1. Stanford University, Graduate School of Business. Very innovative, excellent network.
2. U. of Pennsylvania, Wharton School of Business, and Wharton West (San Francisco). Great technological innovation program.
3. UC Berkeley, Haas School of Business. Good trends research.
4. Pepperdine University, Graziadio School of Management and Business. Strong in organizational development.
5. London Business School. Future focused, good forecasting emphasis.


Evolutionary Development Theory (EDT) Programs: A List for Technical Generalists

To develop a mathematically rigorous model of accelerating change, one that includes modern concepts of universal evolutionary development, log-periodic acceleration, phase transitions, and the comparison and contrast of various finite-time singularities within a range of complex adaptive systems, one would do well to gain a broad understanding in Physics, Astrobiology, and Biological Evolutionary Development through undergraduate and M.S. level research, then to engage in a formal graduate training in complex systems research.

Unfortunately, given the controversial nature of universal evo devo thought, many of our top complex systems research programs do not yet appreciate the developmental nature of accelerating change. A good ideas test for any institution you are considering would be to see if you can find faculty that consider the work of Simon Conway Morris (Life's Solution, 2004) or Eric Chaisson (Cosmic Evolution, 2002) to be worthy of Ph.D. dissertations by incoming students.

Even Nobel laureate Murray Gell-Mann, co-founder of the Santa Fe Institute, the leading complex systems research institute in the U.S., and who has personally told me, on two separate occasions, that he considers the topic of accelerating change both "interesting" and "frightening," presently entertains a restrictive understanding of universal complexity development. In The Quark and the Jaguar: Adventures in the Simple and Complex, 1994, Gell-Mann relates the standard "frozen accident" random symmetry-breaking model as the best synthetic perspective on change, when it is merely the model that is the most mathematically tractable, at present. Such is the dominant paradigm that any developmentalist must operate within if one gets formally trained in many of these institutions.

Several complexity studies-related Ph.D. programs are worth investigating. Here are two:

1. U. of Pittsburgh, Philosophy of Science. An outstanding technical program. Not directly complex systems oriented, but an ideal place within which to study them.
2. Portland State (Systems Science). Little known. Math and computer science orientation.

Some top U.S. institutes for complexity studies are listed below. These do not yet offer Ph.D.'s, so you would typically do a graduate degree at an affiliated university (e.g., in Mathematics or Physics) while affiliating with them, so that you could do work there as a fellow or postdoctoral student.

1. Santa Fe Institute. Top network for US complexity research. No Ph.D. currently available.
2. University of Michigan, Center for the Study of Complex Systems. Home of many of the early greats: Arthur Burks, Robert Axelrod, Michael Cohen, John Holland, etc.
3. U.C. Davis, Institute of Theoretical Dynamics. Nonlinear dynamics in biology, etc.
4. University of Illinois in Urbana-Champaign, Center for Complex Systems Research
5. U.C. San Diego, Institute for Nonlinear Science
6. Florida Atlantic University, Center for Complex Systems and Brain Sciences Research

For students wishing to do a technical distance learning Ph.D. that has at least some applicability to acceleration studies, there are a few options. Let me know if you find others:

1. Nova Southeastern University. Ph.D. in Information Science/Information Systems
2. Walden University. Ph.D. in Applied Mgmt and Decision Sciences/Operations Research

I have not yet discovered any online, distance, research Ph.D. or even M.S. programs in Mathematics, but taking such a program, combined with online tutoring, might be a good way for full-time workers to gain background on phase transition studies. Alternatively, auditing local graduate courses in nonlinear math, dynamical systems, power laws, fractals, self-organization theory, computer science, theory of computing, and related subjects would be another strategy.

You can find graduate tutors at every top university who will help you for a reasonable hourly rate. You might go over classic and interesting papers with them until you can understand and appreciate them, which will add greatly to your self-taught enjoyment. Even without a higher degree, with proper independent part time training you will eventually be able to publish papers, present at relevant conferences, and contribute useful work to your chosen community. If this is your goal, rather than prestige or job security, the only thing holding you back will be your ability to create the study time and your personal determination.

Some leading international programs in complexity studies:

1. Ecole Normale Superieure, Paris, France
2. Max Planck Institute, Gottingen, Germany (Manfred Eigen)
3. Institute for Theoretical Chemistry, Vienna, Austria (Peter Schuster)
4. University of Stuttgart (Hermann Haken)
5. Free University of Brussels (Francis Heylighen)
6. University of Utrecht
7. University of Tokyo, Department of Pure and Applied Sciences, Tokyo, Japan
8. ATR, Kyoto, Japan (Thomas Ray)
9. Chalmers University, Goteborg, Sweden
10. NORDITA, Copenhagen, Denmark
11. International Institute for Applied Systems Analysis, Vienna, Austria
12. Institute for Scientific Interchange, Turin

Finding your Thesis Advisor / Principle Investigator (PI): Some Advice

As Robert Peters reminds us in his acclaimed Getting What You Came For: The Smart Student's Guide to Earning a Master's or Ph.D., 1997, the most important factor for successful M.S. and Ph.D. work is finding a faculty sponsor who 1) has published good work in your area of interest, and 2) graduates a good fraction of his or her students on time and happily.

Acceleration, universal evolutionary development, and futures studies are all radical areas of interest within academia at the present time. Looking through the academic databases like ISI Web of Knowledge, available in the reference libraries of every top university, can you find a full or associate professor who has published on your topics of interest?

Ask your potential faculty sponsor for a list of former students, both graduated and ungraduated. Talk to a number of these students at length to get their impressions of the program and the principle investigator (P.I.) you are considering working under. This individual should also be your thesis committee chairperson, to minimize potentially agonizing and seriously restrictive academic politics.

As discussed in Intro to Acceleration Studies and Universal Evolutionary Development Studies, ASF has a long term goal to promote the development of more graduate programs in Foresight and Futures Studies, Acceleration Studies, Acceleration Management, and Evolutionary Development Theory in coming years.

If you have a similar interest, we urge you to join our community. Meanwhile, happy studying!

Comments? Additions? Critiques? Send your feedback to johnsmart{at}accelerating{dot}org. Thank you.