π3 Training

What future do you envisage? What history do you believe?

Both the past and the future are key determiners for how we create an understanding of the world we believe today. Both influence the paths we choose to create – or accept.

There are many different analogies to explain what kind of people education should be creating for a society’s futures. Many governments have spun the STEM story; that is, the need to teach Science, Technology, Engineering and Math, often at the expense of the Arts and Humanities. The problem is that although STEM is crucial – necessary – no-one has demonstrated how much STEM is sufficient. How much mathematics, science, engineering or technology is needed to bring about the so-called “productive” and “profitable-to-society” future human? What future is it that people envisage when they make claims about STEM? They usually revolve around loose beliefs about growth, GDP and fiscal policies. Almost never do the proponents link health, wellbeing, equity, consumption, respect, or happiness, to name a few. A 2015 OECD publication suggests that the countries that use technology the most in education also have the lowest math and science scores. Alternatively, some East Asian societies that excel in maths seem not to produce equal new knowledge or less stupidity than other societies.

STEM is necessary but how much is sufficient?

Some have used STEAM as the focus for education, adding Arts (and Humanities) into the acronym. This also seems to make a lot of sense. As anecdotal evidence, I asked a person with two Bachelor diplomas – one degree was an Economics major – what was the most important thing he had learned in his studies. His response: History. Why? “It taught me how to search for information, verify the information, collate the information, and present and communicate it in a new form to communicate to an audience. This was the most valuable skill I needed throughout my working career.”

Learning about science does not make you a better thinker, communicator or citizen. Learning complex equations could make you better at mathematics. Learning science could make you better at understanding epigenetic and human physiology. Coding could facilitate a deeper appreciation of how to utilize technologies in meaningful ways. And engineering tools could help you build more dependable infrastructure. They do not correlate or cause better human beings.

STEAM is necessary but how much is sufficient?

Let’s be honest: we really do not know how much STEAM or STEM is sufficient. If I were to iterate a usual sarcastic and cynical comment, I would suggest sufficient seems to be when someone can  compensate the failings and flailing of public figures – elected or self appointed, when someone can help politicians sound intelligent and knowledgeable about other people, when academics and/or bureaucrats promote (or otherwise) the value of certain disciplines over others, amongst myriad other spurious reasons that we accept carte blanche. 

Education, in some societies, focus on developing i-type graduates; those who have a very deep understanding about one specific field or discipline. Perhaps the traditional academic or research or PhD student fit this model. The i-type citizens are crucial for “developing” societies where basic infrastructure are necessary. By basic infrastructure I not only refer to roads and bridges, but economic and commercial structures, as well. Let’s call it the development of Human Security.

Along came the Internet, connectivity and a so-called smaller globe – the Global Village. Suddenly, T-type graduates were necessary: people who have an i-type knowledge of one area but were also well educated to general and world affairs, thus being able to work across cultures, organizations and participate in the global community. Countries, like Japan, sometimes espouse the T-type ideal as a way forward for their citizens, who have traditionally been exceptional i-type people.

The rapid changes in our knowledge and understanding of the world require new graduates: π-type graduates. The number π makes for the perfect analogy because π is the perfect number. π is also infinite – highlighting that we should never stop learning. As a purely theoretical, a wild hypothesis, I might claim that when we recall the number π we reveal our own level of thinking – not only for maths and numbers generally, but possibly even for the way we approach life itself.  π provides an updated image of the graduate that is required to manage the current world, and create the future versions. 

A π-type graduate is one who has a good general knowledge and is therefore able to be connected across peoples, cultures and organizations, but π-type are also specialists in two (or more) fields or disciplines, enabling them to work across specialties. π-type people have a deep knowing and a deep learning of both the discipline itself and the discourse, not merely an understanding of the words, as might occur when two T-type people collaborate. The π-type will enable thinking that will bring the futures.

Unfortunately, our education systems are still, by and large, locked into patterns that produce either i-type or T-type graduates. STEM completely misses understanding futures, unless those futures are built around visions of A.I. machines running everything, leaving us human plebs to be creatures of leisure, hibernating our bodies as we survive by being hooked on gene therapy and mind fantasies. That is, of course, fictional (or is it?).

Notwithstanding, education can not merely (re)produce graduates who excel at mathematics and sciences for not all can be so ‘clever‘ (just consider the allusive, but likely, g in intelligence, or even – heaven forbid! – the genetic influence and the context that facilitate or retard opportunities). And nor does it address the scientific question of necessity and sufficiency. If a society’s goal is to seriously develop future capital – or economic generators – then present resources are being wasted on the future unemployed.

“Why?” you may rightly ask.

A.I. is already able to do mathematics and process factual scientific information better and faster than we average humans are able. A.I. is already building cars – and will soon drive them. A.I. has started to build houses – prefabricated designs constructed in factories in chunks and then added together like Lego blocks on site – or like a joining-the-dots puzzle to reveal the pre-recognised image. A.I. is taking over the financial and investment banking industry (and perhaps we should celebrate that as surely A.I. will not need those distasteful bonuses). A.I. is answering enquiries, by phone, email and at receptions. Bots are running wild. Perhaps, A.I. will one day reinvent itself.¹

Therefore, we must return to the necessary and sufficient question. It cannot be debated that STEM is necessary. Providing evidence on how much is sufficient needs to be forthcoming. STEAM is necessary; but again, sufficiency and a greater effort by those in the Arts and Humanities need to be made to show the necessity and value. Neither STEM nor STEAM are necessarily π-type graduates or people. To facilitate π-type people requires opportunities to engage with ideas and challenge assumed norms and beliefs in ceteris paribus in real world settings. It requires that our education needs to move beyond theoretical assessment alone to one that includes demonstrable knowledge. (Imagine getting a driving license by only passing the written test. Sometimes I wonder why we are so poor at transfer and consistency in our thinking.)

So what are π-type graduates and what is not π-type? And what is π3 training?

Stay tuned… update soon. As a taster, look within these web pages.

¹ As I reflect on this post, nine years post writing, I am amazed how much A.I. has been developed and the possibilities expressed and now histories to build upon.