Why STEM needs more women


Women in STEM, courtesy of cnn.com
Women in STEM, courtesy of cnn.com

Before 1993, most women that visited ER rooms in America were misdiagnosed with various illnesses, many of them would  later be revealed to have had heart disease . A harrowing number of these women were effectively sent to their deaths because of  scientific tests that were essentially devoid of any insights on the accuracy of the tests on women. Until 1993 the pervading belief was that women exhibited the same symptoms as men for cardiovascular disease, it was later found out that this was not necessarily true. This new revelation in science caused standard testing methods for cardiovascular disease to be discontinued, by then of course thousands of women had suffered adverse effects to misprescribed drugs that were created on clinical trials focused on the average sized man. This kind of oversight was motivated by the simplistic idea that women are “emotional” or in slightly more scientific terms, that they have physiological imbalances that make their test results unreliable. Surprisingly, this procedural bias continued in the US drug industry from 1850 to 1992 before health regulatory bodies mandated the inclusion of women in clinical trials. It is now known that women exhibit different symptoms to heart disease and perhaps consequently, that more women die of heart attacks than men. Although macabre, the story reveals a cross cutting homogeneity within the scientific enterprise that provokes us into wondering about what else we continue to miss daily because of gender specific valuations. We can only hope that our ignorance is not nearly as fatal as a heart attack.

So far, the story of women in STEM (Science, Technology, Engineering, Mathematics) has been one of inclusion, and one that is often overdressed in romanticized gender parity rhetoric. Statements such as “women are equal” and “women as just as capable as men” are often meant to imply that women are just like men, or I imagine that is what most men hear. This could be because men are unfortunately the status quo and sometimes when you are the status quo, it is hard to realize that there is another “quo”. The argument of equality for women in STEM in the formative years was poorly articulated and not well understood. This is true for equality for women in general, perhaps this is why, when faced with some ideas of feminism men are quick to retort that women should do their own heavy lifting or hold their own in a bare knuckle fist fight with a man. Of course the argument is more correctly framed today as an issue of equal rights for women. In the hope of building a more just and equitable society, most of us wish for the equal inclusion of women in both the knowledge and monetary economy because we believe that we have to be fair but I’m afraid this sentiment alone is not enough and in fact undermines the real contribution of women in any economy.

rosieforstory_0I am sure by now you have guessed that the author of this article is a man, one that until recently often saw it as a duty to the see the equal representation of women as a way to promote just order in the world. What I didn’t know about is the genius of decentralized design and comparative advantage. The truth is men and women are fundamentally different but most of us are guilt-tripped into ignoring why this is a good thing. There is a thing, a keen perspective, call it “gender innovation”- that only women can offer because they are women. This perspective is the billions of female minds thinking and dreaming up inventions to world problems, inventions we will never get to see because they are actively being repressed and downplayed by the dominant male bias. The male bias is an anachronistic bastion that maintains that only male ideas or ideas that solve men’s problems are worth pursuing because civilizations were built predominantly on the achievements of men, this idea is counter-productive to the say the least.

I often liken our predicament to the benefits brought about by extra-terrestrial inventions or technologies meant for space. Autonomous vehicles for instance where envisaged for space and deep-sea exploration because there is no place more foreign or hazardous to us. These technologies have found earthly/terrestrial applications. In order to solve a problem, woman centric or otherwise and because of the obvious motivation, a woman will invent something that can find far reaching applications, widening our inventory of inventions. This is the key to sustainable design and ostensibly the reason nature breeds diversity, because it makes the biosphere more adaptive to an ever changing environment. This is what we’re missing out on, a plethora of woman-built inventions that make us more adaptable to change in political, health, technological, economic and educational ecosystems. This is why the title of this article reads the why it does, “STEM needs more women”. Science and technology actually need the inventions of women, from a purely scientific, economical, functional and unadulterated point of view you cannot not have a sustainable and growing enterprise in science if you willfully crowd out the contributions of other scientist based on their nationality, ethnicity or gender. If you do this then science becomes esoteric and secretive like religious sects crippled by Aristotelian ideas of a universe with a “special” earth at its center. This should be the dominating argument, plain and bare, objectively presented with compelling numbers that show that less than half of a world’s population worth of intellectual raw material is being wasted. It is the thousands of jobs technology is projected to create with only half a work force to fill these jobs. Gender equality rhetoric in isolation is nothing but well-meant platitudes that mythologise the benefits of real equality.

In our experience teaching computer science thinking and programming to primary age girls, we found that the greatest challenge is convincing the girls that computer science is not a “boys thing”. There is a noticeable lack of a good interpretation of the STEM curriculum that makes it hard for girls to imagine themselves as thriving scientists and engineers. The curriculum is often presented in a skewed way, especially at primary ages it suggests that boys are more suitable for STEM jobs because they have an early experience playing games and toys related to STEM jobs. Scientific jobs are not easy but primary education should not scare girls from choosing STEM careers, same there should be no illusions about how much societal forces will try to discourage them, they should be made aware of the male bias. Women are early adopters of technology, to encourage our Computer Science girls class we often lead with explaining that the worlds first computer programmer was a woman, lady Ada Lovelace. To drive this point home we make references to the 1940s when most men worked hardware engineering jobs while women “manned” office desk jobs working with software and becoming the world’s first software engineering work force, in fact the term “software engineering” was coined by Margaret Hamilton, a woman. Obscure stories about women’s contributions to computer science are bountiful, read this report on the ENIAC six, or this one about the history of programming. . When teaching the girls, you have to situate them in a historical and present day reality all the while checking your own vantage point and bias.The best way to encourage participation of girls in STEM is to give them role models, increasing the prominence of women in STEM galvanises their enthusiasm to pursue STEM careers. Of course dispelling the myths of the male stereotype gets harder when there are daily reminders that there are those who think women have no place in computer science. The gamer gate controversy is an example of how misogynistic sentiment can sometimes scare women out of the tech industry.

Mae Jemison image, the first African-American woman in space has a background in engineering and medical research
Mae Jemison image, the first African-American woman in space has a background in engineering and medical

Debunking the male bias doesn’t happen without debunking cultural and racial constructs.It is undoubtably harder for black women to pursue careers in STEM, even with inclusion programs the overall number of black women in STEM fields has remained alarmingly low. Cultural generalisations that commit women to other professions are a greater challenge to black women. The admission of black women in academia is often just part of meeting a diversity quota, this makes for a good splash of color on the university personnel page. Academic brilliance of women from minority groups is even less acknowledged in academia, so much so that there is an invention of the word “Minority Academia Ghetto”, a place where the non-functional, non-essential minority staff of universities are relegated to. It is evident that minority groups have been kept out of post doctoral and higher management positions, this further marginalizes black women and causes them to suffer from depression and impostor syndrome. Clearly we have a long way to go before women feel completely welcome in STEM but good progress is being made all around, the world is slowly realizing that women will offer an incalculable contribution to science if they are allowed to participate on an even playing field. A more productive world of science would have us see a shift from an emphasis on the gender meritocracy that relies on ideas of victimhood and pity praise, to a realization that excluding women is slowing down innovation that would otherwise make us a more advanced society.

Check out the following resources if you want to get into STEM


Moore’s Law no longer our performance oracle

Integrated Circuit, photo courtesy of http://wonderfulengineering.com

With the debut of technology theories like the technological singularity and the realization of “the internet of things” on the horizon, there has been clamorous panic among technocrats as they debate whether we can continue to accurately predict or control technological advancement. The optic we have used to predict computational power for the last fifty years or so has been Moore’s Law. Without getting into the highly intellectualized rigmarole of digital electronics, Moore’s law reads like this, “the number of transistors that can be placed inexpensively on an integrated circuit doubles approximately every two years” but is interpreted to read like this, ” the number of transistors that can be placed on an integrated circuit doubles approximately every two years increasing computational power or performance exponentially without diminishing returns”.

How did we get here? a simple thought experiment called the Sand Heap Paradox can be used to put things in perspective. We have a heap of sand and we continuously remove one grain from it. The change in the size of the heap is nominal, so much so that we fail to realize that it is reducing in size, although very slow and on a miniscule scale. Fast forward a few years and there is only a single grain of sand left and no heap. Think of the end of Moore’s law as the moment we realize that there isn’t an infinite amount of sand available and that all predictions have their limits. Sand of course is almost poetic in our case since silica is used to make silicon which is a key ingredient found in every microprocessor transistor.


This is where we find ourselves. The number of transistors you can cram into a chip can’t increase forever because of the physical limitations of silicon based chips. Some research is suggesting that this was already the case at 28nm(nanometer) but microprocessor giant Intel reported a 14nm achievement in 2014. The biggest hurdle to keep shrinking transistors to tiny atomic sizes is heat and leakage. At 5nm the laws of physics turn the chip into a frying pan and quantum mechanics at that size scrambles the atom and disrupts information flow (ability for signals to travel through a logic gate on a silicon wafer in a coordinated fashion). So Moore’s law falls short at postulating leaps in computational power primarily because the axiom is untenable at a certain size and that limit is fast approaching. Cutting edge research is instead looking at quantum and molecular computing to foster in the new paradigm for processing power with post silicon transistors. In this TED talk Ray Kurzweil gives the silicon based transistors another 10 years before we reach the performance apex. I need to mention that Kurweil has an impeccable history of predicting trends in technology. Renowned futurist Michio Kaku also echoes Kurzweil’s sentiments. The more closely we examine Moore’s law or its inaccurate interpretation the more it appears that it is a rule of “dumb” or self-fulfilling prophesy that merely coincided with Intel’s success in the microprocessor industry, Moore’s law for any scientific purposes is already dead and is only used purely for marketing purposes. So really the question is not whether Moore’s law is still valid, but for how long it will be be the conceptual framework we use to fuel our postulations of computational processing, pundits say 10 years but add on some reverse engineering with 3D transistor arrangement and we have roughly fifty years more.

mooreslaw_660In conclusion the debate on Moore’s law can be polarized into two camps, those that think computational power on silicon based transistors will keep increasing forever under the Moore paradigm and those that think the days of increasing computational power using silicon based transistors are numbered. Now you’re probably wondering whether all of this matters to you as a consumer, the answer is it probably doesn’t but the next paradigm which we think of to conceptualize computational performance leaps will probably give rise to greater computational power. When we move from Moore’s law and believe me we will, this will punctuate a transformation of our technological civilization. Think positronic brains and human like interactions with virtual personas. The silver lining on the dark cloud of Moore’s law might be as Ray Kurzweil puts it, that

“the dwindling of any paradigm is that it creates research pressure to come up with another paradigm that improves on and supplants the previous paradigm”.

Moshe Y. Vardi who wrote an article (Is Moore’s Party Over?) also seems to agree, adding that the death of Moore’s law will plunge us into a time when we will have to become creative with algorithms and systems in order to leverage the stagnation. Exponential growth of computing power under Moore’s law will definitely slow, perhaps to continue under molecular computing or some other far out concept.That is it for now, time to retire Moore’s law to the same place we put Ptolemaic planetary theories.

You can read Intel co-founder Gordon Moore’s original paper here

Wikipedia and Indigenous Knowledge Systems

You must expect that from time to time this blog will concern itself with research matters around information systems and issues about their appropriation or adoption in indigenous communities. This is because part of our social development agenda is to create tools that aid indigenous communities. That being said I would like to, albeit at a very high level, deconstruct the implications of participatory computing systems like Wikipedia and the role they play in empowering Namibian communities or the communities of other countries like it. This article is a preamble to a more comprehensive report that I’m working on during the course of the year.

Once A Nomad

With the recent advancements in ICT4D, Namibia has seen many of its indigenous communities receive huge investments
in telecommunication infrastructure. There are many reports that document the progress of this endeavor and I suspect they form part of a greater discourse about the proverbial “bridging the digital divide”. My concern however is not whether rural schools are getting educational necessities like internet but rather the socio-technical issues that come with introducing “foreign technologies” into indigenous communities.

I recently got dragged into the maelstrom of Wikipedia and what it means for indigenous knowledge systems. I’m going to ignore any academic citation red tape right now and tell you that indigenous knowledge is popularly defined as “knowledge acquired by people who have had a long rapport with their environment”. The Himba of Namibia for instance would typically qualify as possessors of indigenous knowledge since their livelihood over the years has relied greatly on knowledge they acquired from living in Southern African environments for a long time.

Jimmy Wales, one of the founders of Wikipedia has described Wikipedia’s grand vision as “creating a world where every person on the planet is given free access to the sum of all human knowledge”. I’d like to point out that “sum of all human knowledge” is really where it gets tricky. Currently the regulations that control the commission and omission of information into Wikipedia are laden with what we call a systemic bias. This systemic bias is preventing us from aggregating the sum of human knowledge because generally the curators running the show stem from western origins bringing with them western paradigms. This is being promulgated by a few counter intuitive rules they essentially say everyone is allowed to say their say as long as they do it in erudite English.  One rule (notability) for instance requires that any information contributed to Wikipedia is anchored by reliable sources. The problem is reliable sources is defined from an occidental point of view.

To put things in perspective, this essentially means that if you as a Himba wanted to submit an article to Wikipedia documenting a unique customary tradition this article would have to be substantiated by enough notable sources for it to survive Wikipedia’s unforgiving curators. Now, finding reliable source might not be a problem when writing about a particular butterfly in North America since Zoologist or historians have documented the landscape to near exhaustive limits but this is not the case for Namibia. A lot of Namibia’s history or indigenous knowledge is undocumented and what little has been written about it has been written from the view-point of Western settler intelligentsia that introduce a serious narrative bias.
The entire thing is a Penrose step of never-ending issues, not only socio-technical but sometimes behavioural and cultural as well. With strong cultural underpinnings, we see local value systems clashing violently with those embedded in imported technologies. Perhaps I’m being too idealistic but when we leave this planet for the stars one day I’d like to leave with the wealth of its knowledge on a memory stick and I’m not just talking about knowledge on my favorite composer Frederic Chopin, but also how my ancestors made my favorite traditional drink Oshikundu. Currently, many research groups are experimenting with meta tools that make it easy for potential would-be editors to become frequent contributors. The declining retention rate of editors on English Wikipedia doesn’t help the faint glimmer of hope to encourage contribution to the sum of human knowledge. One would think that to overcome local challenges to the meagre repositories of Indigenous Knowledge we have to wait for a top-down solution but if M-PESA is anything to go by maybe we ought to find local solutions by co-opting a Western technology.

(Note the irony in all the wiki links in this post 😉 )

Nanotechnology: The Future of Faster Electronics

With 15,342 atoms, this parallel-shaft speed reducer gear is one of the largest nanomechanical devices ever modeled in atomic detail.

Nanotechnology refers to an area of science that involves the manipulation of matter on an atomic or molecular scale, generally accepted to be in the 1 to 100 nanometer range in at least one dimension. It involves the creation of chemicals, materials and even functioning mechanical devices at an extremely small scale.

So just how small are these nano objects we’re talking about, I hear you ask? Well since you asked so nicely, I’ll attempt to explain.  For starters – just to give you an idea: 1 nanometer (nm) is about one billionth of a metre. A human hair is about 80,000 – 100,000 nm thick. Using the gift of imagination, let’s shrink ourselves down to the nano scale (effectively making us The Nano-Tech Guys? Has a nice ring to it, don’t you think?).  Now that we’re tiny, let’s adjust the scale of things and take a look at a few familiar objects, to bring things into a more familiar perspective.

If we took 1 nm as representative of 1 metre, then mini me would be 1.7 nm tall. Our previously mentioned human hair would be 80,000 metres thick. That’s 80 kilometres. A sheet of paper would be 100 km thick. So if mini me stood next to a sheet of paper, it would be like big me standing next to something 100 km high. An object the thickness of a coin would be high enough to bump into some low earth orbit satellites. I hope this helps put things into perspective. Anyway, moving on…

I think it’s fair to say nanotech is still in its infancy, owing to the obvious difficulties in manipulating matter on such a small scale. At this tiny scale, many of the materials we’re used to dealing with have very different and very interesting properties, opening up a range of applications and possibilities. Ever the inquisitive one, I hear you ask again – “What can we do with these tiny items?” Well actually, you may have already used devices and products that incorporate nanotechnology. A few examples are:

Yes, sunscreen. Your transparent sunscreen most likely has nano-particles of titanium dioxide and zinc oxide that absorb harmful UV rays.

Nanoparticles are increasingly being added to clothing to offer UV protection, antibacterial action via silver nanoparticles, or nano silica particles for waterproofing. Expect future developments to merge nanotubes and nano fibres into “smart” clothing that can respond to your body, or your immediate environment.

 Computers / Smartphones / Tablets
Yup, those too. The super-fast processors that run your PC, smartphone, etc are manufactured using ultra-small semiconductor components that can be as little as 22 nm across nowadays.

Graphene is an atomic-scale honeycomb lattice made of carbon atoms.


One substance that seems to be causing plenty of excitement in the nanotech world is graphene.
Graphene is simply our old friend carbon – the same stuff that gives us charcoal, pencil lead, and the black stuff you have to scrub off the bottom of the pot when you get carried away playing games and you burn your dinner. Carbon atoms can be arranged in a variety of ways, with very different results. Depending on the configuration of the atoms you can get hard diamond, or soft pencil lead, to name only 2.  Graphene is a hexagonal, 2-dimensional sheet arrangement of carbon atoms, and is only one atom thick. This substance has incredible properties, particularly excellent electrical conductivity, which makes it perfect for manufacturing computer chips. Graphene nanoribbons could be capable of transporting electrons thousands of times faster than a traditional metallic conductor, resulting in fast processors and solid state storage technology that would be a gamer’s dream.

The medical applications of nanotech are shaping up quite well too, with biotelemetry implants the size of a grain of rice that can remain powered (with a graphene technology battery) for up to a month. In the medical field, nanotech also allows for effective drug delivery mechanisms. A nanostructured composition encapsulating a protein called interleukin-2 (IL -2), which is lethal to cancer cells, helps fight cancer more effectively while minimizing the side effects of high dosages of the “naked” IL-2 protein.

Nanotech has the potential to revolutionize a large number of industries. If we can develop better techniques for manipulating matter at this scale, we can expect a myriad of amazing new applications to crop.

 Right, so I’m off to play Crysis, where nanosuits and other cool hi-tech stuff abound. Let’s hope I don’t burn my dinner.