Institutional Citizen Science

Personnel motivation and esprit de corps have always been important in any organization. Citizenship and Corporate Social Responsibility (CSR) have sometimes become as important to the brand as the trade name or logo. For many reasons, it is wise to consider institutional citizen science.

Traditionally, participation in citizen science projects has been done at the individual level. That is, observations (e.g. ecosystem projects), identifications (e.g. galaxy classification), and computational contributions (e.g. protein folding simulation) have been made by individuals. People sometimes join teams of like-minded or geographically grouped participants, and their efforts are often reported or tallied as a team. However, there has been very little organizational-level participation. There are many potential benefits of institutional citizen science, and in particular the computational variety.

Employee engagement can be improved. IT staff can provide leadership in setting up the required infrastructure, even with minimal initial effort. They can provide ongoing maintenance, expansion, and IT efficiency improvements. They can learn a lot along the way. Communications staff can prepare and disseminate any required internal information, and again, learn a lot along the way. Seeing the daily progress of the organization’s participation can engage everyone. A well run project can advance the cause of a more inspired, invigorated, enthusiastic, energized, and empowered staff with more of a sense of ownership for their organization. Progress in citizen science projects could be shown in a dedicated section of the organization’s intranet. Perhaps even a big screen could be located in common areas such as the lobby or cafeteria to show live content (e.g. simulations, animations, numerical results) and promote a sense of community. Management can simultaneously learn a lot about concepts such as computing as talent, cognitive computing, ‘gamification’, and integrating technology.

Institutional culture can benefit. Loyalty and pride in the institution are valuable assets. Leadership in ‘doing good’ is a strong motivator and has been a cornerstone of CSR for decades. There are opportunities for recognition and appreciation of both individual and team efforts. Both individuals and groups can suggest which projects to participate in from the large and growing menu available. Citizen science projects offer opportunities for people to think outside the box, to step out of their comfort zone, to consider more diverse possibilities, to form new partnerships, and to take the long view. A culture with all specialists and no generalists needs fresh air to breathe. The study of nature can offer a welcome break from politics and policy considerations, immediately and easily putting everyone on the same level: an observer.

Institutional innovation can benefit. Although tempting (when myopically studying spreadsheets) to farm everything out to consultants and sub-contractors, in-house innovation can be extremely valuable. Skunkworks (small teams for experimental projects) and Bimodal IT (production and exploration as separate yet symbiotic streams) can provide huge benefits, and citizen science is a natural skunkworks project. Notions of siloed knowledge and operation can be skeptically reviewed and perhaps even challenged without having to disrupt the larger organization. ‘What if’ models can move from pure theory to at least partial practicality. Distributed infrastructure is one example, and computational citizen science is all about distributed processing. Owning innovation, moving it vertically through an organization at the appropriate pace, and finally delivering it to the world can generate and cultivate innovation itself as an asset. Like the old proverb says: “Give someone a fish and they’ll eat for a day. Teach someone to fish and they’ll eat for a lifetime.”

Internal HR can benefit. Management and leadership talent can be identified and incubated in a non-threatening, non-competitive domain. Understanding the internal talent ecosystem is essential for the health and future scalability of any organization.

Governments can draw upon citizen science as well. On a regional or national scale, public policy can both encourage and benefit from an actively engaged citizenry. In-depth issues such as climate change, demographic change, disruptive technologies such as Artificial Intelligence (AI) and Automation, and general scientific and digital literacy become much easier to create a dialog around if the communication and participation is two-way. Agile, multi-disciplinary, multi-lingual, and age-spanning efforts are all increasingly valuable. A sparse and diverse population can come together on a unified effort without sacrificing, and perhaps even benefiting from, that diversity.

In the coming age of AI and Computer-Generated Imagery (CGI), there will be a tsunami of hoaxes, spoofing, and fake news. At best, mistaking such things for real content is embarrassing. At worst, these could represent an existential threat. The surest defense against these dangers is scientific literacy, both in the general population, and particularly within the organization. The first step in avoiding a trap is knowing of its existence.

There is also of course, a direct benefit to scientific research. Citizen science is not a replacement for academic research, it’s an adjunct. Projects run under the supervision and purview of scientists benefit in several ways from citizen participation. There is an increase in resources, harnessing more labor (e.g. collecting data), human intelligence (e.g. categorizing images), and computational power (e.g. crunching numbers for simulations). There is an increase in scope, drawing from a wider pool of time, space, and experience. There is also an increase in public awareness of scientific research and methodology. Scientific research is its own reward, and is worth defending.

Finally, there are the usual advantages that come with economy of scale. By gathering the efforts of many individuals under one roof, much wasteful duplication is avoided. Looking at computational citizen science in particular, instead of having members individually setup and run their own ‘crunching’ computers at home, they can participate at the workplace or remotely (perhaps using the ‘cloud’). The performance per watt of one big machine is much better than many smaller ones. It’s also a way for social skills to be advanced over isolation in the internet age.

Organizational learning requires interaction and participation. Growth requires innovation. Basic scientific literacy improves objectivity and comprehension of a complex world. Computational thinking improves problem solving skills. Improved use of reason and logic for analytical thinking, deduction, and inference might result. These skills and attitudes may not be easily quantified or measured, yet they surely benefit the organization, especially in the long term. Learning becomes an organizational task and goal, resulting in a more knowledgeable enterprise as a whole. Improvements in individual skills, together with deeper and wider internal communication go a long way toward that end. Diversity of learning styles, participation levels, and paces can be accommodated. The best organizations assign the ends, not the means.

“If you want to build a ship, don’t drum up people to collect wood and don’t assign them tasks and work, but rather teach them to long for the endless immensity of the sea.”
– Antoine de Saint-Exupéry

Concatenative Biology

There are several ways to categorize programming languages. One is to distinguish between applicative and concatenative evaluation. Most languages are applicative – functions are applied to data. In contrast, a concatenative language moves a single store of data or knowledge along a ‘pipeline’ with a sequence of functions each operating on the store in turn. The output of one function is the input of the next function, in a ‘threaded’ fashion. This sequence of functions is the program. Forth is an example of a concatenative language, with the stack serving as the data store that is passed along the thread of functions (‘words’). “Forth is a simple, natural computer language” – Charles Moore, inventor of Forth.

One of the great advantages of concatenative languages is the opportunity for extreme simplicity. Since each function really only needs to know about its own input, machinery, and output, there is a greatly reduced need for overall architecture. The big picture, or state, of the entire program is neither guiding nor informing each step. As long as a function can read, compute, and write, it can be an entity unto itself, with little compliance or doctrine to worry about. In fact, in Forth, beyond the stack and the threaded execution model, there’s precious little doctrine anyway! Program structure is a simple sequence, with new words appended to the list (concatenated). The task of the programmer is just to get each word right, then move on to the next.

In nature, the concatenative approach is the only game in town. Small genetic changes occur due to several causes, random mutation being one of them. Each change is then put through the survivability sieve of natural selection, with large changes accumulating over large time scales (evolution). (Evolution is active across the entire spectrum of abstraction levels. Hierarchies emerge naturally, not through doctrine or design.) Concatenation is the way by which these small changes are accumulated. Much of the epic and winding road of human evolution is recorded in our DNA, which is billions of letters long.

This process can be seen happening right now in molecular biology. Consider the ribosome. This is the little machine inside a cell that reads a piece of RNA (a chain of nucleotides) and translates it into a protein (a chain of amino acids). There is no Master Control Program assigning names, delegating work, and applying functions. There is only a concatenative program, built up over the ages by evolution. So, basic life uses a fairly powerful and successful form of computation: DNA for storage, RNA for code, ribosome for computing, protein for application.
(and natural selection for testing) 🙂

We flatter ourselves when we talk of our ‘invention’ of levers, gears, factories, and computers. Nature had all that stuff and much more long before we ever came down from the trees. Math, engineering, and science are great not because of their products, but rather because they enable 3-pound hominid brains to explore nature and ponder the possibilities.

Ancient Metaphors

New nations often use comparisons and metaphors to build a more familiar and solid framework or ‘story’ using the past, especially to evoke visions of ‘glory days’. One example is the symbolism of early America harkening back to ancient Greece and Rome. The founding fathers often learned Greek, Latin, and much of the history of those cultures in their formative years. We can still see that influence today in the architecture of capital government buildings.

It should come as no surprise then, that the same thing happens with computers and the insatiable need for new descriptors and naming conventions. Much of this framework has sprouted up within the last few decades. That doesn’t leave enough time for growing familiarity organically. Past language and literature provide a rich crop ready for immediate harvesting.

Here are two examples:

Beowulf

This epic poem is one of the earliest known pieces of vernacular English literature. The story is about a brave hero who slays monsters in the north of Europe sometime around the 6th century. It is a tale of great strength, difficulties overcome, and distances traveled. The fame of this poem (especially the Old English version) has grown steadily over the last two centuries. It has even been reproduced in literature, popular media, and the cinema. This provides a ready-made metaphor that can be used by something new.

In 1994, Thomas Sterling and Donald Becker built a computer at a contractor to NASA. It was the prototype for what would become the “Beowulf Cluster” architecture. This type of machine uses modest, commodity, even oddly matched PCs connected together to form a single parallel computer. It has acquired a rather stoic and renegade reputation in academia, where it has been used to gain entrance to the exclusive supercomputer club ‘on-the-cheap’. The name is said to have been inspired by the line in the epic poem: “thirty men’s heft of grasp in the gripe of his hand”.

Inferno

Another old epic poem is Dante Alighieri’s “Divine Comedy”. It is an allegory for the soul’s travels and a map of 14th century spirituality. It is as well a multi-dimensional exploration of sensitive/rational human nature and psychology. Again, this work is one of the most studied pieces of literature in history. It is another ready-made treasure trove of meaning and metaphor.

The first of its three parts is “Inferno” (hell). It is graphic and horrifying. It is also strangely open-minded and thoughtful in that figures from classical literature are woven into a Christian narrative. These include Socrates, Plato, and indeed Virgil, Dante’s guide. Perhaps the most apt adjective for “Inferno” is: deep.

“Inferno” was recently used as a template for a “Software Inferno” describing “sinners against software” and their torments (1). By using this template, the author begins with an extensive toolbox of metaphors. Of course, neither “Software Inferno” nor this short blog post should be used as an authoritative representation of Dante. There are plenty of good academic sources for that.

Instead of Virgil, Bell uses the Countess of Lovelace as our guide. More commonly known as Ada Lovelace, she was a mathematician and the daughter of Lord Byron, and is widely considered as the world’s first computer programmer for her work with Charles Babbage. She leads our hapless traveler down through the Inferno, towards the Earth’s core, along a roughly cone-shaped set of circular slices:

  • ANTE-INFERNO developers who couldn’t decide whether to use their skills for good or evil, denied entry to both Heaven and Hell, doomed to eternal obscurity
  • LIMBO developers born too early in history to know of proper software engineering
  • LUST developers who chose power and fame over commitment and responsibility, they gave their time to their computers instead of their family, they sought the spotlight, now they are blinded by its glare for eternity
  • GLUTTONY developers with human heads and pig bodies, IPO and stock bubbles had led them into wasteful, gross over-consumption
  • GREED IT types who gathered every crumb of profit for themselves, neglecting to, share anything with the people who got them there, condemned to a cacophony of falling pennies forever
  • ANGER realm of vitriol and negativity, with inhabitants broiled by burning paper, the only water available had been poisoned just like their own workplaces
  • HERESY developers who knew of good software engineering, yet refused to use it, now chaotically and aimlessly going their own way for all time
  • VIOLENCE developers who had inflicted malware, viruses, and phishing on the public, this pestilence now torments them in turn, and even sleep offers no escape
  • FRAUD techno-hucksters, advocates, evangelists who had foisted crappy software, standards, and models upon desperate users who longed for guidance, they now dwelt in sewage for all time
  • TREACHERY those who had enabled and encouraged this fraud, doomed to keep shoveling this detritus forever

Although intended for an audience of computer developers, the macabre humour is widely understood thanks to the template provided by Dante.

Here are a few other names for computer technology borrowed from the past:
Apollo, Athena, Delphi, Hercules, Hermes, Homer, Hydra, Jason, Janus, Merlin, Midas, Oracle, Odyssey, Phoenix, Phoebe, Pegasus, Sisyphus, Tantalus, Troy, Ulysses, Valhalla, Valkyrie, Zeus
… and of course a whole host of planets, moons, stars, and constellations.

(1) Bell, A.E. (2014). The Software Inferno. Communications of the ACM, 57(1), 48-53.