Ghost Whisperers of Institutional Memory

Ghosts have needs. Memories, like dreams, need to be resolved, and that is how insights come. “Ghost Whisperer,” iRobot, and many crime shows depend on detective work based on access to other people’s memories. “Ghost Whisperer” character Melinda Gordon talks with ghosts so they can “move on” after resolving their memories and their insight and knowledge with the still living. Ghosts with lost memories plead for recognition, and only calm, measured, and respectful tones will bring them to life.

I have great memories from talking to older guys at HUD, who had worked on HUD’s “701” urban planning program. They were urban planners and architects educated in the 1950s, who remaining at HUD, traversed those disciplines’ remnants through the 1990s. The “701” program institutionalized and professionalized urban planning, but it became victim of its own success as well as by political change in the early 1970s.

These men had great stories, and they could not have cared more about the fate of cities. In the mid-1990s, one guy’s primary concern was “sustainability” but there was little attention to that then. Their thoughts were ahead of their time, not in a useless past.

Another friend spent 40 years at USDA (since retired, but still very active in his mission) and was at the forefront of introducing the internet to the government and he organized technology programs teaching thousands of youth in 4H clubs and schools. In the 1970s, he organized the digital transmission of President Carter’s press release text to Seattle about Mount St. Helen’s eruption.

Other friends were involved with the invention of magnetic storage disks that replaced paper tape, magnetic tape, or punch cards. These friends used large laser disks to provide documents and images to the public. Using what then was a significant adaptation, they used “listserv” instead of Twitter. In the 1990s, these friends and others created Americans Communicating Electronically, which was the first collaborative public sector eGovernment group. This was before the current so-called “Digital Revolution,” which is a phrase for a poor repetition of what started 20 years ago.

History may not be important for new government staff to motivate them to be whisperers. However, their jobs would be impossible without their elders’ committed work in technology.

What could you possible learn from older people? They are people who know underlying weaknesses of current technology or how derivative it is in comparison to original breakthroughs. For example, in a coffee shop, named “Crows Coffee” in Kansas City down the street from me, but not related, a guy my age came up to me saying “that stuff will cut you to ribbons.” I was dumbfounded at first, but only because I know about the history of cybernetics and system theory did I understand he was taking about the original use of paper tape which “stored” the code for analogue computers. When the perforated tape broke or unreeled, sharp edges cut people or more tape. Special glue was required to fix the program. He recounted the history of computers he had worked on from vacuum tube mainframes to minicomputers. With his tablet, thanks to the café’s Wi-Fi, he found pictures of those computers. He hardly talked to anyone interested in what he did. I couldn’t absorb the details of his life, and he couldn’t stop talking about the transition from analogue to digital computers. This is a story more about relating to other people than about technology.

Were it not for their lives and stories would I know a little bit about why and how stuff works. For example, it is a trite common place now to mention vaguely the “bug” in the machine of computer history.  The etymology (or entomology) of “bug” may not matter, but the word carries on and should not be trivialized. Does it matter that my use of the phrase “bug” in the machine is a reference to sociology books on technology: “The Ghost in the Machine” (Arthur Koestler, 1967) or the “The Machine in the Garden” (Leo Marx, 1964). Historical echoes matter whether belonging to people, books, or literature.

Young people need expertise that gets them out of their chairs and to step away from their computers. Administrative ghost whisperers, younger staff or not, should seek out older staff. That experience should not be disregarded as a novelty. Institutional memory does not belong to processers or SAN, it is not stored in files or on disks. Harbored in silence, mystery, and memory is insight into the origin of technological triumphs and failures. Even visions of past success might inspire young staff now. Warnings about political and personality intrigue offer sound advice about what and who to stay away from. Stories gained by clandestine or unpopular ways may yield facts that cannot be read from technology companies’ marketing material, administrator manuals, blogs, or user groups. This is not a platitude about respecting your elders. It is about not repeating past mistakes. Repeating past mistakes may be beyond your control when political leadership, who are under pressure to come up with something “innovative,” reject an agency’s status quo, only to repeat the costly failure of the past, which they may willfully ignore. It is not your fault

I’m not a techno-sceptic, and, as an Enterprise Information Architect, I’m immersed in data architecture and technology most of the time. Today, I concentrate on knowing why, when, and where “data science” makes sense and when it does not. Does this matter to staff told to “code” first and ask questions later? Does this apply to “agile” or “application driven” software development?

We do not need homilies, panegyrics, memorials, or prizes dedicated to women and men who made current technology possible. Older agency staff need respect.

Liquid sociology in a geographic context will become rivers or mud

By way of analogy or other figures, analyses such as these below have gained credence in association with a tide of writings about geography. Often the work of Deleuze and Guattari has been channelled through some geographic and geological terms. Deleuze and Guattari (A Thousand Plateauas, 1987) show how, in one of several ways, the borders of fundamental concepts in philosophy cannot be sustained. The concepts and figures typically used cannot sustain their separation often from other concepts drawn from other disciplines or from other ways of thinking. However, described as physical geography, this is analogous to what has been said of the Missouri River in the central US: ”The shifting channel provided a wide variety of hydraulic environments at a large quantity of connected and non-connected off-channel water bodies. Beginning in the early 1800’s and continuing to the present, the channel of the lower Missouri River (downstream from Sioux City, Iowa) has been trained into a fast, deep, single-thread channel.” (Jackobson, Jacobson, B. R., 2014. River-Gorridor Habitat Dynamics Research Lower Missouri River. Washington, DC: United States Geological Survey.2014) emphasis added). Especially in Bateson and Deleuze and Guattari, such themes cohere with at least four disciplinary tributaries: cartography, hydrology, cybernetics, and geology.

Liquid and Lines

Along the angle of refraction of the deep waters of Bateson’s (2000: 407) writing, cybernetic terms and theory readily appear. When Bateson is called a cyberneticist, his work is funnelled toward information theory linking computer technology with geography. (Dyson, 2012: 3) The locus of cybernetics is information; this is not a colloquial expression, but specific to “information” or “communication” theory belonging to the history, logic, and mathematics of electrical engineering and computer science. (Dyson, 2013) Bateson (2000; 406-408) writes: “In cybernetics, mapping appears as a technique of explanation whenever a conceptual ‘model’ is invoked, or more concretely, when a computer is used to simulate a complex communicational process….” Bateson continues insightfully that a fundamental tendency, fallacy, and constitutive error is mistaking “map and territory” or “map for territory.”  While power lines, flows of information, wires, cables, and “wireless” lines are the stuff of cybernetics, they still diagram a linear system, but still can capture neither a map nor a territory.

Reading the very early theory and practice of computer technology and cybernetics, streams of Bateson’s thinking point to a backwater of computer theory. Jagjit Singh (1966: 8, 9) uses a sweeping introduction to cybernetics. In contrast to how “mapping” of data evolved today, the emphasis was on the form of “information,” lines, flows, codes, patterns, and many other terms that seem to be a new vocabulary.  In the profession of electrical engineering, Singh (1966: 21) writes, information is stripped or purified of the semantic content, but is somehow more “lavish” than alphabetic language. Its notation is formulas, tables, and diagrams. The linear diagrams, which depict systems’ design or “roadmaps,” saturate thinking about computer systems. The communication system, expressed as a linear diagram, is composed of an information or message source, encoder, signal, channel, noise, decoder, receiver. Singh’s explanation is not without references to Zeno, the Talmud, Shakespeare, Chinese “ideographic” language, and Hindi symbols; all without touching their content. The form of information is thought to overpower semantics by its “lines of behaviour.” A digital model can be described as a “set of lines of behaviour” or “the field of lines of behaviour,” passage to equilibrium, and ending in a “the terminal field.” (1966: 218) The major concepts of positive and negative feedback are largely missing. This especially is still true of computer systems now. Singh (1966: 236) concludes that assessing the efficacy of computers “require[s] a theory which ensures communication of optimal information without interference by vibrations of noise.”

Bateson is covering the many meanings of “mapping” in theory and professional practice. In practice, and as Bateson explains, “mapping’ has many interwoven meaning. With the subsequent development of information technology, “mapping” has taken on more meanings than Bateson uses.

  1. Mapping means, in professions of software development and data management, comparing the semantics of one group of data values to another group to assess or make them equivalent.   A fairly innocuous example of such ‘mapping’ is making “date_of_birth” in one database the same as “birth_date” in another. A very problematic example would be comparing “poverty_rate” in one database to “rate_of_poverty” in another. The first may refer to a national demographic variable and the other to a periodic rate of poverty income of an individual. Sorting the meaning and logic of concepts and names is covered by the silly word, “disambiguation.’ The semantics of these data elements are critical to the validity and integrity of the data.
  2. Mapping means assigning formal linguistic notation to words and names into a semantic space and network diagram based on the numerical count of their occurrence in a text.
  3. Mapping means assigning data values to coordinates in a graph as in analytic geometry. Data points are set into formulas illustrating geometric figures. This exercise can follow from mapping data elements as above.
  4. When these styles of mapping are applied to or metaphorically confused with “territory” they support the creation of geographic information systems and cartography. In that case, all the history of cartographic problems floods into the problems of software development and database management. That is, the conventions of making maps are the essential condition of building software, data, and cartographic systems.
  5. Mapping becomes reflexive when taking a semantic, logical, rhetorical, or philosophical analysis of the “mapping” natural language categories into data, data to other data, or categories to categories with different meanings as well as any other level of meta-mapping of these to each other.
  6. Mapping the behaviour of mapping becomes a cultural, epistemological, and psychological manoeuvre. One’s professional credibility depends on the skill of negotiating all of these. Usually, as one moves in such rarefied dimensions and away from the immediate tasks of creating a database, the more one is viewed as a misfit.   One can manoeuvre from this point to the first as well, in and out, back and forth depending on the task at hand.

Deleuze and Guattari (1987) use concepts and style from Bateson’s work to become feedback that transforms it. Together, Bateson plus Deleuze and Guattari, the ideas’ volume, valence, and viscosity make their “noise,” as in cybernetic theory, informative. A summary of points or lines of argument in Deleuze and Guattari are not often desirable or possible to regulate and explain by way of citation. That is, whatever might Deleuze and Guattari write in one sentence there are hundreds of others that oscillate the meaning and importance. Language itself is an “overcoded” system meaning that computer code instructions are written to provide redundancy in the case of failure. An “abstract machine” in computer science is a logical statement from which more code is generated and perpetuated. (Deleuze and Guattari, 1987: 148,223)

The word “map” itself has become so overcoded and redundant — with new computer programming languages, overcoding and redundancy signals of error — that leads to more confusion as an emblem of geoscience. The diagrams in the early days of electrical engineering for computers are called maps. Ekprasis in general and specifically, narrative, epic poetry, paintings, textiles, and glyphs were and are now seen as viable representations of geography. However, the more we relay words expressive of geography, the geography itself slides toward being meaningless. Stones, knives, nails, ball bearings, cell phones, scimitars, and little geographic technology combine in light forces, but not weak, to spread horrible events. In each case, territory breaks down. Territory is not the map, and the map is not territory.

Bateson, G., 2000. Steps to an Ecology of Mind. Chicago and London: University of Chicago Press.

Bauman, Z., 2012. Liquid Modernity. Malden(MA): Polity Press.

Dyson, G. D., 2012. Turing’s Cathedral: The Origins of the Digital Universe. New York: Vintage Books.

Singh, J., 1966. Great Ideas in Information Theory, Language, and Cybernetics. New York: Dover Publications, Inc..

What Becomes Geography

Where scales lead.

The concept and measurements of scale are paramount to geographic information science and without this abstraction location, size, and direction in maps would not be possible. The scale sets some middle distance (based on an acceptable ratio for a specific purpose) of geographic pattern recognition. Scale ratios for cartographic purposes — either too small (1:1 billion) or too large (1:1) – to render patterns visible.5

The ratio of scale first covers too large an area (a small scale) and the latter too small an area (a large scale) to be visualizable. Relationships which are measureable can be used with geostatistical or tabular statistical methods. Any perception of relationships would be impossible, and their meaning as geographic patterns lost. There is somewhere an applicable middle distance between macrological and micrological analysis. Unexpectedly, from a strictly geographic information science perspective, Borges’s parables orient readers towards the limits, if not irrationality, of that perspective.

Borges

A parable about the logical consequences of scale precision can be found in Borges’ writings. This is about construction of map so precise that it duplicates everything that it is supposed to be represented. In terms of geographic information science, this describes a cartographic scale of 1:1 where every foot corresponds to every ‘ground-truth’ foot and every topographic detail, at least, must be reproduced.

In that Empire, the Art of Cartography attained such Perfection that the map of a single Province occupied the entirety of a City, while the map of the Empire occupied the entirety of a Province. In time, those Unconscionable Maps could no longer produce satisfactory results, and the Cartographers Guilds struck a Map of the Empire whose size was that of the Empire, and which coincided point for point with it. The following generations, who were not so fond of the Study of Cartography as their Forebears had been, saw that the vast Map was useless, and not without some Pitilessness was it that they delivered it up to the clemencies of the Sun and the Winters. In the Deserts of the West, still today, there are Tattered Ruins of that Map, inhabited by Animals and Beggars; in all the Land there is no other Relic of the Disciplines of Geography (Borges, 1998: 325).

At the heart of understanding geographic precision is the evidence of the scale that a map represents. Borges creates this parable of a passionate pursuit of exacting precision in cartography. Three events happened here. First, a perfect rendering of cartography in a single map of the province was commanded. Second, the map was inscribable because it was not precise enough for the administrative purposes of the Empire. Third, following their mandate to the letter, they produced a map of the entire empire at a scale of 1:1; however, the size of the map rendered it useless, if not redundant. Following generations did not revere the discipline of cartography and casted it into a desert only to become the ‘Tattered Ruins of that Map.’

Every desiccated piece is still at a scale of 1:1 because it is identical to where it was once located. The precision is inescapable no matter how useless it became. The pieces became the ruins of cartographic expertise. Cartographic perfection was preserved in each fragment, but what the map represented could not be discerned. No matter how much the Guild of Cartographers (read the disciplines comprising geographic information science itself until the present, when cartography alone is no longer the sine qua none of the geographic profession) was respected, subsequent generations found it worse than anachronistic. In this case, the passion for precision exceeds the limits through which geography is comprehended. The utility of cartography in its geographic and historical scale contradicts its own foundation. Verification and verisimilitude are oriented to the ruination of the discipline of geography.

The ruins of the geographic profession rendered it irrelevant. A reader of Borges’ parable, who is sympathetic with, if not a member, of the Cartographers’ Guild, is likely to wonder what replaced geographic information science. Something must be replaced of course! Nevertheless, geographic information science became a relic due to its own striving for perfection. With its perfect resolution, ‘field tested’ or ‘ground truthed,’ the map was no longer valuable because it represented nothing while representing everything. It was only a simulacrum of the location of things or the topography.6 There was nothing of interest left to interpret.

Robots, IoT, Drones (RID) and Zombies

Robots, IoT, Drones (RID) and Zombies

Dennis Crow
June 2, 2015
https://www.govloop.com/community/blog/robots-iot-drones-rid-zombies/

The future is hard to predict when the present is torn between the living, the living dead, and the never have lived at all. We don’t know the demographics of robots, sensors of the Internet of Things (IoT), learning machines, and drones. Of course, the count of zombies is unknown because they could very well be increasing at any time. Robots, Internet of Things, and Drones (RID) is advertised as new technological miracles.

If we think that humanity lives in valley of obsolescence, we are asked to favor machines or zombies. My acronym of RIDz points to a “rise of the machines” and the decline of the “human” species. It is clear that the “last hope of humanity” resides in women facing great danger even at the bottom of the technological and human barrel. (See: “Mad Max, Fury Road”) Zombies fill the gap between the still living and the never living. If you watch CW’s program, “iZombie,” the young female seems very much alive and cozies up to the dead in the coroner’s center of a hospital. Brains, situated in an antiseptic environment, make convenient snacks and carry out. Because she works in a hospital, one wonders if she will hook up with surgical robots and medical sensors – but not with the doltish medical records system –instead of the other zombies who are “coming out.” Literally, closer to home, the State of Kansas made zombie apocalypse an acceptable training exercise for the State militia. There are probably private militias doing that as well.

RID’s role in administration is rapidly increasing for medicine, “smart cities,” retail, and farming. This trend exponentially increases without much oversight in spite of FAA’s futile attempts. In IT publications, RID analyses and advertising themselves are constant streams of data. Telemedicine has been used for many years. Now doctors can remotely do surgery, but not through an autonomous robot. Retail sales can be tracked in near real time when and where customers have bought and are sent immediate discount notices based a few meters of location. Agricultural agencies or firms can collect boundary, soil, and crop yield data via RID.

Again zombies exempted, “cybernetics” has been the name of RID since the 1950s. You probably know that a “Universal Turning Machine” (1936) combined an analogue computer and a robot that could perpetually compute and manage itself. (Stuart A. Umpleby, A Brief History Of Cybernetics In The United States, Research Program in Social and Organizational Learning, George Washington University, 2008; Slava Gerovitch, From Newspeak to Cyberspeak: a history of Soviet Cybernetics, 2002) In 1950, the father of cybernetics defined information: ”information is a measurable quantity, and that it can only be studied on a statistical basis.” In the 1960s, Gregory Bateson emphasized that “…the subject matter of cybernetics is not events or objects but the information ‘carried’ by events and objects. We consider the objects or events only as proposing facts, propositions, messages, precepts, and the like.” “Machine learning” is a feedback loop, which is metaphorically applied to the long-ago electrical mechanism of a thermostat.

The industrial dreams of the past still shape the technological labor for the future. At the 1939 World’s Fair, General Motors set up a gallery where people could see interstate highways and self-driving cars; Westinghouse created the “Electro” fake robot, which was a precursor to the iconic B9 robot on “Lost in Space in 1965. These were the fantasies now coming true of a technically skilled household or administrative assistant. The “iRobot” company (www.irobot.com) “designs and builds robots that make a difference in people’s lives.” Either for cleaning a human’s house or for killing them through military applications, iRobot makes “unmanned ground vehicles [to] reduce risk to personnel, operate downrange, report data and deliver predictive intelligence/ISR.” ISR is defined as “an activity that synchronizes and integrates the planning and operation of sensors, assets, and processing, exploitation, and dissemination systems in direct support of current and future operations.” (www.thefreedictionary.com). In “iZombie,” the character ‘Liv Moore’ — aka “live more” (Rose McIver) –inherits the memories of brains she eats to preserve her humanity, and she helps solve crimes, while trying to protect the city from new conniving smart zombies. Today’s evolved earthly zombies differ from the emotionless body snatchers dropped from space, in the original movie “Invasion of the Body Snatchers,” (1956), who really served no purpose. Now brains are for eating, and not for extending science and culture. Robots are a menace to humanity, and not a “labor saving” device.

What administrative purpose does RID serve? Robots, drones, and the internet of things populate the taxonomy of machines. Moreover, they are expected to learn, whether living or not, which has been their purpose since their advent of cybernetics. Since Charles Babbage maybe, “thinking machines” have been personified and designed for personal and administrative functions. In an insightful article, “If Algorithms Know All, How Much Should Humans Help?” Steve Lohr goes after – what used to be called “decisionism” in the age of cybernetics – what he now calls “Data-ism.” (nyti.ms/1MXHcMW) In both cases the fallacy is that “decisions based on data and analysis” and run by “algorithms” yield better decisions. Recently when I was debating this in a coffee shop with other guys, and when the only woman customer rightfully left in disgust, I argued that regardless of the computing power, people had to decide what decisions to decide, decide how to write the algorithms to be calculated, and decide if the results are valid. RID alone cannot do that. As they re-evolve, zombies are more likely to be able to do so in the future; after all, even eating human brains should give them a leg up on robots. Bad and good RIDdance should teach us how we desire more powerlessness and are ready to abdicate human responsibility. I prefer to stick with the ponderous human beings. Because I read about and strategize about RID for agriculture most of every day, if I had to make a choice, I come down on the side of Liv Moore.