DISARMING THE GUN TO GHANA’S HEAD: Using artificial intelligence to increase agricultural yield for IMF debt payment

DISARMING THE GUN TO GHANA’S HEAD: Using artificial intelligence to increase agricultural yield for IMF debt payment

This article illustrates how the IMF has enslaved all of Ghana and proposes a technological solution to use artificial intelligence to provide for debt payment via increased agricultural yield, while surgically removing from Ghana’s mouth the financial fishhook of that pejorative known as “development.”

by Patrick Novak

Copyright ? 2019 by Patrick Novak. All Rights Reserved. Permission granted to share via social media. As with all LinkedIn articles, the contents are personal opinions, not the official statement of any government.

with hommage à H. G. Wells, il miglior fabbro

PREFACE

    How arrogant Dr. Marx must’ve been, to presume that anyone would read Grundrisse der Kritik der politischen ?konomie. I apologize to be similarly supercilious, to presume that anyone would want to read anything that I write. Nonetheless, I would be remiss, were I not to note that the IMF well knows that Dr. Marx illustrated, in great detail, how artificial intelligence can be used to liberate nation-states and their disempowered wage slaves from predatory lenders, intellects vast and cool and unsympathetic, that slowly and surely drew their plans against the Republic of Ghana.

INTRODUCTION

    I’ll ne’er forget the day that I was invited, by the director of the United States Congressional Award Program (the U.S.A.’s plagiarized version of the Duke of Edinburgh’s International Award) to address program participants, directly. The director may have been testing the truth of my dedication to the People, when telling me that, were I to want unfettered access to program participants, that I could meet them on one particular day in Edward R. Murrow Park, while they tended to homeless persons that resided in the park. I’d never previously been to that park, and I’d not even known that it existed; however, I, who was then an employee of the U.S. Department of the Treasury, knew immediately that the reason for its residents’ systemic poverty was across the street from the park: the World Bank, with its conjoined twin, the IMF, beside it. That day presented a powerful opportunity for me to tell younger residents how D.C. really works, but for they might’ve assumed that I was a schizophrenic resident of said park. As such, I merely praised them for their service, as if I were reading a national script. But I’ve seen the international script, and it is thus.

ECONOMIC THEORY AND PRACTICE

You will eat your Big Mac, and you will love your Big Mac.

    The rules of capitalism are three: 1.) There must be winners, and there must be losers; 2.) The winners have the privilege of making the rules, the first of which is that the losers can never become winners; and 3.) The enslaved losers must die a brain-draining death of poverty, literally. 

    The U.S.A. won Multinational Wars II and III; so, it has the privilege to make the rules, which are thus: 1.) The U.S.A. is the core, and all others are periphery; 2.) The periphery must accept the gifts that the core gives to it; and 3.) Those that do not accept the gifts will face the jackals.

The IMF is a nothing more than a neoliberal tool to expand corporate capital.

    The International Monetary Fund is a neoliberal strategy to expand corporate capital via the unencumbered pursuit of new markets and dispossession of wealth, by creating a borderless economic system in which impoverished workers from the Global South will labor for the prosperity of the rich few in the Global North. The IMF prescribes free-market economy, capital in-flows through foreign investments, and opening of markets to export. But the complete ruination of the Argentinian economy should be a warning to anyone that takes the IMF’s poison damned-if-you-do/damned-if-you-don’t pill. 

    IMF loans, pushed as “structural adjustment” to Global South nation-states, involve liberalization, reduction of state intervention, and privatization of public services and natural resources, which result in destruction of private local economies, by transnational corporations. “Development” further worsens extant problems by inflating bureaucracies, benefitting elites, and perpetuating dictatorships. And, often, aid granted is “tied in” to benefit its donor nations, while recipients are expected to buy products and services from core nation-states, which reduce actual aid value. Development aid comes with conditions that result in inflation, plummeting exchange rates, and debt traps. Forcibly impoverished populations then migrate in large numbers to service the global metropoles of the industrialized North, the places where the processes of globalization are produced and managed. There, they fill low-wage, dead-end jobs in an informal sector that denies workers basic legal protections, with women as the worst affected. They are enslaved, truly.

    The IMF has also succeeded in ascribing cost to environmental processes. It degrades ecology. It transfers the burden of maintaining ecology to developing nation-states by pushing agro-fuels as environment-friendly alternatives to fossil fuels. To invite the promised foreign investment, nation-states compete to turn agricultural land into bio-fuel farms, which worsens the food crisis. Thus, even ecosystems are turned into commodities that can be subject to market price and freely traded to sustain unsustainable methods of consumption and profiteering.  It were as if someone read all of Dr. Marx’ work and decided to apply it in an evil way.

The IMF’s terms are pure U.S.A. hypocrisy.

    The two-facedness of the IMF’s predatory practices cannot be reconciled with the text of the very legal document governing the nation-state that birthed the IMF: the Constitution of the United States of America, the Thirteenth Amendment of which prohibits involuntary servitude. The United States Supreme Court, in its landmark case United States v. Kozminski, 487 U.S. 931 (1988), which was brought by the United States’ own Department of Justice, defines involuntary servitude as a condition of servitude in which the victim is forced to work for the defendant by the use or threat of physical restraint or physical injury, or by the use or threat of coercion through law or the legal process. Any overpaid lawyer representing the IMF would argue that, although nation-states risk catastrophe, were they not to fund their governments adequately, the IMF merely encourages nation-states to participate in its lending schemes and does not coerce them. This misrepresents the schemes’ impact.   

    Another Supreme Court case applies: New York v. United States, 505 U. S. 144, 175 (1992), in which the Court determined that the Federal Government of the United States of America had “crossed the line distinguishing encouragement from coercion,” in the way it structured the funding of radioactive waste removal. Instead of simply refusing to approve waste-removal activities of other governments, the Federal Government also threatened to withhold health-care funding from governments that did not follow the prescribed waste-removal scheme. That threat served to force unwilling governments to participate in the waste-removal scheme. With the IMF, as in New York v. United States, the inducements touted as benevolent gift to other nation-states is implemented by a lender that uses more than encouragement—"it is a gun to the head,” as were the words of the Supreme Court. Indeed, where the Constitution stops, the hypocrisy begins: the U.S.A. border. 

The IMF has set in motion a conspiracy to interfere with Ghana’s human rights, generally. In particular, when the IMF refuses to fund governments that have financial hardships, entirely, for all needs, those governments are not free not to participate in the IMF’s lending scheme; every chance at funding becomes lifesaving, that the funding may be used to fund lifesaving programs. Development, for those subjected to the IMF’s predatory lending, means an eternity of underfunded programs. The threat that all funding would disappear were aid recipients not repeatedly to submit more loan requests to the IMF makes for a second, unfunded, full-time job: involuntary servitude—slavery, which is prohibited by a nation-state that doesn’t think it applies to non-citizens, which is exactly how it has always regarded its slaves. Indeed, what the IMF alleges is a borrower-friendly, non-adversarial process to help underprivileged citizenries has literally enslaved them.

    By prohibiting agricultural subsidies, the IMF wants to drain the brains of the citizens of Ghana, for a malnourished brain cannot form questions. However, because the single greatest impact on intellect is nutrition, because nutrition will empower the young citizens of Ghana to control their future, and because the single greatest means to increase agricultural yield is artificial intelligence, the following is proposed.

WHAT THE REPUBLIC OF GHANA SHOULD NOW DO

Consult the great oracle that is A.I.

    When confronted by the Russian hacking threat, the U.K. formed the NCSC, to develop artificial intelligence for cybersecurity, and has funded it well. Artificial intelligence, similarly, could help agricultural activities identify features completely invisible to farmers. 

    A three-step path to a possible artificial intelligence system is thus: 1.) Make a model (abstract, enter-numbers-in-the-blank) of how agricultural yield can be improved, both theoretically and in actual practice. 2.) Enter extant data about factors impacting yield, plus observational data (a certain dry corner of a particular farming area, &c). 3.) Use Bayesian inference methodology to back trace and distinguish, as much as possible, the unknown parameters from the known parameters.

    Such would not be a panacea. No artificial intelligence system could conclude that “Crop X will thrive in Area Y.” However, there would be elicited probabilistic inferences, ranges of possibility, and suggestive patterns, sometimes strong enough to justify investigation by agricultural engineers.

    But this is nothing new, under the sun. Such methodology is already employed by scientists, elsewhere, to measure unobservable data. Astrophysicists, for example, cannot examine most things they study; however, by having a partial understanding of how things like light and gravitational waves move between places, and by having probable models of stellar composition, galactic interstellar gas, &c, they can learn much, even at a distance, despite most of what they want to measure not being accessible via direct observation. Again, not a panacea, but an artificial intelligence system to increase yield quantity and quality is possible, and, in three-dimensional, terrestrial contexts, it could be extremely effective in pinpointing specific sectors that could then be explored, via more direct methodology.

Artificial intelligence for agriculture, explained:

    Though there are many easily-accessible instructional materials regarding Bayesian statistics and Bayesian inference, an informal example (not meant to be an ignorant example that would result in disregard for a tool, itself) would be thus. Suppose a farmer were to discover 100 new, cashew fruits budding in trees of a particular farm on a given day. This would not mean that the farmer’s previous work caused 100 cashew fruits to grow on that day and that there would be no new cashew fruits, were the farmer not to have done any of that work. However, were one to have a good mathematical model of how likely new cashew fruits were to grow, as a result of farming (which could be further modeled based on data such as upcoming weather, day of year, soil conditions, &c), then one could work backwards and derive a probability distribution that would deduce something to the effect that, "With 100% certainty there will be at least 100 new cashew fruits; with 90% certainty there will be at least 187; &c; and there is a 5% chance that there will be more than 2,000." In practice, this is done either through bespoke code or leveraging Stan statistical software, often through R language and environment. One could code such a model using Stan language, and supply both the model and the observations to the system, which would generate a set of probability distributions for each unobserved variable of interest. 

    After that, one would then need to extend a model to include observable variables. For example, in the previous example, one might have begun attempting to model qualitative data observed during planting without thinking about data observed during harvests, but then extend the model to include data observed during harvests because such observation can easily be quantitatively measured, and thus use such data as a first link in a chain backwards to hidden parameters. Next, one would need to construct data sets for all observable variables. Finally, one must then translate a model into something statistical software could compute, run the inference (which is often an iterative process, working with domain experts) and, then, analyze the results. Obtaining the knowledge of domain experts, to input into a formal model, would likely be the hardest step; but, achieve this, and measurably increase agricultural yield, before crops are even planted. 

CONCLUSION 

    Ghana’s greatest capital is not its land, but its citizenry. Millions and millions of young brains that can readily learn how to use simple technological tools to turn the land into a cornucopia, without hard labor. Since antiquity, agriculture has not changed; however, epistemology has. There are millions of factors bearing on any one farmer’s crops, and even an expert farmer could not list a large percentage of such factors. But an artificial intelligence system could evaluate endless data and find patterns where humans never considered looking; it could reveal the unknown unknows.