Infrastructuring AI in the Postcolony

The root of all evil is a premature policy optimization.

In the few decades of the history of computing in India there have been some spurts of proactivity, but by and large other than a large bodyshop in IT, we have been comfortable in a mode largely reactive to global developments, with an industry making negligible contribution to computing technologies. Just after liberalisation, C. R. Subramanian had undertaken a long-view analysis of the matter in his "India and The Computer" - with many of his suggestions ringing true to folks in AI today. Let me therefore reconstruct below the difficulties that were noted over 30 years ago for large scale "harmonious development" (not support and maintainance) of computing and software products in India:

1. The domestic markets in India are too small. To make a mark, we've to address the international high-technology demand, which means society being at the cutting-edge of technology and R&D. Considering quick internet based distribution, open-sourcing and market standardisation, any catch-up oriented strategy would have to fight against strong network effects as well. This will be very hard for domestic industry to do in presence of established foreign competition without some protections until they reach a certain stage of technological and business maturity. 

2. Subramanian clearly recommends 'standardisation first' to be one possible technology strategy, but he also says, "...there is a total lack of concern for this at the highest levels of the administration. Political support has not even been sought for this vital step." Based on my own interactions with the Bureau of Indian Standards and other IT sector actors, 30 years later Subramanian's characterisation of embedding political vision in India's technical standardisation strategy has not changed much. Stock policy formats of "one nation one..." lack compatibility with global standardization environment - one way to address this would be to dissociate IT standards from BIS (which comes under Consumer Affairs) and give it directly to MeitY and technology industry stakeholders bodies who have skin in the game.

3. He says, "the private sector in India does not traditionally invest in high-risk, new technology areas." One of the main reasons for this, perhaps owing to our socialist traditions, is that the industry actors (at least the smaller ones) are not seen with much trust and respect. Hans-Peter Brunner notes that 1984 was perhaps the first time since independence when domestic industry actors in India were given on paper a “respectful place”. The little industry guy is not really accorded the respect of a 'partner' in public-private interactions, not to mention of the babu expectations of profound subservience. Resultingly, the industry has stuck to relatively risk averse and by-the-book activities, having neither the financial incentives nor the resourcefulness for high-technology risks/innovation. 

4. Infrastructural ownership, he says is a "must from the point of view of national security and related developments in the space and defense areas. To allow the World Bank a say in the matter is inviting foreign interference in domestic technology aspirations related to self-reliance." Considering our situation in the semiconductor supply chains and an unwritten policy to export brains (the human infrastructure), and now also with data and platforms, who really has digital infrastructural ownership in India?

5. He notes that the "inconsistency in the various policies — fiscal, licensing, technology development and technology import - prevent harmonious development". The natural evangelist of technology in government anywhere is the military, which faces a policy conundrum in India between satisfying its immediate requirements for finished products vs sticking it out for the development of the "indigenous" industry - unless in view of Atmanirbharta it could take a more strategic role in domestic technology sector. I may remind the reader here that the true union of science with industry happened only in the WWII, which in the US resulted into a cultural osmosis where the military picked up management perspectives and businesses picked up military ones.            

But how soon can these difficulties be overcome? In a world where technology infrastructures are often intermingled with social and political imaginations, a mere exorcism by diplomacy and public relations cannot address India's currently vacuous strategy for technological leadership. Our national security as well as digital technology governance being run predominantly through a policing lense has not halped our cause either. Firstly, I must say that it is not the technical but the management standards in our organisations (including govt and startups) which need to catch up with the engineering talent.   

Thence, the AI hype can be appealing to broken institutions - and can lead quickly into a procurement mentality where run-of-the-mill, off-the-shelf analytics and interaction products (even LLMs wrapped into brands) are acquired in the name of promoting and enabling the AI research ecosystem. That is like getting a website made to enable the development of future internet. Shoppers have to shop, but without deeply trusting your own people, letting them not go, and persevering with them on novel ideas, the technological catch-up would not end very soon. Perhaps it is also time for us to deploy legally a broader definition of CSR finance to include certain kinds of R&D as well.

Consider also, that organisational innovations are needed to integrate technology as a doctrinal component at the highest levels. We do not need an "AI policy" as much as we need to formulate a multi-stakeholder industrial policy that integrates and addresses different sector-specific demands (and expectations) of deploying automation, data processing and cyber security. This is a must for national competitiveness, security and defense, and cannot simply be exorcised by witty diplomats.  

Mbembe writes on his experience in postcolonial Africa, that often the actual development of infrastructure has more to do with access to government contracts and rewarding patron-client networks, and not its technical function or nuances - and some note that "this is why roads disappear, factories are built but never operated and bridges go to nowhere"- as we might sometimes relate as well. Now imagine a super-intelligent AI being developed and deployed in the purview of a similar organisational paradigm. If that is the sovereign national discretion, so be it, but it might be useful to make available trustworthy infrastructural components - standardised and open building blocks, both logical and physical, that can be integrated (and disintegrated) at base/local levels as required by anyone - as the local is not very far from the global here - for pure technology competition, for all practical purposes, implies an overall escalation of force with non-lethal effects.  

The Narcissism of Technical Differences

A couple of years ago, the US quietly put a worldwide export control on convolutional neural network based geospatial imagery software, the reason being its potential use by foreign militaries. It is worth noting that these are commercial software products which if open-sourced, their hardware dependencies aside, would not be treated under international jurisprudence as products but instead as free-speech. Which brings us to the subject of export controls, dual-use emerging technologies, and legacy international institutions.

 

Technology Export & Information

 

Export-control in itself is an old and important tool of statecraft, serving economic as well as military functions. However the present dichotomous classification of technologies based on military and non-military usage is severely outdated and in fact only holds-up when dealing with conventional weapons. AI in itself isn't a weapon but an enabler and having AI-superiority proves hugely advantageous when extending general capabilities across all kinds of defense systems and platforms, giving the machine learning software-stack and hardware accelerators a strong military utility.  

To deal with the problematic usage of such dual-use technologies, the most prominent international regime is the Wassenaar Arrangement. The arrangement, with respect to its fundamental role of helping to prevent the malicious use of technology, is pretty ineffectual when it comes to Artificial Intelligence and its ICT based applications. The de-territorializing effects of cyberspace present a clear institutional, regulatory, and compliance gap, where arrangements like Wassenaar only end up imposing yesterday’s standards over tomorrow’s technology. For example the first time when Wassenaar was invoked, it targeted software during the 90s to stop international adoption of cryptographic techniques over things like e-mail communications. That turned out to be a lot more than just diplomatic failure.  

And Wassenaar isn't the only international regime facing difficulty with technological changes. The MTCR (Missile Technology Control Regime) for example has been updated to include long range UAVs and will need future changes sooner than later. It must be made clear that these controls do not work as intended. There is always great difficulty in enforcing contracts in emerging markets, there is an ever-present tradeoff between transparency and secrecy, and moreover in an environment of deception the compliance can not be truly verified even if states bring (they do) their own technical means of verification. This is a grand version of what game theorists call a POSG (Partial Observation Stochastic Game), really fascinating and quite intractable stuff.

A classic legend, of dual-use exploiting institutional ambiguities, sitting in the ruins of a medieval empire

Scholars have duly noted the inherent ambiguity in Wassenaar Arrangement, especially when dealing with intangible dual-use technologies. There is no consensus on whether the arrangement could adapt to technologies which are both socioeconomically foundational and militarily significant, without ironically turning itself into a dual-use multilateral instrument of coercive and economic statecraft. Such concerns are not unfounded in international politics, take for example when in 1993 the Americans got the Russians to cancel the transfer of cryogenic technologies to India in exchange for some US-Russia space cooperation. Software being fundamentally information, presents more compounded challenges for export controls given the largely unregulated flow of information across borders. Basically the trouble being that if you put sanctions over the export of fishes to someone, failing to prevent him from learning to fish is a foreign policy failure. Not surprisingly therefore, a recent US AI-policy report which declared advertising-technologies as "NatSecTech", contained that "Export controls should be utilized... to slow competitors’ efforts to develop indigenous industries in sensitive technologies with defense applications... (by) targeting discrete choke-points."

Proliferation & The Undefined

 

The Mahabharat is absolutely filled with instances of specialized and more devastating tools being limited-by-distribution to only select few, though those familiar with the text would concur that this non-proliferation regime did little to control privileged actor behavior and eventually an utterly morbid devastation followed up. Multilateral export control regimes today pursue a deterrence by denial framework towards global security. However, in case of ICT based goods when export controls suppress economic interests, proliferation shifts to a black market, even between member states, on shady darknet sites.

It takes no genius to see that legally binding restrictions on AI capabilities will be economically debilitating, so it is going to be really hard to enforce sovereignty over technology or even know which exact technologies to control. Let us consider a hypothetical scenario: Most of the power consumption (>90%) in AI operation happens due to what can be described as "data movement operations" — adjusting features, weights, biases, transferring intermediate results etc — so it is understandable that a better power management technique/toolkit could make the systems significantly more energy efficient. Now consider that in a not-too-distant future these computations are happening in autonomous edge devices fielded on both sides amid a lengthy military standoff in a remote inhospitable region such as the deserted upper reaches of the Himalayas. Would an innovative intangible power model here be treated the same way an advanced battery technology is treated? What if someone strategically open-sources it?

 

Neural Network Power Consumption

Given that even technologies used today in public transportation, agriculture and pollution monitoring, such as LIDAR and hyperspectral tracking, will be very easily directed to military usage; several researchers have suggested to use the phrase "omni-use" to describe AI and other related emerging ecosystem. It should be clear to whomsoever-it-may-concern that they cannot control the flow of omni-use intangible items and neither can it be ascertained decidedly what or from who an omni-use technology must be kept. In an area like this, traditional controls will only bring about shadow regulations and more of other unsavory economics.

 

Way Forward, Institutional Corrigibility

 

Most countries with strong R&D focus prefer their weapon-systems to be approached as black-boxes, not to be reversed engineered or subjected to exhaustive component analysis. On another side, in future insurgencies and urban conflicts, we could be seeing a lot of improvised weapon systems which utilize open-source and low cost OTS components, those which would just not be regulated with current approaches. What technologies are available to militaries greatly guides how societies evolve and technologies also have a tendency to become more efficient relatively quickly because of their near-constant evolutionary cycle of adaptation and reinvention. It is therefore fitting and important to have a better and continuous coupling with all stakeholders, and not get carried away by media headlines, trends and lobbying.

So building Institutional Corrigibility in our context can be thought of as designing mechanisms to facilitate objective stakeholders (from academia and industry) bring necessary outside correction in transgovernmental networks responsible for developing and implementing technology export controls. The multilateral international institutions must understand the difference between essential system complexity and accidental system complexity, and work every bit to minimize and first and obliterate the second.
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Intelligent Money & Cognitive Economies

“We reject kings, presidents, and voting. We believe in Rough Consensus and Running Code.”  David Clark, 1992 

The above quote while originally intended to express many technologists’ view on the matter of internet standardization, also beautifully represents their political and sociotechnical values when it comes to the matter of our economic evolution: that is, rough consensus & running code. 

In An Inquiry into The Nature and Causes of The Wealth of Nations, Adam Smith overcame the constraints of his time in realistically modelling the economic complexity by attributing its emergence to an “invisible hand”. However today we have better techniques to make an accurate representation of the roles, resource flow and the contractual associations among various systems, economic agents and their networks, giving us a possibility to implement “money” as an intelligent self-governing system.

The idea is not new. In pre-cryptocurrency world (2002), Charles Goldfinger briefly wrote about it in ‘Intangible Economy & Electronic Money’, assessing that eventually our finances and money instruments et all will evolve to act intelligently, following an AI agent design paradigm. Thus the global financial system will (somewhat does but not very well) work as a finitely-generated dynamic system consisting of smaller adaptive sub-systems of autonomous money networks and rules for their engagement, each artificial agent having the capacity to form, judge, collaborate and act on their financial world-model. Interesting question is whether we will see a socially differing allocation of value then?

Complexity

While this is an active research area, there have been some recent developments in general causality based discovery models which lower the dependency on time-sequenced data as has been traditionally needed to assess markets, letting us analyze the so far hidden causality structures in economic behavior at the societal level.

Now every once in a while all dreamers have to wake up, but let us still explore this idea just a little further without getting into the nay-saying practicalities of the present-day infrastructure and governments. That being said, gradual and incremental diffusion of cognitive abilities in financial infrastructure will ultimately lead the way. 

Human-to-Machine-to-Machine-to-Human 

With an exploding ‘Internet of Things’ we now even see quantum-resistant cryptocurrencies such as IOTA, into which device maker Bosch' investment semed a good sign for things to come. It is not very hard to imagine that for a varying scale of amount, a user may want a machine to make transactions for him, or even to make the final buying or selling decisions for him. AI after all is a machine to delegate decision making to. Overtime all our personal devices also may learn to emulate and reflect our individual behavior.

So what does this imply? Having an AI agent that interacts with other AI agents and the economic environment on behalf of humans would lead to not only a more socially optimal allocation of assets (and value) but also a more advertising-resilient and intelligent market ecosystem, total market participation being a sum of human and machine activity. The big benefit though lies in the emergence of an economic swarm intelligence at the macro level.

Must overthrow the middle-man.

If we have Intelligent Agents representing buyers and sellers (and intermediaries?), we can make a market out of their supply demand conditions. Most people leave detailed traces of their online activity, so it can be argued that the Agent representing them will have some individual characteristics as well. Let us say that this agent follows a policy iteration algorithm, it has to maximize the utility function of money and the satisfaction of its master. Between its master’s satisfaction and his money’s utility, the agent will make a trade-off somewhere. The issue with utility is that in most markets, it is the intermediaries who control the information and direct the price. It is therefore again the intermediary who has the best estimate of the buyers’ and sellers’ economic potential as well, add to it various search and recommendation systems – and one can see how much markets are driven by the middle-man. The Agent’s information aggregation therefore should go beyond the information provided by the intermediary.

Humans alone are irrational economic agents, mostly making purchases with crafted and limited information. Cognification of economic activity stands to remodel the structural balance of markets, which are already to some degree intelligent, but lack the ability to signal and form internal models. In a complex world, money networks should have the ability to simulate the economy or a part of the economic environment, before proceeding with actions which could have ripple effects on other loosely connected networks. This means digital and intelligent money systems would need more space in the cloud, and evidently have a whole new set of security & architecture issues. 

Integrating The Dark Side

Untraceable & Private

Most of the economics ignores a large portion of economic activity, crime-war-politics. Also the suppression of people’s economic interests anywhere provides impetus to the creation of a black market. A lot of this money is funneled back into the governments as well. It is in the best interest of people involved with this side that their economic activity and the flow of resources is kept as opaque as possible. While currencies like Monero could be useful here, one can argue that cash is still the king and a hurdle in shifting to intelligent money systems.

Nevertheless the networks which have implicit value do thrive on anonymity.

Here I must mention Everett Rogers who gave us the criteria that a new technology must satisfy for incremental adoption:

- Complexity [Can the user understand the use and troubleshoot?]
- Observability [Is the use observed in other people, media?]
- Trialability [Is the tech available for simple non-exhaustive trials?]
- Compatibility [Does it work with the existing social and technical systems?]

The greatest hurdle crypto-currencies have to face is the Compatibility test. But digital national currencies could certainly take a lead in moving towards an intelligent agent based economic approach, if they’re going cashless that is.

It is clear that in such economies, humans will have to share some of their autonomy with the intelligent systems. What are the fundamental limits of this sharing is rather a sociological and game-theoretic question, the answering of which needs to take into account the matter of self-interest vs. public-interest – that is if we are to design such economic governance systems whose purpose is neither to serve, nor to rule. 

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