AI & Targeted Population Management

Artificial Intelligence will play a significant economic role in advanced societies throughout the 21st century and beyond. Whether its advent is enthusiastically welcomed or observed with foreboding, it is inevitable; the challenge for societies is no longer its adoption but, rather, the management of its adoption in the context of social cohesion and the maximisation of economic advantage.

Opponents of AI suggest its potential to make superfluous the unskilled labourer as the primary disadvantage of its adoption. This outcome can be obviated by standing obstinately between mankind and its technological destiny, but, as previously suggested, this represents a slowing rather than prevention of the introduction of AI into advanced economies. If we accept AI as inevitable, which we must, consequently we are required to shift our attention to alternative variables.

A large mass of manual labourers for whom AI spells financial and social doom is the primary complication facing industrial society over the next half-decade. Obviously, inaction has undesirable political, social and economic consequences. In 2020, approximately 44% of people operated within the unskilled labour market; inaction isn’t a valid course of action with numbers such as these. In less enlightened times, autocratic societies pursued this course and sudden technological innovations precipitated an almost-immediate extinction of the redundant class. This equates to inaction which, whilst technically plausible, would almost certainly be violently rejected by its victims and sympathisers.

Sustaining the leftover population through government subsidies, supplied with taxpayer funding and profits absorbed from AI’s productive capacity, is not a valid solution either. While politically desirable by humanitarians and perhaps large sections of the redundant class, it posits a diversion of resources into the perpetuation of large numbers of people who will exist within a dependency loop in perpetuity.

The preferred solution lies in targeted population management. This process utilises the heritability of certain psychological factors that possess high socio-economic predictability, and the accentuation of these traits juxtaposed by the suppression of their opposites.

A 2002 study¹ (Hauser, Robert M.), and many others of similar motive, demonstrated our ability to utilise Intelligence Quotient (IQ) in predicting likely career prospects through providing an IQ range of those present in them. For instance, medical doctors represent the highest range of ordinary professions (approx. 107 – 132), followed by university professors (98 – 132) and electrical engineers (95 – 128) as seen in the table above. The positioning of the ranges positively correlate with the profession’s requisite skill level and, consequently, inversely with the potential for Artificial Intelligence to usurp that position.

Put simply, AI will comprehensively fill janitorial, mechanical and traditional engineering roles, while being generally incapable of filling roles that require biological nuance and ambiguity, such as teaching, scientific research and the customer-facing service economy.

A rather more crude method of visualising this dilemma is through the bell curve.

Here, we could effectively rub out anything lower than -0.5σ, or 0.5 standard deviations below average. This accords with data on IQ’s correlation with likely profession, which suggests individuals with an IQ <90 will struggle to compete with Artificial Intelligence in society’s future economy.

The simplicity of obtaining accurate data in this context presents society with new possibilities and variables to be controlled. With targeted pro- and anti-natal policies, society could, within a generation, quantitively reduce the redundant population to 20%² of its present size; this effectively removes their cost to society, with the additional ability to minimise the political power of the future economy’s opponents. This pathway combines efficiency with humanity without compromising the technological progress of advanced societies, whilst also being applicable to alternate sources of population growth, such as immigration and asylum.

Let me know what you think in the comments below. And while you’re free to critique the mathematics contained in the above piece, please bear in mind these are intended as a guide to a thought experiment and were (quite literally) written on the back of a fag packet.

¹Hauser, Robert M. 2002. “Meritocracy, cognitive ability, and the sources of occupational success.” CDE Working Paper 98-07 (rev). Center for Demography and Ecology, The University of Wisconsin-Madison, Madison, Wisconsin.

²Bouchard, Thomas J. (7 August 2013). “The Wilson Effect: The Increase in Heritability of IQ With Age”. Twin Research and Human Genetics

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s