Making Sense of AI. Anthony Elliott

2 Making Sense of AI

      The rise of AI has stirred massive global controversy. Not just in universities and think tanks, but across industries and business circles. For many, the very idea of AI generates alarm. The advance of AI represents a major threat to jobs, employment, enterprise and industrial manufacture, and stokes up anxieties that pervade many other areas of life too. The more powerful automated systems become, the more many people worry about the risk that artificial general intelligence might result someday in human annihilation or some other irreversible global nightmare. In this scenario, the rise of AI is potentially catastrophic. AI is equated here with an apocalyptic social future. Another response, albeit very different in perspective, views these technological breakthroughs more positively. This response concentrates on new possibilities, hopes – and dreams for a better world. On the face of things, AI is a breakthrough science, and thereby promises great opportunities for the reshaping of economies, societies and political choices today. In this scenario, the coming AI revolution foreshadows the opening of a new era, one which will radically transform people’s daily habits and the world in which they live. AI is a new driver of production and will generate new sources of economic growth, changing how work is done and dramatically increasing growth in businesses worldwide.

The differences between these standpoints, and the stakes involved for economy and society, are great indeed. What emerges very clearly from this controversy, however, is that there is no orthodox consensus on the consequences of AI. On the contrary, divergent interpretations and theories compete for public attention. Newspapers, magazines, radio and TV programmes covering the latest developments in AI highlight an immense diversity of opinions and arguments, in which a mêlée of voices seeks to make sense of the great controversy about the rise of intelligent machines. Nor has AI been properly understood, or effectively responded to, by existing policy frameworks or political traditions. One reason for this is that the political traditions of conservatism, liberalism and socialism are tied, in cross-cutting though distinct ways, to social, economic and political forms of thought associated with industrial modernity. This is perhaps why the impacts of AI have often been understood narrowly – for example, in solely economic terms. Yet the very technologies associated with AI disrupt established economic orthodoxies and political paradigms, creating novel social consequences and powerful global transformations.

      The consequences of AI – what it is doing to our economies and societies, and its future possibilities – have to be systematically understood. Contrasting hypotheses, interpretations and theories of AI and its consequences cluster around two main lines of argumentation. The first of these I shall refer to as the position advanced by sceptics. The sceptics are today in a minority, and yet have significantly influenced public opinion and much policy thinking on AI and its ramifications. Simply put, sceptics say that claims of an AI revolution are overblown. For many of a sceptical persuasion, the spectre of AI is too often invoked to explain away complex institutional changes occurring throughout the world today. These are changes to do with the international economy, workplace change and geopolitics. The contrasting, second position is occupied by those I call transformationalists. The AI revolution, argue transformationalists, is creating a world of radical change. This is the dawn of a new era, one in which the intersecting forces of economy, society and politics shift in fundamentally new directions. From this perspective, AI powerfully disrupts traditional ways of doing things, ushering in new economic conditions, social divisions and political alignments.

Two Theoretical Perspectives: Sceptics and Transformationalists

       Sceptics

Sceptics of AI characteristically focus upon the many and varied overblown claims of technological innovation and scientific advance in the age of intelligent machines. Instead of providing insight into the technological forces reshaping our standards of living and possibilities for the future of humanity, the discourse of AI, argue many sceptics, obfuscates what is actually occurring in terms of social, economic and political change. Broadly speaking, sceptics say that the discourse of AI is used to explain away complex contemporary problems – especially those stemming from workplace change, international economic convergences and geopolitics. In short, sceptics contend that the great AI revolution is no more than ‘hype’. From this vantage point, the discourse of AI is a kind of cover story for the interests of glossy tech companies, all the way from Google and Yahoo to Facebook, Apple and Amazon. AI is permeated through and through with the culture of global capitalism, and as such is denounced by sceptics as façade, escapism, illusion or distortion. In this respect, the core ideologies of AI – that its growth is exponential, its operations ever faster, its complexity unprecedented – are deconstructed as ‘myths’, through which corporate and governmental powers condition contemporary social practice. Embellishing the sceptical argument of AI as hype or myth, many critics, pundits and anti-technologists have sought to debunk the rise of intelligent machines. Hence a string of sceptical books – including Bob Seidensticker’s Future Hype: The Myths of Technological Change, Gemma Milne’s Smoke and Mirrors: How Hype Obscures the Future and How to See Past It and Robert Elliott Smith’s Inside the Machine: The Prejudice of Algorithms – seeks to reveal the gap between the hype of AI and a world in which, for the most part, technology contributes far less than is often presumed to the routines of everyday life.

There is more than a touch of foreboding or nostalgia in the sceptical insistence that AI is a cultural construct based on hype. For one thing, the sheer complexity of smart algorithms, deep learning, neural networks and intelligent machines represents a scandal to much orthodox economic thought, and especially the American dream of individualist self-creation. In certain circles responding to breakthroughs in AI, the very word ‘artificial’ evokes panic. To elevate artificial machine thinking as some kind of ideal for economy and society can only occur at the cost of downgrading human decision-making, or so it appears to many sceptics. Another factor is the wholesale attempt pervading the literature of sceptics to bring low today’s fashionable preoccupation with intelligent machines. From this angle, the idea that complex algorithms driving smart technologies provide proof of advanced machine intelligence – such