This article first appeared in Forum, The Edge Malaysia Weekly on July 3, 2017 - July 9, 2017

As we think of the future in a world of Deep Learning Artificial Intelligence (AI) — where machines are created to “think” the way a human brain does — the question of jobs is a crucial one. Machines have been making routine jobs obsolete for scores of years, now they are capable of making even non-routine jobs obsolete. I have, in a previous column, discussed what the future of education should look like in a world such as this, arguing that our ability to be human is our strongest defence against the rising tide that is to come.

In this essay, I would like to focus attention on another pressing contemporary topic, inequality, set within the context of a future of pervasive Deep Learning AI. In economic theory, the standard production inputs are threefold — capital, labour and land. At a recent discussion, Faisal Ariff, the CEO of BorderPass Malaysia, put forward what I thought was a very impactful point — if robots are to replace labour (since robots do not need lunch breaks, bathroom breaks, annual leave, medical leave and so on) and if only those with sufficient capital can afford robots, then the standard production function will see total domination by owners of capital.

We can think of Faisal’s point in two ways. First, the units of production are reduced from three to two, just capital and land. Second, if robots are labour, and owners of capital own robots, then owners of capital also own labour. Thus, owners of capital are likely to have near total ownership of production in a future of Deep Learning AI. This is a powerful inference. If returns from production go to the owners of production inputs, then all returns — or at least an increasing proportion of returns — are likely to pass into the hands, or rather pockets, of the owners of capital. The implication of this is an even wider chasm in both income and wealth inequality between owners of capital and owners of labour.

Thomas Piketty’s book, Capital in the 21st Century, argues that the worsening of global inequality can be traced, in large part, to the fact that the return on capital, r, has been growing faster than economic growth, g, or, in Piketty’s terms, r > g. He then conjectures that the growing role of untaxed inheritance in society will make the inequality problem even worse; after all, if r > g, inheritances will grow and grow and those fortunate enough to have inheritances will just get wealthier and wealthier. Like all conjectures, this one is certainly up for debate, but it does highlight a risk that inequality is likely to get much worse.

This is a big problem because inequality has several damaging impacts on society. Research has shown that unequal societies have less social mobility and lower scores in mathematics, reading and science. Furthermore, high levels of income inequality are also associated with greater economic instability, higher propensities of financial crises, higher debt and higher inflation. People in more unequal societies are also less likely to trust one another, engage in social or civic participation and to say they are happy. In addition, living in an unequal society has also been shown to cause stress and status anxiety, which have long-term health effects. Inequality also increases property crime and violent crime.

This does not sound like any future we want to live in, unless of course, you would like to live in a Hunger Games-type of world. I do not and so, against this backdrop, I would put forward that there are three things — which require immense political will — that we could do to structurally mitigate the consequences of deeper future inequality on society. The first is to sever the link between “jobs” and “incomes”. The way to do this is via a Universal Basic Income (UBI), which I have argued for in a previous column as well. A UBI will do two things — first, it sets a floor for all members of society on the income they receive and secondly, it enables people to pursue the work they want, rather than simply taking jobs they hate just to pay the bills. Setting a floor and allowing people to seek the employment they want reduces the bargaining power that owners of capital have over owners of labour.

The second thing that we could do is to rethink our policy on immigration. The link, not obvious at first glance, is as follows. In some cases, technology is “exogenous” — meaning that there are people who work on new technology just for the sake of creating new technology. On the other hand, in most cases, technology is “endogenous” — people create new technology to solve a problem they have. This is especially true in high-income nations, which have high cost low-skilled workers. Take the US. The bulk of labour-saving technology such as automated fast-food servers, self-driving trucks and automated postal delivery is because inventors were trying to replace high cost low-skilled workers.

Lant Pritchett, the Harvard economist, asks the question, “Why are the world’s scarcest economic resources (people with entrepreneurial and technical ability) devoted to economising one of the world’s most abundant economic resources (labour)?” He goes on, “Why are these geniuses working on destroying jobs? Well, in part just because it is cool and an interesting technical challenge, but also, at least in part because policy-based restrictions on labour mobility make low-skill labour — which is globally abundant and cheap — artificially scarce in the US.” Therein lies the problem — we look to labour-saving technologies because we do not allow wages to equalise across the world by enabling freedom of movement for people. If people were allowed to freely move, labour would flock from labour-abundant developing nations, where wages are low, to labour-scarce advanced nations, where wages are high. Wages would equalise — they would fall in advanced nations as labour becomes relatively more abundant and vice-versa for developing nations. This reduces inequality. Instead, what we have today is the transmission of labour-saving automation from rich countries into poor countries (which need to create jobs) not because of technological progress per se but because of a broken artificial global paradigm that prevents free movement of people.

To be clear, I am not a Luddite. I look forward to a world of Deep Learning AI and am excited by it. I just don’t think technology should be used to exacerbate a massive global economic distortion. This brings me to my third, and perhaps most important point, which is that we just need to fix broken systems. Once again, I cannot say it better than Pritchett, who writes, “When we complain about inequality in the abstract we aren’t thinking about what is or isn’t fair or just or equitable … So let’s stop talking about inequality and talk directly about the things we ought to care about: absolute deprivation, abusive power, rigged markets and unearned privilege.” He is absolutely right. Inequality is just an outcome of a deeper cause and any discussion of inequality needs to be paired with discussions of justice and fairness. What is fair may not be equal, and what is equal may not be fair. A recent study in the world’s foremost scientific journal, Nature, found that humans naturally favour fair distributions, not equal ones, and, “…when fairness and equality clash, people prefer fair inequality over unfair equality”.

Global megatrends, particularly the unstoppable tide of technology, are pointing towards a worsening of inequality. However, there is still much that we can do to mitigate this potentially deeper chasm. While things like a progressive consumption tax or a global wealth tax — as proposed by Piketty — may help, it is far more important to consider what we can do structurally. We need to break the link between jobs and income, reconsider our policy on freedom of immigration and, finally, to just fix broken systems that cause inequality. These will all be politically very difficult, but the consequences of not trying may be catastrophic.

Nicholas Khaw is an economist with the Khazanah Research and Investment Strategy division

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