The_Future_of_Employment

challenging or critical applications, as in ICUs, algorithmic recommendations
may serve as inputs to human operators; in other circumstances, algorithms
will themselves be responsible for appropriate decision-making. In the financial
sector, such automated decision-making has played a role for quite some
time. AI algorithms are able to process a greater number of financial announcements,
press releases, and other information than any human trader, and then
act faster upon them (Mims, 2010). Services like Future Advisor similarly use
AI to offer personalised financial advice at larger scale and lower cost. Even
the work of software engineers may soon largely be computerisable. For example,
advances in ML allow a programmer to leave complex parameter and
design choices to be appropriately optimised by an algorithm (Hoos, 2012). Algorithms
can further automatically detect bugs in software (Hangal and Lam,
2002; Livshits and Zimmermann, 2005; Kim, et al., 2008), with a reliability
that humans are unlikely to match. Big databases of code also offer the eventual
prospect of algorithms that learn how to write programs to satisfy specifications
provided by a human. Such an approach is likely to eventually improve upon
human programmers, in the same way that human-written compilers eventually
proved inferior to automatically optimised compilers. An algorithm can better
keep the whole of a program in working memory, and is not constrained to
human-intelligible code, allowing for holistic solutions that might never occur
to a human. Such algorithmic improvements over human judgement are likely
to become increasingly common.
Although the extent of these developments remains to be seen, estimates by
MGI (2013) suggests that sophisticated algorithms could substitute for approximately
140 million full-time knowledge workers worldwide. Hence, while
technological progress throughout economic history has largely been confined
to the mechanisation of manual tasks, requiring physical labour, technological
progress in the twenty-first century can be expected to contribute to a wide
range of cognitive tasks, which, until now, have largely remained a human
domain. Of course, many occupations being affected by these developments
are still far from fully computerisable, meaning that the computerisation of
some tasks will simply free-up time for human labour to perform other tasks.
Nonetheless, the trend is clear: computers increasingly challenge human labour
in a wide range of cognitive tasks (Brynjolfsson and McAfee, 2011).
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