TECHNOLOGY AT WORK

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Citi GPS: Global Perspectives & Solutions February 2015
Here data serves as a substitute for the implicit knowledge human workers possess.
Such data (termed training data in the parlance of machine learning) is usually
drawn from recorded human judgment: 47 for example, the data might be humanprovided
labels of the translation of a piece of text. As such, these data can be seen
as a way of encoding human knowledge such that it can be extended to many
different iterations of a task. That is, algorithms allow for scaling beyond the human:
a single dataset of human judgments might be drawn upon to make decisions many
times a second for years. As a result, computerisation is no longer confined to tasks
that can be written as rule-based procedures a priori, but is spreading to any task
where big data becomes available.
Big data is increasing the types of work that
are susceptible to computerisation, including
retail and sales occupations
The ability to store and process large
amounts of data is helpful to the legal
industry…
…and leading to the automation of
diagnostic tasks in healthcare
Retail and sales occupations may become susceptible to computerisation due to the
rise of big data. As an example of the scale of data now employed in retail,
Walmart's databases contain more than 2.5 petabytes (2.5 × 10^15 bytes) of
information. 48 The algorithmic recommender systems used by Netflix, Amazon and
Spotify are built on big data characterising the preferences and spending patterns of
their large customer bases. These recommender systems use sophisticated
machine learning techniques to compare a particular customer's purchases to those
of other customers, and, with instant recall of large product catalogues, can provide
product recommendations that, in many instances, may be more useful than those
of a human salesperson. Finnish company walkbase is taking a similar approach to
physical retail, using big data analytics on in-store customer behaviour in order to
offer in-store product recommendations. We expect these technologies to apply
increasing competition to human retail assistants.
Legal services are also being affected by the ability of computers to store and
process big data. In particular, algorithms are increasingly substituting for tasks
performed by paralegals, contract and patent lawyers. More specifically, law firms
now make use of systems that can scan thousands of legal briefs and precedents to
perform document review and to assist in pre-trial research. As an example,
Symantec's eDiscovery platform is able to perform all tasks "from legal hold and
collections through analysis, review, and production", and proved capable of
analysing and sorting more than 570,000 documents in two days. 49 Similarly, there
are an increasing number of businesses, including Talent Party, Jobandtalent,
Knack and Electronic Insight, using big data to automate recruitment. 50 In particular,
these firms use millions of CVs (résumés) and profiles characterising career
trajectories in order to understand what makes different candidates suitable for
different roles. These data can then be compared against those gathered on a
specific candidate from the patterns of language used in their applications, and, in
some cases, by having them play browser games. The power of algorithms to work
with this big data in a way that is impossible for humans is likely to threaten
employment in recruitment.
In health care, the increasing availability of big data is leading to the automation of
diagnostics tasks. For example, IBM's Watson system is being employed by
oncologists at Memorial Sloan-Kettering Cancer Center 51 to suggest treatment
options for cancer patients. These suggestions are informed by data from 600,000
medical evidence reports, 1.5 million patient records and clinical trials, and two
million pages of text from medical journals. With reference to this data, Watson can
47 The human experts who provide such training data are rarely compensated in
proportion to the value that their data provide.
48 Cukier. (2010).
49 Markoff (2011).
50 Wall (2014).
51 Bassett (2014).
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