Dr. Abigail Fraser, researcher in Epidemiology,
introduces the event: It is a common agreement that different data
infrastructures are mediating, or even leading, a broad range
of aspects in our daily lives, from
communications to transactions to decision-making. Fraser herself recognizes the crucial role of big
volumes of data for her work, without which she would not be able to conduct much of her research, if any. But there is also another side of data gathering
and the decisions being made based
on it, whether directly by humans or with the mediation of human-designed
algorithms. There seems to be an unquestioned acceptance of data ideology, according to which
all the decisions made based on the data are inherently neutral, objective and effective. Nevertheless, the growing evidence provided by the speakers
disproved many of these assumptions.
The evolution of the data infrastructure
Cristianini is the first to mention during the
evening the enormous amount of research that has been put into hardware and software since his teen years in the early 80s. At that time, he
would have to instruct his computer
beforehand in order for it being able to answer who, for example, Alexander V was. Today, he just has to take out his smartphone and speak to it. Various internals based on Artificial Intelligence (AI)
would then recognize his speech, look for the
answer amongst huge volumes of data and, in a matter of seconds, produce an answer for anyone
listening.
Computers can now learn and what Cristianini demonstrated live was possible not only
because of our technological evolution, but also
the status of our social institutions. We have overcome great challenges thanks to AI and the availability of large volumes of data, but we have not developed our laws, learning and morals accordingly in pace with these changes. A series
of mostly unquestioned social consequences of the gathering and use of data
became then the focus of the event, especially in the cases for which there is
not an individual consent or an informed social consensus. Concrete cases
included people being progressively fed only with the kind of news they want to
hear about, the exercise of mass surveillance by several governments, staff
selection processes and banks and insurances companies making decisions using
data from even social network profiles.
What can go wrong with massive data gathering?
Charlesworth elaborated the most on the matter
of massive data gathering and storage. One of his main concerns was the
evolution of Law within the United Kingdom, particularly now the Investigatory Powers Act has been passed by the House of Lords. One
of the most infamous parts of this law mandates internet providers to keep a
full record of every site its customers have visited for the government’s use.
Different aspects discussed and related to this
issue were the lack of evidence for the effectiveness of mass
surveillance, its potential to cause alienation on communities, and the lack of
adequate safeguards to protect against misuse or exfiltration of the surveillance
data. Evidence supporting these views, amongst others, was addressed to
the House of Commons by one of the PublicBill Committees earlier this year, but without much success.
On other grounds, Charlesworth was also concerned by the
oft-repeated line that there is nothing to worry
about as these kind of practices were already taking place outside
the rule of law and public scrutiny. The legitimization of mass state
surveillance and the extension of powers recently approved are, he explained,
something to worry about. After enumerating some of the forty-seven agencies that can access this data without any warrant, he pointed out that the big number of data breaches suffered by UK institutions in the
pasts does not help with trusting
this data collection and storage.
Ladyman expanded on the chilling effect of people of being or feeling watched.
Society is damaged when individuals have to think constantly about the
consequences of their communications or web browsing, as it has been shown that
people tend to avoid researching or debating about matters that challenge established social norms and factual
powers. A number of sociologist, philosophers and lawyers have addressed this question, but perhaps one of
the most famous experiments would be that of “The Chilling Effects of
Surveillance” conducted by Gregory White and Philip Zimbardo.
During White and Zimbardo’s study, two group of
participants were made: One being told that their statements would be shared
with the police for training purposes, and one that was not. Fear of
authorities equating dissent with wrongdoing, a threat or any kind of
punishable behaviour made the former group more likely to condemn marijuana
usage and to use second and third person pronouns in their language. Whereas
77% of the group not given a surveillance warning advocated for legalization,
only 44% of those who were told that their data would be shared with the police
did so. Moreover, 31% of the monitored participants looked for approval from
the people conducting the experiment when talking, whereas only 7% of the other
group did so.
Last but not least, Ladyman remarked that the
way on which we gather, store and represent data, as well as how we decide which
of this information is to be retained or not, is not aseptic. One of his side
comments, of which the cryptological community is very aware of, was that the
fact of eliminating some potentially sensitive or discriminatory entry from a
database does not mean that it cannot be inferred by the use of correlations
within the same dataset or with the help of some external information.
Next post will continue with the other main
concern of the discussion: Are exclusively data-based decisions always
objective and desirable?
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