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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