the privacy fallacy [book review]

“The World changed significantly since 1973.” (p.10)

I read this book, The Privacy Fallacy: Harm and Power in the Information Economy, by Ignacio Cofone, upon my return from Warwick the past week. This is a Cambridge University Press 2023 book I had picked from their publication list after reviewing a book proposal for them. A selection made with our ERC OCEAN goals in mind, but without paying enough attention to the book table of contents, since it proved to be a Law book!

“People’s inability to assess privacy risks impact people’s behavior toward privacy because it turns the risks into uncertainty, a kind of risk that is impossible to estimate.” (p.31)

Still, this ended up being a fairly interesting read (for me) about the shortcomings of the current legal privacy laws (in various countries), since they are based on an obsolete perception that predates AIs and social media. Its main theme is that privacy is a social value that must be protected, regardless of whether or not its breach has tangible consequences. The author then argues that notions that support these laws such as the rationality of individual choices, the confusion between privacy and secrecy, the binary dichotomy between public and private, &tc., all are erroneous, hence the “fallacy” he denounces. One immediate argument for his position is the extreme imbalance of information between individuals and corporations, the former being unable to assess the whole impact of clicking on “I agree” when visiting a webpage or installing a new app. The more because the data thus gathered is pipelined to third parties. (“One’s efforts cannot scale to the number of corporations collecting and using one’s personal data”, p.93) For similar reasons, Cofone further states that the current principles based on contracts are inappropriate. Also because data harm can be collective and because companies have a strong incentive to data exploitation, hence a moral hazard.

“Inferences, relational data, and de-identified data aren’t captured by consent provisions.” (p.9)

“AI inferences worsen information overload (…) As [they] continue to grow, so will the insufficiency of our processing ability to estimate our losses.” (p.75)

As illustrated by the surrounding quotes, the statistical and machine-learning aspects of the book are few and vague, in that the additional level of privacy loss due to post-data processing is considered as a further argument for said loss to be impossible to quantify and assess, without a proper evaluation of the channels through which this can happen and without a reglementary proposal towards its control. This level of discourse makes AIs appear as omniscient methods, unfortunately.

“Inferences are invisible (…) Risks posed by inferences are impossible to anticipate because the information inferred is disproportionate to the sum of the information disclosed.” (p.49)

“The idea of probabilistic privacy loss is crucial in a world where entities (..) mostly affect our privacy by making inferences” (p.121)

The attempts at regulation such as opt-in and informed consent are then denounced as illusions—obviously so imho, even without considering the nuisance of having to click on “Reject” for each newly visited website!—. De- and re-identified data does not require anyone’s consent. Data protection rights, as of today, do not provide protection in most cases, the burden of proof residing on the privacy victims rather than the perpetrators. The book unsurprisingly offers no technical suggestion towards ensuring corporations and data brokers comply with this respect of privacy and on the opposite agrees that institutional attempts such as GDPR remain well-intended wishful thinking w/o imposing a hard-wired way of controlling the data flows, with the “need of an enforcement authority with investigating and sanctioning powers” (p.106) . The only in-depth proposal therein is pushing for stronger accountability of these corporations via a new type of liability, with a prospect of class actions (if only in countries with this judiciary possibility).

[Disclaimer about potential self-plagiarism: this post or an edited version will eventually appear in my Books Review section in CHANCE.]

off to BNP!

Today I am off to Chile, to attend the 13th Bayesian non-parametric conference, BNP13. Which follows BNP11 that took place in Paris. And BNP12, which took place in Oxford (just prior to O’Bayes in Warwick, which in retrospect was the wrong strategy as most attendees did not extend their stay…). The programme is quite diverse and exciting, plus involving a lot of friends I had not seen for quite a while (as they weren’t at ISBA in Montréal). And the location is fabulous, sitting by Lake Llanquihue [whose waters may prove too cold!] and facing the [tantalizing] volcán Osorno (2652m). Which was observed by Darwin on his second trip, during a 1835 eruption. (The last eruption was in 1869, hopefully staying the same for the whole week!)

in defense of subjectivity [sound the gong]

When browsing the IMS Bulletin [01 October] a few days ago, I saw that Ruobin Gong (from Rutgers) had written a tribune about Subjectivism. In response to [IMS President] Krysz Burdzy’s presidential address at the IMS Meeting in London a few months earlier. Address that I had missed and where he was calling for the end of the term subjective in statistics… (While ironically attending the Bayesian conference in Montréal!) Given the tone of his Search for Certainty book, which Andrew and Larry and I discussed a while ago, I am not at all surprised by another go at Bayesian statistics, but I will not indulge into another response, since Krysz found my earlier review “venomous”! Especially since Ruobin has produced a deeply argument ed and academically grounded criticism of the presidential address (which, if I may mention it, sounds rather rambling away from statistics). In particular, Ruobin introduces Objectivity³ as “an interpreted characterization of the scientific object”, which reminds me of Nietzsche’s aphorism about physics. And where personal and collegial inputs are plusses, even though they could be qualified to be “subjective”. This was also Poincaré’s argument for Bayesian reasoning. In conclusion, I think that the London call to cease using the term in statistics was neither timely (as the subjective-versus-objective debate has sort of dried out) nor appropriate (in that it clashed with the views of part of the IMS community).

keep meetings hybrid

I was reading the latest ISBA Bulletin and the tribune by ISBA President Sudipto Banerjee celebrating the return to the physical ISBA World meeting, along with worries about participants who caught COVID there. (Unfortunately, one good friend of mine experienced symptoms that went beyond the mild cold-like ones I zoomed through a few days ago.) This particular issue of creating a COVID cluster [during coffee breaks?!] provides [me with] one further argument for my supporting hybrid and multimodal meetings on a general basis. Which should [imho] appear in the proposals for the 2026 and 2028 World Meetings (deadline on 31 October)…(The 2024 meeting in Venezia will certainly involve hybridicity! As will BayesComp in Levi.) Discussing the topic with others in some scientific committees recently made me realise this was not such a shared perspective, from reasons varying from worrying about balancing the budget, to zoom fatigue, to the added value of informal interactions. Still, there also are reasons for hybridising our meetings, from reduced travel impact, to more inclusiveness,  on geographical, diversity, affordability, seniority grounds. Holding hybrid conferences with multiple regional mirrors allows for a potentially higher degree of interaction and local input.  And a minimal organisational effort.

the strange incident of the bottle in the fridge