Monthly Archives: April 2018

Discussion: Cambridge Analytica and Research Ethics

From Joe Pater. Comments enabled

The Cambridge Analytica scandal has hit very close to home. Robert Mercer is a computational linguist, and Aleksandr Kogan is a cognitive psychologist. What should we academics be doing to respond and to prevent future violations of our ethical codes – and what exactly were the violations? I’ll share my current current thoughts in this post, and I would very much welcome others’ contributions on what I think is an important, and complicated, question.

The news yesterday (April 24, 2018) has shed a lot of light on Kogan’s work in collaboration with SCL, CA’s parent company, and how it likely violated the ethical standards of research in cognitive psychology. First, the Guardian released correspondence from the Cambridge University Ethics panel that it obtained with a FOI request. The letter rejects Kogan’s application to conduct research using the data he had acquired from Facebook because he had not obtained informed consent. The two pages of correspondence are well worth reading in whole.

Also yesterday in a news conference, CA’s spokesperson Clarence Mitchell admitted conducting research using those data (in explaining that the data were not useful for targeted advertising, and were therefore not used in the Trump campaign). This distinction between ethical standards for academic and industry research is troubling, though Kogan seems not to be troubled by it, as shown in this quote from his testimony yesterday to a British parliamentary hearing, published in another Guardian article.

Kogan also argued that his firm did not need ethics approval from Cambridge University, still his primary employer, since “there’s no real mechanism for a company to seek ethics approval for a commercial deal.

“I’ve never heard of anybody who runs a company trying to get ethics approval for a dataset whose primary function was really a commercial enterprise. Our primary deliverable here, first and foremost was the obligation in regards to SCL. Secondary purposes come later when you try and bring the work in for the university.”

Kogan admitted that, in transferring the data he had harvested from Facebook, he had acted against the specific words of its developer agreement. But, in a bizarre exchange with Labour’s Paul Farrelly, he argued that he had not broken the policy, because Facebook’s document did not amount to a policy.

“For you to break a policy it has to exist and really be their policy,” Kogan said. “But the reality is that Facebook’s policy is unlikely to be their policy.”

Part of the subtext here is a battle between Facebook and Kogan over who is to blame. My view is both have grievously violated generally held standards of ethical research.

The problematic distinction between academic and industry standards for non-medical human subjects research is also alluded to in the Cambridge University ethic board’s letter, in a discussion of  Kramer et al.’s 2014 PNAS article “Experimental evidence of massive-scale emotional contagion through social networks”. As the subsequent PNAS Editorial Expression of Concern explains, the study had not been reviewed by the authors’ Institutional Review Board at Cornell because it was done under the auspices of Facebook. The “expression of concern” is with the unacceptably weak definition of participant consent used by Facebook. PNAS does not seem to have stated, however, that the publication of the article was in violation of its policy. I have written to the current PNAS Editor-in-Chief for clarification of the policy, and will post any response I get in the comments. (Update April 26: see also the Fiske and Hauser editorial “Protecting human research participants in the age of big data”, which explicitly discusses differences between industry and academic research).

All of this points, I believe, to one thing that we academics can do to respond. We can demand that our journals apply a uniform standard of informed consent for academic and industry-based studies. In medical research, academic and industry standards seem to be basically identical (according to my father, who was the Director of the Clinical Trials Group of the Canadian National Cancer Institute; his e-mail to me on this is at the end of this post). It seems unlikely that we can achieve this standardization in non-medical research through the same mechanism – governmental regulation – but we certainly can at least press our professions’ journals and societies to maintain a uniform standard.

Robert Mercer’s role in Cambridge Analytica is comparatively old news – it came out in yet another Guardian piece, from February 2017. Mercer is the recipient of a lifetime achievement award from the Association for Computational Linguistics, and there have been some calls for this award to be revoked. Particularly relevant to the question I posed at the outset of this post is the way that Adam Goodkind, a Northwestern PhD student, frames his argument for this action in his change.org petition, in terms of violations of his discipline’s ethical codes:

  • Robert Mercer’s firm illegally, or at least unethically, acquired personal information, and used this data expressly to influence a foreign election.
  • Robert Mercer’s firm deliberately misled the population from which it collected data, exploiting their willingness to share personal information for purely financial and political gain.

https://www.change.org/p/marti-hearst-petition-to-revoke-robert-mercer-s-acl-lifetime-achievement-award

====

E-mail of April 23, 2018, from Joseph L. Pater:

In the US, industry clinical trials (which is the main form of industry research on humans) are governed by an FDA regulation (CFR Title 21, Section 312). All clinical research funded by HHS, i.e., NIH, is governed by a federal regulation (45 CFR 46) that is enforced by an office within HHS called OHRP (the Office for Human Research Protections). For HHS funded clinical trials that require regulatory approval (i.e., involving investigational drugs) both regulations apply.

In Canada, there is a similar division. All research funded by the federal granting councils is governed by the Tri-Council Policy Statement (TCPS 2) whereas industry research is governed by something called ICH-GCP (International Council on Harmonization – Good Clinical Practice). Again, academic research that requires regulatory approval is subject to ICH-GCP as well as TCPS.

Most ethics committees that deal with clinical trials set themselves up to be compliant with everything at once.

I haven’t read the rules carefully in a long time, but it’s probably the case that you would be hard pressed to find anything substantially different, in principle at least, among these various requirements, so, in fact, industry and academia are supposed to follow more or less the same rules. My guess is that industry is better at following the letter of the law. For what it’s worth, historical examples of really egregious ethical violations like Tuskegee have come from academia.

Clayards in Linguistics, Friday 4/27 at 3:30

Meghan Clayards of McGill University will present “Flexibility and individual differences in speech perception” Friday April 27th in ILC N400 at 3:30. An abstract is below. All are welcome!

Abstract. In order to understand spoken words, listeners integrate information across multiple acoustic dimensions such as spectral frequencies and durations. For each phonological contrast (e.g. bet vs. bat) we must learn which dimensions are relevant and how much to pay attention to each dimension (cue weights). This talk will focus on two aspects of this process. First, flexibility in what we pay attention to in perception and how this is tied to production patterns. Secondly, despite consistent overall patterns for particular contrasts/languages, there seem to be important individual differences in how people perform in speech perception tasks. I will present some data from my lab that is beginning to explore these differences.

Sue Carey Friday, April 20 at 3:30

Sue Carey, Department of Psychology, Harvard, will present “Do Non-Linguistic Creatures have a Fodorian (Logic-Like/Language-Like) Language of Thought?” Friday, April 20 at 3:30pm in ILC S131.  The talk is sponsored by the Five College Cognitive Science Speaker Series and the UMass Initiative in Cognitive Science. An abstract is below.

Abstract. The adult human conceptual repertoire is a unique phenomenon earth. Human adults build hierarchical representations on the fly, distinguishing “Molecules are made of tiny atoms” (True) from “Atoms are made of tiny molecules” (False). It is unknown whether non-linguistic creatures are capable of representing structured propositions in terms of hierarchical structures formulated over abstract variables, assigning truth values to those propositions, or are capable of abstract relational thought. How abstract knowledge and abstract combinatorial thought is acquired, over both evolutionary and ontogenetic time scales, is one of the outstanding scientific mysteries in the cognitive sciences, and has been debated in the philosophical literature at least since Descartes. Many philosophers, from Descartes through Davidson, have argued that abstract combinatorial thought is absent in creatures who lack natural language; others, such as Fodor, argue that such thought must be widely available to non-linguistic creatures, including human babies and animals at least throughout the vertebrates. A priori arguments will not get us far in settling this issue, which requires both theoretical analysis and empirical work. Theoretically, those who think there is a joint in nature between the kinds of representations that underlie perception and action, on the one hand, and abstract combinatorial thought, on the other, owe us an analysis of the essential differences between the representations and computations involved in each. Empirically, then, we must develop methods that could yield data that bear on the question of whether non-human animals or human infants have representations/computations on the abstract combinatorial thought side of the putative joint in nature. I will illustrate progress on both the theoretical and empirical fronts through two case studies: logical connectives and abstract relations.

CogSci Workshop and Sue Carey talk Friday the 20th

A reminder that the fourth annual UMass CogSci Workshop will be held in conjunction with Sue Carey’s visit to the campus on April 20th (https://websites.umass.edu/cogsci/2018/01/30/sue-carey-friday-april-20th-at-330/). The workshop will consist of a poster session from 2:15-3:15; please submit your poster info here: https://goo.gl/forms/mt9v6NYU30zywGNe2. As always, previously presented work is allowed, even encouraged (don’t print a new poster if you can use one you already have!).

Music and language events this week

On Tuesday April 10th 3-4 pm in ILC N458, there will de a discussion of “Harmonic syntax of the 12-bar blues” by UMass Linguistics undergrad alum Jonah Katz. A link and abstract appear below.

On Friday April 13th 2:30 – 3:30 in ILC N400, Stefanie Acevedo (Yale) will present “Explaining expectation entropically: An empirical study of harmony in popular music” (abstract below).

At 3:30 Friday the 13th, David Temperley (Eastman School of Music) will present “A Model of Emotional Expression in Rock”.

All are welcome to all of these events. Please contact Joe Pater if you would like to meet with either Acevedo or Temperley while they are here.

==========

Jonah Katz (2017). Harmonic syntax of the 12-bar blues: a corpus study. Music Perception, 35(2), 165-192. Preprint (LingBuzz). Supplementary materials: data, statistical models, tree graphs, description of modeling.

Abstract. This paper describes the construction and analysis of a corpus of harmonic progressions from 12- bar blues forms included in the jazz repertoire collection The Real Book. A novel method of coding and analyzing such data is developed, using a notion of ‘possible harmonic change’ derived from the corpus and logit mixed-effects regression models describing the difference between actually occurring harmonic changes and possible but non-occurring ones in terms of various sets of theoretical constructs. Models using different sets of constructs are compared using the Bayesian Information Criterion, which assesses the accuracy and complexity of each model. The principal results are that: (1) transitional probabilities are better modeled using root-motion and chord- frequency information than they are using pairs of individual chords; (2) transitional probabilities are better described using a mixture model intermediate in complexity between a bigram and full trigram model; and (3) the difference between occurring and non-occurring chords is more efficiently modeled with a hierarchical, recursive context-free grammar than it is as a Markov chain. The results have implications for theories of harmony, composition, and cognition more generally.

Acevedo abstract: Given a preponderance of common _stock_ progressions in popular music, like the “Doo-Wop” (I-vi-IV-V) or the “Axis” (I-V-vi-IV) progressions, sequences of chords are often taken as a starting point for analysis. These chord sequences contextualize the sometimes _non-functional_ chord usage in popular music. While recent music-theoretical work uses computational methods to analyze harmonic probabilities in musical corpora and model their stylistic norms, it often focuses on analyzing lower-order probabilities such as single chord counts or chord-to-chord transitional probabilities. In this talk, I propose the use of information entropy, a measure of statistical uncertainty, as a way to segment harmonic progressions in a corpus of popular music (the McGill Billboard Corpus). The resultant harmonic segments are classified into prototypical chains based on functional categories that are determined by chord sequences as opposed to individual chords. The results and implications of the project are contextualized within recent research on popular music harmony and implicit learning of musical style.

Temperley abstract. In this talk, I present a framework for the analysis of emotional expression in rock music. The talk surveys some of the material in my new book The Musical Language of Rock (Oxford, 2018).

I begin with a two-dimensional model of emotion, well-established in music psychology, with valence (positive versus negative emotion) on one axis and energy (also known as arousal or activity) on the other. Valence is determined mainly by pitch collection (roughly, major versus minor, though there is more to it than that); energy depends on a variety of cues such as tempo, pitch register, loudness, and textural thickness. I then add a third dimension for complexity, or (in experiential terms) tension. Tension is affected by the density of events and also by their expectedness, with faster rhythms and low-probability events being higher in tension. Low-probability events can arise from such things as surprising harmonies, shifts outside of the currently established scale, irregular phrases, and extreme or unusual syncopations.

I then apply this model to the verse-chorus unit (VCU)—a formal section containing a verse and chorus; this is the core element of conventional rock form. We find consistent trajectories across the VCU in all three expressive dimensions—valence, energy, and tension. The chorus tends to be higher in energy than the verse; in terms of valence, many songs show a “sharp-ward” shift between verse and chorus, reflected not only in simple minor-to-major shifts but also in more subtle ways. With regard to tension, however, the peak tends to be in the middle of the VCU, either in the prechorus (if there is one) or in an extension of the verse. I present a number of examples, showing how the current model sheds light on both normative and exceptional cases.

Reading for Music and Language meeting Tuesday April 10th at 3 pm

The music and language CogSci Incubator’s second meeting will be Tuesday April 10th 3-4 pm in ILC N458. The reading is the following (by UMass Linguistics undergrad alum Jonah Katz). The abstract is appended below.

Jonah Katz (2017). Harmonic syntax of the 12-bar blues: a corpus study. Music Perception, 35(2), 165-192. Preprint (LingBuzz). Supplementary materials: data, statistical models, tree graphs, description of modeling.

Abstract. This paper describes the construction and analysis of a corpus of harmonic progressions from 12- bar blues forms included in the jazz repertoire collection The Real Book. A novel method of coding and analyzing such data is developed, using a notion of ‘possible harmonic change’ derived from the corpus and logit mixed-effects regression models describing the difference between actually occurring harmonic changes and possible but non-occurring ones in terms of various sets of theoretical constructs. Models using different sets of constructs are compared using the Bayesian Information Criterion, which assesses the accuracy and complexity of each model. The principal results are that: (1) transitional probabilities are better modeled using root-motion and chord- frequency information than they are using pairs of individual chords; (2) transitional probabilities are better described using a mixture model intermediate in complexity between a bigram and full trigram model; and (3) the difference between occurring and non-occurring chords is more efficiently modeled with a hierarchical, recursive context-free grammar than it is as a Markov chain. The results have implications for theories of harmony, composition, and cognition more generally.

Chang in Cognitive Bag Lunch Weds. April 4 at 12:00

Junha Chang (PBS) will be giving the cognitive brown bag Wednesday April 4 in Tobin 521B, 12:00-1:20).  Title and abstract follow.

Search guidance is sometimes, but not always, adjusted by experience with search discriminability

These experiments show that previous experience with certain types of visual search can influence current search guidance, and explore factors that determine whether these effects of experience arise or not. In a dual-target search task, two subject groups either experienced difficult color discriminability in half of the trials (i.e., hard-discrimination group) or experienced easy discriminability in all trials (i.e., easy-discrimination group). In both experiments, subjects were required to respond whether either of two targets was present or not among distractors. In Experiment 1, the same two colors served as possible target colors for the entire experiment. Fixation rate was high for distractors with colors similar to a target color, and gradually decreased for colors less and less similar to the target color. There was no significant difference between two groups in both eye movement and behavioral results. In Experiment 2, the colors of the two targets were varied from trial to trial in order to increase working memory demand. The hard-discrimination group fixated more distractors with target-dissimilar colors than the easy-discrimination group, suggesting the hard-discrimination group used color information to guide search less than the easy-discrimination group. The results demonstrate that experience of difficult color discriminability discourages observers from guiding attention by color and encourage them to use shape information, but only when working memory load is demanding.