- What is a boolean function?
- And how many boolean functions are possible for
ninputs? - Using that formula, how many boolean functions with 2 inputs can be modeled with a single layered perceptron?
How many 2-ary boolean functions can a perceptron model?
Matt Might wrote 6 blog tips for busy academics, and I am intending on following all tips. This post follows two tips specifically.
Tip 2: “Reply to public” as post
Many of the academics that “don’t have time to blog” seem to have plenty of time to write detailed, well-structured replies and flames over email.
Before pressing send, ask yourself, should this answer be, “Reply,” “Reply to all,” or “Reply to public”?
If you put effort into the reply, don’t waste it on a lucky few. Share it.
And also a part of tip 3:
Any question asked more than once is a candidate for a blog post
Today I graded assignments about perceptrons learning to model logical functions, such as A /\ B or A / B. As a warm-up question first year students were asked how many boolean functions we can define for two and three inputs respectively. And in the case of two inputs, how many of those boolean functions can a perceptron model? I noticed that quite some people did not answer these questions correctly, and moreover I received emails asking me to explain the answer because the final exam is coming up in two days. And so I heard Matt Might’s voice calling me out to write this. I hope it is of use to someone out there. I suggest you give it a try yourself before looking at the answer!
I like to think of a function informally as a mapping from inputs to outputs such that each possible input has exactly one output.
A Boolean is a data type that can take on two values that usually represent a truth value, for example in classical logic or programming.
Classical logic makes the assumption of the excluded middle, namely that any proposition P is either true or not true (false): P \/ ~P.
In computer science and programming, truth is usually denoted with a 1 and non-truth with a 0.
So a boolean function is a mapping such that it takes an amount n of inputs and then returns true (1) or false (0).
We could write that as such:
f: {0,1}^n -> {0,1}
We can see that the amount of inputs n determines the space of possible inputs.
The question how many boolean functions there are for n inputs can thus be formulated as such: in how many ways can we map the set of all possible inputs to the set of possible outcomes?
Another name for such a mapping is a truth table.
For example, this is the truth table of the logical disjunction A \/ B:
A B | A \/ B 1 1 | 1 0 1 | 1 1 0 | 1 0 0 | 0
This truth table corresponds to one boolean function, because it maps each possible input to exactly one output.
Another way of asking how many boolean functions we can make with n inputs is thus: how many of these truth tables are possible?
Notice that the disjunction above is a boolean function with 2 inputs that we here called A and B.
Each input can take two values because it is either true or false, so there are in total 2^n possible options for the inputs.
In other words, for 2 inputs we know that our truth table has 2^2=4 rows.
But notice that the ordering of the output column in the truth table matters! For example, if we switch the last two outputs of the disjunction, we end up with a different truth table and thus a different boolean function, which happens to be the material implication:
A B | A -> B 1 1 | 1 0 1 | 1 1 0 | 0 0 0 | 1
So given that each truth table has 2^n rows, we now need to know how many possible sequences of 1s and 0s we can have in the output column.
This is equivalent to throwing a coin for 2^n times and writing down all possible outcome sequences of head and tails.
How many of those sequences are possible?
Well, the outcome is again either 1 or 0, so for each row we have two options.
We already established we have 2^n amount of rows.
So for n inputs, 2^n rows, and 2 output options per row, we have 22n possible truth tables, and hence so many boolean functions.
For 1 input, it’s not much work to draw out all 2^(2^1) = 4 options:
A | o1 o2 o3 o4 0 | 0 0 1 1 1 | 0 1 0 1
Likewise, for two inputs we have 2^(2^2)=2^4=16 possible boolean functions,
and for three inputs 2^(2^3)=2^8=256 possible boolean functions.
Now, the more interesting follow-up question was: how many of these boolean functions with two inputs can be modeled by a single-layered perceptron?
Perceptrons can model logical functions by classifying everything on one side of a decision boundary as true, and false on the other. Using the perceptron learning rule we can learn this decision boundary in a supervised manner by iterating over examples from the truth table of the function we want to model, but that’s a topic for another day. Such a decision boundary looks like so:
From the 16 possible boolean functions with two inputs, perceptrons can thus model those whose layout allows all positive instances to be separated from the negative instances.
This is only not possible for the XOR and its negation, the XNOR.
Boolean functions where each input is mapped to true, or each to false, can actually be modeled with a decision boundary far off to the side.
So single-layered perceptrons can model 16-2=14 boolean functions.
Hugo template snippets of new website features
I have made progress in my understanding of Go templating, and in particular its scope limitations (see for example this). This allowed me to implement some new features that I was struggling with before. In this post I give an overview of new features, together with their implementation in Hugo. Most new features are small tweaks that extend on existing functionality. However, since I joined the IndieWeb, I also added a completely new aspect to this website, namely so-called “microposts”. Twittering is not my style, but I did crave for a place to share interesting bookmarks and other blogs in a more dynamic fashion than your classic blogroll (which I also have by the way). I had to write some code to support microformats2, which is what my microposts use.
Below I summarize the new features and provide related code snippets. Perhaps they are of use to you!
Preview of first two tags above each post ¶
On the homepage I display the most recent blog posts (I call them “engrams”). For each post I wanted to add a preview of its tags. I limited the preview to two tags only, because otherwise the tags overflow on mobile phones. If the post has more tags then two, dots will be displayed.
You can navigate the site by clicking on the tags, try it out! Clicking on a tag will reload the same page, but you will see that the previewed blog posts all correspond to the chosen tag.
The following assumes you are looping over your posts:
<aside>{{ .Date.Format "January 2, 2006"}}
{{ if not (eq .Params.tags nil) }}
{{ range first 2 $value.Params.tags }}
<a href="{{ "/tags/" | relLangURL }}{{ . | urlize }}/"
style="text-decoration:none">#{{ lower . }}</a>
{{ end }}
{{ if gt (len .Params.tags) 2 }}
...
{{ end }}
{{ end }}
</aside>
Show a preview of the latest post ¶
Hugo offers a handy summary option that automatically generates an “abstract”. If the summary is too long, you can manually truncate it to a particular amount of characters.
<div class="preview">
{{ range $index, $value := first 6 (where .Pages ".Type" "posts") }}
<p>
<a href="{{ .Permalink }}">{{ .Title }}</a>
{{ if .Params.guest }} (by {{ .Params.author }}) {{ end }}
{{ if .Draft }} <span style="color:#FF4136;">(unpublished)</span> {{ end }}
</p>
{{ if (eq $index 0) }}
<blockquote>{{ truncate 350 .Summary }}
<p><a href="{{ .RelPermalink }}">Read more</a><p>
</blockquote>
{{ end }}
{{ end }}
<br>
<p> See <a href="{{ .Site.BaseURL }}/archives"> archives</a> for more ... </p>
</div>
Deduplicated tags in Tag Roulette ¶
On my homepage I have an overview of the tags of all posts, so that one can pick a tag of interest and browse through corresponding posts.
Previously I looped over all my posts, and then immediately rendered their tags.
The result of this naive approach is that the tag overview will have many duplicate tags.
In a normal programming language this is a trivial issue: you would keep track of a list of tags and make sure to not add duplicate tags (or perhaps work with a set), before rendering anything.
However, Go templating has its own unique way of defining the scope of variables.
For example, when you range over tags, the broadest scope you can access from within that loop ({{ . }}) is that tag.
This means it is not straightforward to work with variables outside of that scope.
That is… until I found out about Hugo’s scratchpad, which allows you to define custom variables on the scope of the whole page.
You can add data of interest under a particular key that you define yourself.
One detail I had to get right in order to make this work, is to ensure that tags are added to a list, rather than replacing the previous value.
So rather than using the .Scratch.Set method, I used the .Add method.
The .Add method assumes we are working with a list though, whereas our tags are strings.
So before adding tags, I convert it to a list with the slice function.
<div class="tags">
<h2 id="tags"> Tag roulette </h2>
<br>
{{$tags := newScratch }}
{{ range .Site.Pages }}
{{ if eq .Type "posts"}}
{{ range .Params.tags }}
{{ $name := lower . }}
{{ $array := $tags.Get "tags" }}
{{ if not (in $array $name)}}
{{ $tags.Add "tags" (slice $name)}}
<a href="{{ "/tags/" | relLangURL }}{{ . | urlize }}/">{{ lower $name }}</a>
{{ end }}
{{end}}
{{ end }}
{{ end }}
</div>
The only thing that still bothers me is that I did not figure out how to do {{ $array := $tags.Get "tags" }} inline.
Preview of latest micros ¶
The most important element here is to distinguish pages of the type “micro” from regular posts. The layout “content_only” calls a partial that I wrote for displaying html using microformats2 (see next section).
<div>
<h2 > Micros </h2>
{{ range first 3 (where .Site.RegularPages ".Type" "micro") }}
<div class="hover-box">
<p>{{ .Render "content_only" }}</p>
</div>
{{ end }}
<p> See <a href="{{ .Site.BaseURL }}/microblog"> microblog</a> for more ... </p>
<br>
</div>
Microformats2 ¶
I wanted to display different type of micros in different manners. For example, I wanted bookmarks to show a book symbol with the URL of the bookmark. For events I want to show a calender, and for music events (a subcategory) I want to show a music notes instead. For replies, I want to provide the URL of the post I am replying to. For likes, I want to show a heart.
This is work in progress, but for now I wrote the following partial:
<body>
{{ if not .Params.event }}
<div class="h-entry">
<div class="u-author h-card" style="display:none">
<a href="{{ .Site.BaseURL }}" class="u-url p-name">Edwin Wenink</a>
</div>
<div class="micro">
<a href="{{ .Permalink }}">
<h4>{{ .Title}}</h4>
<aside>{{ .Date.Format "January 2, 2006"}}</aside></a>
{{ if .Params.reply }}
<p>In reply to → <a class="u-in-reply-to" href="{{ .Params.target}}">{{ .Params.target }}</a></p>
{{ end }}
{{ if .Params.like }}
<p>Edwin ❤ <a class="u-like-of" href="{{ .Params.target }}"> {{ .Params.target }}</a></p>
{{ end }}
{{ if .Params.bookmark }}
<p>📖 <a class="u-url u-uid" href="{{ .Params.target }}">{{ .Params.target }}</a></p>
{{ end }}
{{ else }}
<div class="h-event">
<div class="micro">
<h4 class="p-name">
<a class="u-url" href={{ .Params.target }}>
{{ if eq .Params.category "music" }}
♬
{{ else }}
📆
{{ end }}
{{ .Title }}</a>
</h4>
<a href="{{ .Permalink }}">
<aside><time class="dt-start">{{ .Date.Format "January 2, 2006 15:04" }}</time></aside>
</a>
{{ end }}
<p class="e-content">
{{ if .Content }}
↬ {{ .Content | markdownify }}
{{ end }}
</p>
</div>
</div>
</body>
Links to latest, previous and next post ¶
Hugo makes this feature extremely easy by providing default functions.
The with function is particularly handy, because it knows how to deal with nils.
This ensures that when the are at the latest post, we will not cause any errors by trying to find the next post, which does not exist.
<div>
{{$posts := ($.Site.GetPage "section" "posts").Pages.ByPublishDate.Reverse}}
<!--Grab the most recent-->
{{ range first 1 $posts }}
<p><b>Latest</b>: <a href="{{ .Permalink }}">{{ .Title }}</a></p>
{{ end }}
{{ with .NextInSection }}
<p><b>Next:</b> <a href="{{ .Permalink }}">{{ .Title }}</a></p>
{{ end }}
{{ with .PrevInSection }}
<p><b>Previous:</b> <a href="{{ .Permalink }}">{{ .Title }}</a></p>
{{ end }}
</div>
What would be a cool improvement for the future is also linking to a relevant post with a similar tag.
Show latest comments (WIP) ¶
The most recent feature (I started on it today) is a preview of the latest comments on my website. The challenge for this feature was that comments are stored in a separate data folder in a nested manner, where each post has its own comment directory. Sorting all comments on their date per post is trivial, but it is harder to find the latest comment overall, so from all posts. Again, I could not solve this problem before I figured out how to use Hugo’s scratchpad. A nice feature I added is that clicking on each preview brings you to the exact location of the comment. I also distinguish between comments on the original post, and replies on comments of other people.
<div>
{{ $all_comments := newScratch }}
{{ range $commented_posts := $.Site.Data.comments }}
{{ range . }}
{{ $all_comments.Add "comments" (slice . ) }}
{{ end}}
{{ end }}
<h2> Latest comments </h2>
<br>
<aside>Last 4 of {{ len ($all_comments.Get "comments") }} comments in total:</aside>
<p>
{{ range first 4 (sort ($all_comments.Get "comments") ".date" "desc") }}
{{ if .reply_to}}
{{ .name }} replied to <a href="{{ "posts/" | absLangURL }}{{ ._parent | urlize }}#{{._id}}">{{._parent}}</a> on {{ dateFormat "Monday, Jan 2, 2006" .date }}<br>
{{ else}}
{{ .name }} commented on <a href="{{ "posts/" | absLangURL }}{{ ._parent | urlize }}#{{._id}}">{{._parent}}</a> on {{ dateFormat "Monday, Jan 2, 2006" .date }}<br>
{{ end}}
{{ end }}
</p>
</div>
There are still things to do though. I want to display the name of the post in a more pretty manner, rather than showing its url. In case of replies, it would also be nice to retrieve the name of the person replied to, but this has low priority and is rather complex due to the way my comment system is set up (see this post).
Deepfakes and democracy: a case for technological mediation
Introduction ¶
Recent successes in the production of so-called “deep fakes” sparked both the imagination and the fears of many. The word “deepfake” is a contraction of “deep learning” and “fake”, indicating the use of Artificial Intelligence (AI) to synthesize images and videos that are not real, while simultaneously not or barely being recognizable as fabricated. For example, the recently launched website thispersondoesnotexist.com [12] by Philip Wang showcases AI-generated non-existing faces that are extremely realistic. Notably, the underlying neural network technique based on Generative Adversial Networks (GANs) is published [8] and publicly available - including code - to those who are interested in implementing similar applications. Currently, an app called FakeApp is being developed with the goal to make the “technology available to people without a technical background or programming experience.”[2]. At the same time, there are serious concerns that as this technology becomes even better, not only images but also videos can be completely faked. In the current state-of-the-art it is already possible to “face swap” existing faces in videos, allowing for example the face of President Trump to be inserted in an arbitrary video. Despite leading to some very entertaining videos, this technology is simultaneously a next step in the production of fake news and has the potential to thoroughly disrupt democratic discourse.
In this essay I first highlight main threats of deepfakes to democratic discourse. I claim that what these threats have in common is that they result from a deepfake’s potential to mediate what we perceive to be “real”. Secondly, I discuss how awareness of these negative societal consequences elicits different stances towards the underlying AI-technology, in particular concerning the responsibility that developers have in openly publishing (or not) these technologies. Thirdly, I argue that a philosophy of technological mediation is not only an adequate framework for understanding how deepfakes threaten democratic discourse through mediating what is “real”, but also for expressing the full complexity of the question who is responsible for negative societal consequences.
Deepfakes disrupting democratic discourse ¶
Societally undesirable applications of deepfake technology have already emerged, and more negative consequences are anticipated to emerge as the technology matures. One major negative application threatening individuals is the creation of fake porn videos of celebrities, which are now actively being banned from reddit and porn sites as they amount to non-consentual porn [2] [1, p.18]. But on a societal level, there are major concerns that deep fakes might significantly disturb the type of political discourse that is essential for democracy to function. Bobby Chesney and Danielle Citron [1] are the first to extensively explore the relationship between deep fakes and democratic discourse. Deepfakes first of all enlarge threats to democracy that are already present in what some consider to be a “post-truth” era, in which fake news can be as effective for achieving political goals as actual news based on facts. This threatens democratic discourse because, as Chesney et al. adequately express: “One of the prerequisites for democratic discourse is a shared universe of facts and truths supported by empirical evidence. In the absence of an agreed upon reality, efforts to solve national and global problems will become enmeshed in needless firstorder questions like whether climate change is real. The large scale erosion of public faith in data and statistics has led us to a point where the simple introduction of empirical evidence can alienate those who have come to view statistics as elitist.” [1, p.21]. Deepfakes in this sense contribute to what Chesney et al. call intellectual vandalism in the marketplace of ideas [1, p.21]. That development is undesirable for democracy irrespective of its particular form, but is particularly worrisome for those supporting a pluralist or deliberative democracy, as they see opinion forming in a free and open dialogue or debate as essential to democracy [9, 4-5].
But secondly, deep fakes can even more effectively undermine fair and democratic intellectual competition in this marketplace of ideas than “normal” fake news does. Imagine a deepfake video spreading on the evening before elections, showing one of the candidates committing a serious crime. Due to the power of social media such a video can go “viral” and do serious damage to the eligibility of a candidate. In modern media “not guilty until proven otherwise” often hardly holds, and one can be convicted in the public eye for a crime that was not committed, without fair trial. A well timed deep fake can heavily disrupt fair democratic elections in this manner before there is a chance to debunk the deepfake. But even if a deepfake is exposed as false, its disruption of fair elections can still be effective by having set a cognitive bias in the minds of the electorate [1, p.19].
Using deepfakes to disrupt democratic discourse will be even more effective if they target situations that are already extremely tense. Imagine for example a deepfake of “an Israeli official doing or saying something so inflammatory as to cause riots in neighboring countries, potentially disrupting diplomatic ties or sparking a wave of violence.” [1, p.20]. Once such a situation is escalated, despite the cause being “fake news”, it is extremely hard to de-escalate them. In contexts where such distrust is already present, deep fakes can further erode trust in institutions of open democratic discourse. As Chesney et al. point out, in such tense situations the likelihood that opposing camps will believe negative fake news about the other side is higher, and only increases as deepfakes exploit this mechanism to further enlarge social divisions [1, p.23]. Not surprisingly, techniques to detect deepfakes are being developed to counteract these risks, for example by the US military DARPA [4]. But due to the flexibility of GAN neural networks it is likely that whatever technology is developed in detecting fake videos might also be used as a feedback mechanism, ultimately only improving the quality of deepfakes [4]. These examples show that combatting the threats of deepfake technology to democracy cannot be an exclusively technological story. Despite technological counter-measures, deepfakes still threaten democracy by setting cognitive biases and eroding a commonly agreed upon reality that serves as the background for a meaningful democratic dialogue. I argue in this essay that the mentioned threats to democratic discourse are grounded in a deepfake’s potential to mediate what humans perceive to be “real”. Furthermore, through mediating what is “real”, deepfake artefacts can co-determine human praxis. Because of how fundamental this theme is, I think we also need a philosophical story to understand the impact of deepfakes. In the following sections I first explore two diametrically opposed ways of coping with the societal impact of deepfakes. I then show how a theory of technological mediation is an appropriate philosophical framework for understanding this impact, and moreover that it is able to grasp the complexity of the question how to bear responsibility for it.
Stances on technological disclosure ¶
When one develops a technology that has a large societal impact, a quite fundamental ethical question is to what extent the developer is responsible for that impact. Philip Wang of thispersondoesnotexist justifies promoting the GAN technique used for deepfakes in an interview by pointing out that those “who are unaware are most vulnerable to this technology” [7]. This taps into what can be called a deterministic view on technology, which lets societal necessity follow quite automatically from technological potentiality with the motto: “if it can be done, it will be done”. In the field of AI deterministic attitudes are well represented as AI-technology is increasingly changing society. To the deterministic-minded person even those who worry about these societal changes and remind us of the dangers, are nevertheless equally subjected to the great historical impetus of technological progression. And this person then reasons: if the technology will emerge in society at some point in any case, then the best thing we can do now is raise awareness. In this way we, as a society, can adapt to the technology - rather than adapting the technology to human needs.
Other developers of AI-technology share the concerns for its potential negative societal impact, but conceive of their own responsibility differently. For example, the OpenAI research organization, which is dedicated to making sure AI benefits humanity, announced last month that they developed an AI that can write paragraphs of text that “feel close to human quality and show coherence over a page or more of text” [6]. However, contrary to the publications about video deepfakes, the OpenAI organization decided not to release the used datasets, nor the trained model or the used code, due “to concerns about large language models being used to generate deceptive, biased, or abusive language at scale” amongst other “malicious applications of the technology” [6]. They did however release a smaller trained model with less potential for abuse in order to still display the technical innovations that “are core to fundamental artificial intelligence research” [6]. As scientists, they do not want to counteract progression of the field. This experiment in responsible AI disclosure amounts to a more instrumentalist view on technology: its development is controlled by humans, instead of being an autonomous deterministic force to which humans have to adapt.
The primary hope of the decision to withhold the AI is that this will give the AI community as well as governments more time to come up with ways to prevent or penalize malicious use of AI technologies, quite similar to the practice of responsible disclosure in cryptography, where organizations are given time to repair security weaknesses before they are publicized. Interestingly, OpenAI’s explicit concern for the societal impact of their technology is framed in the context of political actors waging “disinformation campaigns” by generating fake content, requiring that “the public at large will need to become more skeptical of text they find online, just as the “deep fakes” phenomenon calls for more skepticism about images” [6]. In their policy OpenAI thus explicitly respond to the media attention surrounding deepfake neural networks that become better at deceiving people and are increasingly publicly available. Although not free of some hint of determinism, the OpenAI initiative exerts a responsibility for actively controlling technological development in AI, to make sure that it brings forth useful instruments that are to the benefit, and not the detriment of humanity.
The contrast in the positions between a) the open publishing of deep fake technology including trained models and code, and b) the controlled disclosure of text-generating networks, again shows that the development of these technologies does not only raise technical issues, but also societal ones. In both cases, the researchers are aware of the societal dangers of their technology, but take responsibility for it in different ways. In a deterministic vein, there is no reason to control disclosure of technology: someone else will publish it anyways, and it is better to inform people as soon as possible. From a more instrumentalist point of view, the act of disclosure is not as neutral: since humans have at least some control over technology, they also share responsibility for possible negative consequences within reasonable limits. After all, the technology itself is just a neutral instrument. Whether it is put to good use depends on humans.
Both views have in common that they conceptualize the human-technological relationship in terms of a subject-object divide, in which subject and object are external to each other, irrespective of whether the subject is human or some technology. But I think that these terms are no longer sufficient for understanding the complexity of deepfakes that heavily blur the demarcation between what is “real” and what is not, and consequently also not sufficient for understanding how this is the foundation of a threat to democracy. Accordingly, if we are to conceptualize the responsibilities of developers of such technologies, we need to take into account how these technologies mediate reality and human praxis.
Deepfakes and Technological Mediation ¶
In this section I argue that the philosophy of technological mediation as put forward by Verbeek [11] [10] is appropriate for conceptualizing the threat of deepfakes to democracy in terms of their mediation of human praxis. Technological mediation “concerns the role of technology in human action (conceived as the ways in which human beings are present in their world) and human experience (conceived as the ways in which their world is present to them)” [10, p.363]. That technological artefacts mediate means that they “are not neutral intermediaries but actively coshape people’s being in the world”, and that they do so in two directions: they mediate how the world appears to humans (perception) and how humans give shape to their own reality by acting in the world through the use of technological artefacts (praxis) [10, p.364]. The mediation of deepfakes can be shown in both directions, and I will indicate how they are interrelated in the example of democracy.
First of all, what the name “deepfake” expresses is that a given image or video is perceived to be “real”, while what is represented does not exist in the represented capacity: i.e. it is “fake”. I chose this specific formulation because a deep fake of Trump does not necessarily mean that Trump does not exist, but merely that he did not say or do what is represented in the deep fake video or image.
Now imagine a video of a man committing a serious crime, with the face of Trump swapped in. In case of a successful deepfake, we do not see a man with Trump’s face superimposed. Instead we perceive this man as Trump. The “as” in that sentence indicates an important insight from hermeneutic philosophy: the beings in our world always already appear to us as meaningful in a quite practical sense. The stereotypical example, based on Heidegger’s early philosophy, is that we see a hammer not as a composite object with one wood handle and one metal head, but intuitively and immediately take it as something we can hit nails with [10, cf. p.364]. Philosophical hermeneutics regards this as an act of interpretation that is not some scholarly exercise, but one that quite fundamentally determines how beings become present to us in the context of a world [cf. 5]. The particularity of deepfakes is that their technology mediates this process by making us pre-reflectively take something “fake” as something “real”. What is important is that, against instrumentalism, a deepfake’s deceiving character is not simply due to the bad intention of its designer. The technology itself is not a completely neutral tool in the theory of technological mediation. As it helps to shape what counts as “real”, this technology quite fundamentally sets a horizon for human moral and/or political action. Instead, mixing up fiction and reality is a core feature of the GAN technology that actively influences the relationship between a human and its world. A deepfake can thus be said to have its own “technological intentionality” [10 p.456] that affords (not causes!) the interpretation of “fake” as “real”.
But against determinism, this technological intentionality does not imply that the technological artefact autonomously decides our social realities, as if the technological artefact takes care of its own interpretation. As Verbeek makes clear, following Don Ihde, this technological intentionality only takes form in the interaction with humans [10 p.456]. Stating that technological intentionality does not coincide with human intentionality is analogue to the hermeneutic insight that the meaning of a text is not equal to the intention of its author. Despite this independence from the author’s intention however, it is equally naive in hermeneutics to say that the meaning of a text resides solely in the text itself as some pure ideal content, which would then be the same and equally complete even if nobody ever read it. Instead, and herein lies the analogue, a text’s meaning unfolds in the interaction with a reader. With respect to deepfake technology, this also means that its effects cannot be fully predicted independent of any real world interaction of humans with deepfake artefacts. I argue that in this manner a deepfake mediates how we perceive beings in the world by affording an interpretation of the fake as the real. If effective, a deepfake is not seen as just a video, but as representing an event in the world as we perceive it around us. But this interpretative step is everything but neutral. If we revisit the example of a deepfake of Trump performing a criminal act, we can see that this does not only imply we perceive the criminal as Trump, but that it also implies we now might perceive Trump as a criminal. We can then see how the hermeneutical effect of deepfakes underlies its effects in praxis:
If the fake is interpreted as real, then the real is reinterpreted in terms of the fake.
So if a candidate for a democratic election is shown in a deepfake to perform e.g. criminal acts (something fake is interpreted as real), then this candidate is potentially reinterpreted and reassessed by citizens as if he were a criminal (the real interpreted in terms of the fake). The aforementioned cognitive bias could also be interpreted along these lines: it is a re-valuation of something in the world because the deepfake artefact meddled with the interpretative process by which we take something as something.
Deepfakes thus contribute to the further blurring of the demarcation between real and fake news. As a result, even real and genuine discourse can become suspect, as it is now fair game to the question “fake or real?” But can we then still establish what we said was necessary for democracy? Can we in the future still have the certainty of an agreed upon reality, on the basis of which we can have a meaningful dialogue in the marketplace of ideas within a democracy?
Conclusion ¶
I have argued that the threat of deepfakes to democracy can be framed in terms of technological mediation, as we have regarded serious threats to democracy as a result of interpreting something fake as real. That means that deepfake technological artefacts can mediate both the (hermeneutic) experience of the surrounding world, and the actions humans take in it. But the perspective of technological mediation only makes the question who is responsible for (unintended) negative consequences more complex. One the one hand, developers of these technologies cannot be held fully responsible for negative consequences of technology, because they cannot fully predict how the interaction with users works out. But neither can developers realistically waive all responsibility by claiming that the development of AI is a historical movement shaping our social realities, independent of human interaction. Instead, when AI increasingly changes our social and political reality in unexpected ways, the more accurate position is admitting that somehow responsibility is distributed between developers, the technology itself, and its users. And especially if AI systems take on more autonomy in the future, the question of sharing responsibility with moral machines becomes increasingly urgent and intriguing.
Although such an open conclusion is not satisfying, it is the more honest position. When it comes to the moral responsibility (rather than a more limited legalistic story), issues around deepfakes can join the ranks of complicated ongoing debates about ethical responsibility in accidents with self-driving cars, or killer drones. The unresolved paradox is that unforeseen negative consequences may occur due to the learning capacity of AI, whereas at the same time, this flexibility is intended and exactly the main innovation of state-of-the-art AIs. And yet, we can reasonably ask of developers to foresee certain undesirable applications of their technologies. From the viewpoint of technological mediation both the stances of Philip Wang and of the OpenAI foundation have their own place. The decision of OpenAI to withhold their AI technology results from a reasonable anticipation of negative consequences, awaiting further democratic discussion before full disclosure. At the same time, this attitude should not tip the balance towards censorship. Withholding a technology from society in order to protect democracy seems paradoxically undemocratic and patronizing if not based on a sustained debate. Informing the general population about the threats of a technology is also desirable, but should not depart from a deterministic motivation. It is good, not because we have to learn to adapt to an uncompromising technology, but to spark a democratic debate with all involved stakeholders about how to design a better interaction with the technology [cf. 10].
References ¶
[1]: Robert Chesney and Danielle Keats Citron. Deep Fakes: A Looming Challenge for Privacy, Democracy, and National Security. SSRN Electronic Journal, 2018. doi: 10.2139/ssrn.3213954.
[2] Samantha Cole. We are truly fucked: Everyone is making ai-generated fake porn now, 2018. URL https://motherboard.vice.com/en_us/article/bjye8a/reddit-fake-porn-app-daisy-ridley. (accessed: 2019- 03-21).
[3] Maarten Franssen, Gert-Jan Lokhorst, and Ibo van de Poel. Philosophy of technology. In Edward N. Zalta, editor, The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University, fall 2018 edition, 2018. URL https://plato.stanford.edu/archives/fall2018/entries/technology/. (accessed: 2019-03-27).
[4] Will Knight. The defense department has produced the first tools for catching deepfakes, 2019. URL https://www.technologyreview.com/s/611726/the-defense-department-has-produced-the-first-tools-for-catching-deepfakes/. (accessed: 2019-03-23).
[5] C. Mantzavinos. Hermeneutics. In Edward N. Zalta, editor, The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University, winter 2016 edition, 2016. URL https://plato.stanford.edu/archives/win2016/entries/hermeneutics/. (accessed: 2019-03-27).
[6] OpenAI. Better language models and their implications, 2019. URL https://openai.com/blog/better-language-models.
[7] Danny Paez. 'this person does not exist' creator reveals his site's creepy origin story, 2019. URL https://www.inverse.com/article/53414-this-person-does-not-exist-creator-interview. (accessed: 2019-03-21).
[8] Timo Aila Tero Karras, Samuli Laine. A style-based generator architecture for generative adversarial networks, 2019. URL https://arxiv.org/abs/1812.04948. (accessed: 2019-03-21).
[9] Jan A. G. M. Van Dijk. Digital democracy: Vision and reality. Innovation and the Public Sector, 19:49-62, 2012. doi: 10.3233/978-1-61499-137-3-49.
[10] Peter-Paul Verbeek. Materializing morality: Design ethics and technological mediation. Science, Technology, & Human Values, 31(3):361-380, 2006. doi: 10.1177/0162243905285847. URL https://doi.org/10.1177/ 0162243905285847.
[11] Peter-Paul Verbeek. Mediation theory. 2019. URL https://ppverbeek.wordpress.com/mediation-theory/. (accessed: 2019-03-23).
[12] Philip Wang. Thispersondoesnotexist, 2019. URL https://thispersondoesnotexist.com/. (accessed: 2019- 03-21).
Book review: Van der Heiden - The Truth (and Untruth) of Language
Gert-Jan van der Heiden THE TRUTH (AND UNTRUTH) OF LANGUAGE Heidegger, Ricoeur, and Derrida on Disclosure and Displacement 300pp. Paperback. Duquesne University Press. 978-0-8207-0434-0
In philosophy equivocal language can count on resistance and criticism. It is often considered as unnecessary and striving against philosophy’s main imperative to be clair et distinct, if I may borrow Descartes famous phrase here. The unnecessary use of unclear and equivocal language is a point of criticism often uttered against some philosophers that are known to be difficult to read and understand, such as Martin Heidegger and Jacques Derrida, who happen to be two protagonists of Gert-Jan van der Heiden’s reworked edition of his doctoral thesis. Van der Heiden investigates how language can disclose beings to our understanding, but is also characterized by several displacements that problematize the idea that language can present reality unequivocally. Fortunately for us, van der Heiden succeeded in writing a book that excels in clarity, which is a major accomplishment considering the difficulty of his subject and his choice of authors.
Van der Heiden sets out to investigate the relationship between truth and language in contemporary hermeneutic philosophy. This branch of philosophy is called ‘hermeneutic’ because its major intuition is that we can have no access to the world and the beings existing in it outside of linguistic structures (‘hermeneutics’ is traditionally the art of text interpretation). When reality is structured like a ‘text’, so to speak, hermeneutics deals with our access to reality and becomes of philosophical interest. Our language use is then not simply a representation of a reality otherwise unaffected by understanding and interpretation. With this conception of language another conception of truth arises that does not presuppose the presence of things, but rather concerns their coming into presence, which is then seen as a primordial function of language: it lets things be. This is a different conception of language than one that understands sentences only as assertions about a pre-existing world. In that case truth is understood as the correspondence between language and reality, and untruth as the lack thereof. When language is understood in its power to let things be in the first place, this disclosing function has been said by Heidegger to denote an experience of truth as aletheia (disclosedness) that the Ancient-Greeks already had, but that had been pushed to the background in the history of philosophy that followed by a conception of truth as correspondence (or varieties thereof). This conception of truth brings with it another form of untruth. Untruth is in this case not a lack of correspondence, but rather the simple concealment that is necessary in order for things to be unconcealed. This simple concealment makes truth as disclosure possible, and is called untruth precisely because it is the space out of with truth lights up, which of course cannot be measured according to truth itself. Then we have an indication of the title: both the truth and untruth of language are at stake here.
When we take the sketched ‘linguistic turn’ for granted, we can understand the two major tracks Van der Heiden identifies in this hermeneutic philosophy. One the one hand, language becomes the medium through which things are disclosed and show themselves. On the other hand, language causes all sorts of displacement. Metaphorical language, for example, transfers a word from its proper domain into another. When Van der Heiden discusses metaphoricity, it is not so much for the sake of beautiful poems or engagement with art, but rather to address the metaphorical power of language to displace itself and the things it discloses. It is not accidental that in Van der Heiden’s treatment of displacement the notion of writing takes a central position, because it is writing par excellence that embodies the displacing characteristics of language that poses a danger for the desired clarity and univocality of philosophical concepts. Written language distances us from the original place and time of utterance, allowing distortion of the intended meaning and thus facilitating misunderstanding. For Plato this was reason enough to say that serious philosophy should not be written down. It would distort the full understanding of truth, and created the risk that philosophical truth would be ridiculed by the masses that also gained (superficial) access to it if it was written down. Language as it is spoken apparently does not have these dangers. When I teach someone my philosophical insights I am present to correct them and the truth of what I say takes place in the here and now. When truth is thought of as something absolute, this apparently immaterial taking place of language in my saying indeed seems to be the most undiluted presentation.
Seen from that perspective the displacing qualities of language are a danger to its ability to disclose something truthfully. It is fitting that Van der Heiden’s book begins with a treatment of Heidegger, because it is he who stresses this ability of language to disclose things. But although Heidegger in general is trying to overcome, insofar that is possible, the tradition that thought of writing as a danger to the immediate pureness of truth, Van der Heiden argues that Heidegger still privileges speech above writing. Thinking truth as disclosure presupposes also the thought of ‘something’ concealed. Without this concealment there would be no occurrence of truth in the sense of unconcealment. But one of the dangers that has always been attributed to writing is that, although it is not fit for truth, it appears to be so. Phrased in these terms, the danger of writing is that it acts as a disguise, it shows something, but only in a covered up way while acting as if it is the correct one. This concealment (pseudos) is not the concealment (lethe) that is necessary for truth as unconcealment (a-letheia), but rather the concealment that covers up the more primordial disclosure of things and the simple concealment involved in it, that Heidegger understands following the model of saying. So it seems that in the end the displacements involved in language are secondary to a most primordial disclosure of the being of things in language. In order to let itself be grasped by this disclosure, thinking has to finds its proximity to poetry, struggling with language to seek a genuine way of saying that does not displace the primordial disclosure of being.
This turn to poetry in Heidegger late works is quite famous (some would say notorious), but strangely enough the metaphoricity that we usually associate with poetry is not embraced at all by Heidegger. Van der Heiden succeeds in providing a very clear overview of Heidegger’s thought on metaphor, without ever losing the healthy distance that is required in order to differentiate himself – a philosopher writing about Heidegger – from a fanatic disciple (a so-called ‘Heideggerian’). In order to understand Derrida’s comments on metaphor for example, it is very important to understand why Heidegger renounces metaphor. According to Heidegger, metaphors imply a distinction of domains that is metaphysical, that is to say, they imply a transference from the domain of what we are familiar with (‘the sensible’) to an unfamiliar domain of abstraction (‘the intelligible’). The distinction itself is metaphysical, and poses the intelligible as a separate domain. The ultimate conclusion of this separation of domains is that in the end we cannot access the intelligible domain in itself, but only from the perspective of what we already know. For Heidegger this is typical of the very metaphysics he tries to overcome: it tries to answer the question of what the being of a being is, by looking at a being that is familiar to us. But then ‘being’ in general is only knowable for us insofar as we have metaphorical access to it, because it resembles something we already know. Then we implicitly act as if the being of a being is a being. In Plato’s famous allegory of the cave for example, the notion of the Idea of ‘the Good’ is metaphorically accessed through the image of the sun. Van der Heiden provides a very clear overview of Heidegger, and highlights all the relevant points for setting up a discussion with Ricoeur and Derrida, but not without questioning for example Heidegger’s thought that metaphors only exist within metaphysics (it only seems obvious in the case of philosophical metaphors). Van der Heiden never fails to remain clear-headed and always provides a fresh and clear overview of the discussed authors. To be honest, this is a quality that cannot be underestimated when you think of the literary hocus-pocus and bewildering erudition going on, especially while reading Heidegger and Derrida, but often also in secondary literature that deals with them.
Heidegger is in a way the hinge around which the theme of this book unfolds, for his thought forms the background against which both Ricoeur and Derrida develop their own thought. But both Ricoeur and Derrida understand the displacement of language as a productive element, rather than something risking to disguise the original disclosure of being through language. It is fitting that Van der Heiden spends two chapters on metaphor and on mimesis, because in these themes the lines of disclosure and displacement intersect. They have a connection to both the creative and productive aspects of language and to the displacing aspects. In the case of metaphors, a word is transferred and thus displaced to another domain, but by doing so it provides a new understanding. Mimesis presents something anew, but is at the same time a representation and thus a displacement. So in these cases displacement is not seen as a disguise of disclosure, but rather as itself constitutive of a new or repeated disclosure.
The choice to focus on Derrida and Ricoeur in discussing disclosure and displacement is a good one, because they both take on the heritage of Heidegger in characteristic ways. Generally speaking, we can say that Ricoeur follows up on Heidegger in line with the ‘hermeneutic’ tradition, while Derrida appropriates the ‘hermeneutic’ way of thinking language in order to deconstruct it. Van der Heiden shows convincingly that for Ricoeur the disclosure resulting from the displacement involved in a metaphor is taken up in the process of interpreting that aims at deciphering a hidden ideal meaning of a text. So here disclosure does not so much give us meaning in the first place, but is guided by a meaning of the text that precedes it. Metaphors provide in grasping this ideal meaning.
Derrida lays more emphasis on other aspects of Heidegger’s heritage, and thinks disclosure more fundamental than Ricoeur does. Derrida follows Heidegger’s thought that disclosure and truth are only possible on the basis of a preceding untruth. But Derrida radicalizes this thought by arguing that every disclosure can only be a disclosure on the basis of a previous displacement because in order for something to be given in language, this language is always a repetition, which involves a transmission and translation from context to context. (Those who are interested should investigate Derrida’s notion of ‘iterability’). As I said earlier, the relation between the clarity of the philosophical concept and the displacing powers of metaphor is full of tensions. Derrida drives this tension to its ultimatum by arguing that the metaphor does not simply exist within metaphysics, but rather points to the original displacements that make philosophical language possible in the first place.
I had to indulge in giving these abstractions, because, frankly this book is very abstract. The matters discussed in The Truth (and Untruth) of Language are mainly of theoretical philosophical concern, so surely this book is not for everyone. It is written in an academic style and for academic purposes. Reading this book will not fulfil a reader looking for a revolutionary reading, a bag of literary tricks or fun storytelling. Apart from the last, one could always read for example works of Derrida himself. But then again, I would say this is in no way a shortcoming on behalf of Van der Heiden. Academic language can be revolutionary in this case, because it brings together authors that can themselves be quite enigmatic, to say the least, with a comprehensibility that is not often achieved. This philosophy of truth is hermeneutic, but certainly not hermetic.
Het merkteken van ongenade (Dutch)
‘I don’t know what the question is any more. Between Lucy’s generation and mine a curtain seems to have fallen.’ (Coetzee 2000, 210).
In het boek Disgrace van J.M. Coetzee wordt het leven van de academicus David Lurie en zijn dochter Lucy overhoop gegooid door een aanval op de boerderij van Lucy, op het platteland van Zuid-Afrika, waar David na zijn ontslag vanwege een ongepaste relatie met een studente tijdelijk verblijft. Daarbij raakt David gewond aan zijn oor, en wordt Lucy verkracht door de drie zwarte overvallers. Na het voorval doet Lucy alsof er niets aan de hand is, en probeert zij het plattelandsleven weer op te pakken. Zij spreekt er niet over, wil er niet over spreken. Pas aan het einde van het boek uit ze zich voorzichtig, maar toch schieten woorden dan te kort:
‘I can’t talk anymore, David, I just can’t,’ she says, speaking softly, rapidly, as though afraid the words will dry up. ‘I know I’m not being clear. I wish I could explain. But I can’t. Because of who you are and who I am, I can’t. I’m sorry.’ (Coetzee 2000, 155).
De verkrachting, een gebeurtenis die alleen Lucy op een specifiek moment heeft ondergaan, markeert haar voor het leven. Lucy kan de gebeurtenis hoogtens verwoorden met een geweldadige metafoor: ‘Pushing the knife in; exiting afterwards, leaving the body behind covered in blood’ (Coetzee 2000, 158). Tegelijkertijd is die letterlijke insnijding in haar lichaam een demarcatielijn tussen David en Lucy, die hen van elkaar vervreemdt. Tot aan de verkrachting hebben David en Lucy een goede verstandhouding, maar daarna vormt de verkrachting steeds dat punt waarop het gesprek tussen David en Lucy stokt. Het fysieke trauma dat Lucy heeft opgelopen lijkt voor David ondanks goede bedoelingen voorbij elke verstaansmogelijkheid te liggen. Zo zegt Lucy:
Stop it David! I don’t need to defend myself before you. You don’t know what happened. (Coetzee 2000, 134).
Ondanks de dreiging van een nieuwe aanval is Lucy vastberaden op het platteland te blijven wonen, terwijl voor David vaststaat dat ze het beste kan vertrekken naar een veiligere plek. De volstrekt singuliere gebeurtenis van de verkrachting ontwricht de relatie tussen vader en dochter. Het is niet een gebrek aan rationaliteit of simpelweg onwilligheid waardoor David en Lucy niet nader tot elkaar kunnen komen, maar een door de verkrachting geïntroduceerde andersheid: ‘because of who you are and who I am’.
Geconfronteerd met de begrenzing van zijn begrip, probeert David de betekenis te vatten van wat er gebeurd is, en biedt Lucy de volgende interpretatie aan:
‘It was history speaking through them,’ he offers at last. ‘A history of wrong. Think of it that way, if it helps. It may have seemed personal, but it wasn’t. It came down from the ancestors.’
(Coetzee 2000, 156).
Het volstrekt dramatische moment van de verkrachting is dus beladen met een betekenis die niet alleen persoonlijk, maar ook historisch is. Op zeer geweldadige wijze wordt Lucy ingevoegd in een historisch gesprek dat al gaande was voordat zij er deel aan ging nemen: een Zuid-Afrikaans gesprek tussen wit en zwart, tussen een geschiedenis van overheersing en slavernij, van discriminatie en apartheid. Dit is geen onschuldig gesprek, maar een gesprek dat gaat over de toekomst van Zuid-Afrika, dat cirkelt om de vraag: hoe moeten we, met in ons achterhoofd de herinnering aan een geschiedenis van apartheid, samenleven? Daaronder gaat een andere vraag schuil: hoe kunnen we ons vanuit de vooroordelen die onze verschillende tradities meebrengen, ons openstellen voor de ander, in het bijzonder wanneer dat ook gevaren met zich meebrengt? Dit is één van de meest fundamentele problemen van de hermeneutische filosofie, die alleen maar aan maatschappelijke relevantie wint met de opkomst van identiteitspolitiek.
Na de verkrachting van Lucy begint de discussie over wat ze nu moet doen. David meent dat Lucy weg moet vluchten naar het veilige (en voornamelijk blanke) Nederland, waar raciale spanningen minder leven dan in Zuid-Afrika. Lucy besluit echter te blijven, blijkt zwanger te zijn van haar verkrachters, en zoekt bescherming bij Petrus, een zwarte man die eerst de status van een hulp had en naar het einde van het boek steeds meer een zelfstandig landeigenaar wordt.
We hebben al gezien dat de verkrachting demarceert, David en Lucy van elkaar onderscheidt. We zien nu een mogelijke grond van die demarcatie: Lucy is een gesprek over haar toekomst aangegaan dat David niet meer kan volgen. De verkrachting heeft haar in dat gesprek gedwongen, ze moest het een plaats geven. Hij kan met geen mogelijkheid de keuze van Lucy begrijpen om op dezelfde plek te blijven wonen. David gaat het gesprek over de toekomst niet aan zoals Lucy dat doet. Want: ‘he is too old to heed, too old to change.’ (Coetzee 2000, 209). David is niet meer bereid zijn vooroordelen te overstijgen en zich te openen voor de ander. De verkrachting heeft hem in de positie van een buitenstaander geplaatst, wat een fundamenteel thema is dat terugkeert in Coetzee’s romans en een belangrijke reden waarom hij de Nobelprijs voor literatuur gewonnen heeft.
Lucy daarentegen accepteert op een wrange manier de verkrachting. Door de verkrachting, bezien vanuit Davids interpretatie als een botsing van verschillende geschiedenissen, heeft zij toegang gekregen tot de kern van de zaak van een historisch gesprek. Zij heeft daarin gezien wat het voor haar betekent om in Zuid-Afrika te wonen. Lucy zegt op een gegeven moment zelfs:
‘But isn’t there another way of looking at it, David? What if… what if that is the price one has to pay for staying on? Perhaps that is how they look at it: perhaps that is how I should look at it too. They see me as owing something. They see themselves as debt collectors, tax collectors. Why should I be allowed to live here without paying? Perhaps that is what they tell themselves.’ (Coetzee 2000, 158).
Op een bepaalde manier berust zij, hoe cru het ook is, in de verkrachting. Zij berust erin dat ze bescherming nodig heeft van een zwarte man (Petrus) wil zij als alleenstaande blanke vrouw stand houden. Zij besteedt geen bijzondere aandacht aan de jonge jongen die bij de verkrachting aanwezig was, wanneer blijkt dat deze jongen familie is van Petrus. Zij dient geen officiële aanklacht in. Zij is zwanger van haar verkrachters, maar heeft geen abortusplannen. David daarentegen is het met alle bovenstaande stappen oneens, en elke keer wanneer hij zich rond Lucy begeeft ontstaan er spanningen. Lucy symboliseert hier een toekomst van een verzoening tegen een hoge prijs, en David een oneigenlijke toekomst die in het verleden wil blijven hangen.
Zowel Lucy als David zijn gemarkeerd door de verkrachting en aanval. ‘They have marked me’ (Coetzee 2000, 158), zegt Lucy. Beiden dragen een merkteken, zijn onherstelbaar gemarkeerd met ongenade (disgrace). Ten opzichte van de verkrachting zijn er twee houdingen: die van het vergeten met het oog op de toekomst, en die van het herinneren. Lucy wil het merkteken, de insnijding die in haar lichaam is gemaakt, vergeten, er niet stil bij blijven staan, en doorgaan. David wil herinneren. Wanneer hij een zwarte jongen op een feest van Petrus herkent van de aanval en verkrachting, wil Lucy gewoon weg, maar zoekt hij de confrontatie op. De passage van die confrontatie eindigt met: ‘He lifts a hand to his white skullcap. For the first time he is glad to have it, to wear it as his own.’ (Coetzee 2000, 135). Zijn verbrande oor, zijn merkteken, zijn fysieke herinnering aan de verkrachting, aan de aanval en aan zijn onvermogen er iets aan te doen, is een herinnering aan de ongenade waarin hij is vervallen door zijn oneervolle ontslag en de situatie met zijn dochter. David wil die herinnering niet vergeten, maar wil gerechtigheid voor daden uit het verleden. Maar die gerechtigheid heeft geen plaats in de Zuid-Afrikaanse praktijk waar Lucy zich in bevindt, en verstoort die praktijk zelfs. Lucy neemt hem dat kwalijk: ‘Everything had settled down, everything was peaceful again, until you came back.’ (Coetzee 2000, 208).
De vraag naar het merkteken en hoe daarmee om te gaan wordt in Coetzees Disgrace op bijzondere wijze aan de kaak gesteld, maar niet beantwoord. Het boek opent een labyrint van vragen. Moet het verleden koste wat het kost herinnerd blijven worden? Kunnen we op die manier een vruchtbare toekomst tegemoet gaan? Of moeten we vergeten met het oog op vredig samenleven? Maar kunnen we ons verleden wel vergeten, wanneer die in onze taal, cultuur en vooroordelen is ingesleten?
De toekomst ligt nog open, het gesprek gaat door. Enerzijds is er het toekomstige kind van Lucy, dat zelf een merkteken van de verkrachting is. In de letterlijke vermenging van zwart en wit biedt het kind een toekomstperspectief. Echter, de zwarte jongen die aanwezig was bij de verkrachting van Lucy, roept na een aanvaring met David: ‘We will kill you all!’ (Coetzee 2000, 207). In deze tegenstelling, maar ook in die tussen Lucy en David, tussen verschillende generaties, openbaart zich een Zuid-Afrikaanse spanning tussen verleden en toekomst die ik hier heb laten cirkelen om Coetzees beschrijving van een verkrachting.
Tot slot: de verkrachting zelf is niet hermeneutisch – in diens afgrondelijke geweld spreekt hooguit het onvermogen te spreken. De verkrachting krijgt echter een hermeneutische duiding in Disgrace omdat het op een zeer problematische manier de ruimte opent voor een gesprek. Dat gesprek heeft het karakter van een moeizame therapie, van een verwerkingsproces dat nog lang door zal gaan. Zoals David tegen Petrus zegt: ‘It is not finished. On the contrary, it is just beginning. It will go on long after I am dead and you are dead.’ (Coetzee 2000, 202). Het gesprek gaat voort, al is het zonder ons.
Bibliografie ¶
Coetzee, J.M. 2000. Disgrace. London: Vintage.
Friendship, death, and writing in Michel de Montaigne's Essays
Introduction ¶
In the center of the first book of Michel de Montaigne’s (1533-1592) Essais we find his famous essay on friendship. We should not ascribe the central location of this essay to coincidence, in particular not when we take the introduction of this famous essay on friendship into consideration. In that introduction Montaigne compares his Essais with the work of a painter he had employed. This painter meticulously placed his paintings on the wall. In the middle of each wall he placed his best paintings, which showed all of his capabilities as a painter, and he filled the surrounding space with so-called grotesques, paintings that display fantastic and strange figures that are only enjoyable in that strange capacity. Montaigne’s analogy follows immediately:
And what are these things of mine, in truth, but grotesques and monstrous bodies, pieced together of divers members, without definite shape, having no order, sequence, or proportion other than accidental? (Montaigne 2010, 187).
However, Montaigne stresses that the analogy is not complete. Despite his Essais being like these grotesques, Montaigne deems himself incapable of producing the well-rounded central artwork. That is why he instead announces that as the 28th essay he will place an essay of his dear friend, Etienne de La Boétie, with a work from his youth that Montaigne deems fit to take this prominent place. In addition, sonnets from the same friend will make up the 29th essay. As the 28th and 29th of the 57 essays of the first part of the Essais, Montaigne thus places the work of his friend at the center of his labyrinth of grotesque writings; a labyrinth that thus, void of any intrinsic necessity, more or less accidentally and without order, floats around a focal point: around the friend, around their friendship. And in particular, as occurs so often in the history of the writing on friendship: around the deceased friend, the friend that has passed away.
In this essay I ask why the writing on friendship is so often connected to the death of the friend. In particular, what does this say about writing, and what does it say about the friendship? How do the motives of friendship, death and writing coincide in Montaigne’s essays?
Derrida on the love that mourns ¶
The testamentary character of friendship is emphasized by Jacques Derrida in his book The Politics of Friendship. Although Derrida distinguishes historical periods in the writing and thinking on friendship - namely: the Greek-Roman model, the Christian model, and “Nietzschean” thought on friendship (Berns 2013, 218) - he observes that the relation between friendship and the death of the friend is a recurrent theme, parallel to or throughout those periods. Derrida remarks that already in Aristotle the relation between friendship and survival is present - and with that the mourning of the other, the friend (even though in the Greek-Roman model the friend still circulates in the economy of the self). That connection between friendship and death concerns the durability and stability (bébaios: ‘stable, established, certain, assured’ (Derrida 2005, 15)) of the friendship, and in particular Aristotle’s preference for the activity of loving rather than the passivity of being loved. What else is friendship rather than a particular form of loving - as an activity?
According to Aristotle friendship does not primarily exist in a particular event that is passively endured, but instead in the activity of loving even before any situation of being loved arises. Derrida summarizes this position on the passivity of being loved:
It says nothing of friendship itself which implies in itself, properly, essentially, the act and the activity: someone must love in order to know what loving means; then, and only then, can one know what being loved means. (Derrida 2005, 8)
This privileging of the act has everything to do with knowledge. According to Aristotle the highest friendship is for the sake of what is good, relative to which friendship for utility and pleasure are mere derivatives, and is thus always characterized by durability, bébaios, through the presupposition that reason is being used in making decisions for the sake of the good. Now, the particular type of loving specific to friendship is as an activity accompanied by knowledge, whereas being the passive object of love can remain a secret to the one being loved. Conversely, the loving considered as an activity is never strictly secret: even if the love1 is not proclaimed aloud, the love is always already at least proclaimed to the lover itself. In Aristotle’s view, the phenomenon of friendship can thus not, in its essence, primarily be understood as a passive and potentially unknowingly undergoing of a type of love.
As a result, Derrida argues that Aristotle’s view on friendship is embedded in a rational system of contrapositions and preferences for one over the other. Indeed, these preferences are traditional preferences of philosophy itself:
Loving will always be preferable to being-loved, as acting is preferable to suffering, act to potentiality, essence to accident, knowledge to non-knowledge. It is the reference, the preference itself. (Derrida 2005, 11).
Aristotle would accordingly claim that if a friend should choose between knowing and being known, he would choose knowing, precisely because knowing characterizes true friendship. In that context Aristotle claims that “we” (i.e. the Ancient Greek) praise the friend that keeps loving a dead friend, because in that scenario that friend knows, without the reciprocity of being known. The object of knowing can thus potentially be a dead friend or a lifeless object, whereas the knowing subject is necessarily alive in the act of friendship. Considering an object of knowing, there is thus always already the possibility of that object being dead. This holds accordingly in the act of friendship, which is necessarily accompanied by the (self-)knowledge of this love:
Friendship for the deceased thus carries this philía to the limit of its possibility. But at the same time, it uncovers the ultimate spring of its possibility: I could not love friendship without projecting its impetus towards the horizon of this death. (Derrida 2005, 12).
The limit case of loving the dead friend thus shows that in Aristotle’s view the object of love does not essentially have to exist. In other words, true friendship anticipates the death of the other. The possibility of loving a friend and possibility of the death of the loved one emerge from the very same origin:
I could not love friendship without engaging myself, without feeling myself in advance engaged to love the other beyond death. Therefore, beyond life. I feel myself – and in advance, before any contract – borne to love the dead other. (Derrida 2005, 12).
We thus see that that together with the heterogeneity between activity and passivity, act and potentiality, knowing and not knowing etc., an invisible line between life and death at the same time.
It is inherent to every friendship that one friend survives the other.
Derrida will proceed to play out contradictions in Aristotle’s view on friendship in the usual fashion of deconstruction, transforming Aristoteles’ position into new insights along the way.
Tracing the steps of that deconstruction is not the aim of this essay.
Instead, the goal was to introduce the connection between friendship and death, because this thread returns throughout history in the thinking about friendship, for example in Cicero, Seneca, Augustinus, and also in Derrida himself, who published several memorials about friends.
Another interesting author where this connection can be examined is Michel de Montaigne.
The essay as Grotesque ¶
What Montaigne adds to the aforementioned connection between friendship and death is, I argue, that in his essay on friendship textuality itself enters into relation with death as well. I mean that in a more concrete sense than for example Derrida, when he argues that writing is the principle of death2 in a history of logocentrism, because writing breaks the ideality of the voice. The voice is there understood as an auto-affection that is seemingly not stained by the materiality of any signifier, fully present and self-present. This theme could perhaps shed a light on how Montaigne’s essay of friendship expresses the desire for the presence of a lost friend.3
But here I want to focus on the structure and status of the 28th essay itself, as well as its special position in the Essais as a whole, regarded in light of the remarks Montaigne makes about his own texts at the beginning of the essay on friendship. I already partly summarized those remarks in the introduction. But what we should add now is that the announced center piece dedicated to his friend Etienne de la Boétie - of essay 28 and 29, and as such also the center of the Essais as a whole - is remarkably absent. The “grotesques” of Montaigne thus circulate around an absent center, a central absence that we can understand in a negative fashion as a vanishing point. In the very heart of the Essais the disappearance of the friend is materially inscribed.
Moreover, in the rather bizarre introduction to his Essais Montaigne describes that he intended the essays as a self-portrait.
This, reader, is an honest book. It warns you at the outset that my sole purpose in writing it has been a private and domestic one. I have had no thought of serving you or of my own fame; such a plan would be beyond my powers. I have intended it solely for the pleasure of my relatives and friends so that, when they have lost me - which they soon must - they may recover some features of my character and disposition, and thus keep the memory they have of me more completely and vividly alive. Had it been my purpose to seek the world’s favour, I should have put on finer clothes, and have presented myself in a studied attitude. But I want to appear in my simple, natural, and everyday dress, without strain or artifice; for it is myself that I portray. My imperfections may be read to the life, and my natural form will be here in so far as respect for the public allows. Had my lot been cast among those peoples who are said still to live under the kindly liberty of nature’s primal laws, I should, I assure you, most gladly have painted myself complete and in all my nakedness. So, reader, I am myself the substance of my book, and there is no reason why you should waste your leisure on so frivolous and unrewarding a subject. (Montaigne 1993, 23).
We see first of all that the text anticipates the death of Montaigne himself,
and is intended to function as a necrology for family and friends (here in the plural), in which Montaigne’s self becomes readable and recoverable.
He adds immediately that, even though he is being honest in representing himself, he cannot offer a full-on nude portrait of himself, but only a portrait ‘in so far as respect for the public allows’.
The self-portrait tries to conjure up the self in a lively fashion,
but cannot do so completely.
Montaigne’s remark reaffirms how such a narrative of the self is a construction, a simulation, which could be understood paradoxically as an illusion produced by the dissimulation of the self.
He writes his self in the text as something that will essentially be absent.
Who reads the Essais indeed has the idea, even if it is an illusion,
that the voice of Montaigne speaks from the text itself, even though it
is clear that structurally this particular presence signifies the absence, the death of Montaigne himself.
And Montaigne makes this insight even more explicit by anticipating his own death at the very moment of writing.
Besides this subtle textual self-renunciation in the self-portrait, it is also remarkable that in the very display and literary creation of his ‘self’ Montaigne circumscribes his own subjectivity with the words of others. In this light the comparison of his own essays with grotesques is not innocent at all, because Montaigne thus places himself in a position of marginality and eccentricity with respect to the central theme of death.
As Brad Epps puts it:
What arises is a self-portraiture beside itself, or better yet, a self-portraiture which consists of an elaborate cir-cumlocution, or en-framing, of the words and images of others: La Boétie, of course, but also Horace, Catullus, Ariosto, Cicero, Terence, and so on (Epps 1995, 41).
Montaigne’s autobiography is thus simultaneously a biography of his dead friends, and in particular of his dead friend (in the singular), Etienne de la Boétie. In his article Grotesque Identities Brad Epps considers the grotesque as a method of self-portraiture. The strangeness and even the monstrosity (a term that Montaigne himself uses in essay 28 with emphasis) of the grotesque thus becomes more insightful:
For if the grotesque is strange, even monstrous, it is in part because it styles the self as twisted round and shot through with otherness. (Epps 1995, 41).
This fascinates me because the blending in of the other in the self - an otherness so radical that it becomes a monstrosity - is a crucial element of how Montaigne describes the true friendship:
In the friendship I speak of, our souls mingle and blend with each other so completely that they efface the seam that joined them, and cannot find it again. If you press me to tell why I loved him, I feel that this cannot be expressed, except by answering: Because it was he, because it was I. (Montaigne 2010, 192).
So according to Montaigne, he and La Boétie where such good friends that one could no longer discern a rigid difference between ‘I’ and ‘you’, between ‘you’ and ‘I’. This is different than the reciprocity that is central to the Greek-Roman thinking on friendship, in which the otherness of the friend is from the onset considered to be a mirror of the self, on equal footing, and in which the otherness of the friend is thus immediately assimilated in the economy of the self. The equality and reciprocity of the Greek-Roman model of friendship are replaced by Montaigne by the ‘heteronomy, transcendence and infinity’ (Berns 2013, 220, my translation) that is so typical of the Christian idea of friendship4. That transcendence and infinity are illustrated clearly when Montaigne says about his friend:
he surpassed me infinitely in every other ability and virtue, so he did in the duty of friendship. (Montaigne 2010, 198).
By speaking of this infinite transcendence Montaigne’s praises his friend quite literally into heaven; almost as if the friend here replaces the position of God. What thus takes shape is some sort of negative theology through which Montaigne strictly distinguishes his friendship with La Boétie from ’normal’ friendships, family ties, sexual relations with women (and from the ‘Greek love’). What is left after the negation of these expressions is beyond words. The only utterance that is left for Montaigne to express this friendship is “Because it was he, because it was I.” In this mystical experience - I think you can call it that - he can find no reason for the friendship outside of the singularity of the other. The ontological question what friendship is, as for example Aristotle asked it, is rendered inoperable and of no use for structuring and articulating the friendship (Berns 2013, 220).
This point is important for my overall argument because I want to show how the structure of the Essais incorporates, as it were, Montaigne’s thinking on friendship. That the essay is a grotesque means that the written self-display of Montaigne encircles the heterogeneous other, the infinite transcendence of the friend. There is thus a connection between Montaigne’s writing and his experience of friendship. But there are more connections to point out. Both friendship and the grotesques relate to death. I already highlighted the connection between friendship and death with the help of Derrida’s interpretation. With respect to Montaigne I would like to add that friendship does not only anticipate the death of the other, as we saw in Aristotle, but that friendship as Montaigne envisions it is so ideal, so mystical, that perhaps it could only take place if and only if the friend is dead.
The suspicion that gave rise to this essay is that that the ideal friendship of Montaigne only first takes place in the text, in the writing about friendship, in the grotesque writing of a self-portrait in which the dead friend is being remembered and the ideal friend is being born.
My main claim thus is that Montaigne’s friendship is fundamentally written.
And perhaps the grotesque nature of Montaigne’s writing thus structures his friendship. His writings are grotesque in sofar as they are scribbles in the margin of a central absence, an emptiness that is inscribed in essay 28 as an empty space at the place where La Boétie’s La Servitude Volontaire should have been. It is this central emptiness, the death of the friend, that perhaps inspired the writing of the Essais and the writing on friendship. Kuisma Korvonon states:
One important story about the Essais (…) is the one where Montaigne starts to write his book after the death of his friend Etienne de la Boétie – the story of an ideal friendship, with the text serving as its memorial. (Korvonen 2006, 78).
Montaigne’s friendship has a testamentary character, it exists by the grace of an epitaph, a series of testamentary signs that summon a ’living’ image of the friend, while inevitably it is the very death of this friend that is its possibility and inspiration5. The form of the grotesque is appropriate for this structure of friendship. Epps states about this form:
The ornamental flourish of figures neither fish nor flow, the reticular profusion of cryptic signs and images, is the most visible stuff of the grotesque, but so too are death, burial, emptiness, creativity, excess, and exuberance: an entire thematics of mortality and vitality that heightens, and is heightened by, the significance of form (Epps 1995, 44).
In this regard the form of the 28th essay itself highly meaningful: its profusion of signs results from a central lack and emptiness, namely the strange and plural absence of the announced text from La Boétie. I say plural, because at the end of the 28th essay Montaigne first of all excuses himself for not placing the text of his friend that he promised, due to the controversial and unintended role it had started to play in its use by protestants under the name Le Contre Un6. But secondly, the piece that he promised to publicize instead, ‘produced in that same season of his life, gayer and more lusty’ (Montaigne 2010, 199), he also did not publish.
In the line of my argument this however make sense: which text could possibly live up to his image of the infinite transcendence of his friend? Both Montaigne’s grotesque writing and his notion of friendship encircle a void left by a central death, that is too ideal to be filled materially.
About this essay:
This essay is a translation and edit of a Dutch essay I wrote about five years ago. You can contact me if you are interested in the Dutch version.
Bibliography ¶
Berns, Gido. 2013. “De tijd van de vriendschap. Vriendschap, broederschap en democratie bij Derrida.” Tijdschrift voor Filosofie 75: 215-46.
Derrida, Jacques. 2005. Politics of Friendship. Translated by George Collins. London: Verso.
Derrida, Jacques. 1974. Of Grammatology. Translated by Gayatri Chakravorty Spivak. Baltimore: The John Hopkins University Press.
Epps, Brad. 1995. “Grotesque Identiteit: Writing, Death, and the Space of the Subject (Between Michel de Montaigne and Reinaldo Arenas. " The Journal of the Midwest Modern Language Association 28: 38-55.
Korhonen, Kuisma. 2006. Textual Friendship. New York: Humanity Books.
Kurz, Harry. 1950. “Montaigne and la Boétie in the Chapter on Friendship.” PLMA 65: 483-530.
Montaigne, Michel de. 2010. “On Friendship.” In Other Selves. Philosophers on Friendship, redactie door Michael Pakaluk, 185-99. Indianapolis: Hackett Publishing Company.
Montaigne, Michel de. 1993. Essays. Vertaald en ingeleid door J.M. Cohen. London: Penguin Books.
Schlossman, Beryl. 1983. “From La Boétie to Montaigne: The Place of the Text.” MLN 98: 891-909.
I consider friendship here as a specific form of love. This essay does not go into further detail about the relation between concepts of friendship and love. ↩︎
‘What writing itself, in its nonphonetic moment, betrays, is life. It menaces at once the breath, the spirit, and history as the spirit’s relationship with itself. (…) Cutting breath short, sterilizing or immobilizing spiritual creation in the repetition of the letter, (…) it is the principle of death and of difference in the becoming of being.’ (Derrida 1974, 25). ↩︎
For an exposition about the Essais from this more psychoanalytic perspective, consider ‘From La Boétie to Montaigne: The Place of the Text’ from Beryl Schlossman. He argues that Montaigne’s love for the friend cannot be seen apart from a homosexual desire, a possibility that Montaigne himself explicitly excludes in his essay. ↩︎
Although Berns emphasized together with Derrida that Montaigne’s position cannot be seen as a radical departure from the Greek-Roman model of reciprocity. That is not of direct concern for us though. ↩︎
To clarify: it is death that give cause to place a tombstone to remember the deceased person, and to praise his friendship. The placing of a tombstone for a living person is nonsensible. But even if the person for whom the tombstone is intended is still alive, the tombstone as such still presupposes his death. ↩︎
For a history of this piece and its protestant renaming see the article ‘Montaigne and La Boétie in the Chapter on Friendship’ by Harry Kurz. ↩︎
Two methods for exporting EPUB annotations (.annot)
See here for a follow-up.
My personal goal for this summer break was reading more, as I really enjoy it but do not schedule enough time for it during the many hectic days throughout year. I always enjoy reading a book, but somehow the threshold for doing some project behind my pc is lower than simply sitting down in a chair with a good book. A complication for reaching my goal was however that I would go backpacking for three weeks throughout Europe. I needed to pack very lightly, and even bringing a single book would be a major compromise to that. This is where, despite being a bit of a chauvinistic philosopher that prefers the touch of “real” books, the e-reader comes into play. I purchased a Kobo Clara HD, and I have to say that the experience has been great. During my travels I finished “Crime and Punishment” from Dostojevski, read “Slaughterhouse Five” from Kurt Vonnegut, and read half of the uncomfortably thick “The Brothers Karamazov”, also from Dostojevski. And even now that I am home I notice how much easier it is to pick up the e-reader, compared to a book.
During reading, I made many annotations and notes on my Kobo. Now that I am home, I was wondering how to export these notes to my pc, because that would save the trouble of manually finding back citations on the Kobo itself, which is slow, and perhaps typing them over by hand, which is even slower. To my surprise, there was no default exporting option for annotations.
Method 1: adjusting the Kobo configuration file ¶
A reddit user however found a solution. This solution was suggested for another Kobo version, but also works for my Clara HD. I summarize the solution here for completeness:
- Connect your Kobo to your computer.
- Find and open “Kobo eReader.config” in the Kobo drive. Mine is at /.kobo/Kobo/, relative to the root of your Kobo e-reader.
- Add the following code, including the newline. This section is brand new, so it’s probably easiest to just add it at the bottom of the file:
[FeatureSettings]
ExportHighlights=true
- Eject Kobo and boot it up.
- This adds another option in the menu that is available when reading books, namely to “Export highlights” under the “Notes” tab. After entering a filename the annotations will be saved to the root directory of the Kobo.
The export function produces a plain text file, starting with the title of the book, followed by a separate paragraph for each annotation. Notes are displayed in a similar manner, as such:
The original citation goes here Note: this is my smart comment
And voila! With this method you have fast access to all your annotations in an open text format, so you can directly use it in an editor of your choice.
Method 2: customize the exporting to your own needs by parsing the annotation files ¶
However, if for some reason you want to export your annotations in a different manner, then you can always find the full xhtml markup with all annotations at “/Digital Editions/Annotations/books/”. If we inspect it, we see that the xhtml does not really contain much more relevant information than we already exported. Per annotation, we also have the date at which we made the annotiation, as well as some non-human-readable identifiers. Having the date of an annotation is not essential, but if you intend to archive your notes, dates would give insight in your lecture of for example a few years back, and add some flexibility. One could for example later sort the notes on date to distinguish notes from a first and a second reading.
What I would have liked to include in my export was some more structure, for example grouping notes by chapter. What I also think is weird with the default export, is that the author of the book is never listed, and neither is the publisher of the book, which is handy for later reference. Another argument for writing our own “export function” is the possibility of immediately using a specific output format of choice. For example, I currently store my notes in Markdown on Github, so we could export the notes immediately using Markdown syntax. Another idea is to at least number the annotations, given the absence of an ordering in chapters and the unavailability of a meaningful page numbering with the epub format.
If someone knows how to parse chapters and pagination from .annot files, please hit me up!
Solution with a Python script ¶
The annotation files with the .annot extension are written in xhtml. For parsing xhtml we can use the lxml xml parser. Consider this remark on their site:
Note that XHTML is best parsed as XML, parsing it with the HTML parser can lead to unexpected results.
I like using Python, and luckily Python has a nice package called BeautifulSoup that offers a simple interface for using the lxml parser.
The Python script I wrote extracts the title, author, publisher and writes them to a file in the YAML format, which can be used within Markdown files and is supported both by Github Markdown and Pandoc Markdown (the two dialects I use). Pandoc’s default LaTeX engine for producing pdf files actually knows how to read the YAML entries and display them as a default LaTeX titlepage, which allows you to directly create a smooth pdf without writing any LaTeX.
The script also distinguishes between annotations and notes, and displays them differently. All annotations are displayed in a numbered list. Notes are indented as block quotes, directly below the annotation to which they belong. Because the list itself is also already indented, I double the indentation as such “> > “. In Pandoc Markdown this adds extra indentation, in Github Markdown the extra “>” does not do anything, but is also not necessary since blockquotes receive a different color on Github.
This is the script:
import os
import sys
from bs4 import BeautifulSoup
args = sys.argv[1:]
if not args:
print('usage: kobo_export.py filename')
sys.exit(1)
filename = args[0]
try:
with open(filename, "r", encoding="utf-8") as f:
soup = BeautifulSoup(f, "lxml-xml")
except FileNotFoundError:
print("The annotation file was not found")
title = soup.find('title').get_text()
author = soup.find('creator').get_text()
publisher = soup.find('publisher').get_text()
annotations = soup.find_all('annotation')
# YAML metadata
metadata ="""---
title: {}
author: {}
publisher: {}
---
""".format(title, author, publisher)
export = []
export.append(metadata)
for i, annotation in enumerate(annotations):
date = annotation.date.get_text()
citation = annotation.target.find('text').get_text()
export.append('{}. "{}" ({})\n\n'.format(i,citation, date))
note = annotation.content.find('text')
if note:
export.append('> > ' + note.get_text() + "\n\n")
with open(filename + ".md", "w", encoding="utf-8") as output:
output.writelines(export)
The result looks good in plain text, on Github as well as a pdf when produced from the Markdown with pandoc. Consider these extracted annotations from Emil Cioran’s very gloomy youth work:
Plain text ¶
---
title: On the Heights of Despair
author: E. M. Cioran
publisher:
---
0. "In illness, death is always already in life. Genuine ailment links us to
metaphysical realities which the healthy, average man cannot understand. Young
people talk of death as external to life. But when an illness hits them with
full power, all the illusions and seductions of youth disappear. In this world,
the only genuine agonies are those sprung from illness. " (2019-08-26T11:46:10Z)
...
6. "The vulgar interpretation of universality calls it a phenomenon of quantitative
expansion rather than a qualitatively rich containment." (2019-08-23T10:19:09Z)
7. "Each subjective existence is absolute to itself. For this reason each man lives
as if he were the center of the universe or the center of history. Then how could
his suffering fail to be absolute? I cannot understand another's suffering in
order to diminish my own. " (2019-08-24T08:21:54Z)
8. "One of the greatest delusions
of the average man is to forget that life is death's prisoner." (2019-08-26T11:38:32Z)
...
36. "The melancholy look is expressionless, without
perspective. " (2019-08-31T07:28:00Z)
> > De afwezige blik in het oneindige externaliseert de ruimtelijkheid
die volgens Cioran intern bij de melancholie hoort
37. "The sharper our consciousness of the world's infinity,
the more acute our awareness of our own finitude" (2019-08-31T07:29:48Z)
Github ¶
See this gist.
Pdf through LaTeX ¶
Dynamic BibTeX bibliography paths with spaces
Although LaTeX is amazing in many aspects, I often encounter relatively small issues that somehow take way too long to fix. Today I encountered a very specific use case that gave me a headache, and I want to write up my solution so I never have to think about it again.
The scenario ¶
I’m currently working on my bachelor thesis for Artificial Intelligence, which is due in a week, so I have no time to waste.
My thesis lives in a github repo, so that I always have my latest work available depending on whether I work from my laptop running Arch Linux, or from my desktop running MS Windows.
My bibliography file is also saved in that repo, so loading the bibliography file from LaTeX is as trivial as \bibliography{thesis}, which loads the file called thesis.bib.
However…
I’m using Mendeley as my reference manager, and in the past exported a group of references manually to a bib file.
However, currently I’m updating my references very frequently so that manual copying becomes an annoyance.
It turns out that Mendeley has a BibTeX synchronization option that keeps bib files up to date automatically.
You can either synchronize one bib file for your whole bibliography, or create a bib file per group of references.
The latter option is appropriate for me, because I grouped together all references for my thesis.
Unfortunately, you cannot choose an export folder per group.
Instead, all bib files will be exported to a single directory.
It does not make any sense to store all my bib files in the repository for my thesis, so I had to put the folder somewhere else on my system.
This is where the trouble starts. This situation created two issues for me.
- Because the bibliography file now lives outside the repository on my desktop, I would not have access to it on my Linux laptop without manually copying files again.
- I now have to provide a path, but both my Windows path and the Mendeley export files contain spaces in them.
Solutions ¶
In order to solve the first issue, I loaded \usepackage{ifplatform}.
This allows LaTeX to do an operating system check.
But in order to do so, you need to give the compiler explicit access to your shell through a shell-escape.
I did so with the following command:
pdflatex -shell-escape -job-name="thesis" master.tex
The idea is that I will specify the bibliography path both for my Windows and Linux system within a conditional, so that I can work on my TeX files from both systems without having to adjust anything.
Solving the second issue was a pain. I had a lot of trouble making LaTeX deal with spaces in my Windows path. This issue never occurred before because I can straightforwardly use relative paths that are completely contained within my repo and thus do not point to different directories on different systems. Ultimately I found a solution that worked. If you want to get around spaces in LaTeX on Windows, either 1) rename whatever contains the space, 2) use a legacy DOS path.
In order to get the DOS variant of your path, you have to open your command prompt (not PowerShell, it seems), and run dir /x.
Do this for all folders that contain spaces, as this path representation does not contain any spaces.
These paths however do contain ‘~’, which you need to escape with \string.
Combining these two fixes produced the following solution:
\ifwindows
\bibliography{C:/Users/EDWINW\string~1/Bib/ARTIFI\string~2}
\fi
\iflinux
% the bib command for linux
\fi
The Windows-style corresponding path was C:\Users\Edwin Wenink\Bib\Artificial Intelligence-Bachelor Thesis.
(Note how that also uses ‘' instead, which is annoying because that is an escape sequence in LaTeX.
Okay granted, the easier solution would have been to go for option 1 by making Mendeley not export any spaces and then still go for relative paths… But that is a statement by Captain hindsight.
What I would have done ideally, is simply make a reference to my home folder with ~ like you would do on Unix based systems, but LaTeX doesn’t support that feature and I could not find a quick hack.
Let me know if you do!
This domain joined the IndieWeb!
I joined the IndieWeb!
What does that mean? For the long version, I recommend reading An Introduction to the IndieWeb. Here is a super short version:
- This web domain now is my main online identity, and I can use my domain as a way of authentication with a) “rel=me” links b) and my domain name via IndieAuth
Examples:
1a: I was invited to the Mastodon instance of @arjen and verified my identity as “Edwin Wenink” by linking from Mastodon to my domain, and then from my domain to Mastodon as such: < a rel=“me” href=" https://idf.social/@edwin"Mastodon></ a>. IndieWeb applications look at these “rel=me” links as an identity claim, and can confirm that these two domains point to each other. As a result, you can see my domain with a green check mark on my profile.
1b. I logged in with my domain name on webmention.io using IndieAuth. Because my domain and GitHub were linked through “rel=me” links, I could authenticate using GitHub, while using my domain name instead of GitHub credentials.
My content now follows the microformats2 format, which allows other members of the IndieWeb and related applications to find and parse my content and my online identity in a unified manner.
I can POSSE content to other sites if I want to, and feed responses back into my own website using webmention.io. POSSE simply means that you publish everything on your own website, and “syndicate” a linked copy to other places. This can be done in such a way that the responses to your copied post on that other website are fed back into your own website again through “webmentions”. This thus facilitates all kinds of interaction with social platforms or other blogs without leaving my own website. Most importantly, contra usual social networks, all data of this interaction is controlled through my own domain, collected in one place, belonging to and shaping a sensible online identity.
In principle this interaction requires that other services also follow IndieWeb standards, but luckily there are services such as bridgy that are able to translate e.g. tweets into “webmentions” following the microformats2 format. You can either handle these webmentions yourself in order to display them on your website, or let another service handle the webmentions. I do the latter since I have a static website.
So for example, let’s assume there exists a possible world in which I would tweet. Then I could post tweets from my own website by POSSEing the tweets, feeding back the responses to webmentions.io with bridgy, and maintain all my tweets including responses, even if Twitter goes bankrupt or becomes super evil. I could for example also post comments on GitHub pull requests on my own website, and then syndicate them to the appropriate place on GitHub. There is even a bridgy for federated networks.
To setup everything, I simply followed the steps of indiewebify.me, the sole purpose of which is to help you make the transition easily. Most of it is relatively straightforward if you read up on the underlying principles, but I have to admit I got lost in the IndieWeb wiki at least four times before getting the point and finding the right links. So I hope this post provides some pointers if you are interested.
To interact with the webmention.io API in order to show webmentions under this post, I used this JavaScript gist. What’s also very nice is that I can subscribe to an RSS feed of webmentions coming in, so I keep up to date about responses to my website in real-time.
There’s still much to learn for me, but my website now fulfills the minimum requirements to be part of the IndieWeb. But a more interesting question is perhaps: What does this mean all mean for you?
It means that you can now, in addition to my not-so-regular “regular” comment system, react here to my posts through your own service. As long as your reaction follows microformats2, it can be displayed directly under this post. In contrast to my normal comments, which I store on my own domain, the reply will thus live on your own social network/site/domain. I could of course decide to maintain a repository of copies of responses, but nevertheless you maintain your authority over your data on your own domain. What you see now under my post is merely a link pointing to your response, without any reference to a central repository. In this way a decentralized interaction between individual personal websites takes shape, which can be the basis of a network of federated conversations.
Isn’t that how the web was supposed to be? Really a web.
If you make your website IndieWeb compatible, let me know below through a “webmention”. You can submit your reaction to be displayed by filling in the URL of your reaction (again: look at microformats2). You can see an example reaction here, which is linked below in the brand new “Webmentions” section. To conclude, I added some useful links on my blogroll.
Vacancy Recommender Hackaton with Spark
BigData Republic organized a small hackathon for the Big Data course I currently follow at university. The challenge was to build a job recommendation system using real data from one of their clients, RandStad, which is a big employment agency. To my surprise, I ended up with the highest score and went home with a nice book as a prize. I was fully convinced that the score I achieved was very low, and I know for a fact that the road to victory had way less to do with intelligence than with strategic pragmatism. I will not share the Spark notebook itself, as the data we worked with is not open and much of the code was already provided by BigData Republic. Nevertheless I did gain some insights that I would like to share.
The challenge ¶
Employment agencies such as RandStad want to show customers looking for a job the most relevant vacancies, given their preferences. The challenge for this hackathon was to build a recommender system that predicts a top 15 of vacancies, that can be shown to the user.
Data ¶
All data was anonymized.
- A dataset containing information about the behavior of clients in the webinterface of RandStad. It stores whether users opened a particular vacancy, started an application or finished a vacancy, alongside further information about that vacancy, such as how many hours per week it is, the wage per hour etc.
- A dataset of user profiles storing user preferences, such as the desired wage, minimum and maximum working hours, and maximum travel distance.
- A dataset of vacancies, of which we will make a selection for recommendation.
Architecture of the solution ¶
The basic model used for recommendation is Collaborative filtering using alternating least squares.
There are two basic ingredients for this type of recommendation systems:
We have some data of users using some items, e.g. buying products in a supermarket. We can represent this in a user-item matrix. However, most users do not buy all items, and most items are not bought by all users, so this matrix is sparse, i.e. mostly filled with zero-entries.
We thus need some way to associate users with products they didn’t buy yet so we can potentially recommend those products, based on the knowledge we already have of user preferences for particular products. In other words, zero-entries need to be filled in with a preference estimation. The Collaborative Filtering with ALS technique does this through finding a factorization of the user-item matrix into two matrices with lower dimensions, that map users onto a number of latent factors (a “user profile”), and these latent factors back unto the items (an “item profile”). With ALS one tries to find two matrices that approximate the bigger input matrix when they are multiplied with each other. Based on these smaller estimated matrices with latent factors, it is possible to re-compute the user-item association matrix, which now has preference scores for items that previously had zero-entries.
To implement this model in Spark, there are two major things to take into consideration:
Implicit versus explicit feedback ¶
Preferences of users for particular products can be explicit, for example when you ask users to rate the products they buy on a scale from 1 to 10 in a questionnaire. However, one can also have an implicit measure of preferences. If for example a particular customer very often buys cucumbers, we can infer from that that user has a preference for cucumbers, even though we do not have an explicit normalized rating of cucumbers.
When it comes to Big Data, it is more likely that you have implicit preference data at your disposal. In the case of this hackathon, the indirect information we have of customer preference is a log of what vacancies users click on in the vacancy search machine of RandStad. If users click more on a particular type of vacancy, e.g. for management functions, we can infer this user prefers management functions, rather than for example being a cashier in a supermarket.
Cold-start problem ¶
Another challenge for this setup is the so-called cold start problem. Computing an user-item association matrix for a given set of users and items is computationally quite expensive. But in the case of a big employment agency, new job vacancies come in continuously. Unless you retrain the whole model, you then cannot recommend these new vacancies, which obviously is very undesirable. At the same time, it is prohibitive to continuously redo all your work to include these vacancies in real-time.
The workaround suggested by the people from BigData Republic and used in this hackathon, is to not train the recommendation model on user-vacancy preferences, but instead on user-function preferences. This is a good solution because function titles are not as volatile as individual vacancy descriptions. In other words, if a new vacancy comes in, we already know the preference of a user for that function title, because the ALS model is trained on many other vacancies with the same function description.
We thus end up with a model like this (written in Scala):
val als = new ALS()
.setMaxIter(20)
.setRegParam(0.001)
.setRank(10)
.setUserCol("candidate_number")
.setItemCol("function_index")
.setRatingCol("rating")
.setImplicitPrefs(true)
val model = als.fit(grouped_train)
grouped_train is the data of user clicks where vacancies are grouped under their function name.
Recommending vacancies ¶
But given that basic model, we have a recommendation score for functions, and not vacancies. If we take the top 3 preferred functions for a user, and then join all vacancies on these function descriptions, then we end up with a very large list of recommended vacancies for a user.
Therefore the rest of the work in the hackathon was to come up with a good way of selecting a top 15 in this long list of vacancies. This is done by joining in profile data containing further user preferences such as the desired wage, working times, and maximum traveling distance. Based on that information you can either filter out vacancies, or integrate these preferences in a final weighted recommendation score.
The end result of this whole process is a top 15 of vacancies to first display to the end user.
Parameter optimization, weighing factors for a final prediction ¶
Everyone used the same general approach with the ALS model, so what distinguished my solution from others where 1) model parameters and 2) further scoring and processing of vacancies based on profile data.
This is where the hackathon really started feeling “hacky” to me.
A major practical limitation was that I was running a Spark notebook on a real-life data problem, within docker, on an old ThinkPad with limited computing power and memory. This effectively resulted in the Spark notebook kernel dying on me regularly, so running the whole data pipeline even once was quite a hassle. Using fancy techniques to search for optimal parameter settings where thus out of the question for me, and I had to resort to playing around with parameters manually.
Especially because running the whole process took a while, I really wanted to be smart about what parameter combinations I tried out. But the somewhat disappointing answer (not a bad answer though) I got from one of the BigData Republic people was that there were no very specific rules of thumb, for example for choosing the amount of latent factors in the ALS model. Normally, instead of having 12Gb of working memory, similar Spark code would be run on a cluster with 1TB of working memory… which allows automated search for the best parameter settings.
From there on pragmatism took over. With respect to model parameters, the adagium “higher is better” did not hold for me, first of all because it made my pc crash, and secondly because the risk of overfitting on the training data became larger. So w.r.t default ALS paramaters, I actually only lowered them: less iterations and less latent factors in the matrix factorization.
The largest improvement in my final score was achieved by using profile data and weighing various factors differently. We computed a score for whether the vacancy matched the preferred working hours or not, and a normalized score for how far away the job is from the candidate. These factors, together with the recommendation score for the function title of a particular vacancy, were weighed together to produce a final score per vacancy. It turned out that people care a lot about how far the job is, and I gave this factor a very big weight of 10:1 compared to the recommendation score for the actual function title (but note that only vacancies for the top 3 function descriptions were taken into account, so the ALS model already fulfilled its purpose).
Result and reflection ¶
The final score for the competition was a very simple recall measure, i.e. what percentage of the vacancies candidates actually applied for (can be extracted from the dataset of browsing behavior) was recommended in the top 15 vacancies by the recommendation model. My final recall score on a test set was 16.8% (19.8% on the validation set). A baseline performance of 2.9% for comparison was calculated by always predicting the 15 most popular vacancies.
I thought my score was pretty low (and I’m sure it is) so I was very surprised to win, but given that all competitors were beginners and faced similar hardware issues as I did, the playing field of recall scores was more or less between 13-17%. People with more interesting ideas about parameter optimization where probably not successful in their efforts due to serious hardware limitations. Perhaps people also put more effort in optimizing their ALS model, only to see it overfit on the training data and really drop in score on the test data. The overall impression I am left with, is that real data science is extremely hard to do properly. For the mortals not designing the algorithms and data structures themselves, the most intelligence is required for choosing the right methods for the problem at hand, and making smart design decisions on what information to exploit. But apart from that, I have the feeling that the average attitude is: please don’t ask too about the internals of the algorithms or the meaning of a parameter setting. I suspect that for many people in the data business “data science/engineering” is mostly slapping together pre-existing models and making computers crunch a lot on optimizing them.
Tools used ¶
- Docker
- Scala
- Spark ML
- Spark Dataframes
- Spark SQL
- My poor old ThinkPad