On politics

As a scientist, in principle, you are curious, but comfortable with not knowing. you wait until scientists find ways to unlock nature’s mysteries. you try to do it yourself as well. You may build theories but you wait for the data, or you search for them, that will be meticulously mined from nature and prove a theory or not. you don’t let yourself slip into fantasies, like God(s) and Satan(s), just to fill in the gaps. Same if you are researching the behavior, mind and brain of the people, as eg a neuroscientist. Underneath this behavior though is your belief that nature doesn’t lie, it has no intention to hide itself, it is under your control, and if it lies you have a way and you are free to use it in order to understand it. So you wait without knowing, actively researching. someday maybe you know or maybe you won’t, it’s fine, no one is hurt, at least because of waiting.

What happens now though when your under research system lies, you can’t get data, you can’t control it, it tries to stop you and silence you when you try to understand it, and in the mean time it does horrors that you witness day after day?

This is the state of the system that we are trying to understand today, as human beings, but you happen also to be a scientist.

You could wait until it decides to show you itself, but you know this won’t happen. You could be ok with it, but waiting hurts defenseless people and yourself with which you are not ok.

Like in the COVID era, you could tell that it was an international subjugation of people, but as a scientist you knew that knowledge takes time, makes mistakes and you waited for the vaccine to be found by scientists. Because with the vaccine people would be protected, and lives would be saved. So you were patient and accepted the to be short-term subjugation. Again you were assuming that people overall actually cared about people’s lives. Well, this ship has already sailed.

When it comes to politics, as a system you want to understand, you see that lying is its basis and not only it openly withholds data and information, but goes after you if you try to make sense of it. In this case you can’t wait for the data, they won’t allow you to have all the data. You could wait until the rich and powerful decide to expose themselves but you know that this won’t happen. You could be ok with being in the dark, as you are used to as a scientist, but your moral self doesn’t let you sleep at night.

This is when morality hits the scientist and makes her wonder what she can do.

So what can you do? You can’t have data and as a moral human being you feel the pressure of exposing the truth and protecting defenseless victims, like children and oppressed people. Waiting won’t change anything, it will only make it worse. You can’t afford to wait, you try to understand with whatever you have at your disposal, regarding data and tools.

What are the tools that you can use on the little scrambled data you have?

Again, as in history that I was saying earlier, our last resort is to study it at its interface, with human psychology and analyzing language. For example, who compares food with human flesh? Who finds funny to simulate sacrificing a baby to a devil? How can you walk a jerky beef?
and so on.

On history

An important and pressing question, that comes from philosophy of history, is how do we discern facts from narrative and propaganda.

How do we know that what Herodotus and Thucydides to today historians and media are saying has actually happened?

It’s not about the physical findings, those are also made by people as stories are made by people. History is like fiction. And as we are living deeper into the AI digital world, it will be harder to tell what really happened.

Then, only nature changes, those beyond human control, are the only objective indicators? Sadly, this doesn’t tell us much.

I see that maybe the only way to tell fiction from history is via understanding human psychology within context. The way language is used, who and when is using it, and in which context, is what matters.

For example, when the NYT write “Gazans are starving” and “Palestinians bombed Israel”, they may think that they serve the Zionist propaganda, but they don’t realize that they fall into contradiction which can be detected. When the perpetrators say we are ashamed of what we did, they most probably did it. Things said in private and confidentially, like in the Epstein files, are likely to be true. and so on.

So maybe this is the only promising method for discerning facts from narrative and propaganda, as long as there are people willing to meticulously do it.

On religion

Even the holy books must be rewritten. Is it possible for Judaism to get rid of Jewish Supremacy? for Christianity and Islam to get rid of Men Superiority? Either religions will adapt to human and animal rights or they must all vanish.

You don’t need religion, their stories, their rituals and the communities they build to believe in God, or Gods. Believing is a personal human right. Religions’ only function is to create groups distinguished to others which inevitably promotes racism. With the absurd aftereffect of the non religious, secular Jews, and secular Christians, just in order to belong in a distinguished community.

And we don’t need God(s) to be moral. On the contrary, we see over and over again how immoral religious people are.

It really amazes me how it is 2026 (even this number is religion based) and we are still talking about religions, and worse: we can’t talk about religions. Humanity hasn’t advanced yet as much as we think it has.

How is it that all these VIP “intellectuals” turn out to be so stupid, with such “poor judgment”, as they or their friends say after they have been exposed to be associated with the largest in history international human trafficking and farming ring?

It makes you think of what we haven’t talked about enough that lies in the heart of epistemology. The sociology of knowledge. How is it that throughout history mostly famous in the realm of thinking and knowledge are men, and why some specific ones? Is it because what they say is indeed so deep, unique, and important for humanity or is it the result of the privilege of attention and money from their associates with similar privileges, and the structures they build, apparently based on the abuse, oppression of women and the burial of their thoughts?

Could it be that what it is true is what it is agreed to be true by those who are heard and paid attention to? If you observe the history of thinking and knowledge there is not much of novelty. Core ideas are reiterated every few generations in a different language and context, presented as new.

Their voices are heard and they enjoy fame that comes from associations and their position in the thinking network. Enterprises, funded and associated by abusers, like edge.org of John Brockman, “Closer to the truth” of Robert Kuhn, pouring money and attention, claim to know what’s profound and worthy of being heard, and it is reinforced by those who want to be in their ranks, accepting it like a herd, driven by their ambition.

If we really want to get closer to the “truth” we need to liberate ourselves from admiring persons over ideas and from lusting to be admired.

How do we do that? The big obstacle is resources. It is indeed very hard to engage in deep thinking and research when you are struggling for survival and when you are taking care of others. You need time, free of distractions, to do that. Funding brings admiration, admiration brings funding. Our academic structures promote the “publish or perish” mechanism, leading to accumulation of money and fame in a few, ie academic capitalism, and all others trying to become like them. How can this change? One first thought is by democratizing thinking. Thinking cannot be a privilege of the few. Sure, everybody thinks, but the question is what makes someone to be heard and be part of the discussion. Academic Elites and VIPs limit human advance in knowledge and understanding of the world and life.

First thing is to stop being impressed by names. Second, to grant access to resources to anyone who is willing to put the time and energy on knowledge pursuit, like a public good, after a proper public education. Third have horizontal platforms where their thoughts and work are presented and easily searched and discussed. Something like what is happening with the social media, but maybe less chaotic. What else?

–

Men have been trained to be the mentally weak sex.

By weakness I mean the underdevelopment of morality, empathy, and the inability to understand the ethical implications of one’s actions.

Boys grow up in social environments that grant them early on entitlement to power over girls, children, women and vulnerable groups. It is not that they are biologically incapable of empathy or moral understanding. It is that these capacities are not cultivated with the same urgency. Instead, dominance and entitlement are cultivated by one generation of men to the next. It has become a cultural avalanche.

Girls, on the other hand, are typically trained from early on to be considerate, emotionally attentive, accommodating, and ethically alert.

Empathy and moral reflection are mislabeled as weakness. This is a profound mistake.

Societies do not remain stable through dominance. They remain stable through trust, safety, and mutual recognition, through development of moral capacities. What is called “soft” is in fact structurally foundational.

For long term change to occur, moral and emotional development must become central in the upbringing of boys as well. We need to cultivate empathy, accountability, and ethical reflection as essential strengths.

Women, who have long carried the work of relational and ethical maintenance, are in the position to reshape these conditions, to transform the standards by which maturity itself is defined.

What is needed is a shift of our value system: Weakness = moral underdevelopment, empathy = structural societal strength. In the short term it falls on the shoulders of women to fight for it.

We are used to think that in order for women to rise in power hierarchy need to fit in male created environments, to become like them: dominant and abusive. We see this often, in many fields. I’ve seen this a lot in academia. But it is not the sustainable way. We don’t need to fit in men’s environment, we need to change the environment.

The term “inclusion” that has been used a lot in the recent past in many industrial, academic and other environments is a deeply misleading and offensive term. We don’t need to be included. Included where? By whom? It is our world as it is theirs.
We demand to co-create it.

This evening I was at the debate of the Philosophy of Deep Learning conference “Do large language models need sensory grounding for meaning and understanding?” organized by NYU and Columbia, held at the NYU Cantor Film Center in NYC. The recording of the meeting will be soon online.

The debate ended before I got to ask my question, so I thought of writing it here, which I hope will also help me to clarify it in my mind. The debate was especially interesting to me because many years ago, back in 2011, I wondered whether someone could think without sensory input. At that time, in my naivety, I didn’t know that others were wondering about that way before I was born, nor I was expecting to go in a few years to a debate about that in NYC, organized by NYU and Columbia (:o).

While listening to the debate, a question bothered my mind:

How helpful or impeding is the fact that we are using our experience to answer the question of whether a system, different from ours, has a sense of understanding? Aren’t human language models extensions of our minds? We are using our experience and sense of understanding to look for it in the language model. For example, we use our experience of the color red to feed it into the system. And say, we get to a point where we are convinced that it understands language the way we do - with or without sensory grounding. Does this mean that the model understands our language or does it mean that we think that it does because it behaves in the way we do when we understand our language? Is it possible to know the difference, and how? Languages come in many forms. Let’s assume that we are extinct and aliens find the same text data that we have used and will use to train our language models to the extent that we are convinced that they understand human language. Could they -who lack the same sensory experience and sense of understanding as us- tell whether the language models understand the language they are trained on? Or to put it differently.. and more pragmatically, we are not the only species that use language. Other primates, such as marmosets, use language (see this presentation I gave in 2017 on monkey talk for more info). First, it is still unresolved the decoding of their language, and I’d be very interested to see progress on this front. But, can we decode it? Or else, can a large language model trained on marmoset language (auditory) data understand their language? Could we tell whether it has achieved it? Or only a marmoset can tell whether a language model trained on marmoset language data understands marmosets’ language? If we are bound to the way we understand language, how much of the understanding goes to the language model, and how much to us; are they different?

before closing, let me give a couple of remarks on the debate, in case someone finds them useful for future debates..

• I missed a clear definition of what understanding is and how we can tell whether a system has it. How can we answer the question of whether a large language model requires sensory grounding for understanding if we don’t know what we are looking for and how?
• that applies in all talks: f you want to pass along a message, do not fill up your slides with lots of text that you are not reading out loud, or a lot of information that you are not addressing. It is not only pointless to give the talk if people cannot follow what you are saying, but also frustrating.
• it didn’t feel like it was a debate, but rather like independent talks on a similar subject. To increase interaction between the speakers and create the sense of a debate it would maybe be helpful to give a guideline to the speakers before they prepare their slides. The guideline could be a list of questions that the speakers need to address so that there is interaction.
• it was nice that there was online streaming of the event, but it would have been even nicer if it were interactive, where the online audience could also ask a question (with priority to those in person).

όπως και άλλα προγένεστερα πρόσφατα άρθρα όπως αυτό περί της σημαντικότητας της θεωρητικής νευροεπιστήμης (https://academic.oup.com/nsr/article/7/9/1418/5856589)

Στα επόμενα αναπτυξιακά στάδια θα ανακαλύψει τη θέση της στον κόσμο, όταν αναγνωρίσει τη σημαντικότητα της αλληλεπίδρασης της με τη φιλοσοφία. Αυτό ισχύει για όλες τις επιστήμες. Αυτο θα γίνει όταν περάσουμε από την υπερεξειδίκευση στην αντίληψη του πλαισίου δράσης εκάστοτε επιστήμης, της αλληλοεπικάληψης και αλληλοσυμπλήρωσής τους, καθώς και της θέσης τους στην κοινωνία. Σήμερα όλο και περισσότερες επιστήμονες οδεύουν προς αυτήν την διαπίστωση και έχουν αρχίσει να γίνονται βήματα προς αυτήν την κατεύθυνση.

Θυμάμαι να λέω σε συναδέλφους στο εργαστήριο για φιλοσοφία και δε με έπαιρναν στα σοβαρά. Όταν άρχισαν να βγαίνουν άρθρα σχετικά (όπως πχ αυτό (https://www.pnas.org/doi/epdf/10.1073/pnas.1900357116_) άρχισαν να το ξανασκέφτονται. Σήμερα ακόμα και αυτοί που μου λέγανε “εγώ είμαι υπερ του σκάσε και υπόλογισε” τώρα μου λένε ότι θέλουν να μάθουν περισσότερα για φιλοσοφία.

Δεδομένης της ιλιγγιώδους ανάπτυξης της τεχνητής νοημοσύνης και της αμήχανης θέσης στην οποία μας φέρνει, η εξελίξη των επιστημών, και δη της θεωρητικής νευροεπιστήμης, σε αυτά τα επόμενα στάδια είναι αναπόφευκτη ανάγκη.

Deep learning models exhibit astounding intellectual capacity. Their responses demonstrate that they possess several cognitive functions, such as attention, working memory, cognitive inhibition, decision making and reasoning. Additionally, they exhibit flexibility in their reasoning and in their use of language to express this. Having artificial systems with cognitive capacities can reveal aspects of human cognition that would otherwise be difficult to study. Artificial neural networks can help explore how cognitive representations and processes are implemented by neural circuits in the brain: they can provide insights that are technically prohibitive to garner from experiments, and they can help develop and evaluate entire spectra of biologically plausible and implausible neuro-computational mechanisms of cognitive function. Furthermore, increasingly, artificial neural systems can surpass human cognition, showing us its limitations as well as its unexplored possibilities.

However, artificial neural networks, like deep learning models, still lack certain fundamental human cognitive capacities. We would like to highlight capacities that pertain to a fundamental cognitive function, namely knowledge acquisition. For example, humans often rely on meta-cognition and creativity to generate novel insights and acquire knowledge. When told we have made an error in a mathematical computation, we are able to identify why we made that mis-calculation. This meta-cognitive process is central to refining and improving our knowledge base. The existence of an entire mathematical system built from imaginary numbers underscores another uniquely human ability to create concepts that lie outside the distribution of natural experience. To reach human-level cognition, deep learning systems would need to be originally creative, which is a capacity that is challenging to possess for systems that acquire knowledge solely within the distribution of the data they are trained on, such as deep learning systems. Thinking outside of the data is difficult to achieve in an artificial system.

Another example pertains to the acquisition of knowledge, via the distribution of the training data. While deep learning models are remarkably adept at learning from massive text corpi, the knowledge they extract therefrom is limited by the expressive power of language. The acquisition of human knowledge requires a medium of communication, language, together with human-like experience to contextualize what is being communicated. Otherwise, the acquired knowledge is limited by the expressive power of the medium alone. Language is itself insufficient to completely capture human experience. We argue that a system trained on language, but which by-passes experience, cannot genuinely understand it. When asked why a human should be happy, chatGPT, the most advanced language model today, responds with a list of utilitarian reasons. Yet, it fails to mention the most experiential aspect of happiness - it is a positive and therefore desirable experience to have. This inability to reason through a fundamentally experiential aspect of emotion highlights a failure of the system to understand what it means to be human.

Another way we see that deep learning systems do not genuinely understand what they have been trained on, is by examining its reasoning through logic. For instance, if you ask chatGPT whether the sentence “Aristotle is a feeling” is correct, it will answer no. Based on the data it is trained on, men do not appear as feelings. However if you present chatGPT with a valid argument like “Aristotle is happy, happy is a feeling, Aristotle is a feeling”, it reasons that the syllogism is wrong because Aristotle cannot be a feeling. This is a clear conflation of what is objectively correct (through syllogism) based on its own training data, and what is subjectively wrong (Aristotle is a feeling) also according to its own training data. We argue that a lack of experience can result in such conflations.

Accumulated experience over the course of our lives provides us with the capacity to understand language. Meta-cognition and creativity afford us the capacity to reason within and beyond our experience. Deep learning systems lack human-like experience, as well as the cognitive functions to reason within and beyond it,, which stymies their ability to genuinely acquire knowledge and achieve human-like cognition. And it is not yet straightforward how they can do so otherwise.

September 24th was National Postdoc Appreciation week. What a bad joke or a sadist’s idea.
We know that postdocs —post-doctoral researchers— are the workhorses of science, especially in the life sciences.
But at what cost?

Let me, an almost 7 years postdoc, tell you something about it. To start with, it doesn’t make sense to have a specific working category for something that is so generic. Anyone who has finished their doctorate is technically a postdoc. Professors are postdocs. Associate Professors are postdocs. Yet, here they are, the postdoctoral researchers who are just postdocs. Why?

The poor working conditions for postdocs has long been an open secret, but the Covid era brought it to the surface. Article after article has pointed out the pressure postdocs face due to their bad working conditions. A 2020 survey in Nature confirmed it. To be fair, for some postdocs it works out well, but not for everybody; exactly not for the 90% of them. That’s right, only 10% of postdocs survive the Academic arena.

First and foremost, it is the uncertainty. Postdocs only get contracts for a year or two — usually in another country or even continent, because mobility is good for the CV. Postdocs enter the elastic middle between a Ph.D. and a faculty position until they are frustrated or drained enough to leave. Also, just a few years of postdoc are considered too few, yet many years too much. You need to find the sweet spot to get a faculty position before you are considered expired.

Then there is the low pay, especially in comparison to industry; the lack of benefits, such as child-care, and parental leave; the indignation due to biases that only accumulates as years pass; the fierce competition; the power imbalance; and the under-appreciation and being treated as a trainee.

Why postdocs are called trainees, I still don’t understand. Postdocs are doing the research; bringing ideas for new projects; teaching classes; mentoring students; and writing grants. Meanwhile, their bosses, the heads of the lab, or else the principal investigators (PIs), do little more than management. The PIs get most of the credit and build their careers on the shoulders of their consumable trainees. Yes, of course, postdocs learn a lot. But one always learns, and they could be learning while they have a secure independent job — like as a PI.

Postdocs must end. How?

If graduate students stop applying for a postdoc position, PIs stop hiring them, grants and especially Faculty positions stop requiring them. PhD students can instead apply for jobs as faculty, independent researchers, or for a grant of their own. At the same time, we must stop building empires around a PI, but instead create cooperative working environments where peers do research together and learn from each other.

Of course, this shouldn’t prevent students from doing a Ph.D. Doing a Ph.D evolves oneself and benefits society. It cultivates critical thinking and produces high-skilled specialized community members. But why go on to waste the most creative and motivating years of your life only to be disappointed and end up doing something that you could be doing much earlier while being mentally healthy?

So next year in September please do not appreciate the postdocs. Do something to end them.

Πήγα μόνη διακοπές σε νησί στην Καραϊβική, πρώτη φορά, σε κάμπινγκ, και δεν έπαθα τίποτα –εκτός από το κάψιμο, την κούραση και τον πανικό την 1η νύχτα στο απομονωμένο κάμπινγκ μέσα στο εθνικό πάρκο μέχρι να μάθω τι ζώα έχει–

σε όποιον μιλούσα εντυπωσιαζόταν όταν έλεγα πως ήρθα μόνη και μένω στο κάμπινγκ πάνω στο βουνό και παρόλο το “ρίσκο” να είμαι στο ταξί ή με ωτοστόπ μόνη στις ερημιές, ήταν όλοι τους κύριοι. Γιατί δε θα έφταιγε το ότι ταξίδευα μόνη, αλλά το ότι αυτοί θα ήταν βιαστές και δολοφόνοι.

Όταν μου έλεγαν ότι είμαι θαρραλέα τους έλεγα “μπα αυτό δεν είναι τίποτα, φαντάσου να πήγαινα σε νησί στην Ελλάδα με το αγόρι”. Ποιος ξέρει σε ποιο χαντάκι θα με βρίσκανε.

Γιατί δε θέλω να είμαι θαρραλέα, θέλω να είμαι ελεύθερη.

Νέα Υόρκη, 19 Ιουλίου 2021

Let us suppose that there is a man in an isolated environment.* There is nothing to see by vision, nothing to feel by tactition, nothing to hear by audition, nothing to smell by olfaction and nothing to taste by gustation. Would this man be able to feel temperature, happiness, pain, hope, love, etc.? Would he be self-aware? Certainly other senses and feelings are dependent of the so called the traditional five senses. But, could they exist independently? Due to memory and the functional development of his brain until the moment we remove him from normal conditions, they could. As they do exist in normal conditions, during the so called resting state. But again, what is that makes us recall, think, imagine? And, if he were in a such isolated system, without ever being exposed to any external stimulus, from the first moment of his existence, could they? And, if they could, what would this mean? That the stimulus is internal coming from the mind? meaning that mind is beyond, although related to, the brain? What is that would make the neurons fire?

*of course in order for the person to be alive, oxygen and nutrients are needed. Thus, the environment can not be totally isolated. But, let us suppose that we could provide these supplies in the most non-interactive way.

Η λογική ενός παράλογου μυαλού είναι πιο λογική από τον παραλογισμό ενός λογικού ακόμη και αν για τον παράλογο είναι απολύτως λογικός, μιας και η απόλυτη λογική είναι παραλογισμός.

The logic of an irrational mind is more logical than the irrationality of a logical one even if for the irrational mind it is absolutely logical, since absolute logic is irrational.