The Impossibility Conjecture of Humanoid Artificial Intelligence and the Non-Benign Singularity

Abstract

[A Rough Draft of a Work-in-progress.]

The idea of machines which are almost identical to human beings has been so seductive that it has captured the imaginations of the best minds as well as laypeople for at least a century and half, perhaps more. Right after Artificial Intelligence (AI) came into being, it was almost taken for granted that soon enough we will be able to build Humanoid Robots. This has also led to some serious speculation about ‘transhumanism’. So far, we do not seem to be anywhere near this goal. It may be time now to ask whether it is even possible at all. We present a set of arguments to the effect that it is impossible to create or build Humanoid Robots or Humanoid Intelligence, where the said intelligence can substitute human beings in any situation where human beings are required or exist.

1. Humanoid Intelligence, the Singularity and Transhumanism

Before we proceed to discuss the terms of the title of this section and the arguments in the following sections, we first define the foundational terms to some degree of conciseness and preciseness:

1. Human Life: Anything and everything that the full variety of human beings are capable of, both individually and collectively. This includes not just behaviour or problem solving, but the whole gamut of capabilities, emotions, desires, actions, thoughts, consciousness, conscience, empathy, creativity and so on within an individual, as well as the whole gamut of associations and relationships, and social, political and ecological structures, crafts, art and so on that can exist in a human society or societies. This is true not just at any given moment, but over the life of the planet. Perhaps it should include even spiritual experiences and ‘revelations’ or ‘delusions’, such as those hinted at in the Philip K. Dick story, Holy Quarrel [Dick et al., 1985].

2. Humanoid: A living and reproducing entity that is almost identical to humans, either with a human-like body or without it, on a different substrate (inside a computer).

3. Intelligence: Anything and everything that the full variety of human beings are capable of, both individually and collectively, as well as both synchronically and diachronically. This includes not just behaviour or problem solving, but the whole of life as defined.

4. The Singularity: The technological point at which it is possible to create (or have) intelligence that is Humanoid or better than Humanoid.

5. Transhumanism: The idea that, after the singularity, we can have a society that is far more advanced, for the better, than the current and past human societies. From 1910 to 1927, in the three volumes of Principia Mathematica [ 1925–1927], Whitehead and Russell set out to prove that mathematics is, in some significant sense, reducible to logic. This turned out to be impossible when Godel published his incompleteness theorems in 1931 [Sheppard, 2014, Nagel et al., 2001]. During the days of origins of modern Computer Science, before and in early 1930s, it would have been easy to assume that a computing machine would ultimately solve any problem at all. This also proved to be impossible with Turing’s undecidability theorem [Hopcroft et al., 2006] and the Church-Turing thesis of computability [Copeland and Shagrir, 2018]. Since then, other kinds of problem have been shown to be undecidable.

Now that we are supposed to close be enough to the Singularity [Kurzweil, 2006] so that it may happen within the lifetime of a large number of human beings, perhaps it is time to ask ourselves whether real intelligence, in particular Humanoid Intelligence (as defined above) is possible at all. We suggest that there are enough arguments to ‘prove’ (in an informal sense) that it is impossible to build, to create or to have Humanoid Intelligence. We argue that even though the Singularity is indeed possible, perhaps even very likely (unless we stop it), it may not be what it is supposed to be. The conjecture presented here is that the Singularity is not likely to be even benign, however powerful or advanced it may be. This follows from the idea of the impossibility of Humanoid Intelligence.

2 Some Notes about the Conjecture

We have not used the term theorem for the Impossibility and the reasons for this should be evident from the arguments that we present. In particular, we do not, and perhaps cannot, use formal notation for this purpose. Even the term conjecture is used in an informal sense. The usage of terms here is closer to the legal language than to the mathematical language, because that is the best that can be done here. This may be clearer from the Definition and the Story arguments. It is due to a similar reasoning that the term ‘incompleteness’ is not used and, instead, impossibility is used, which is more appropriate for our purposes here, although Godel’s term ‘essentially incomplete’ is what we are informally arguing for about Humanoid AI, and perhaps AI in general. No claim is made as to whether or not a formal proof is possible in the future at all. What we present is an informal proof. This proof has to be centred around the distinction between Micro-AI (AI at the level of an intelligent autonomous individual entity) and Macro-AI (very large intelligent autonomous systems, possibly encompassing the whole of humanity or the world). To the best of our knowledge, such a distinction has not been proposed before. While there has been some work in this direction [Brooks, 1998, Signorelli, 2018, Yampolskiy, 2020], for lack of space, we are unable to explain how this work differs from previous such works, except by noting that the argumentation and some of the terms are novel, a bit like in the case of arguments for or against the existence of God, which question has been debated by the best of philosophers again and again over millennia, which as we will see at the end, is relevant to our discussion.

3 The Arguments for the Impossibility Conjecture for Micro-AI

The Definition Argument): Even the Peano Arithmetic [Nagel et al., 2001] is based on three undefined terms (zero, number and is successor of ), which are relatively trivial terms compared to the innumerable terms required for AI (the core terms like intelligence and human, or terms like the categories of emotions, leave alone the terms like consciousness).

The Category Argument: A great deal of AI is about classifying things into categories, but most of these categories (e.g. anger, disgust, good or bad) have no scientifically defined boundaries. This is related to the following argument.

The Story Argument: It is almost established now that many of the essential concepts of our civilisation are convenient fictions or stories [Harari, 2015] and these often form categories and are used in definitions.

The Cultural Concept Argument: Many of the terms, concepts and stories are cultural constructs. They have a long history, most of which is unknown, without which they cannot be modelled.

The Individuality, or the Nature Argument: An individual intelligent autonomous entity has to be unique and distinct from all other such entities. It originates in nature and we have no conception of how it can originate in machines. We are not even sure what this individuality exactly is. However, all through history, we have assigned some degree of accountability to human individual and we have strict provisions for punishment of individuals based on this, that indicates that we believe in the concept of the ‘self’ or the ‘autonomous individual’, even when we deny its existence, as is becoming popular today.

The Genetic Determinism Argument: Individuality is not completely determined by nature (e.g. by our genes) at birth or creation once and for all. It also develops and changes constantly as it interacts with the environment, preserving its uniqueness.

The Self-organising System Argument: Human beings and the human societies are most likely self-organising [Shiva and Shiva, 2020] and organic systems, or they are complex, non-equilibrium systems [Nicolis and Prigogine, 1977]. If so, they are unlikely to be modelled for exact replication or reproduction. The Environment, or the Nurture Argument: Both intelligence and individuality depend on the environment (or on nature). Therefore, they cannot be modelled without completely modelling the environment, i.e., going for Macro-AI. The Memory, or the Personality Argument: Both intelligence and individuality are aspects of personality, which is known to be dependent on the complete life-memory (conscious and unconscious) of an intelligent being. There is not enough evidence that it is possible to recover or model this complete temporal and environmental history of memory. A lot of our memory, and therefore our individuality and personality is integrally connected with our bodily memories.

The Susbstrsate Argument: It is often taken for granted that intelligence can be separated from the substrate and planted on a different substrate. This may be a wrong assumption. Perhaps our intelligence is integrally tied with the substrate and it is not possible to separate the body from the mind, following the previous argument.

The Causality Argument: There is little progress in modelling causality. Ultimately, the cause of an event or occurrence is not one but many, perhaps even the complete history of the universe.

The Consciousness Argument: Similarly, there is no good enough theory of consciousness even for human understanding. It is very unlikely that we can completely model human consciousness, nor is there a good reason to believe that it can emerge spontaneously under the right conditions (which conditions?).

The Incompleteness/Degeneracy of Learning Source and Representation Argument: No matter how much data or knowledge we have, it will always be both incomplete and degenerate, making it impossible to completely model intelligence.

The Explainability Argument: Deep neural networks, which are the state-of-the-art for AI, have serious problems with explainability even for specific isolated problems. Without it, we cannot be sure whether our models are developing in the right direction.

The Test Incompleteness Argument: Perfect measures of performance are not available even for problems like machine translation. We have no idea what will be the overall measure of Humanoid Intelligence. It may always be incomplete and imperfect, leading to uncertainty about intelligence.

The Parasitic Machine Argument: Machines completely depend for learning on humans and on data and knowledge provided by humans. But humans express or manifest only a small part of their intelligent capability. So machines cannot completely learn from humans without first being as intelligent as humans.

The Language Argument: Human(oid) Intelligence and its modelling depend essentially on human language(s). There is no universally accepted theory of how language works.

The Perception Interpretation Argument: Learning requires perception and perception depends on interpretation (and vice-versa), which is almost as hard a problem as modelling intelligence itself.

The Replication Argument: We are facing a scientific crisis of replication even for isolated problems. How could we be sure of replication of Humanoid Intelligence, preserving individual uniqueness?

The Human-Human Espitemic Asymmetry Argument: There is widespread inequality in human society not just in terms of money and wealth, but also in terms of knowledge and its benefits. This will not only reflect in modelling, but will make modelling harder.

The Diversity Representation Argument: Humanoid Intelligence that truly works will have to model the complete diversity of human existence in all its aspects, most of which are not even known or documented. It will have to at least preserve that diversity, which is a tall order.

The Data Colonialism Argument: Data is the new oil. Those with more power, money and influence (the Materialistic Holy Trinity) can mine more data from others, without sharing their own data. This is a classic colonial situation and it will hinder the development of Humanoid Intelligence.

The Ethical-Political Argument: Given some of the arguments above, and many others such as data bias, potential for weaponisation etc., there are plenty of ethical and political reasons that have to be taken into account while developing Humanoid Intelligence. We are not sure whether they can all be fully addressed.

The Prescriptivastion Argument: It is now recognised that ‘intelligent’ technology applied at large scale not only monitors behaviour, but changes it [Zuboff, 2018]. This means we are changing the very thing we are trying to model, and thus laying down new mechanical rules for what it means to be human.

The Wish Fulfilment (or Self-fulfilling Prophecy) Argument: Due to prescriptivisation of life itself by imperfect and inadequately intelligent machines, the problem of modeling of Humanoid Intelligence becomes a self-fulfilling prophecy, where we end up modeling not human life, but some corrupted and simplified form of life that we brought into being with ‘intelligent’ machines.

The Human Intervention Argument: There is no reason to believe that Humanoid Intelligence will develop freely of its own and will not be influenced by human intervention, quite likely to further vested interests. This will cripple the development of true Humanoid Intelligence. This intervention can take the form of secrecy, financial influence (such as research funding) and legal or structural coercion.

The Deepfake Argument: Although we do not yet have truly intelligent machines, we are able to generate data through deepfakes which are not recognisable as fakes by human beings. This deepfake data is going to proliferate and will become part of the data from which the machines learn, effectively modeling not human life, but something else.

The Chain Reaction Argument (or the Law of Exponential Growth Argument): As machines become more ‘intelligent’ they affect more and more of life and change it, even before achieving true intelligence. The speed of this change will increase exponentially and it will cause a chain reaction, leading to unforeseeable consequences, necessarily affecting the modelling of Humanoid Intelligence.

4 The Implications of the Impossibility

It follows from the above arguments that Singularity at the level of Micro-AI is impossible. In trying to achieve that, and to address the above arguments, the only possible outcome is some kind of Singularly at Macro-AI level. Such a Singularity will not lead to replication of human intelligence or its enhancement, but something totally different. It will, most probably, lead to extinction (or at least subservience, servitude) of human intelligence. To achieve just Humanoid Intelligence (Human Individual Micro-AI), even if nothing more, the AI system required will have to be nothing short of the common notion of a Single Supreme God. Singularity at the macro level will actually make the AI system, or whoever is controlling it, individual or (most probably small) collective, a Single Supreme God for all practical purposes, as far as human beings are concerned. But this will not be an All Powerful God, and not a a Kind God, for it will be Supreme within the limited scope of humanity and what humanity can have an effect on, and it will be kind only to itself, or perhaps not even that. It may be analogous to the God in the Phiilip K. Dick story Faith of Our Fathers [Dick and Lethem, 2013], or to the Big Brother of Orwell’s 1984 [Orwell, 1950]. We cannot be sure of the outcome,
of course, but those as likely outcomes as any others. That is reason enough to be very wary of
developing Humanoid Intelligence and any variant thereof.

References

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Alfred North Whitehead and Bertrand Russell. Principia Mathematica. Cambridge University Press, 1925–1927.

Barnaby Sheppard. Gödel’s Incompleteness Theorems, page 419–428. Cambridge University Press, 2014. doi: 10.1017/CBO9781107415614.016.

E. Nagel, J.R. Newman, and D.R. Hofstadter. Godel’s Proof. NYU Press, 2001. ISBN 9780814758014. URL https://books.google.co.in/books?id=G29G3W_hNQkC.

John E. Hopcroft, Rajeev Motwani, and Jeffrey D. Ullman. Introduction to Automata Theory, Languages, and Computation (3rd Edition). Addison-Wesley Longman Publishing Co., Inc., USA, 2006. ISBN 0321455363.

B. Jack Copeland and Oron Shagrir. The church-turing thesis: Logical limit or breachable barrier? Commun. ACM, 62(1):66–74, December 2018. ISSN 0001-0782. doi: 10.1145/3198448. URL https://doi.org/10.1145/3198448.

Ray Kurzweil. The Singularity Is Near: When Humans Transcend Biology. Penguin (Non-Classics), 2006. ISBN 0143037889.

Rodney Brooks. Prospects for human level intelligence for humanoid robots. 07 1998. Camilo Miguel Signorelli. Can computers become conscious and overcome humans? Frontiers in Robotics and AI, 5:121, 2018. doi: 10.3389/frobt.2018.00121. URL https://www.frontiersin. org/article/10.3389/frobt.2018.00121.

Roman V. Yampolskiy. Unpredictability of ai: On the impossibility of accurately predicting all actions of a smarter agent. Journal of Artificial Intelligence and Consciousness, 07(01):109–118, 2020. doi: 10.1142/S2705078520500034.

Y.N. Harari. Sapiens: A Brief History of Humankind. Harper, 2015. ISBN 9780062316103. URL https://books.google.co.in/books?id=FmyBAwAAQBAJ.

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id=4TmTzQEACAAJ.

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Shoshana Zuboff. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. 1st edition, 2018. ISBN 1610395697.

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A Great Lesson from History

One of my favourite lessons from History, now in the form of a three part documentary:

Of course, it is not just about alcohol (or any other intoxicant). It is about any moral, ethical or legal issue. It is about unintended consequences. It is also about politics and meta-politics and the influence of religion, race, money etc. over it. It is about racism and anti-immigration. It is about religious bigotry. It is about gender bias. It is about organization and mobilization. It is about rural versus urban life. It is about conservatism versus liberalism. It is about the proletariat versus the bourgeoisie. It is about solidarity. It is about crime and punishment. It is about Human Nature. It is about what is radical in a time and place and what is not. Finally, it is about economics.

All these are connected in real life. The Great Dilemma of real world politics is, however, that the lesson from it seems to be that single issue politics is most likely to succeed in the short term.

But an opposite lesson is that it is also guaranteed to fail in the medium or long term. That’s one of the reasons why real political change is so difficult to achieve.

There are many sub-lessons too, for example in the way the Women’s Suffrage movement thought about Prohibition before and after this great mistake.

Still, in spite of its relevance, we have to keep in mind that times have changed in some very fundamental ways. Just to give a small example, we have no H. L. Mencken now. Nor F. Scott Fitzgerald. Nor even an FDR.

The Mainstream Media has transformed, across the political spectrum, into something I can’t express without using some very very derogatory words. There is widespread TV now, which is far worse than even the Mainstream Media.

Not to mention the technological and economic changes.

And the core specific issue is going to be super-relevant because a whole new generation of intoxicants are on the way. And they are coming from the top, not from the immigrants, but the local heroes of the New Global Establishment. You won’t be able to stop them. You will only be able to regulate them, if you don’t want to repeat history catastrophically.

Have you started thinking about that?

***

It is not really now. It was aired in 2011. And it was aired on PBS, which is part of the Mainstream Media. Even so, PBS is somewhat special case. Sitting here in India, it seems very special.

The Prohibition itself (the 18th Amendment) started in 1917 and ended in 1933. Till recently, it was not that unusual to see such programs on Mainstream TV almost 80 years after the whole affair ended. To some extent, on some channels in some countries, it still happens. Could it have been made (and shown) before 1933?

In the coming years (or months, or days, who knows in these times) even this kind of History lesson may become hard to get because now History is being re-written like never before, at least since Enlightenment.

Where will future generations find the truth (as much as it can be found, even with best efforts). Some Select Few might still have access to it, but even that does not seem certain now.

How long will PBS last as it exists today?

Big Data and Big Information and Smaller Knowledge and Tiny (or Zero) Understanding. And what is Wisdom? Back to thousands of years ago, perhaps.

What will politics mean then? What does it already mean? Have we reached a point of no return?

***

But what about Prohibition of the original intoxicant: alcohol? Is it gone forever, or at least everywhere? Not at all. It still exists in many places. Just as it did in the US back then. And it is following almost the same trajectory. And in these places, it can cause even more problems, if not for any other reason than simply because of poverty and the stigma.

Even in the past, Prohibition has been used politically in many other countries. For example, it was used (the movement of it), perhaps not that rigidly, but still as a rallying cry for reform by someone as illustrious as Gandhi. And most Gandhian (or those who call themselves Gandhian: the gap is getting larger as with any other ideology), still argue for it in some or the other form.

In places where it is still used, the reasons given (often very valid ones) are almost the same as for Prohibition in the US. The biggest similarity has been, perhaps in all cases of Prohibition, the support of women, particularly rural women. That support is based on just as valid grounds as the one in the documentary. Another big similarity is that, for similar reasons, it can swing elections. Many politicians have once again realized the political utility of it. Most probably they have known all along, but they didn’t believe it could swing elections.

A party in existential crisis in 2015 won the state elections by promising Prohibition and kept that promise. Seeing the success, others also started talking about it.

Same valid reasons, justifications and grievances. The same disastrous results. The same long term positive effects. Or may be not the last part, may be not in all cases.

I personally have little to do with it. Strange as it may sound, as alcohol use is widespread in India even with the enormous stigma, I hadn’t actually even seen an alcoholic drink till the age of around 25 or more likely 27. It wasn’t till the age of 38 that I had tried out one spoonful out of a glass that someone in a celebration had ordered. Now I have been to many conferences where there are (usually paid) banquets where liquour is served and I have tasted a glass or two several kinds of alcoholic drinks.

However, it is almost embarrassing to admit that I still haven’t developed a taste for such drinks. Not that I have ever been against alcohol as such. Nor do I have anything against those who drink.

One reason for me is that they are so bitter (particularly beer) and we don’t like bitter in India! We like sweets, lots of sweets. Very sweet. Too much sweet. The kind a westerner might taste and say (perhaps silently, Ugh!).  I did too (liked sweet, that is). I still do, but not the ‘sweets’ themselves, just the taste sweet. Moderate sweet. Have I become Europeanized. That is, to some extent, a fact worth taking for granted for all those who are ‘well-educated’ and live in urban areas.

There is a very large number of Indians that drinks, so they must like it for some reasons, but I am not sure whether bitterness is one of them.

I am sure there are many many people in India who have actually never tasted alcohol in their whole life, as they consider it a sin, as did so many people the world over and throughout history.

But I can’t resist repeating again. The world is changing radically. In fact, the word radical isn’t even enough to describe that change.

For both who drink and those who don’t drink. Or those somewhere in between, like me.

Two Laws of Reviewing

After a few years in research, I have discovered two laws which the process of reviewing (of research papers) follows. Not very original, but here they are:

  1. You can always find some reasons for accepting any paper.
  2. You can always find some reasons for rejecting any paper.

English is Language Independent

It’s the Global Language, right? So how can it be language dependent? You propose a theory based on English. It has to apply to all languages. You propose a Natural Language Processing (NLP) or Computational Linguistics (CL) technique for a particular problem. For English. It applies to all languages. You build a software for some purpose. For English. It has to be useful for all languages. You build a dictionary…

Never mind.

But the vice versa is not true. You propose a theory based on Hindi. It is language specific. It doesn’t count for much. You propose an NLP technique for a particular problem. For Hindi. It is language specific. It doesn’t count for much. You build a software for some purpose. For Hindi. It is language specific. It doesn’t count for much.

That’s how it works in practice, if not theory. Or may be even in theory, with some help from the (very valid) idea of Universal Grammar (except that the UG may be the UG of English).

Even today I have got a review of a paper on a problem which is like one of the holy grails of NLP or CL. One of the comments is that the approach has been evaluated on Hindi so it can’t be compared to other techniques that already exist. True. But what is the number of papers published in the ‘first class’ NLP/CL conferences and journals in which the approach has been tried only on English? Doesn’t matter, because English is language independent. If you only evaluate your technique on English, that’s OK. But if you evaluate on only Hindi, that’s not acceptable. Because Hindi is language specific.

We know this very well in India. The Elite talks about (Indian) literature. And sometimes the Elite magnanimously (or dismissively) talks about (Indian) literature in languages. The first, of course, refers to literature in English. The second refers to literature in other languages. Indian languages.

The Elite talks of media. And the Elite (rarely and mostly negatively) talks of language media.

Hindi is a language. English is not a language.

Pardon me.

Hindi is a language. English is the language.

English is above being merely a language.

That’s why all the work done in English is language independent. Not just research. Not just in NLP/CL. Anything. Movies, literature, music.

I am guilty of the sin of indulging too much in mere languages. I should be working mostly on English. Not just writing blog posts in English. Sometimes, of course, I can bestow a bit of my attention on languages. Like Hindi.

But I won’t do that. I will do the opposite. I am incurable.

A Comment on an Influential Article

A colleague has been sending me links to articles by Philip Greenspun. When I got another link today and just finished reading it (a rather long article), I thought I needed to comment on that article. So here it is (I have posted it at his site too):

A great looking intellectual construction, but it is based on some fundamental flaws. So, even though a lot of the things said are correct and sensible, the most important ones are not.

For example, let’s take the practical implications: You first suggest that it is poverty that is increasing the ranks of the suicide bombers. But then you conclude that if we keep these third world incompetent Muslims poor for eternity, we might just save ourselves from terrorism. A dead giveaway I would say.

That’s the trouble with people like you. You ask others to look in the mirror, but you yourself don’t.

What about America’s record in general? I mean active participation in or encouragement of mass murder: Chile, Vietnam, Cambodia, Laos, etc.? Could that have something to do with the fact a lot of people around the world ‘hate the US’?

The ‘conventional wisdom’ that you quote (“Nations don’t have friends. They have interests.”) is from a person who is actually a mass murderer and a war criminal. You seem to have no problem with these ideas. And this person happened to be a Jew.

But so is Noam Chomsky. So was Spinoza. So was Einstein. So was Joseph Heller. So is Woody Allen.

Like most ‘Experts’, though in a slightly better way, you have presented a mixture of true facts and unjustified simplifications to come up with a theory that is sufficiently complex to bore most people into accepting it as true. It is coming from an Expert after all. Why should we bother to look deeper into it? In fact, most people will be overawed by just the MIT label.

You look hard enough at everyone else: Muslims, Europeans, Third Worlders, etc. but you are unwilling to look that hard at the deeds of the Americans, i.e., the establishment of the USA. You put the USA and Canada in the same category, but the facts, if you look deep enough, wouldn’t allow you to do this. Canada has hardly any record of imperialism and attempts of dominating the world as an unchangeable policy that can justify even mass murder, assassinations, drug trafficking to fund terrorism against enemies (as in Afghanistan against the Soviet Union) as long as it is hidden and there is scope for plausible denial.

You even refer to decolonization as if it was only a bad thing. I come from a country where more people died at the time of independence and the partition (of India at the time of ‘decolonization’) than did in the Holocaust. There is no way you are going to confuse me into thinking that the independence (decolonization) was the same as (or the cause of) the horrible events that followed. Decolonization was a good thing. A lot of the events that followed were horrible. There are two different things we ought to be talking about. But, of course, you are not interested in that. It might show the flaws in your theorizing. For example, did colonialism have anything to do with the fact that a lot of non-westerners ‘hate’ westerners even if they try their best to get into the western paradise? And the fact that the US now represents what the UK did in an earlier age. The empire that seeks to rule the whole world and won’t be satisfied until it has risen enough and then falls down (perhaps to be replaced by another empire that would also be hated by the rest of the world). At a huge cost to be paid by people other than you.

On Blind Reviewing

This is something about which I have wanted to write for a long time. Since, like many other things about which I want to write, it is quite an important matter, I didn’t want to write in a hurry. Which meant that I had to wait for a time when I could write at enough leisure to be able to write at enough length with enough time for making it rigorous enough. Now, since it is very difficult (for me at least) to get enough of all these, this effectively meant that writing about this topic was postponed indefinitely.

But I don’t want this to be postponed indefinitely. I want to write about this now. So, I would just write and try to be as rigorous as it is possible to be in a blog post written in one or two short sittings. This applies to many other posts, whether written already or to be written in future. You can take it as an apology or you can take it as a disclaimer.

What is the problem? Well, the problem, or rather the question, is whether what is called ‘blind reviewing’ is a good thing or not. And, of course, this is in the context of peer reviewing of scientific (or claimed to be scientific) research papers or articles for the purpose of selection for inclusion in the proceedings of a conference or workshop or for inclusion in a journal.

Excuse the legal sounding language.

First of all, let me list all the reasons in favour (‘favor’ for the dominant party) of the so-called ‘blind reviewing’ process, so that no one can jump and dismiss the whole affair as trivialization by saying you don’t know what you are talking about:

  1. Human beings can be biased. So, if a reviewer knows that a research paper is written by a person she doesn’t like or has strong disagreement with, she can get biased against the paper and will not be able to review the paper fairly.
  2. Apart from the above kind of biases, there can be the bias in terms of the weights associated with the names of the authors, their institutions, their countries, their group, even their academic background. Most of the people who have been working in NLP/CL[1] for some time know about the linguistics vs. statistics or machine learning bias. This kind of bias increases the chance of your paper being rejected or accepted depending on whether you seem to be in favour (or favor) of a linguistics heavy approach to NLP/CL or of a statistics (or machine learning) heavy approach. There are variants of this bias in other fields too. For the closest example, we can consider Linguistics. Where your paper is perceived to be situated along the Chomskyan or Empiricist or Cognitive or Computational axes with respect to the chosen position of the reviewer can have a large impact on the decision about your paper, irrespective of what else your paper says. And the chances of such a perception can be increased if the identities are known.
  3. Human beings can be unduly confrontational and they can also be unduly wary of confrontation. So, if the identity of the reviewer is not withheld, the author(s) may be offended by the reviewer and they may also become confrontational and carry on this confrontation with the reviewer, thus making the process of reviewing difficult and something which a lot of people would like to run away from. Also, the reviewer may avoid making adverse comments, especially if the reviewer doesn’t want to offend the author(s).
  4. If the author(s) don’t know who the reviewer is and vice versa, the whole reviewing process may be more fair for the above specified reasons and because of the general association between anonymity and fairness. If you don’t know who is criticizing and the person criticizing also doesn’t know who is being criticized, then you can expect more fairness.
  5. If the Program Committee (PC) chair(s) also don’t know who the authors are and who the reviewers are, then they can assign equal weight to all the reviews for making the final decision about a paper.
  6. If the author(s) don’t know who the reviewer is, then they won’t have any reason to attribute bias or prejudice to the comments made or ratings given by the reviewer.
  7. Peer reviewing of research papers, like the administration of justice, should not just be fair, but seen to be fair. And this can only happen with blind reviewing.
  8. Blind reviewing, through the use of the device of anonymity, gives a true meaning to the idea of ‘peer reviewing’, because if the identities are not known, all the people involved can be treated as peers, even if some of them are senior most pioneering researchers or Directors of first class institutions in first world countries, while some others are graduate students in second class institutions in third world countries.
  9. If the identities are not known, both the reviewer and the author can focus on the content of the paper and the review, respectively.
  10. Finally, the very practical reason that blind reviewing provides a reasonably fair mechanism to ensure the selection of the best research papers such that everyone can be more or less satisfied with the outcome and no one will have valid reasons to complain.

I think the above list makes as strong a case for blind reviewing as can be made. I mean in a blog post, not in a book.

Now, in the next post (that means in some future post) I will discuss what is or can be wrong with blind reviewing and will try to draw some conclusions. You must have guessed that the reason I am writing all this is that I am not sure whether blind reviewing is the best thing possible. But by writing all this, I am also trying to get things straight in my own mind.

[1]: With apologies to Martin Kay and others, I am using NLP and CL as interchangeable terms because I think my arguments in this matter are not affected by the distinction between the two, a distinction which may be important in many but not all contexts (i.e., in my opinion).