Archive for March, 2011

Precis of time travel to the past

March 31, 2011

To summarize: objectors to time-travel-to-the-past say that the traveler would change the past, and that would contradict the past and the present through the chain of causality. Therefore time-travel-to-the-past cannot be.

But I show that their conclusion is not necessary because they have ignored a hidden assumption that is itself incoherent (part of their view). (more…)

Time travel to the past

March 30, 2011

Is it possible? Well, I don’t think it’s logically impossible at all.

Objectors to time travel point out that going back in time would change the course of the present which would change the traveler herself. If she went back, for example, and accidentally killed her infant self, what would happen to the traveler? Similarly for any alteration induced by the traveler’s presence, given the multiplying effects of chaos.

Seems this objection trades on a mistaken view of time and of time travel. We usually think that time is on a kind of line


from A to B and thence to the future.  And time travel is viewed as some person, say, Jay, removing himself from the line and going back to a previous position on the line. So infant Jay at time A grows in time to point B and then decides to time-travel by going back to point A.

But that’s to assume that time A is a kind of permanent place to visit, and to assume that Jay can get out of time and go back to that same place. Both are mistaken. When Jay decides to time travel, Jay is not going back on a line, but, with respect to his personal “timeline”, is going “forward” or continuing in his own time of his life. In this progress of his life, he encounters himself as an infant. He manages to kill that infant. In the future of Jay-the-traveler there will be no youthful Jay, just Jay-the-traveler. But there’s no reason to believe that Jay-the-traveler can’t continue himself. In fact, you’d expect he would. Why wouldn’t he? He’s already there, and time and causality only move forward.


Baby J>—–Grown J>——Grown J kills baby J>——Grown J continues

By point C/A, it’s too late for baby Jay’s death to affect grown Jay causally. He’s already there and he’s moving forward in one and only one world.

The going-back view of time traveling implies a kind of dual time with parallel worlds that are somehow related causally. If you go back and kill your infant self, then, cause-by-effect in time you could never have lived to travel and kill your infant self; hence time travel to the past could be argued to be logically impossible (on the going-back view).

That’s actually a reductio ad absurdum. Suppose time travel to the past were in fact possible. The above objection would say that the possible is logically impossible. That is itself a contradiction. So objectors conclude from logic that time travel is impossible regardless of the facts. That’s for logic to determine facts that are independent of logic.

The reductio misses because there are two premises, not just the one premise “time travel to the past is possible.” The other premise that the reductio can rule out is “there is a causal chain from the reprised time to the new present.” And there’s no reason to believe that.

If time travel to the past is impossible, logic isn’t the reason.  The reason, more likely, is that the past doesn’t exist at all. It’s a fiction of memory. There’s no place “the past” that perdures. Time is just change and change is just the things that were that aren’t anymore. Time, as it were, moves only forward, just as motion is always forward, whichever direction it is going. Walking back home at night is moving forward, just in a different direction from the direction you took in the morning. Flipping backward on a video is moving forward, even if it looks funny. The only remnant of the past is its causal consequences for the present and future. Otherwise it isn’t. But if we could come to a place of our past, there would be no contradiction in influencing it (to use Horwich’s important distinction between influencing the past and changing the past), partly because influencing it would only influence the one world in which we are, and partly since there’s no ‘real’ past there to change anyway. We’d just be moving forward with a difference like the world of the movie Groundhog Day. But we’ll never get there, because it’s not there.

Social illusions, freedom, autonomy, authenticity

March 25, 2011

The Times the other day had an interesting piece about free will: When people are persuaded that their actions are deterministic, they give reign to their desires irrespective of ethics. People who believe themselves to be free agents tend to curb their selfish inclinations in consideration of the consequences for others.

It’s a wonderful support for the notion of moral realism and moral universalism: as soon as people believe they are moral agents, they incline towards the universal principles (see below a couple of posts ago “Jesse Prinz at Philosophy Now”). It’s not conclusive — there might be cultural pressures — but it makes a great test for other cultures. It turns morality into an empirical question, which really is kind of wonderful.

The piece goes on to wonder whether people actually are moral agents — are we free? It seems odd to me that this is still a question. On the one hand, if you reject determinism, you still can’t give an account of freedom. Suppose your choices originate from yourself. So what is that self? If there’s a motivation behind it, then it’s not free. If it has no motivation, then it’s just mere randomness, not a coherent self.

On the other hand, if you accept determinism, there’s no reason to reject selfhood and responsibility. Just because it’s an illusion doesn’t mean you can’t believe it and hold to it, and allow yourself to be treated as if it were real — for the simple reason that you believe it and insist that others believe it too.

Surely we all by now know that the self is an illusion. It isn’t integral, it is moved by unconscious motives, it shifts according to context and emotion, it is deceived by motives that are hidden from itself.

But it’s a useful illusion. The question of agency is one of personal dignity. We accept responsibility in order to maintain the fiction that we have integrity and dignity. Otherwise how would we take credit for our accomplishments? I helped that family — I get to congratulate myself. I wrote that book — I’m proud of myself. I fixed up that chair — how clever I am! My friends like me — me for me, not for some robot. It’s all foolishness, but a very pleasant foolishness.

It’s a sham but one we cherish. And it seems to be determined for us. We all have it as individuals. But it’s also convenient socially. It’s the basis of criminal law and punishment and an integument of social, business, academic, interpersonal interaction.

We don’t hold to it categorically. The criminally insane are not held responsible. We fudge on our own self identity. We are always in a twilight between the illusion of integrity and succumbing to selfish interests, aware or unaware. The whole point of the illusion of free will and agency is a kind of self flattering. It is itself a selfish interest, but with a difference. It’s about human dignity, which is well beyond mere selfishness. It’s noble, even if completely false. And its nobility only emerges in traditional, universalist morality.

The selfhood that brags about its great accomplishments, however delightful to ourselves, is, after all, repulsive to everyone else.

Yet more again (see “Why explain” below)

March 19, 2011

Here’s another weakness of empirical inductive statistical observation: it can’t define the range of data to exclude obvious exceptions, exceptions “that  prove the rule” and degraded data. Consider a stuck key on the keyboard. The repetition of letters on the screen has to be included among the behaviors of the key strokes. So the statistical account of the relation between keys and screen letters has to indicate that each stroke can result in multiple letters on the screen. At best it indicates an aberration, but the anomaly doesn’t rise to an indication of failure. It’s just a falsification of the inductive inference. Uninformative.

If you have a description of the machine independent of the stroke-letter correlation, you can systematically rule stuck key behavior out of the data set of machinery-ideal behaviors. The exceptional repetitions are now “mistakes” derived from machinery malfunctioning.

The same applies to linguistics. If the linguist, following Bloomfield or Diver, takes English to be all the utterances of English, how rule out stuttering utterances, stumbling utterances, half-finished sentences? What about utterances spoken by non native speakers who barely know English? How can the empirical purist rule out those speakers?

The generativist has a principled answer. Her account of English is based on a description of an independent phenomenon, the brains of English speakers. The account of those brains in turn depends on an independent description of brain evolution. And it goes like this:

1. All normally developing humans and only humans have this kind of language. Therefore, it is a species trait.

2. Humans learn language without being taught it — they learn it just by exposure. Therefore it is an instinct (via imprinting, “imprinting” broadly defined, along with internal extrapolation and selection).

3. Humans learn language during the maturational period. Therefore native language can be roughly defined by imprinting, selection and extrapolation during the maturational period.

From these three, it follows that only native speakers of English have command of the natural language. And since comprehension is part of the language capacity, the degraded data can be described as mistakes, the utterances of non native speakers can be excluded, and there is no circularity in defining the speakers (the circularity of the definition of English speakers was an embarrassment of the empiricist).

Hempel and Goodman point out the importance of counterfactuals and subjunctive conditionals for laws. But neither of these establish the authority of a law. Of course it’s true that a law provides counterexamples and subjunctive conditionals that mere statistical descriptions can’t. But what justifies the application of the counterfactuals and conditionals? No mere inductive generalization can support a counterfactual beyond mere conjectural hypothesis. What licenses the law is the independent background theory — the description of some other phenomenon that defines and determines the explananda. Newton’s laws of motion are a theory about bodies, not about special planetary motions. The theory of bodies explains the planets and at once categorizes planets as independent bodies like all other independent bodies, not special objects set in Aristotle’s rotating spheres. The independent background theory explains and redefines the phenomena, categorizing them and identifying those that belong and why those that don’t don’t.

If the key were to get stuck, the letters would repeat on the screen. If an utterance were spoken with prepositional phrases embedded with cross relations over its embedding, it would be incomprehensible. The machine explains.

Follow up on Weinberg (see previous post below)

March 16, 2011

To finish up: Weinberg sets out the problem of explanation as a question of fundamentality, generality and derivation. Are Newton’s laws more fundamental than Kepler’s? Maybe not, if the laws are derived from Kepler’s orbits. And Kepler’s orbits, he points out, apply to electrons where Newton’s don’t, so we can’t easily determine which are more general.

I’m suggesting that these are not the right questions at all. It’s a question of, well, questioning. When the purely descriptive inductive inference is falsified, there is no question to ask. You can’t say, why did the key fail? You’ve simply got a statistical degrading. But if you’ve got a theory about the machinery, then you can ask “what went wrong with it?” Then you can fix it. That’s what “why” is all about. How to fix.

When you have a background hypothesis that is more than just a statistical correlation among phenomena, that’s when you can ask, “why?” Conversely, if you ask “why?,” you’re appealing to some hypothesis beyond the statistical description. The two approaches, empirical and generative/law-governed, give very different answers to “how does it work?” One leads to a successful fix, the other to an inferential failure.

To be fair, Weinberg recognizes up front that explanation is part of what science does, and he criticizes those who try to eliminate explanation by reducing it to mere description general or description fundamental or description derivational. As he says, it’s not for scientists to redefine our common language words. If a scientific explanation happens also to be a description, then it is both a description and an explanation: a description of a broad range of phenomena that the description classes together; and, sometimes just by virtue of classing them together, an explanation of those phenomena. No reason for description and explanation to be mutually exclusive.

But I think that those explanations that do no more than categorize — this flower inclines towards the sun because all flowers incline towards the sun — may be explanatory, but it’s little more than a broader inductive generalization. It gives a sneaking feeling of question-begging. Why does this flower incline? Because all flowers do. But why do all flowers do? Somehow, the inductive generalization hasn’t got beyond just describing. Why does this flower incline? Because it’s a flower. Why is it a flower? The answer to that will likely be genuinely circular unless there is a deeper hypothesis, like photosynthesis, than “flowers incline to the sun.”

I don’t see why it would matter whether photosynthesis is more general than inclining, or whether scientists discovered photosynthesis by deriving it from inclining, or whether inclining is more fundamental than photosynthesis. What’s important is that the explanation appeals to something other than flower behavior. Photosynthesis is a phenomenon independent from the flowers. It’s not about the mere inclinations. The science of photosynthesis regards a separate theory, and that theory added to the knowledge of flowers predicts the behavior the empiricist observes among the flowers. But the empiricist doesn’t observe photosynthesis directly. Photosynthesis does not logically require inclinations at all. It’s about sunlight and chemical transformations.

A true non-question begging explanation has to appeal to a theory that is separate from the mere observation.

Now, the curious may ask, so why is there photosynthesis? And there should be a further answer reaching back into genetics, and if the curious ask about that, there should be a further answer reaching even further into basic chemistry and physics, and, if we keep asking, we may get to a final answer about the fundamental physical “laws of nature.” And it’s likely that someday we won’t be able to ask “why” any further. But it won’t be because we don’t know how to look beyond. It’ll be because the universe is just so and there isn’t anything beyond. Maybe.

Will that end in circular answwers and question-begging? I guess, but at least it won’t be our fault.

Why explain?

March 15, 2011

I just read a Steven Weinberg’s “Can science explain everything? Anything?” in his Lake Views. Weinberg is a Nobel-prize-winning physicist who writes frequently on science in, among other venues, the NY Review of Books. Here he addresses a basic problem for the philosophy of science: what is an explanation?

Many contend, including some scientists, that science only describes. What purports to be an explanation, they say, is just more description or more general description or broader and more comprehensive description. Others, more contentious still, claim that science should only describe; that any pretense to get beyond description, underneath the phenomena, inside the phenomena, anything but just the phenomena, is philosophy maybe, but not science.

There are, for example, linguists who believe that science must limit itself to the statistical occurrences among words. To them, there is no fixed grammar, only statistical correlations among words. The study of language is the study of those statistical relations only. Positivists, empiricists and behaviorists hold to this purity in their research. It’s admirably spare. For them, language is nothing but the stream of sound and its meaning.

At the other end of the extreme are the linguists who find that the statistical correlations are just the descriptive first step. Discovering the underlying machinery that generates the correlations is the scientific goal. They are looking for the explanatory story, the explanation of the correlations. The empiricits believe that the explanation is unjustified, chimeras. Weinberg asks as well, which explains, the correlations or the discovered machine. Do Newton’s laws explain Kepler or does Kepler explain Newton? Newton derived his laws from Kepler, yet we think Newton explained Kepler. What’s going on?

The romantic scientist dreams of explaining, telling a long and complicated story, full of surprises and apparent digressions that turn out to be essential, a plot that brings all the characters and twists into one simple conclusion. Satisfaction and surprise, that’s what the romantic scientist promises.

I’m a romantic. So I’m going to try my hand in making simplicity out of this troublesome conflict over explanation.

Suppose you’ve got before you a mysterious machine with a screen and a keyboard. When you tap a key a letter appears on the screen. Each keystroke brings a different letter on the screen. What is this thing before you?

The strict empirical positivist will answer with an investigation into the correlation between the keys and the letters. This key to the far left brings up an “a,” the one to its right brings up an “s.” When he’s done, you’ve got a complete inductive account of the keyboard.

Does the “a” key always bring up the letter “a” on the screen? Induction can’t go so far as to prove it, but that is the inductive hypothesis. And if it happens that the “a” fails, then the inductive hypothesis is falsified and the inductive account came to nothing but a statistical probability.

Now, you’re already way ahead of my story. You want to break open the mysterious machine, look at its parts, see how it functions and give an account of why and how the keys relate to what appears on the screen. Why stop at the statistical correlation of the mere phenomena? Don’t we want an explanation of that correlation?

Is that an explanation? Or is it just more description — a deeper description or a description of more stuff related to the correlation? How can science be anything more than just description?

Well, there is a difference between mere description of phenomena and a description that explains. Suppose you’ve figured out the machine and how it appears to work. And suppose now that the “a” stroke suddenly fails to bring up the letter on the screen. Has your hypothesis about the machine failed? Not at all.

When your computer keyboard doesn’t respond, you don’t come to the conclusion that you were wrong all the while about computers: the keys aren’t designed to bring up letters, that’s just a statistical likelihood. Sometimes it works, sometimes it doesn’t. There’s no more to be said.

No; you don’t stop there. When your keyboard doesn’t work, you think: either the keyboard is broken, or the connection is loose, or the software has a bug or the processor has got a virus, or — you know there’s an explanation in that machine. You know where to look. If worse comes to worst, you know where to go for help at the Apple Store. You see, the statistical probability is minimally informative, too minimal to be qualitatively useful. It’s not explanatory. It doesn’t tell you why. It doesn’t tell you anything when the inductive hypothesis fails. You have no reply to its falsification.

When you’ve explained the machine (described how and why the keys work) and the key fails, your hypothesis doesn’t fail now at all. If the key fails, your hypothesis now has an opportunity for counterfactual support. Because according to your hypothesis, if a key fails, there must be a failure in the mechanism’s hard or software. This is the moment of experimentation. You look to find the mechanical failure. If you find it, then you have additional support for your hypothesis.

And you can experiment further. If you can predict how each mechanical piece works, you can fool around with the mechanism and predict how those changes will change the operations. If you succeed, you’ve got more counterfactual support.  Remove this piece, no “a” on the screen. Replace the piece, restore the “a.”

Getting back to the linguist. The positivist, behaviorist linguist objects to the use of made-up sentences that are a hallmark of generative linguists. If language is just the stream of speech — he’s pounding his fist on this one — how can anything be learnt by inventing experimental sentences that have never been said?

Believe it or not, there are schools of linguistics that hold this purism. No experiments. English is speech spoken among those who understand English. The data of English are only utterances from those speakers.

(Note that the empiricist has a chicken and egg problem. How does he know who the English speakers are? But I think even generativists have to face this one too.)

For starters, the empiricist ignores that comprehension of English is just as much a part of English as speech is. Comprehension may not be the same faculty, but it is patently a part of English and it is closely related to the speech faculty, since people who can’t speak English generally can’t understand it either. That correlation is more than just a coincidence.

And if comprehension is part of English, then the comprehension or lack of comprehension of experimental sentences is a datum of the language, even if the sentence has never been spoken. So there is nothing unscientific in making up experimental sentences. At least they tell us something about comprehension. But not least, if comprehension is integral to the language, they tell us about the structure of the language, its speech indirectly, as well as comprehension directly.

What’s more, when you’ve analysed the grammar through the use of counterfactually supportive experimental sentences that define the language, laying out its boundaries, then you can say when an utterance is a fumbled sentence, or an unfinished sentence, or a sentence distracted midway and returned to. The empiricist, relying only on speech can at best identify statistical aberrations. The generativist can say with confidence: that sentence was half finished, it’s not reflective of English as English speakers know and understand it.

That’s just the beginning of explanatory power. But you have to look behind and beyond the correlations of the phenomena. You have to look at what it is that’s generating those correlations. When you’re done, of course you’ve got another description — a description of a generative machine. But that generative machine does something new for your phenomenal correlations. What had been statistical aberrations in a pure but naive view of phenomena now are counterfactual support for what’s really going on, a reality that was not apparent, but which now is now both apparent itself and apparent in the workings of the phenomenon.


In linguistics it’s generally not possible to open up the machine and look at it. Linguists usually figure out the machine by experimenting with sentences (see the entry “Syntax for the uncertain” below), not by opening up the skull as you might open up a computer to see what’s inside.