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In this post I try to fathom an informal definition of Self, the “essential qualities that constitute a person’s uniqueness”. I assume that the most important requirement for a definition of self is time-consistency. A reliable definition of identity needs to allow for time-consistent self-referencing, since any agent that is unable to identify itself over time will be prone to make inconsistent decisions.

Data Loss

Obviously most humans don’t want to die, but what does that mean? What is it that humans try to preserve when they sign up for Cryonics? It seems that an explanation must account and allow for some sort of data loss.

The Continuity of Consciousness

It can’t be about the continuity of consciousness as we would have to refuse general anesthesia due to the risk of “dying” and most of us will agree that there is something more important than the continuity of consciousness that makes us accept a general anesthesia when necessary.

Computation

If the continuity of consciousness isn’t the most important detail about the self then it very likely isn’t the continuity of computation either. Imagine that for some reason the process evoked when “we” act on our inputs under the control of an algorithm halts for a second and then continues otherwise unaffected, would we don’t mind to be alive ever after because we died when the computation halted? This doesn’t seem to be the case.

Static Algorithmic Descriptions

Although we are not partly software and partly hardware, we could, in theory, come up with an algorithmic description of the human machine, of our selfs. Might it be that algorithm that we care about? If we were to digitize our self we would end up with a description of our spatial parts, our self at a certain time. Yet we forget that all of us possess such an algorithmic description of our selfs and we’re already able back it up. It is our DNA.

Temporal Parts

Admittedly our DNA is the earliest version of our selfs, but if we don’t care about the temporal parts of our selfs but only about a static algorithmic description of a certain spatiotemporal position, then what’s wrong with that? It seems a lot, we stop caring about past reifications of our selfs, at some point our backups become obsolete and having to fall back on them would equal death. But what is it that we lost, what information is it that we value more than all of the previously mentioned possibilities? One might think that it must be our memories, the data that represents what we learnt and experienced. But even if this is the case, would it be a reasonable choice?

Indentity and Memory

Let’s just disregard the possibility that we often might not value our future selfs and so do not value our past selfs either for that we lost or gained important information, e.g. if we became religious or have been able to overcome religion.

If we had perfect memory and only ever improved upon our past knowledge and experiences we wouldn’t be able to do so for very long, at least not given our human body. The upper limit on the information that can be contained within a human body is 2.5072178×10^38 megabytes, if it was used as a perfect data storage. Given that we gather much more than 1 megabyte of information per year, it is foreseeable that if we equate our memories with our self we’ll die long before the heat death of the universe. We might overcome this by growing in size, by achieving a posthuman form, yet if we in turn also become much smarter we’ll also produce and gather more information. We are not alone either and the resources are limited. One way or the other we’ll die rather quickly.

Does this mean we shouldn’t even bother about the far future or is there maybe something else we value even more than our memories? After all we don’t really mind much if we forget what we have done a few years ago.

Time-Consistency and Self-Reference

It seems that there is something even more important than our causal history. I think that more than everything we care about our values and goals. Indeed, we value the preservation of our values. As long as we want the same we are the same. Our goal system seems to be the critical part of our implicit definition of self, that which we want to protect and preserve. Our values and goals seem to be the missing temporal parts that allow us to consistently refer to us, to identify our selfs at different spatiotempiral positions.

Using our values and goals as identifiers also resolves the problem of how we should treat copies of our self that are featuring alternating histories and memories, copies with different causal histories. Any agent that does feature a copy of our utility function ought to be incorporated into our decisions as an instance, as a reification of our selfs. We should identify with our utility-function regardless of its instantiation.

Stable Utility-Functions

To recapitulate, we can value our memories, the continuity of experience and even our DNA, but the only reliable marker for the self identity of goal-oriented agents seems to be a stable utility function. Rational agents with an identical utility function will to some extent converge to exhibit similar behavior and are therefore able to cooperate. We can more consistently identify with our values and goals than with our past and future memories, digitized backups or causal history.

But even if this is true there is one problem, humans might not exhibit goal-stability.


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What if I’m wrong?

Sebastian Marshall asks, “What if I’m wrong?”:

What if you were really wrong? Like, not just the wrong course of action, but what if your whole idea of the setup and cause and effect and payoffs and long term consequences of your actions were flawed? What if you made a serious mistake somewhere in your evaluations, and you were going to get the opposite result of what you wanted? What if you got a horrific result?

[...]

What if your safe job is actually a trap?

What if your favorite food is making you fat and diabetic and killing you?

What if you’re slowly killing the person you’re trying to save? What if they’re slowly killing you?

What if getting your preferred politics turned your society and culture into an apocalyptic wasteland?

What if your favorite leisure activity is wrecking your mind, making you stupid, and holding you back from heights you can’t even imagine from where you’re at?

What if being “ultra-hardcore” at the gym is likely to cause injury and destroy your strength, flexibility, and health? What if resting more actually produced larger, safer gains?

The satisfaction of needs

Becoming less wrong is just one of your preferences and needs, as a human being you need to acknowledge and account for all your preferences and needs.

“What if I’m wrong?”

You have to draw the line where asking that question once more will make you never ask the question again. In other words, if you notice that you need to eat, drink or sleep then stop asking the question, because otherwise you won’t be able to ask it anymore. This also counts for pleasure and leisure, if you feel unhappy about not being able to play that new game then go play it until you feel satisfied. If you don’t do it, if you don’t play the game or watch that movie and continue to ask yourself if it is worth it, if it might be the wrong choice, then your unhappiness might turn into depression which in turn will make you reluctant or unable to ask that question anymore.

You can only do your best

What if I’m wrong about the above? I can only do my best.

Whatever intelligence is, it can’t be intelligent all the way down. It’s just dumb stuff at the bottom.
Andy Clark

We are fundamentally dependent on unintelligent processes and naive introspection. We do not plan when and how to think. We rely on an unconscious hierarchical decision procedure that decides to filter out most sensory data. Only what is deemed “important”, what is above a certain threshold, is forwarded far enough to reach conscious reflection. It would be stupid to allocate resources equally.

I, my brain and body, might be wrong to conclude that I need sleep. But I am not thinking about that possibility, not only because I’m a computationally bounded agent but also because thinking in and of itself is an activity that I might be wrong about, just like sleeping. All in all, everything taken into account, sleeping simply turned out to have the most weight right now.

But what if there are monsters under the bed? Then either I survive, learn from that incident and assign enough weight to the possibility of monsters hiding under my bed as to take it into account the next time, or I die and only those agents who “naturally” allocate enough resources to fighting monsters, before going to bed, will survive.

We can only do our best, which includes the allocation of resources to preemptive measures against black swan events.


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Google Streetview ist nun auch mit 20 deutschen Städten online. Leider ist Gütersloh noch nicht dabei. Sehr schade ist natürlich, dass es auch in den jetzt zur Verfügung stehenden Städten einige wenige aber doch auffällige Lücken gibt. Diesen Versuch der Unterhöhlung des öffentlichen Raums lässt sich allerdings entgegenwirken und der Schaden zum Teil rückgängig machen. Es gibt gesetzliche (legale) Möglichkeiten die Unkenntlichmachung und Zensur von Google Streetview aufzuheben bzw. zu umgehen.

Wie gesagt, es ist zum Glück möglich, den durch die Paranoia der Deutschen (Medien) ausgelösten Zensurwahn von Google Streetview rückgängig zu machen. Es besteht die Möglichkeit zur Bereitstellung privater Streetview-Daten mittels der Foto-Sharing-Webseite Panoramio. Anders ausgedrückt lassen sich private georeferenzierte Fotografien zu Panoramio umsonst hochladen, also Fotos, die Daten wie die Aufnahmeposition (GPS Ortsinformationen) oder die Ausrichtung der Kamera im dreidimensionalen Raum beinhalten. Dieser Dienst fügt solche Fotos dann nach einiger Zeit als Ebene zu Google Maps (auch Google Earth) hinzu und integriert sie in Google Streetview.

Street View Verpixelung durch Panoramio Umgehen

Street View Verpixelung durch Panoramio Umgehen

Einige weiterführende Links zum Thema:

Zum Schluß hier noch ein paar nette Kommentare (Tweets) zum deutschen Start von Goolge Streetview und der damit einhergehenden Zensur:

RT @CineKie: Wer sein Haus bei Google #StreetView verpixeln lässt, gibt viel mehr über seine Person preis, als es die Fassade je hätte tun können.

RT @andiliciouscom: Genial! > Muhaha! Wie sinnvoll die Verpixelung in #StreetView ist,sieht man an dieser Stelle wunderbar: http://maps.google.com/maps… (RT @haascore)

RT @Balkonschlaefer: Wer sein Haus unkenntlich gemacht haben will sollte Christo und nicht Google rufen. #streetview

RT @weckgeschnappt: Verpixelte Häuser in der Nachbarschaft? http://www.computerbild.de/artikel… “So laden Sie eigene Bilder bei Panoramio hoch” ;) #streetview

P.S.

Wenn euch der obenstehende Text ein bisschen komisch anmutet oder übertrieben erscheint, ihr habt ja Recht. Es dient dazu möglichst viele Suchbegriffe abzudecken und somit viele Leute auf die geschilderte Möglichkeit aufmerksam zu machen.

Nachtrag (2010-11-20):

Nachtrag (2010-11-22):

Google scheint wohl zu viel Angst vor den 3% der Bevölkerung zu haben, die alle anderen ihre Paranoia aufzwingen wollen. Oder vielleicht doch eher vor den alten und mitlerweile in einer Existenzkrise befindlichen Medien, wie dem WDR (mit vom Austerben bedrohter Zuschauerschaft), der in der naiven Annahme damit Quoten zu machen, ständig Schwachsinn berichtet und so Stunk gegen Google macht? Ist auch egal, spätestens wenn u.a. Google bald mit ihrem Internet Fernsehen auf dem Markt kommen, wird das sowieso ein jehes Ende nehmen. Also genug davon, jedenfalls hat Google schnell seine Einbindung von Panoramio geändert. Man kann damit zwar immer noch die Zensur umgehen, muss allerdings nun auf das Foto klicken. Die schöne Integration von privaten Fotos zu einer eigenen Street View Ebene ist erst mal in der ursprünglichen Form nicht mehr zu sehen. Ändert aber nicht viel, nachfolgend ein paar Screenshots von Google Earth und Google Maps:

Google Earth (3D / Street View / Panoramio)

Google Streetview & Panoramio

Ich werde euch auf den laufenden halten und diese Post aktualisieren, wenn ich etwas Neues erfahre.


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Christopher Hitchens deconstructs the ten commandments and adds a few of his own for the April issue of Vanity Fair.


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Scientists admit that radiometric dating, one of the fundamental techniques used to show the earth is billions of years old is flawed!!! The earth is not 4.55 billion years old. Watch and find out just how old it really is.

Of course, scientists are always refining their techniques, it’s part of of science works. Creationists have pointed to a number of “results” from radiometric dating that prove it doesn’t work. Here I go over all the reasons why. Why is there Carbon-14 in some coal. Why did Potassium-Argon dating of the 1980 eruption of Mount Saint Helens give ages on the order of hundreds of thousands of years.

To download this video, copyright free, please go to:
http://www.mediafire.com/?yytzwtrzmwh

To download the scientific paper featured in this video please go to:
http://www.mediafire.com/?mhljmmzn3m2

If you wish to translate the subtitles please download them from here:
http://www.mediafire.com/?0mynummmyz0

More: youtube.com/user/cdk007


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More: overcomingbias.com/2010/03/econ-of-nano-ai.html

Slides: hanson.gmu.edu/ppt/Econ%20of%20AI%20n%20Nanotech.ppt

Robin Hanson: “Economics of Nanotech and AI” at Foresight 2010 Conference from Foresight Institute on Vimeo.

All January 2010 Foresight Conference videos:

http://www.vimeo.com/album/176287

Join email list:

http://www.foresight.org/d/list_signup

Bio for this speaker:
Robin Hanson is an associate professor of economics at George Mason University, a research associate at the Future of Humanity Institute of Oxford University, and chief scientist at Consensus Point. After receiving his Ph.D. in social science from the California Institute of Technology in 1997, Robin was a Robert Wood Johnson Foundation health policy scholar at the University of California at Berkeley. In 1984, Robin received a masters in physics and a masters in the philosophy of science from the University of Chicago, and afterward spent nine years researching artificial intelligence, Bayesian statistics, and hypertext publishing at Lockheed, NASA, and independently.

Robin has over 70 publications, including articles in Applied Optics, Business Week, CATO Journal, Communications of the ACM, Economics Letters, Econometrica, Economics of Governance, Extropy, Forbes, Foundations of Physics, IEEE Intelligent Systems, Information Systems Frontiers, Innovations, International Joint Conference on Artificial Intelligence, Journal of Economic Behavior and Organization, Journal of Evolution and Technology, Journal of Law Economics and Policy, Journal of Political Philosophy, Journal of Prediction Markets, Journal of Public Economics, Medical Hypotheses, Proceedings of the Royal Society, Public Choice, Social Epistemology, Social Philosophy and Policy, Theory and Decision, and Wired.

Robin has pioneered prediction markets, also known as information markets or idea futures, since 1988. He was the first to write in detail about people creating and subsidizing markets in order to gain better estimates on those topics. Robin was a principal architect of the first internal corporate markets, at Xanadu in 1990, of the first web markets, the Foresight Exchange since 1994, and of DARPA’s Policy Analysis Market, from 2001 to 2003. Robin has developed new technologies for conditional, combinatorial, and intermediated trading, and has studied insider trading, manipulation, and other foul play. Robin has written and spoken widely on the application of idea futures to business and policy, being mentioned in over one hundered press articles on the subject, and advising many ventures, including GuessNow, Newsfutures, Particle Financial, Prophet Street, Trilogy Advisors, XPree, YooNew, and undisclosable defense research projects. He is now chief scientist at Consensus Point.

Robin has diverse research interests, with papers on spatial product competition, health incentive contracts, group insurance, product bans, evolutionary psychology and bioethics of health care, voter information incentives, incentives to fake expertise, Bayesian classification, agreeing to disagree, self-deception in disagreement, probability elicitation, wiretaps, image reconstruction, the history of science prizes, reversible computation, the origin of life, the survival of humanity, very long term economic growth, growth given machine intelligence, and interstellar colonization.

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If you enjoyed this video, please consider making a donation to the non-profit Foresight Institute:

http://www.foresight.org/forms/php/donate.php


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The term “Mind Projection Fallacy” was coined by the late great Bayesian Master, E. T. Jaynes, as part of his long and hard-fought battle against the accursed frequentists.  Jaynes was of the opinion that probabilities were in the mind, not in the environment – that probabilities express ignorance, states of partial information; and if I am ignorant of a phenomenon, that is a fact about my state of mind, not a fact about the phenomenon.

I remember (dimly, as human memories go) the first time I self-identified as a “Bayesian”. Someone had just asked a malformed version of an old probability puzzle…

You’ve probably seen the word ‘Bayesian’ used a lot on this site, but may be a bit uncertain of what exactly we mean by that.

Bayes’ theorem was the subject of a detailed article. The essay is good, but over 15,000 words long — here’s the condensed version for Bayesian newcomers like myself.

Bayes’ Theorem for the curious and bewildered; an excruciatingly gentle introduction.

Eliezer Yudkowsky’s T-Shirt

This post is elementary: it introduces a simple method of visualizing Bayesian calculations. In my defense, we’ve had other elementary posts before, and they’ve been found useful; plus, I’d really like this to be online somewhere, and it might as well be here.

Everyday use of a mathematical concept.

I recently came up with what I think is an intuitive way to explain Bayes’ Theorem…

Bayes' theorem

A law of probability that describes the proper way to incorporate new evidence into prior probabilities to form an updated probability estimate. Bayesian rationality takes its name from this theorem, as it is regarded as the foundation of consistent rational reasoning under uncertainty. A.k.a. “Bayes’s Theorem” or “Bayes’s Rule”.

Eliezer Yudkowsky is on bloggingheads.tv with the statistician Andrew Gelman.

Several different points of fascination about Bayes…

When looking further, there is however a whole crowd on the blogs that seems to see more in Bayes’s theorem than a mere probability inversion…

Bayesian statistics is a system for describing epistemological uncertainty using the mathematical language of probability.
Bayesian probability is one of the most popular interpretations of the concept of probability.

Edwin T. Jaynes was one of the first people to realize that probability theory, as originated by Laplace, is a generalization of Aristotelian logic that reduces to deductive logic in the special case that our hypotheses are either true or false. This web site has been established to help promote this interpretation of probability theory by distributing articles, books and related material. As Ed Jaynes originated this interpretation of probability theory we have a large selection of his articles, as well as articles by a number of other people who use probability theory in this way…

Bayesian statistics is so closely linked with induction that one often hears it called “Bayesian induction.” What could be more inductive than taking a prior, gathering data, updating the prior with Bayes Law, and limiting to the true distribution of some parameter?

Gelman (of the popular statistics blog) and Shalizi point that, in practice, Bayesian statistics should actually be seen as Popper-style hypothesis-based deduction. The problem is intricately linked to the “taking a prior” above.

Or, how to recognize Bayes’ theorem when you meet one making small talk at a cocktail party.

Still, I’m sure Blogger won’t mind me using their resources instead. The basic idea is that there’s a distinction between true values x and measured values y. You start off with a prior probability distribution over the true values. You then have a likelihood function, which gives you the probability P(y|x) of measuring any value y given a hypothetical true value x.

In other words, What is so special about starting with a human-generated hypothesis? Bayesian methods suggest what I think is the right answer: To get from probabilistic evidence to the probability of something requires combining the evidence with a prior expectation, a “prior probability”, and human hypothesis generation enables this requirement to be ignored with considerable practical success.

Andrew Gelman recently responded to a commenter on the Yudkowsky/Gelman diavlog; the commenter complained that Bayesian statistics were too subjective and lacked rigor.  I shall explain why this is unbelievably ironic…

Maybe this kind of Bayesian method for “proving the null” could be used to achieve a better balance.

Bayesian brain is a term that is used to refer to the ability of the nervous system to operate in situations of uncertainty in a fashion that is close to the optimal prescribed by Bayesian statistics.


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P.S.

Expect this link collection to be permanently updated.

Please post a comment if you have something to add.


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via acceleratingfuture.com/michael/blog/


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This video describes rewarding brain stimulation.
For references and more information visit iplant.eu/rbs.html


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