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Automating Science: Panel – Stephen Ames, John Wilkins, Greg Restall, Kevin Korb

A discussion among philosophers, mathematicians and AI experts on whether science can be automated, what it means to automate science, and the implications of automating science – including discussion on the technological singularity.

– implementing science in a computer – Bayesian methods – most promising normative standard for doing inductive inference
– vehicle : causal Bayesian networks – probability distributions over random variables showing causal relationships
– probabilifying relationships – tests whose evidence can raise the probability

05:23 does Bayesianism misrepresent the majority of what people do in science?

07:05 How to automate the generation of new hypotheses?
– Is there a clean dividing line between discovery and justification? (Popper’s view on the difference between the context of discovery and context of justification) Sure we discuss the difference between the concepts – but what is the difference between the implementation?

08:42 Automation of Science from beginning to end: concept formation, discovery of hypotheses, developing experiments, testing hypotheses, making inferences … hypotheses testing has been done – through concept formation is an interestingly difficult problem

Panel---Automating-Science-and-Artificial-Intelligence---Kevin-Korb,-Greg-Restall,-John-Wilkins,-Stephen-Ames-1920x10839:38 – does everyone on the panel agree that automation of science is possible? Stephen Ames: not yet, but the goal is imminent, until it’s done it’s an open question – Kevin/John: logically possible, question is will we do it – Greg Restall: Don’t know, can there be one formal system that can generate anything classed as science? A degree of open-endedness may be required, the system will need to represent itself etc (Godel!=mysticism, automation!=representing something in a formal deductive theory)

13:04 There is a Godel theorem that applies to a formal representation for automating science – that means that the formal representation can’t do everything – therefore what’s the scope of a formal system that can automate science? What will the formal representation and automated science implementation look like?

14:20 Going beyond formal representations to automate science (John Searle objects to AI on the basis of formal representations not being universal problem solvers)

15:45 Abductive inference (inference to the best explanation) – & Popper’s pessimism about a logic of discovery has no foundation – where does it come from? Calling it logic (if logic means deduction) is misleading perhaps – abduction is not deductive, but it can be formalised.

17:10 Some classified systems fall out of neural networks or clustering programs – Google’s concept of a cat is not deductive (IFAIK)

19:29 Map & territory – Turing Test – ‘if you can’t tell the difference between the model and the real system – then in practice there is no difference’ – the behavioural test is probably a pretty good one for intelligence

22:03 Discussion on IBM Watson on Jeopardy – a lot of natural language processing but not natural language generation

24:09 Bayesianism – in mathematics and in humans reasoning probabilistically – it introduced the concept of not seeing everything in black and white. People get statistical problems wrong often when they are asked to answer intuitively. Is the technology likely to have a broad impact?

26:26 Human thinking, subjective statistical reasoning – and the mismatch between the public communicative act often sounding like Boolean logic – a mismatch between our internal representation and the tools we have for externally representing likelihoods
29:08 Low hanging fruit in human communication probabilistic reasoning – Bayesian nets and argument maps (Bayesian nets strengths between premises and conclusions)

29:41 Human inquiry, wondering and asking questions – how do we automate asking questions (as distinct from making statements)? Scientific abduction is connected to asking questions – there is no reason why asking questions can’t be automated – there is contrasted explanations and conceptual space theory where you can characterise a question – causal explanation using causal Bayesian networks (and when proposing an explanation it must be supported some explanatory context)

32:29 Automating Philosophy – if you can automate science you can automate philosophy –

34:02 Stanford Computational Metaphysics project (colleagues with Greg Restall) – Stanford Computational Metaphysics project – formalization of representations of relationships between concepts – going back to Leibniz – complex notions can be boiled down to simpler primitive notions and grinding out these primitive notions computationally – they are making genuine discoveries
Weak Reading: can some philosophy be automated – yes
Strong Reading of q: can All of philosophy be automated? – there seem to be some things that count as philosophy that don’t look like they will be automated in the next 10 years

35:41 If what we’re is interested in is to represent and automate the production of reasoning formally (not only to evaluate), as long as the domain is such that we are making claims and we are interested in the inferential connections between the claims, then a lot of the properties of reasoning are subject matter agnostic.

36:46 (Rohan McLeod) Regarding Creationism is it better to think of it as a poor hypothesis or non-science? – not an exclusive disjunct, can start as a poor hypothesis and later become not-science or science – it depends on the stage at the time – science rules things out of contention – and at some point creationism had not been ruled out

38:16 (Rohan McLeod) Is economics a science or does it have the potential to be (or is it intrinsically not possible for it to be a science) and why?
Are there value judgements in science? And if there are how do you falsify a hypothesis that conveys a value judgement? physicists make value judgements on hypothesis “h1 is good, h2 is bad” – economics may have reducible normative components but physics doesn’t (electrons aren’t the kinds of things that economies are) – Michael ??? paper on value judgements – “there is no such thing as a factual judgement that does not involve value” – while there are normative components to economics, it is studied from at least one remove – problem is economists try to make normative judgements like “a good economy/market/corporation will do X”

42:22 Problems with economics – incredibly complex, it’s hard to model, without a model exists a vacuum that gets filled with ideology – (are ideologies normative?)

42:56 One of the problems with economics is it gets treated like a natural system (in physics or chemistry) which hides all the values which are getting smuggled in – commitments and values which are operative and contribute to the configuration of the system – a contention is whether economics should be a science (Kevin: Yes, Stephen: No) – perhaps economics could be called a nascent science (in the process of being born)

44:28 (James Fodor) Well known scientists have thought that their theories were implicit in nature before they found them – what’s the role of intuition in automating science & philosophy? – need intuitions to drive things forward – intuition in the abduction area – to drive inspiration for generating hypothesis – though a lot of what get’s called intuition is really the unconscious processing of a trained mind (an experienced driver doesn’t have to process how to drive a car) – Louis Pasteur’s prepared mind – trained prior probabilities

46:55 The Singularity – disagreement? John Wilkins suspects it’s not physically possible – Where does Moore’s Law (or its equivalents in other hardware paradigms) peter out? The software problem could be solved near or far. Kevin agrees with I.J. Good – recursively improving abilities without (obvious) end (within thermodynamic limits). Kevin Korb explains the intelligence explosion.

50:31 Stephen Ames discusses his view of the singularity – but disagrees with uploading on the grounds of needing to commit to philosophical naturalism

51:52 Greg Restall mistrusts IT corporations to get uploading right – Kevin expresses concerns about using star-trek transporters – the lack of physical continuity. Greg discusses theories of intelligence – planes fly as do birds, but planes are not birds – they are differing

54:07 John Wilkins – way too much emphasis is put on propositional knowledge and communication in describing intelligence – each human has roughly the same amount of processing power – too much rests on academic pretense and conceit.

54:57 The Harvard Rule – under conditions of consistent lighting, feeding etc – the organism will do as it damn well pleases. But biology will defeat simple models.. Also Hulls rule – no matter what the law in biology is there is an exception (inc Hull’s law) – so simulated biology may be difficult. We won’t simulate an entire organism – we can’t simulate a cell. Kevin objects

58:30 Greg R. says simulations and models do give us useful information – even if we isolate certain properties in simulation that are not isolated in the real world – John Wilkins suggests that there will be a point where it works until it doesn’t

1:00:08 One of the biggest differences between humans and mice is 40 million years of evolution in both directions – the problem is in evo biol is your inductive projectability – we’ve observed it in these cases, therefore we expect it in this – it fades out relatively rapidly in direct disproportion to the degree of relatedness

1:01:35 Colin Kline – PSYCHE – and other AI programs making discoveries – David Chalmers have proposed the Hard Problem of Consciousness – pZombies – but we are all pZombies, so we will develop systems that are conscious because there is to such thing as consciousness. Kevin is with Dennet – info processing functioning is what consciousness supervenes upon
Greg – concept formation in systems like PSYCHE – but this milestone might be very early in the development of what we think of as agency – if the machine is worried about being turned off or complains about getting board, then we are onto something

Bayeswatch – The Pitfalls of Bayesian Reasoning – Chris Guest

Chris Guest - Headshot 1Bayesian inference is a useful tool in solving challenging problems in many fields of uncertainty. However, inferential arguments presented with a Bayesian formalism should be subject to the same critical scrutiny that we give to informal arguments. After an introduction to Bayes’ theorem, some examples of its misuse in history and theology will be discussed.

Chris is a software developer with an academic background in Philosophy, Mathematics and Machine Learning. He is also President of the Australian Skeptics Victorian Branch. Chris is interested in applying critical reasoning to boundary problems in skepticism and is involved in consumer complaints and skeptical advocacy.

 

Talk was held at the Philosophy of Science Conference in Melbourne 2014

Video can be found here.

Science vs Pseudoscience – Kevin Korb

Science vs PseuodoscienceScience has a certain common core, especially a reliance on empirical methods of assessing hypotheses. Pseudosciences have little in common but their negation: they are not science.
They reject meaningful empirical assessment in some way or another. Popper proposed a clear demarcation criterion for Science v Rubbish: Falsifiability. However, his criterion has not stood the test of time. There are no definitive arguments against any pseudoscience, any more than against extreme skepticism in general, but there are clear indicators of phoniness.

Demarcation

Science v Non-science – What’s the point? Possible goals for distinguishing btw them: Rhetorical, Political, Social Methodological: aiming at identifying methodolgical virtues and vices; improving practice How to proceed? Traditional: propose and test necessary and sufficient conditions for being science Less ambitious: collect prominent characteristics that support a “family resemblance”

What is Science?

Science is something like the organized (social, intersubjective) attempt to acquire knowledge about the world through interacting with the world. In the Western tradition, this began with the pre-Socratic philosophers and is especially associated with Aristotle.

science-pseudoscienceNature of Science Science contrasts to: Learning: individuals learn about the world. Their brains are wired for that. Mathematics/deduction: a handmaid to science, but powerless to teach us about the world on its own. Dogma, ideology, faith: These may be crucial to driving even scientific projects forward (as are good meals, sleep, etc.), but as they are by definition not tested by evidence, they are not themselves science.

A Potted History of the Philosophy of Science

Wissenschaftsphilosophie – The Vienna Circle Early 20th Century Scientific Major Success Stories: Charles Darwin (evolutionary biology) Gottlob Frege (formal logic) Albert Einstein (physics) The sciences were showing themselves as the most successful human project ever undertaken. In Vienna a group of great philosophers asked themselves: Why? How did this happen? With the Vienna Circle philosophy of science became a discipline, attempting to answer these questions.

The Vienna Circle & Logical Positivism : The beginning was the appointment of Ernst Mach as Professor of the Philosophy of the Inductive Sciences at the University of Vienna, 1895. Thereafter, Mortiz Schlick founded the Vienna Circle (and Logical Positivism) in 1922. Through the helpful activities of Adolf Hitler, the leading philosophers of science introduced the Vienna Circles ideas throughout the English speaking world.
Vienna Circle Ernst Mach Moritz Schlick Rudolf Carnap Hans Reichenbach Karl Popper Paul Feyerabend Noretta Koertge Positivismus Falsifikationismus Anarchismus
The Vienna Circle Basic Principles: Philosophy as logical analysis The logical foundation of science lies in observation & experiment e.g., Rudolf Carnap’s 1928 title: The Logical Construction of the World!! Key: Verifiability Criterion of Meaning What cannot be proven empirically, is meaningless. E.g., metaphysics, religion, superstition. {h, b e1, . . . en; e1, . . . en} verifies h
Karl Popper Objects Many scientific hypotheses are universal: E.g., light always bends near large masses. But {h, b e1, . . . e∞; e1, . . . e∞} is not even a possible state of affairs Aside from that, metaphysics is an ineliminable part of science; all science has fundamental presuppositions.
Karl Popper Falsificationism Key: Demarcation criterion for science What cannot be falsified empirically, is unscientific. E.g., Marxism, religion, psychoanalysis. {h, b e, ¬e} falsifies h Theses: We can make scientific (or social) progress alternating between Bold Conjectures and Refutations. The ideal test (severe test) is guaranteed to falsify one of two (or more) alternative conjectures. Progress: refuting more and more theories; not accumulating more and more knowledge.
Imre Lakatos Sophisticated Falsificationism {h, b e, ¬e} falsifies (h&b) Hypotheses stand or fall in networks, networked to each other and to theories of measurement, etc. = research programmes If a research programme makes novel predictions that come up true, it is progressive If a programme lies in a sea of anomalies and is dominated by ad hoc saving maneuvers, it is degenerating Unfortunately, there’s no definite point at which a degenerating research programme rationally needs to be abandoned.
Thomas Kuhn Scientific Revolutions In The Structure of Scientific Revolutions (1962) he introduced the idea that science moves (not: progresses) from “normal science” through a sea of anomalies to “revolutionary science” to a new “normal science” – from “paradigm” to “paradigm”. According to Kuhn, the process is not rational, but explained in terms of psychology, social processes and power relationships.
Paul Feyerabend Epistemic Anarchy In 1958 Feyerabend went to Berkeley, where he turned against Popper, promoting “Epistemological Anarchism” instead (Against Method, 1974). He embraced the inability to reject research programmes, promoting methodological pluralism instead. Denunciations of witchcraft, pseudosciences, etc. are mere expressions of prejudice.
Ludwig Wittgenstein Open Concepts Natural language concepts have an “open structure”, based on family resemblance, not definition.
Ludwig Wittgenstein Open Concepts One of Wittgenstein’s examples: Define “game”, in terms of the necessary and sufficient conditions. Now let’s play a game involving changing those conditions. . . Socrates’ game of taking some sophist’s definition for “love”, “knowledge”, “good” and poking holes in it could be played forever. Hence, Socrates’ phony humility in claiming that he knew nothing. The reality is that our understanding and use of language doesn’t depend on definitions.
1“Science” is an Open Concept Instead of assembling inadequate necessary and sufficient conditions, let’s collect examples of science and non-science and see what the former share in family resemblances. Leave problematic cases for later. Physics Mathematics Epidemiology Medicine Paleontology Religion Climatology Mining Evolution Theory Creationism Economics Politics Political Science Fox News
“Science” is an Open Concept I’d like to suggest the key family resemblances are: Empiricism: insistance on an empirical base versus ideological dominance Abstraction (generalization) and mathematization (when possible) versus anecdotal evidence Social processes encouraging objectivity, intersubjectivity, peer review, Popperian critical rationality versus authoritarianism
Some Pseudoscientific Arguments AGW/ecology/genetic regulatory/etc models are highly abstract, lose track of detailed reality and so are not scientific. George Box: “All models are wrong, but some are useful.” Any computer model will misrepresent continuity, but does it matter? The question is whether the property of the model of interest (mapping to reality) is preserved under model dynamics, not whether irrelevant details are carried along. The demand for “proof” in science is a good indicator of dishonesty.
Some Pseudoscientific Arguments Similarly: the model predicts overall process ok, but omits some really tiny details and therefore is wrong. Here’s an example I gave a data mining class; 120 years of data on business profits. Looks like three different trends concatenated. Let’s just regress just the points from 80-120.
Some Pseudoscientific Arguments Not bad. But some ornery shareholder says, let’s just try years 109-120 instead.
Some Pseudoscientific Arguments As we can all see profits are hardly moving; let’s turf out the board!!
Some Pseudoscientific Arguments NB: profit = global surface temperature; competitiveness = solar energy.
Some References on Scientific Method F Bacon (1620) Novum Organum Scientiarum. JS Mill (1843) System of Logic. M Gardner (1957) Fads and Fallacies in the Name of Science. Dover. T Kuhn (1962) The Structure of Scientific Revolutions. K Popper (1963) Conjectures and Refutations. R Carnap (1966) An Introduction to the Philosophy of Science. C Hitchcock (2004) Contemporary Debates in Philosophy of Science.

Slides can be found here:

 

Kevin KorbMy research is in: machine learning, artificial intelligence, philosophy of science, scientific method, Bayesian inference and reasoning, Bayesian networks, artificial life, computer simulation, epistemology, evaluation theory.

See http://www.csse.monash.edu.au/~korb/ The page is out of date, but accurate as far as it goes.

http://theconversation.com/is-passing-a-turing-test-a-true-measure-of-artificial-intelligence-27801

Email kbkorb [at] gmail {dot} com twitter: @kbkorb
http://theconversation.com/profiles/kevin-korb-115721

Aubrey de Grey – Ageing & Suffering

The main thing that people misunderstanding is the actual relationship between aging and the diseases of old age – and this is largely the fault of gerontologists….people would go out and say, all the time, ‘Aging is not a disease’ – that’s not useful. Ultimately it’s very counter productive. What happened was people would think to themselves ‘well ok then, aging is this natural thing that’s never going to be amenable to medical intervention, because it’s not a disease – and also because it’s not a disease, then why should we care about it?’ – so it was absolutely the wrong thing to be saying… it’s even more the wrong thing to be saying because it’s not even true. Aubrey de Grey

 

Aubrey-de-Grey---Ageing-&-Suffering

 


Aubrey de Grey is the chief science officer of the SENS Research Foundation, which is a 501(c)(3) public charity that is transforming the way the world researches and treats age-related disease.

The research SENS funds at universities around the world and at SENS own Research Center uses regenerative medicine to repair the damage underlying the diseases of aging. The goal of SENS is to help build the industry that will cure these diseases.


Aubrey de Grey was interviewed by Adam Ford in 2012.

Here is a playlist of all the interview sections:

Panel on Skepticism & Science

Panelists: Terry Kelly (Former president of Vic Skeptics), Chris Guest (Current president of Vic Skeptics), Bill Hall (Researcher at the Kororoit Institute)

Discussion includes the history of skepticism, what skepticism is today, the culture of skepticism as a movement and how skepticism relates to broader philosophy.

00:26 Terry discusses Active Skepticism – Where Science, Skepticism & Consumer wrights overlap,  – he brings up hypnotism

01:26 Skepticism does not equal cynicism – including some cool observations about the difference between the empiricism and the plausibility argument.  The issue of plausibility vs empiricism – some issues might seem implausible… some things are so implausible they have to be addressed in that way… but some people bring up the argument that some things may seem counter-intuitive – but end up being likely after empirical observation.

4:14 Chris Guest – Discusses passion about critical thinking – it’s not so much what skeptics believe, it’s the approach to arguments –

4:42 Historical definitions of skepticism – relating to cynicism (ancient greeks).  Though skepticism is not considered cynicism today, ideally they are treated as separate concepts – there are a lot of magicians in the skeptics movement – they have a trained eye – intuitively see past common blind spots and cognitive biases – whereas scientists often take things on face value.

6:22 Bill Hall discusses his background in Popperianism – and pseudoscience and belief vs rational thinking (NOTE: Contrast with Kevin Korb’s presentation on Pseudoscience vs Science – Kevin isn’t a Popperian and thinks that falsificationism is flawed).  The demarcation problem between science and mysticism.   Bill says falsification is part of skepticism – part of debunking false claims.

08:55 Chris Guest discusses group dynamics and belief systems – people reinforce each others beliefs – so Chris tries to be tougher on people they agree with than those whom he disagrees with demanding a higher standard of argument.   Straw man arguments – where someone sets up a really bad representation of an opponents arguments rather than going into the specifics of the opponents arguments.   Steel Man arguments – kind of the opposite of straw man arguments – rather than trying to create a refutable form of the opponents arguments, try to put together the best possible representation of their arguments, even better than the one they are presenting to you – take on the best possible, most charitable arguments.   Value in moving beyond conflicts based on group identity.

11:00 Terry Kelly discusses disproving a persons beliefs – though this often results in them going away and believing harder than before.  Ashley Barnett brought up an example earlier that intelligent people are easier to fool because they had stronger attention – James Randi says academics are easier to fool because they belief if they can’t work it out, since they are so smart then it must be a special power.   Intelligent people will find smart ways to justify their rational beliefs.  So sometimes it’s not so easy to change peoples minds even though you have good evidence.

 

14:36 Chris Guest discusses approaches to debating climate change deniers – using existing models that make predictions find out what assumptions the climate change deniers disagree with, and ask for an alternative model that gives better predictions.   Then the deniers might claim that the climate alarmists get more funding to create the models as an explanation to why they have the more robust models.

15:35 Q: How people asses the nature of evidence?
Chris Guest: Instead of going head to head with someone who believes in homeopathy, say ‘let’s go to a homeopathy open day and listen to the talks’ – then let people go through their own process of discovery.

 

17:37 How people become rational – how do people go from magical thinking to being rational?  Turning point or slowly drift into it?

 

Acoustics made it difficult to hear people asking questions

“Where skeptics get interested is whether people are getting what they paid for” – Terry Kelly

 

 

Science & Skepticism - Terry Kelly - Chris Guest - Bill Hall

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Can Spiritual Experience be Scientifically Validated?

At a Melbourne skeptic’s meeting in Australia, theoretical physicist Lawrence Krauss was asked whether spiritual experiences could ever be scientifically validated.

Lawrence Krauss – Can Spiritual Experience be Scientifically Validated _“The spiritual things — the exotic phenomena people experience — in general violate the things we know to be correct on the basis of experiment, so they’re highly likely to be wrong,” Krauss answered.

“I can’t say to someone who’s heard God in their ears that they’re not hearing God,” he continued. “But I can say that it’s much more likely that they’re hallucinating, based on what we know.”

As for the existence of extraterrestrial life, he said that accounts of alien encounters are “much more likely to be due to the irrationality of humans than the rationality of aliens.”

“When you think about the likelihood that a space-craft would come here,” Krauss said, “almost anything you can think about is more likely. And what science deals with is not ‘true’ and ‘false,’ it’s ‘likely’ and ‘less likely.’ And some things are so unlikely, you just chop them off.”

“So I can’t tell someone that what they’ve heard, or what they’ve seen, or [have had] some mystical experience — I can only say that it’s likely a coincidence,” he concluded.

“But none of us like to believe that things that happen to us are coincidences. We’re all hard-wired to believe that things that happen to us are significant.”

This video was recorded by Adam Ford. The full video of Lawrence Krauss’s presentation is available here soon.  Please subscribe to the YouTube Channel for further updates.

Note this article has been adapted from an article ‘Physicist Lawrence Krauss: God is a byproduct of your hard-wired narcissism‘ that appeared on Raw Story.

When you think about the likelihood that a space-craft would come here,” Krauss said, “almost anything you can think about is more likely. And what science deals with is not ‘true’ and ‘false,’ it’s ‘likely’ and ‘less likely.’ And some things are so unlikely, you just chop them off. Lawrence Krauss

Lawrence KraussLawrence Maxwell Krauss (born May 27, 1954) is an American theoretical physicist and cosmologist who is Foundation Professor of the School of Earth and Space Exploration at Arizona State University and director of its Origins Project. He is known as an advocate of the public understanding of science, of public policy based on sound empirical data, of scientific skepticism and of science education and works to reduce the impact of superstition and religious dogma in pop culture. He is also the author of several bestselling books, including The Physics of Star Trek and A Universe from Nothing.

Initially, Krauss was skeptical of the Higgs mechanism. However, after the existence of the Higgs boson was confirmed by CERN, he has been researching the implications of the Higgs field on the nature of dark energy.

Krauss mostly works in theoretical physics and has published research on a great variety of topics within that field. His primary contribution is to cosmology as one of the first physicists to suggest that most of the mass and energy of the universe resides in empty space, an idea now widely known as “dark energy”. Furthermore, Krauss has formulated a model in which the universe could have potentially come from “nothing,” as outlined in his 2012 book A Universe from Nothing. He explains that certain arrangements of relativistic quantum fields might explain the existence of the universe as we know it while disclaiming that he “has no idea if the notion [of taking quantum mechanics for granted] can be usefully dispensed with”. As his model appears to agree with experimental observations of the universe (such as of its shape and energy density), it is referred to as a “plausible hypothesis”.

Aubrey de Grey – SENS Therapy Delivery

In this interview Aubrey discusses some of the various approaches that SENS therapy will likely be delivered. Mostly covering gene therapy. Also see this interview where Aubrey de Grey discusses using artificial organs and synthetic devices as replacement parts to aid in defeating aging.

Ex-Vivo Gene Therapy

Ex Vivo Gene Therapy

ref: yolasite.com (click for larger image)

Some things that people are already looking at, for instance introducing new blood stem cells into AIDS patients that contain an AIDS resistant gene named CCR5. A very small portion of people have a natural variant of that gene, called Delta32, which confers very strong resistance to HIV. If you could give this variant of CCR5 this could be a very powerful therapy – luckily the cells that need to have that variant are blood cells – blood cells come from stem cells – so bone marrow transplants with this appropriately modified version of this gene would be very powerful, and that is already being worked on.
There may be very many other cases of inherited diseases (especially) which could be modified and indeed perhaps cured by using genetic modification of stem cells for stem cell therapy.
Now in the case of ageing, this may also be a good way of delivering certain of the SENS therapies – the one that’s most obvious is LysoSENS – the Lyso Enhancement idea for getting rid of the molecular garbage inside of cells – because here we have to introduce new enzymes into these cells (enzymes that are not encoded into the normal human genome) and in some cases it may make sense to actually introduce the enzymes by injecting the enzymes into the circulation in the same way we already treat certain inherited diseases of Lysosomal function (called Lysosomal storage diseases). But in other cases it may be actually be preferable to make genetic modifications to stem cells so that the blood cells or the other cells that are created from those stem cells are able to have that genetic modification and thereby not to accumulate the molecular garbage that we are talking about – perhaps even to eliminate the molecular garbage that had already accumulated.

Somatic Gene Therapy

In_vivo_gene_therapy

ref: yolasite.com (click for larger image)

Some of what were going to need to do in genetic modification of people so as to implement SENS will not, or almost certain not be able to be implemented using ex-vivo gene therapy – the genetic modification of cells outside the body that are then introduced into the body. Some of it is going to have to be done by genetically modifying cells in the body itself. That is what is called ‘Somatic Gene Therapy’ – the way it’s normally done is by engineering a virus contain the engineered DNA that we are interested in and not to contain the DNA that the virus naturally has that makes it bad for us*. And of course gene therapy as an idea has been around for quite a long time – and in fact the first clinical trials of gene therapy happened about 20 years ago. But it’s had a pretty rocky ride because in fact there is an awful lot of risks involved in gene therapy and it doesn’t really work very well yet.
There are certain diseases with a very low hit rate – that is getting a suitable genetic modification to a very small number of cells is enough to be able to actually cure the disease. But in most cases you have to hit quite a lot of cells and we really just don’t know how to do that yet. We at SENS foundation are very interested in helping to address that problem and there is one particular approach to improving very substantially the ability to very safely introduce new DNA into a lot of cells into the body which we are just starting a project to explore. **

* Note this interview was done shortly before CRISPR was discovered.
** This project is called?? Note I will follow up with Aubrey de Grey on this point – but my feeling is that CRISPR may have solved the problem, at least partially

Adeno-Associated Virus

Adeno-associated_virus_serotype_AAV2One of the biggest dangers in somatic gene therapy and also it’s a danger for ex-vivo gene therapy (where you genetically modify stem cells and then you introduce them) is that on occasion the engineered gene may go into the genome in the wrong place – into a place that causes damage in the form of disrupting the DNA that was already there – in a way that you don’t want.  In general that disruption is harmless, but very occasionally it may not be harmless – it may actually make the cell cancerous (and there have been genuine cases of this in clinical trials for particular gene therapies).  So, people are very interested in ways to stop that from happening.  The most obvious way to stop that from happening is to develop a gene therapy vector (a type of virus) that preferentially goes into a particular harmless place in the genome and not go into any of the potentially harmful places – now it turns out that there are some viruses that naturally do this – there is something called AAV (Adeno-Associated Virus) which preferentially go into one particular site of chromosome 19 and people have been very interested in that virus for quite a long time for exactly that reason.  However it turns out that its quite complicated to make that really work and the hit-rate is not good enough – it still has random integration at an unacceptably high level.   So people will want to find other ways to go about this – and there really are lot’s of very creative technologies out there that are being explored to do exactly that.  I’m very optimistic that quite soon we will have gene therapy that very robustly does not disrupt DNA that it would be dangerous to disrupt.

RNA Interference

I believe there are other types of manipulation of gene expression other than gene therapy are also potentially valuable in treatment of ageing and of course medicine in general.  A lot of interest these days is in RNA Interference (RNAi) which is a method for inhibiting expression of particular proteins by introducing short RNA molecules that interfere with that process.  And that’s got a lot of potential – people are looking into it in a variety of different applications – one area that people have been trying to look into it for is cancer.  So see if one can close down cells that are over -expressing when they shouldn’t be over-expressing (for example).  Personally I’m not very optimistic about this application for cancer because it’s just too easy for cancers to mutate into a form that makes the RNAi in-effective – so the short RNA does not work anymore.  But in other applications it might be useful.

Neuro-Regeneration

So the brain is of course arguably the most essential to repair from the damage of ageing – there’s not much point in rebuilding the rest of the body if you are demented – how hard is that?  In particular is it significantly harder (to repair) than the rest of the body?  I believe it’s not significantly harder than the rest of the body – ultimately the brain is certainly vastly more complicated than any other organ, and we are vastly more ignorant about how it works than we are about any other organ – but the thing about SENS, the thing about the whole preventative maintenance approach to combating ageing is that we don’t need to understand how the organ works in order to restore its function or we need to do is understand what its made of, and more specifically how what it’s made of changes throughout life so that we can reverse these changes – repair those changes – and put structure and composition of the organ back to how it was at an earlier stage in early adulthood and thereby restore its function irrespective of our ignorance of how that function arises from that structure – that’s just as true for the brain and any other organ.  So one example of this is the fact that brain cells (neurons) don’t divide, and in most cases don’t have per-cursor cells that don’t divide either – there are a couple of areas of the brain that do exhibit the creation of new neurons throughout adulthood – the rest of the brain doesn’t luckily the rest of the brain exhibits a very very very slow rate of cell death – so it’s not really a problem – and the problems we need to fix are the problems of accumulation of garbage inside neurons for example, or outside of neurons that make those neurons not work so well even while those neurons are still alive.

 

Aubrey-de-Grey---SNES-Therapy-Delivery


Aubrey de Grey is the chief science officer of the SENS Research Foundation, which is a 501(c)(3) public charity that is transforming the way the world researches and treats age-related disease.

The research SENS funds at universities around the world and at SENS own Research Center uses regenerative medicine to repair the damage underlying the diseases of aging. The goal of SENS is to help build the industry that will cure these diseases.


Aubrey de Grey was interviewed by Adam Ford in 2012.

Here is a playlist of all the interview sections:

The Revolutions of Scientific Structure – Colin Hales

colin hales orange bg“The Revolutions of Scientific Structure” reveals an empirically measured discovery, by science, about the natural world that is the human scientist. The book’s analysis places science at the cusp of a major developmental transformation caused by science targeting the impossible: the science of consciousness, which was started in the late 1980s by a science practice that cannot, in principle, ever succeed. This impossible science must fail, not because it is malformed, but because it cannot deliver to engineers what is needed to build artificial consciousness.

The book formally reveals how fully expressed scientific behaviour actually has two faces, like the Roman god Janus. Currently we only use one face, the ‘Appearance-Aspect’ and it is measured and properly documented by the book for the first time. Where some scientists accidentally use the other, the two faces are shown to be confused as one. There are actually two fundamental kinds of ‘laws of nature’ that jointly account for the one underlying natural world. The recognition and addition of the second kind, the ‘Structure-Aspect’, is the book’s proposed transformation of science.

The upgraded framework is called ‘Dual Aspect Science’ and is posited as the adult form of science that had to wait for computers before it could emerge a fully formed butterfly from its millennial larval form that is single (appearance)-aspect science. Only ‘Structure-Aspect’ computation can scientifically reveal the principles underlying the nature of consciousness — in the form of the consciousness that is/underlies scientific observation. While this outcome ultimately affects all scientists, initially only neuroscience and physics are those that, together, have the responsibility for the empirical work needed for the introduction of Dual-Aspect science. This is not philosophy. This is empirical science.

More information on this title can be found at: http://www.worldscientific.com/worldscibooks/10.1142/9211#t=aboutBook .

Document of presentation available here:

Philosophy of Science – What & Why?

Interview with John Wilkins:

John-Wilkins---Phil-Sci-IntroEvery so often, somebody will attack the worth, role or relevance of philosophy on the internets, as I have discussed before. Occasionally it will be a scientist, who usually conflates philosophy with theology. This is as bad as someone assuming that because I do some philosophy I must have the Meaning of Life (the answer is, variously, 12 year old Scotch, good chocolate, or dental hygiene).

But it raises an interesting question or two: what is the reason to do philosophy in relation to science? being the most obvious (and thus set up the context in which you can answer questions like: are there other ways to find truth than science?). So I thought I would briefly give my reasons for that.

When philosophy began around 500BCE, there was no distinction between science and philosophy, nor, for that matter, between religion and philosophy. Arguably, science began when the pre-Socratics started to ask what the natures of things were that made them behave as they did, and equally arguably the first actual empirical scientist was Aristotle (and, I suspect, his graduate students).

But a distinction between science and philosophy began with the separation between natural philosophy (roughly what we now call science) and moral philosophy, which dealt with things to do with human life and included what we should believe about the world, including moral, theological and metaphysical beliefs. The natural kind was involved in considering the natures or things. A lot gets packed into that simple word, nature: it literally means “in-born” (natus) and the Greek physikos means much the same. Of course, something can be in-born only if it is born that way (yes, folks, she’s playing on some old tropes here!), and most physical things aren’t born at all, but the idea was passed from living to nonliving things, and so natural philosophy was born. That way.

In the period after Francis Bacon, natural philosophy was something that depended crucially on observation, and so the Empiricists arose: Locke, Berkeley, Hobbes, and later Hume. That these names are famous in philosophy suggests something: philosophy does best when it is trying to elucidate science itself. And when William Whewell in 1833 coined the term scientist to denote those who sought scientia or knowledge, science had begun its separation from the rest of philosophy.

Or imperfectly, anyway. For a start the very best scientists of the day, including Babbage, Buckland and Whewell himself wrote philosophical tomes alongside theologians and philosophers. And the tradition continues until now, such as the recent book by Stephen Hawking in which he declares the philosophical enterprise is dead, a decidedly philosophical claim to make. Many scientists seem to find the doing of philosophy inevitable.

So why do I do philosophy of science? Simply because it is where the epistemic action is: science is where we do get knowledge, and I wish to understand how and why, and the limitations. All else flows from this for me. Others I know (and respect) do straight metaphysics and philosophy of language, but I do not. It only has a bite if it gives some clarity to science. I think this is also true of metaphysics, ethics and such matters as philosophy of religion.

Now there are those who think that science effectively exhausts our knowledge-gathering. This, too, is a philosophical position, which has to be defended, and elaborated (thus causing more philosophy to be done). I don’t object to that view, but for me, it is better to be positive (say that science gives us knowledge even if other activities may do) than to be negative (deny that anything but science gives us knowledge). It may be that we get to the latter position after considering the former; if so, that would be a philosophical result.

I am fascinated by science. It allows us to do things no ancient Greek (or West Semitic) thinker would have been even able to conceive of. It means we make fewer mistakes. Philosophy is, and ought only to be, in the service of knowledge (I’m sure somebody has said that before). Science is a good first approximation of that.

But scientists who reject philosophy, as if that very rejection is not a philosophical stance (probably taken unreflectively or on the basis of half-digested emotive appeals), them I have no time for as philosophers. They should perhaps stick to their last and not make fools of themselves.

Not, of course, that every philosopher is worth reading. Sturgeon’s Law (90% of everything is crap) applies here too. But lest any scientist get too smug, recall that 99% of all scientific papers are never cited again many scientific papers are uncited . In philosophy, that ratio is perhaps lower… probably almost down to the Sturgeon limit.

See this post by John Wilkins at Evolving Thoughts: http://evolvingthoughts.net/2011/07/why-do-philosophy-of-science.

The Shaky Foundations of Science: An Overview of the Big Issues – James Fodor

James Fodor 2013Many people think about science in a fairly simplistic way: collect evidence, formulate a theory, test the theory. By this method, it is claimed, science can achieve objective, rational knowledge about the workings of reality. In this presentation I will question the validity of this understanding of science. I will consider some of the key controversies in philosophy of science, including the problem of induction, the theory-ladenness of observation, the nature of scientific explanation, theory choice, and scientific realism, giving an overview of some of the main questions and arguments from major thinkers like Popper, Quine, Kuhn, Hempel, and Feyerabend. I will argue that philosophy of science paints a much richer and messier picture of the relationship between science and truth than many people commonly imagine, and that a familiarity with the key issues in the philosophy of science is vital for a proper understanding of the power and limits of scientific thinking.

Slides to the presentation available here: