Scientific facts and democratic values

I spoke at the Circling the Square conference last week, keeping closely to the text I put up before I went to Nottingham.  The most significant change was that I ended with a comment on a claim made by an experimental physicist (hereafter labelled as "EP")   the previous day that "E=mc2 is a fact" and was on the following panel where he argued that "Science is  not democratic".  I want to explore these two points.

As a mathematician, E=mc2 looks like a model, and I come from a tradition that lives by the aphorism that "all models are wrong".  But this is simplistic, a better argument is presented by Poincare, who is an authority I suspect that EP would be reluctant to dismiss with the confidence that they dismiss sociology.

Poincare is difficult to read, because his approach is to take ironic positions that he then dismantles.  In Chapter 6 of Science and Hypothesis he does this with the playful statement

The English teach mechanics as an experimental science; on the Continent it is taught always more or less as a deductive a priori science.  The English are right, no doubt

He then proceeds to cast doubt on that indubitable statement.  Poincare notes that the issue is that

treatises on mechanics do not clearly distinguish between what is experiment, what is mathematical reasoning, what is convention and what is hypothesis

Over a hundred years on physicists are still unclear about these things, something that annoys sociologists.  Later, in Chapter 8, Poincare untangles the difficult concept of energy, and it is in this context that I asked the question "Is E=mc2 a definition", if this is the case and we associate facts with definitions we are close to Nominalism.

In response, the EP raised a cup as if to drop it and the claim was made that it will accelerate at 9.81.. m/s2 and this was a fact, known within definite errors.

A fact with error bars on it, mmmm.  Not convincing.

The point is this fact, even with error bars, is dubious.  I worked in the oil industry and one way of prospecting is to search for gravity anomolies, that is to make money by looking for where the model fails.

Thus far EP has failed to justify to me that physics is based on facts, but I still believe in physics.  What is my reasoning.

In Chapter 7 of Science and Hypothesis Poincare asks the reader to imagine a planet that is covered with thick clouds, so much so that they cannot see the stars.  He then argues that, at some point, a Copernicus will "come at last'' to the planet and would argue that

 It is more convenient to suppose the earth turns round, because the laws of mechanics are thus expressed in much more simple language. 

and then he goes on to say

these two propositions "the earth turns round,'' and "it is more convenient to suppose that the earth turns round,'' have one and the same meaning

This statement was picked up by a mathematician and  philosopher, Edouard LeRoy. LeRoy was a friend and follower of the philosopher Henri Bergson, who is associated with philosophical irrationalism and  LeRoy believed that science "can teach us nothing of truth; it can only serve as a rule of action'' and, following Bergeson,  "the intellect deforms all it touches'' and is a version of Nominalism.  Poincare was forced to write his second book The Value of Science  where he clarifies his earlier work and argues, passionately, for the value of science.

Poincare starts by arguing that science is not simply a 'rule of action' in the same way that there are rules to a game,

[If science has] a value as `recipes' have a value, as a rule of action, it is because we know they succeed, generally at least.  But to know this is to know something and then why tell us we know nothing?

He then goes on to distinguish a 'crude fact' from a 'scientific fact'

The scientific fact is only the crude fact translated into a convenient language. 

Poincare observes that the convenient language could be French or German (or  Euclidean or non-Euclidean geometry), but the point is that, in science at least, a French speaker could come to understand German, "because there remains between the French and Germans something in common, since both are men''.  The nominal language that scientists use is only a convenient veneer on the universality of science.

Poincare then goes on to answer the fundamental question: What is science? and offers the following

 it is before all a classification, a manner of bringing together facts which appear separate, though they were bound together by some natural and hidden kinship.  Science, in other words, is a system of relations.  Now, ..., it is in the relations alone that objectivity must be sought

followed by

 Therefore when we ask what is the objective value of science, that does not mean: Does science teach us about the true nature of things? but it means: Does it teach us about the true relations of things? (my emphasis)

The equivalence of the statements "the earth turns round,'' and "it is more convenient to suppose that the earth turns round,'' is a consequence of the relativity of space.  To state that either "The earth turns around'' or "The earth does not turn around'' only has meaning if space absolute, and not if science is about relations of things.

Having set the scene with Poincare, to entice the EP in,  I will run forward to modern philosophy.  Susan Haack gives us the metaphor of knowledge (scientia) as a crossword puzzle, we answer some clues and infer others.  For example if in my crossword I see the letters "f_l_c_t_" I am justified in filling in "felicity" (without referring to the crossword clue), just as a physicists are justified by filling in "E=mc2" in science.  But, if I find the answer that gave me the "l" is wrong, I have to re-visit "felicity"; it could be "ferocity" or "frascati".  Metaphorically, my issue with multiverses is that I feel physicists are solving  the clue with "fulocite" (rhymes with "full of ..."); inventing a meaningless word to fill in the blanks.

Haack is not immediately interested in the natural and physical sciences, her main concern is the law and how science influences legal judgements (which is itself related to the topic of the conference).  The reason Haack, Poincare and I take this line in knowledge is that we want science to take a central role in policy making.  This implies we cannot be exclusive in our definition of science as that which relates to nature.

What I mean by this is I believe it is equally justified to claim the "E=mc2" and that "Raping three year olds is wrong" and I need to have a framework that acknowledges the equivalence of these claims.  The reason I use an extreme example is that the question of raping children is clearly predominantly a moral question, so what I am claiming is that my intellectual framework needs to be equally robust in supporting "facts" as "values".  I cannot immediately justify either claim, I rely on a confidence that I can discover robust justifications.  Furthermore, I would conject that the proportion of the British population who reject both claims is similar, and more controversially that there is an overlap in the groups.  My basis for the second claim is in the recognition of a link between emotivism, that moral statements are essentially emotional, in moral philosophy and relativism in philosophy more generally.

Now the sting in the tail:  emotivism is closely related to logical positivism, notably through the work of A. J. Ayer.  I see a connection between logical-positivism, that the only truths are those that can be verified through experimentation, with emotivism, that moral statements are propositionally empty,  with relativism, that there can be no absolute justification for a claim.  If you take the logical positivist out of the laboratory their position, for me, becomes untenable and relates to the relativists they typically despise.  N.B. Do not quote this argument in a 101 Philosophy paper.

Why do I care?  Why do I need to employ a framework that acknowledges the equivalence of the claims?  The reason is that, like Haack and Poincare,  I believe that scientists have a role in policy.  I finished my statement at the conference with the hyperbole that the Credit Crisis was caused by people who are committed to the idea that E=mc2 is a fact.  Let me explain.

Since the 1980s investment banks have been actively recruiting, at an increasing rate, graduates from science, technology, engineering and mathematics backgrounds.  The reason was the increasingly quantitative nature of finance.  This was not new, there has always been a strong relationship between science and finance that had become overshadowed between 1914 and 1970 when states set exchange rates deterministically.  Finance gained much from these graduates, but they came with baggage, they believed in the truth-bearing nature of mathematics and did not recognise an ethical dimension of the equations they employed.  As the Financial Crisis Enquiry Commission reported, the Credit Crisis was a result of "a systemic breakdown in accountability and ethics".  It was not the mathematics that was wrong it was the moral context in which they were used. In response,  my work since 2010 has centred on un-covering the ethical dimension of the abstract mathematics employed in finance.

Something that struck me at the Conference was the extraordinary status of finance and economics.  I plan to explore this in a future post - I need to check what people actually said on the recordings rather than rely on what I think I heard - but for the benefit of those who were not their it came up a number of times that no-one, from the Parliamentary Office of Science and Technology, the government's scientific advisers, academics and so on, challenge the basis of financial decisions.  This is extraordinary because modern policy decisions are based primarily on economic arguments.    For example, the Stern case for taking action today to mitigate uncertain climate change in the future rests on taking an unconventional financial position.  As economists are reluctant to take this position, there is never an economic case in favour of many mitigation strategies.  In un-covering the ethical dimension of the abstract mathematics employed in finance I present a case for Stern's position.  If there is no questioning of the financial basis of policy decisions, most of the discussion about scientific advice is redundant.

As something of an aside, but an issue that came up at this conference and after the Mathematical Cultures meeting is the widespread belief that the root of science's problems is "neo-liberalism".  I have explained a number of times that "neo-liberalism" is a technical term relating to a synthesis of statist and classical liberal policies.  The financialisation of academia, taking it from public to private control,  is a return to "liberal" policies.  There seems to be a reluctance to associate what is bad with policies that originate, in part,  with Bentham and Mill.  One academic responded "Well at least we've never had "liberal" governments then".  The problem is we have.  The British policy of Russell's government in response to the Irish Famine from 1846 was classically liberal and perceived as being "scientific" (in accordance with Mill's conception of political science) at the time.  Peel's Tory policy had been both less liberal and motivated by Christian charity and is usually perceived as humane, but flawed.

This leads me on to the second statement by EP: Science is undemocratic.  Given that I had made the point that, as a bystander, I think that the climate debate has degenerated into one of seeing which camp can have the most peer-reviewed papers published, suggests that we are in agreement.  Maybe, but not in how to present the case.  I argue that the issue is inside academia - it is about getting papers published, EP suggests the problem is outside the academies, in the public space.

Claiming "E=mc2 is a fact" and "Science is undemocratic" are both problematic: the first is open to challenge, as I have done, and if it looks invalid it undermines subsequent claims.  The second raises in the hearers mind, if it is not democratic, what exactly is it: technocratic? plutocratic? theocratic? In my work I identify a correspondence between good scientific, democratic and commercial practice.  I build this case on Cheryl Misak's Truth, Politics and Morality, which, according to the publisher, "argues that truth ought to be reinstated to a central position in moral and political philosophy": nothing woolly there.  Misak's argument is essentially that if we are to arrive at something we can call truth we must put our claims up to be challenged; this is the democratic ideal.  The very fact that EP embarks on an admirable crusade to challenge published work demonstrates that they advocate that science is democratic: they are rejecting the autocratic authority of the journal and the peer review process.

Poincare suggested that what distinguishes the scientist is their ability to ask the right questions, not their ability to deliver the right answers.  My feeling towards the end of the Circling the Square conference that academics seem to be becoming very introspective.  When EP claims that "Science is undemocratic" they are talking to other academics, not to the broader public. The discussions focussed on climate science, particularly geo-engineering and the badger cull.  As Sheila Jasanoff pointed out, the academics' main mechanism for affecting climate policy, the IPCC,  has failed and we should move on to thinking of something workable while someone else pointed out that public opinion on the fate of British badgers was clear: we don't care.  I was left thinking that academics are fighting amongst themselves over the scraps under the table, when the juicy joint has been left unguarded on the table.  All this was going on while  a significant portion of the European public was going to the polls and giving the establishment, of which publicly funded academics are part, a significant vote of no confidence.

Piketty and the problems of data interpretation

I have not read Piketty, but like many in my position I will not let that stop me talking about the debate of his book focusing on data interpretation.

After leaving university I worked for a number of oil industry related consultancies, the formative time being spent with a firm that made their money by providing expert witness testimony in legal disputes around the revenue split from oil fields that crossed legal, often and lucratively international, boundaries.  The charismatic founder of the consultancy, a Napoleonic Inverness-ite, liked to tell the junior technical staff that lawyers started with a case and gathered the evidence, where as scientists gathered the evidence to build a case.  Now that I am older I wonder if this was more nuanced than I imagined in my twenties: scientists will gather evidence in order to answer the question at hand, they do not, as Francis Bacon seems to suggest, just gather the data and watch the science precipitate out of it.

In the early '90s the firm realised that there was money to be made in 'data management': collating the information on an oil reservoir, cleaning it up and delivering it to oil companies for their technicians to interpret.  The boss was happy to provide this service for paying customers, but for the consultancy work of his firm, the interpreters gathered and cleaned up the data.  The reason for this is that in the process of collating the information the interpreter develops deep tacit knowledge of strengths and weaknesses in the data that goes on to  inform the interpretation.  Most data sets are incomplete, clearly contain errors and in the process the interpreter needs to make judgements about how the data is manipulated to make it coherent.  Understanding this helps in the analysis.

The Financial Times has identified manipulations in Piketty's data set, and no doubt the journalists who did this felt they were on to a significant scoop relating to the intellectual phenomena of the year.  I think this highlights the journalist's unfamiliarity with the scientific process rather than problems with Piketty's work.  I am immediatley reminded of Pierce's pragmatic metaphor of science: it is a cable not a chain.  What this means, is that a chain fails when a link breaks where as a cable can suffer the breakage of a number of strands before it fails.  The evidence is the Forth Road suspension bridge that has microphones attached to its ageing cables counting the strands that have broken to inform on its integrity.

The FT journalists were able to identify the issues with the data because Piketty had made so much data available for review. It is difficult to criticise his science because of this basic fact.  The FT has raised doubts about the data, and he has responded with a justification, the justification that as someone experienced with interpreting data, I would expect.  Again his science is difficult to fault.  If we are going to claim that because he had to clean up the raw data, his conclusions are unsound, we need to be prepared to write of the vast majority of science, ancient and modern.  I would start with the discovery of the Higgs Boson, for example.  I think the UK (and possibly US) are in the midst of a real crisis of science because of the obsession we have with "the data" at the expense of the process (see my previous post).

I have not read Piketty's book but I will, I will do so on the basis that I am dubious about his conclusions and I base this doubt on an intuition that he believes that capitalism inevitably leads to wealth inequality.  I see this is a marxist (as distinct from Marxist) interpretation that rests on a sense of determinism.  I believe that capitalism can take on many characters, just as eating is done differently in East Asian and West European cultures.  In this respect we can construct a capitalism that does not lead to wealth inequality. (Of course, this may rest on how capitalism is defined, if it is defined on the basis of profit maximisation rather than market exchange, there is no hope for capitalism, in my opinion).

Is it robust knowledge or make believe? Evidence, uncertainty and the role of values.

I am participating in the "Circling the square:Research, politics, media and impact" conference next week and I am collecting my thoughts.  This is a preview of my opening statement.

A few years ago I attended a meeting on the applications of mathematics to "energy problems" sponsored by the Engineering and Physical Sciences Research Council and the London Mathematical Society.  During one of the presentations a British Nuclear Engineer noted that in France they do not employ probabilistic arguments in favour of nuclear power because probabilistic arguments are too advanced for the public.  Two people who did not snigger at the ignorance of the French were myself and the senior probabilist at the University of Oxford.  We understood the French position: mathematical probability is a branch of mathematical analysis.  The British, by and large, associate probability with statistics, counting things and calculating relative frequencies.

The difference is captured in the different words we use for the English mathematical term 'expectation', the French use the word espérance, with the literal translation of hope.  Since the Latin root of expectation is associated with waiting, and in the past 'expect' and 'wait' have been used synonymously (i.e. Dickens's Great Expectations), we can infer that there is a tendency for the English speaker to anticipate a mathematical expectation, where as a French speaker merely hopes for it.   Similar issues exist within English for the words 'risk' and 'uncertainty'.  An economist will usually interpret a risk as calculable chance, a physicist might view an uncertainty as an error rather than something undependable.

I sometimes distinguish mathematical probability from statistics by using the analogy of hope (Spes, Elpis) and faith (Fides, Pistis).  Most theologians agree that faith is necessary because there is doubt: statistics is a necessary part of science because our results are doubtful.  Statistics provides a justification for our doubtful claims based on what has happened in the past.  Probable also implies provable and true, but where as statistics has an empirical angle, probability has a more metaphysical aspect.  This was exemplified in the medieval genesis of probability in the context of jurisprudence where conscience and moral certainty were key issues, issues that were still important in Bernoulli's The Art of Conjecture and through the eighteenth century discussions of the Petersburg game.  They disappeared in the post-Laplacian conception of probability.

One of the original purposes of probability was to price contracts and it did this by considering ratios, on which justice is based, this is present in Aristotle's Nicomachean Ethics.  The word 'rational' is derived from 'ratio' and is associated with reasons and accounts: justification.  Mathematical probability emerged in the mid-seventeenth century as a result of centuries of discussion around the morality of commercial contracts.  When Huygens coined the term expectatio in the first treatise of probability he did so in to context of establishing the fair, or just, price of a contract.  If we win £10 on a head and £2 on a tail the expectation of the coin toss, its fair price, is £6. We can not 'expect' to win £6 because it will never happen.  I argue that this ethical dimension to probability is still implicit in Financial Mathematics, but not recognised.

My main point is, the mathematics of probability and statistics exist because we need to justify our claims.  My secondary point is that historically, there was an explicit moral dimension to the process of valuation that became obscured in the nineteenth century, at the same time as episteme came to dominate discourse (before Foucault).

If the question was "Is it episteme or make believe?"  I think the question would be wrong.  Firstly the dichotomy is false.  It is not a choice between "scientific" or "true knowledge"  and "make believe" it is a problem of deciding on the best course of action in the uncertain, undependable, world outside a controlled laboratory.   Aristotle distinguished  episteme, passive knowledge from phronesis, active thinking and I think the issue pertinent to "Research, politics, media and impact" is robust thinking rather than just robust knowledge.  The antonym of "make believe" is not "true belief" but "justified belief" and, it is my opinion, that science should focus on the manner of its justifications rather than its results.

 Re-emphasising  phronesis, with the aim of good, virtuous, living, might be worth considering in light of our experience of the Financial Crisis, which highlighted that scientific knowledge is not as robust as many of us would like to believe.  For example, most of the research in Financial Mathematics has been focused on establishing the "true" price of a contract, some of my work is about re-orientating the discipline to focus on the principles that make thinking robust, given that we cannot rely on certain knowledge in an uncertain world.  For example, I argue that the origins of Financial Mathematics are in the synthesis of the virtues Faith, Hope and Charity (Caritas, Agape).  I am not alone in thinking this way, Rethinking Economics argue that

It is clear that maths and statistics are crucial to our discipline. But all too often students learn to master quantitative methods without ever discussing if and why they should be used, the choice of assumptions and the applicability of results.

I interpret this as it is not the tools of mathematics that are important, but how they are employed.  This observation is as pertinent to most students and their teachers.

My motivation for these comments originates in a conversation I had before the crisis about the use of mathematics in finance.  Basically  mathematical models were being used as rhetorical devices: if a trader had a "better" model than the risk manager, they could do what they wanted to; the trader didn't necessarily believe the model but justified their actions.  This idea emerged in the Bank of England's testimony to the Parliamentary Commission for Banking standards

unnecessary complexity [of mathematical models] is a recipe for […] ripping off […], in the pulling of the wool over the eyes of the  regulators about how much risk is actually on the balance sheet, through complex models. 

The existence of a model was enough, there is no understanding of how it works, how it justifies.

More generally I sense a connection here to issues around, for example, climate science.  As a bystander I feel that the climate debate is one of which camp has the larger collection of peer reviewed papers wins.  There seems to be little rational discourse of making a claim, challenging a claim, justifying a claim.  The claim, if published, stands as a fact. The problem is that while many academics are judged on their ability to create facts, a collection of facts is no more science than a collection of bricks is a house.  Le savant doit ordonner, the role of the academic is to turn the facts into `science'.

Objections to Objectivity

I start with a warning that this is a synthesis-in-development of some thoughts about mathematics, economics, objectivity and justification.  As a work in progress it might be a bit incoherent.  I have been thinking about "justification" having read Cheryl Misak's Truth, Politics and Morality on the advice of the pragmatist Matthew Festenstein when giving me feed-back on my Reciprocity paper.  Matthew had identified a relationship between the influence on seventeenth century commerce on politics (his field) and finance (my interest) and given it takes place in the seventeenth century there is a third node: science.

Following reading Misak I went to Susan Haack's Putting Philosophy to Work that discusses science in the context of pragmatism.  Misak and Haack got me thinking that fundamental to the pragmatic conception of politics and science, and by induction, finance, is the idea that in making a claim you put it up for criticism, if there is no criticism the claim passes but if it challenged the claim needs to be justified in a discursive manner.  Eventually a consensus is reached.  The problem for philosophy is under what conditions can the consensus be regarded as truth.  Clearly a "democratic" conception that 51% signifies truth is inadequate, and this opens the door to wondering if 90% of "scientists" signifies truth or if the "market" determines truth.

With this in mind I attended a workshop on Mathematical Cultures during which Norma Beatriz Goethe gave a talk on Leibnitz.  What caught my attention was in the pre-amble Norma discussed how in the mid-seventeenth century there was a tradition of representing the scientist as a spectator at a theatre, with nature being what occurred on the stage.  This was interesting to me because one of the cornerstones of pragmatism is the rejection of the Cartesian belief that the scientist can be an objective observer of the world.  This is a reasonable working hypothesis for the physical sciences, but begins to break down in the natural sciences (the "anthropocene"), is dubious in the social sciences and untenable in the human sciences.

However, what really caught my attention was an illustration in this vein which had the "scientist" in a room that enabled them to eavesdrop on those around them, with massive "hearing horns" and spyglasses observing activities in a public space.  What struck me was a correspondence between these prototypical conceptions of science, the scientist as the observer, and recent crises of mathematicians working for security services monitoring the public's activity.

My talk, in order to justify its place in a discussion of Mathematical Cultures, centred on financial mathematics as a language to facilitate discourse rather than the more popular conception as the key to unlocking the secrets of financial markets.  A concern I share with many applied mathematicians - and regulators - is that contemporary financial mathematics has become too complex to be useful.  However, more pertinent is the fact that research mathematicians might become irrelevant because in the markets there seems to be a paradigm shift away from sophisticated models to simpler models that incorporate  CVA - a basic accounting tool abhorrent to a PhD trained quant.  Though I am sure us mathematicians could, given time, make CVA incomprehensible to the uninitiated as well.  I note with interest that Mark Davis (my mathematical grandfather) is questioning mathematicians' objections to VaR as a risk measure and re-poses the mathematical question: "Instead of asking whether our model is correct, we should ask whether our objective in building the model has been achieved."  I suggest we can interpret this as a statement that we do not require objective justification for the validity of the model, rather we need a subjective, i.e. relative to our aims, assessment. The mathematician is an actor on the stage of finance.

Twitter alerted me to two posts by @MarkThoma.  One from last year makes the observation that

We like to think or ourselves as scientists, but if data can’t settle our theoretical disputes – and it doesn't appear that it can – then our claim for scientific validity has little or no merit.

while one from yesterday is titled 'Pretending To Do Something Like Science'??? and is a quote from Paul Krugman

Were the freshwater guys always just pretending to do something like science, when it was always politics? Is there simply too much money and too much vested interest behind their point of view?

Both these posts, and Mark's presentation, (implicitly) ask the question "what is science", a question that dominates much of my thinking as a "scientist" working in finance.

With regard to Mark Thoma's 2013 post, Poincare was always sceptical of the Anglo-Saxon obsession with "facts", "facts are to science what bricks are to houses: a collection of facts is no more science than a pile of bricks is a house".  In this setting mathematics has the role of mortar or cement, identifying the relationships between facts and linking them together.  Something else I learnt from Poincare is that mathematics is essential when you cannot perform an experiment: Higgs' mathematics being proved by the Large Hadron Collider is an example.  This is why mathematics is essential for economics and finance: because we cannot experiment in economics because the system is so dynamic we need a way of disentangling the myriad of facts that we are presented with.

The main point of the 2013 post is that economic mathematicians cannot agree on "one model" for the economy.  I would suggest is that Thoma is wishing to place economists in the audience where they can objectively deduce the "true" model for the economy that enables its control.  I would suggest a better aim is to follow Mark Davis' lead and evaluate different models on the basis of the aim in mind, different aims will require different models, but now single model can accomplish multiple aims.  Anyone who recognises Mark Thoma's predicament could do worse than read three of Poincare's essays: "The Mathematical Sciences" and "The Objective Value of Science" from The Value of Science and "The Scientist and Science" from Science and Method.

I think Paul Krugman's frustration with the "freshwater guys" more troubling because it is a symptom of a general degradation of science.  I worry that scientific discourse has degenerated into the accumulation of publications.  For example. I have been critical of an important (because it is cited) paper on financial stability.  My issue is that the authors - physicists - construct a discrete-time/finite state economy that they show becomes unstable when the number of assets traded is four times the number of possible states.  Cramer's Rule tells me that as soon as the number of states equals the number of assets, the economy becomes deterministic (it is 'complete'). One of the authors responded to my criticism, which was nice.  But what troubled me was this attitude

As for any paper, there is a time to defend it, which is when it is submitted to a journal and it goes to the referees. Once published, it should defend by itself. 

This implies to me that the author believes that a claim is "justified" if two or three (like minded) individuals   agree with what is claimed.  My criticism need not be considered, and if I have a criticism I should not raise it publicly, but privately.

I think beliefs like these are at the root of Krugman's concern.  If my friends and I can come up with a coherent set of claims that we can get peer-reviewed and published, they justified. I do not have to justify my claims to criticism, particularly external criticism.  This is not a problem of economics but much of what is currently perceived as science: it is a feature of the climate debate and pharmaceutical research.  It is damaging to science but corrosive to society as a whole where politics is dominated by the sound bite and "fact" with little effort or interest of many politicians to justify themselves.  I believe the popularity of UKIP, the 'Tea Party' and Front National are the consequences of  mainstream political leaders to justify their claims in any meaningful way.

My objection to objectivity is that it elevates the scientist to a position of authority that cannot be challenged by non-scientists, or scientists that you do not disagree with.  Suggesting that scientists accept they acknowledge they are on the stage diminishes their authority, they become fallible, but in doing so I think we can actually solve problems rather than fail to control situations.