l Application of Adult-Learning Principles to Patient Instructions: A Usability Study for an Exenatide Once-Weekly Injection Device By clinical.diabetesjournals.org Published On :: 2010-09-01 Gayle LorenziSep 1, 2010; 28:157-162Bridges to Excellence Full Article
l Engaging Patients in Education for Self-Management in an Accountable Care Environment By clinical.diabetesjournals.org Published On :: 2011-07-01 Christine A. BeebeJul 1, 2011; 29:123-126Practical Pointers Full Article
l Helping Patients Make and Sustain Healthy Changes: A Brief Introduction to Motivational Interviewing in Clinical Diabetes Care By clinical.diabetesjournals.org Published On :: 2008-10-01 Michele HeislerOct 1, 2008; 26:161-165Practical Pointers Full Article
l Hospital Management of Hyperglycemia By clinical.diabetesjournals.org Published On :: 2004-04-01 Kristen B. CampbellApr 1, 2004; 22:81-88Practical Pointers Full Article
l Diabetes Self-Management in a Community Health Center: Improving Health Behaviors and Clinical Outcomes for Underserved Patients By clinical.diabetesjournals.org Published On :: 2008-01-01 Daren AndersonJan 1, 2008; 26:22-27Bridges to Excellence Full Article
l Cardiac Manifestations of Congenital Generalized Lipodystrophy By clinical.diabetesjournals.org Published On :: 2016-10-01 Vani P. SanonOct 1, 2016; 34:181-186Feature Articles Full Article
l Hypoglycemia in Type 1 and Type 2 Diabetes: Physiology, Pathophysiology, and Management By clinical.diabetesjournals.org Published On :: 2006-07-01 Vanessa J. BriscoeJul 1, 2006; 24:115-121Feature Articles Full Article
l Standards of Medical Care in Diabetes--2019 Abridged for Primary Care Providers By clinical.diabetesjournals.org Published On :: 2019-01-01 American Diabetes AssociationJan 1, 2019; 37:11-34Position Statements Full Article
l Perspectives in Gestational Diabetes Mellitus: A Review of Screening, Diagnosis, and Treatment By clinical.diabetesjournals.org Published On :: 2007-04-01 Jennifer M. PerkinsApr 1, 2007; 25:57-62Feature Articles Full Article
l Amylin Replacement With Pramlintide in Type 1 and Type 2 Diabetes: A Physiological Approach to Overcome Barriers With Insulin Therapy By clinical.diabetesjournals.org Published On :: 2002-07-01 John B. BuseJul 1, 2002; 20:Feature Articles Full Article
l The Disparate Impact of Diabetes on Racial/Ethnic Minority Populations By clinical.diabetesjournals.org Published On :: 2012-07-01 Edward A. ChowJul 1, 2012; 30:130-133Diabetes Advocacy Full Article
l Standards of Medical Care in Diabetes--2016 Abridged for Primary Care Providers By clinical.diabetesjournals.org Published On :: 2016-01-01 American Diabetes AssociationJan 1, 2016; 34:3-21Position Statements Full Article
l What's So Tough About Taking Insulin? Addressing the Problem of Psychological Insulin Resistance in Type 2 Diabetes By clinical.diabetesjournals.org Published On :: 2004-07-01 William H. PolonskyJul 1, 2004; 22:147-150Practical Pointers Full Article
l A Real-World Approach to Insulin Therapy in Primary Care Practice By clinical.diabetesjournals.org Published On :: 2005-04-01 Irl B. HirschApr 1, 2005; 23:78-86Practical Pointers Full Article
l Standards of Medical Care in Diabetes--2018 Abridged for Primary Care Providers By clinical.diabetesjournals.org Published On :: 2018-01-01 American Diabetes AssociationJan 1, 2018; 36:14-37Position Statements Full Article
l Standards of Medical Care in Diabetes--2017 Abridged for Primary Care Providers By clinical.diabetesjournals.org Published On :: 2017-01-01 American Diabetes AssociationJan 1, 2017; 35:5-26Position Statements Full Article
l Standards of Medical Care in Diabetes--2015 Abridged for Primary Care Providers By clinical.diabetesjournals.org Published On :: 2015-04-01 American Diabetes AssociationApr 1, 2015; 33:97-111Position Statements Full Article
l Empowerment and Self-Management of Diabetes By clinical.diabetesjournals.org Published On :: 2004-07-01 Martha M. FunnellJul 1, 2004; 22:123-127Feature Articles Full Article
l Microvascular and Macrovascular Complications of Diabetes By clinical.diabetesjournals.org Published On :: 2008-04-01 Michael J. FowlerApr 1, 2008; 26:77-82Diabetes Foundation Full Article
l The Heroic Leadership Imperative By blog.richmond.edu Published On :: Fri, 06 Mar 2020 15:34:27 +0000 Allison, S. T. & Goethals, G. R. (2020). The heroic leadership imperative: How leaders inspire and mobilize change. West Yorkshire: Emerald. Our next book describes a new principle that we call the heroic leadership imperative. We show how leaders who fulfill the imperative will inspire followers and initiate social change. The imperative consists of … Continue reading The Heroic Leadership Imperative → Full Article Our latest books on HEROIC LEADERS
l 10 Examples of Heroism Arising From the COVID-19 Pandemic By blog.richmond.edu Published On :: Sat, 04 Apr 2020 20:26:56 +0000 By Scott T. Allison In any tragedy or crisis, you will see many people standing out and stepping up to save lives and make the world a better place. These heroic individuals can range from leaders of nations to ordinary citizens who rise to the occasion to help others in need. During this COVID-19 pandemic, … Continue reading 10 Examples of Heroism Arising From the COVID-19 Pandemic → Full Article Commentary and Analysis COVID19 heroes
l The Miniseries ‘Devs’ Delivers a Delicious Dose of Heroism and Villainy By blog.richmond.edu Published On :: Mon, 20 Apr 2020 13:06:15 +0000 By Scott T. Allison Devs is the ideal TV mini-series for people to sink their teeth into, for many reasons: (1) It’s both science and science-fiction; (2) it’s brilliant mix of psychology, philosophy, religion, and technology; (3) it tantalizes us with the mysteries of love, life, death, time, and space; and (4) it features a … Continue reading The Miniseries ‘Devs’ Delivers a Delicious Dose of Heroism and Villainy → Full Article Commentary and Analysis
l Heroism Science: Call for Papers, Special Issue: The Heroism of Whistleblowers By blog.richmond.edu Published On :: Tue, 21 Apr 2020 17:11:14 +0000 Heroism Science: Call for Papers, Special Issue The Heroism of Whistleblowers Edited by Ari Kohen, Brian Riches, and Matt Langdon Whistleblowers speak up with “concerns or information about wrongdoing inside organizations and institutions.” As such, whistleblowing “can be one of the most important and difficult forms of heroism in modern society” (Brown, 2016 p. 1). … Continue reading Heroism Science: Call for Papers, Special Issue: The Heroism of Whistleblowers → Full Article Activist Heroes
l The Innovation Dilemma By decisions-and-info-gaps.blogspot.com Published On :: Tue, 09 Aug 2011 10:09:00 +0000 "If it ain't broken, don't fix it."Sound advice, but limited to situations where "fixing it" only entails restoring past performance. In contrast, innovations entail substantive improvements over the past. Innovations are not just corrections of past mistakes, but progress towards a better future.However, innovations often present a challenging dilemma to decision makers. Many decisions require choosing between options, one of which is both potentially better in the outcome but markedly more uncertain. In these situations the decision maker faces an "innovation dilemma."The innovation dilemma arises in many contexts. Here are a few examples.Technology. New and innovative technologies are often advocated because of their purported improvements on existing products or methods. However, what is new is usually less well-known and less widely tested than what is old. The range of possible adverse (or favorable) surprises of an innovative technology may exceed the range of surprise for a tried-and-true technology. The analyst who must choose between innovation and convention faces an innovation dilemma.Investment. The economic investor faces an innovation dilemma when choosing between investing in a promising but unknown new start-up and investing in a well-known existing firm.Auction. "Nothing ventured, nothing gained" is the motto of the risk-taker, while the risk-avoider responds: "Nothing ventured, nothing lost". The innovation dilemma is embedded in the choice between these two strategies. Consider for example the "winner's curse" in auction theory. You can make a financial bid for a valuable piece of property, which will be sold to the highest bidder. You have limited information about the other bidders and about the true value of the property. If you bid high you might win the auction but you might also pay more than the property is worth. Not bidding is risk-free because it avoids the purchase. The choice between a high bid and no bid is an innovation dilemma.Employer decision. An employer must decide whether or not to replace a current satisfactory employee with a new candidate whose score on a standardized test was high. A high score reflects great ability. However, the score also contains a random element, so a high score may result from chance, and not reflect true ability. The innovation dilemma is embedded in the employer's choice between the current adequate employee and a high-scoring new candidate.Natural resource exploitation. Permitting the extraction of offshore petroleum resources may be productive in terms of petroleum yield but may also present officials with significant uncertainty about environmental consequences.Public health. Implementation of a large-scale immunization program may present policy officials with worries about uncertain side effects.Agricultural policy. New technologies promise improved production efficiency or new consumer choices, but with uncertain benefits and costs and potential unanticipated adverse effects resulting from use of manufactured inputs such as fertilizers, pesticides, and machinery, and, more recently, genetically engineered seed varieties and information technology. (I am indebted to L. Joe Moffitt and Craig Osteen for these examples in natural resources, public health and agriculture.)An essay like this one should - according to custom - end with a practical prescription: What to do about the innovation dilemma? You need to make a decision - a choice between options - and you face an innovation dilemma. How to choose? All I'll say is that the first step is to identify what you need to achieve from this decision. Recognizing the vast uncertainties which accompany the decision, choose the option which achieves the required outcome over the largest range of uncertain contingencies.If you want more of an answer than that, consult your favorite decision theory (like info-gap theory, for instance).I will conclude by drawing a parallel between the innovation dilemma and one of the oldest quandaries in political philosophy. In The Evolution of Political Thought C. Northcote Parkinson explains the historically recurring tension between freedom and equality.Freedom. People have widely varying interests and aptitudes. Hence a society that offers broad freedom for individuals to exploit their abilities, will also develop a wide spread of wealth, accomplishment, and status. Freedom enables individuals to explore, invent, discover, and create. Freedom is the recipe for innovation. Freedom induces both uncertainty and inequality.Equality. People have widely varying interests and aptitudes. Hence a society that strives for equality among its members can achieve this by enforcing conformity and by transferring wealth from rich to poor. The promise of a measure of equality is a guarantee of a measure of security, a personal and social safety net. Equality reduces both uncertainty and freedom.The dilemma is that a life without freedom is hardly human, but freedom without security is the jungle. And life in the jungle, as Hobbs explained, in "solitary, poor, nasty, brutish and short". Full Article innovation dilemma
l No-Failure Design and Disaster Recovery: Lessons from Fukushima By decisions-and-info-gaps.blogspot.com Published On :: Tue, 09 Aug 2011 10:21:00 +0000 One of the striking aspects of the early stages of the nuclear accident at Fukushima-Daiichi last March was the nearly total absence of disaster recovery capability. For instance, while Japan is a super-power of robotic technology, the nuclear authorities had to import robots from France for probing the damaged nuclear plants. Fukushima can teach us an important lesson about technology.The failure of critical technologies can be disastrous. The crash of a civilian airliner can cause hundreds of deaths. The meltdown of a nuclear reactor can release highly toxic isotopes. Failure of flood protection systems can result in vast death and damage. Society therefore insists that critical technologies be designed, operated and maintained to extremely high levels of reliability. We benefit from technology, but we also insist that the designers and operators "do their best" to protect us from their dangers.Industries and government agencies who provide critical technologies almost invariably act in good faith for a range of reasons. Morality dictates responsible behavior, liability legislation establishes sanctions for irresponsible behavior, and economic or political self-interest makes continuous safe operation desirable.The language of performance-optimization − not only doing our best, but also achieving the best − may tend to undermine the successful management of technological danger. A probability of severe failure of one in a million per device per year is exceedingly − and very reassuringly − small. When we honestly believe that we have designed and implemented a technology to have vanishingly small probability of catastrophe, we can honestly ignore the need for disaster recovery.Or can we?Let's contrast this with an ethos that is consistent with a thorough awareness of the potential for adverse surprise. We now acknowledge that our predictions are uncertain, perhaps highly uncertain on some specific points. We attempt to achieve very demanding outcomes − for instance vanishingly small probabilities of catastrophe − but we recognize that our ability to reliably calculate such small probabilities is compromised by the deficiency of our knowledge and understanding. We robustify ourselves against those deficiencies by choosing a design which would be acceptable over a wide range of deviations from our current best understanding. (This is called "robust-satisficing".) Not only does "vanishingly small probability of failure" still entail the possibility of failure, but our predictions of that probability may err.Acknowledging the need for disaster recovery capability (DRC) is awkward and uncomfortable for designers and advocates of a technology. We would much rather believe that DRC is not needed, that we have in fact made catastrophe negligible. But let's not conflate good-faith attempts to deal with complex uncertainties, with guaranteed outcomes based on full knowledge. Our best models are in part wrong, so we robustify against the designer's bounded rationality. But robustness cannot guarantee success. The design and implementation of DRC is a necessary part of the design of any critical technology, and is consistent with the strategy of robust satisficing.One final point: moral hazard and its dilemma. The design of any critical technology entails two distinct and essential elements: failure prevention and disaster recovery. What economists call a `moral hazard' exists since the failure prevention team might rely on the disaster-recovery team, and vice versa. Each team might, at least implicitly, depend on the capabilities of the other team, and thereby relinquish some of its own responsibility. Institutional provisions are needed to manage this conflict.The alleviation of this moral hazard entails a dilemma. Considerations of failure prevention and disaster recovery must be combined in the design process. The design teams must be aware of each other, and even collaborate, because a single coherent system must emerge. But we don't want either team to relinquish any responsibility. On the one hand we want the failure prevention team to work as though there is no disaster recovery, and the disaster recovery team should presume that failures will occur. On the other hand, we want these teams to collaborate on the design.This moral hazard and its dilemma do not obviate the need for both elements of the design. Fukushima has taught us an important lesson by highlighting the special challenge of high-risk critical technologies: design so failure cannot occur, and prepare to respond to the unanticipated. Full Article
l Baseball and Linguistic Uncertainty By decisions-and-info-gaps.blogspot.com Published On :: Sun, 21 Aug 2011 14:00:00 +0000 In my youth I played an inordinate amount of baseball, collected baseball cards, and idolized baseball players. I've outgrown all that but when I'm in the States during baseball season I do enjoy watching a few innings on the TV.So I was watching a baseball game recently and the commentator was talking about the art of pitching. Throwing a baseball, he said, is like shooting a shotgun. You get a spray. As a pitcher, you have to know your spray. You learn to control it, but you know that it is there. The ball won't always go where you want it. And furthermore, where you want the ball depends on the batter's style and strategy, which vary from pitch to pitch for every batter.That's baseball talk, but it stuck in my mind. Baseball pitchers must manage uncertainty! And it is not enough to reduce it and hope for the best. Suppose you want to throw a strike. It's not a good strategy to aim directly at, say, the lower outside corner of the strike zone, because of the spray of the ball's path and because the batter's stance can shift. Especially if the spray is skewed down and out, you'll want to move up and in a bit.This is all very similar to the ambiguity of human speech when we pitch words at each other. Words don't have precise meanings; meanings spread out like the pitcher's spray. If we want to communicate precisely we need to be aware of this uncertainty, and manage it, taking account of the listener's propensities.Take the word "liberal" as it is used in political discussion.For many decades, "liberals" have tended to support high taxes to provide generous welfare, public medical insurance, and low-cost housing. They advocate liberal (meaning magnanimous or abundant) government involvement for the citizens' benefit.A "liberal" might also be someone who is open-minded and tolerant, who is not strict in applying rules to other people, or even to him or herself. Such a person might be called "liberal" (meaning advocating individual rights) for opposing extensive government involvement in private decisions. For instance, liberals (in this second sense) might oppose high taxes since they reduce individuals' ability to make independent choices. As another example, John Stuart Mill opposed laws which restricted the rights of women to work (at night, for instance), even though these laws were intended to promote the welfare of women. Women, insisted Mill, are intelligent adults and can judge for themselves what is good for them.Returning to the first meaning of "liberal" mentioned above, people of that strain may support restrictions of trade to countries which ignore the health and safety of workers. The other type of "liberal" might tend to support unrestricted trade.Sending out words and pitching baseballs are both like shooting a shotgun: meanings (and baseballs) spray out. You must know what meaning you wish to convey, and what other meanings the word can have. The choice of the word, and the crafting of its context, must manage the uncertainty of where the word will land in the listener's mind.Let's go back to baseball again.If there were no uncertainty in the pitcher's pitch and the batter's swing, then baseball would be a dreadfully boring game. If the batter knows exactly where and when the ball will arrive, and can completely control the bat, then every swing will be a homer. Or conversely, if the pitcher always knows exactly how the batter will swing, and if each throw is perfectly controlled, then every batter will strike out. But which is it? Whose certainty dominates? The batter's or the pitcher's? It can't be both. There is some deep philosophical problem here. Clearly there cannot be complete certainty in a world which has some element of free will, or surprise, or discovery. This is not just a tautology, a necessary result of what we mean by "uncertainty" and "surprise". It is an implication of limited human knowledge. Uncertainty - which makes baseball and life interesting - is inevitable in the human world.How does this carry over to human speech?It is said of the Wright brothers that they thought so synergistically that one brother could finish an idea or sentence begun by the other. If there is no uncertainty in what I am going to say, then you will be bored with my conversation, or at least, you won't learn anything from me. It is because you don't know what I mean by, for instance, "robustness", that my speech on this topic is enlightening (and maybe interesting). And it is because you disagree with me about what robustness means (and you tell me so), that I can perhaps extend my own understanding.So, uncertainty is inevitable in a world that is rich enough to have surprise or free will. Furthermore, this uncertainty leads to a process - through speech - of discovery and new understanding. Uncertainty, and the use of language, leads to discovery.Isn't baseball an interesting game? Full Article
l Robustness and Locke's Wingless Gentleman By decisions-and-info-gaps.blogspot.com Published On :: Tue, 20 Sep 2011 07:49:00 +0000 Our ancestors have made decisions under uncertainty ever since they had to stand and fight or run away, eat this root or that berry, sleep in this cave or under that bush. Our species is distinguished by the extent of deliberate thought preceding decision. Nonetheless, the ability to decide in the face of the unknown was born from primal necessity. Betting is one of the oldest ways of deciding under uncertainty. But you bet you that 'bet' is a subtler concept than one might think.We all know what it means to make a bet, but just to make sure let's quote the Oxford English Dictionary: "To stake or wager (a sum of money, etc.) in support of an affirmation or on the issue of a forecast." The word has been around for quite a while. Shakespeare used the verb in 1600: "Iohn a Gaunt loued him well, and betted much money on his head." (Henry IV, Pt. 2 iii. ii. 44). Drayton used the noun in 1627 (and he wasn't the first): "For a long while it was an euen bet ... Whether proud Warwick, or the Queene should win."An even bet is a 50-50 chance, an equal probability of each outcome. But betting is not always a matter of chance. Sometimes the meaning is just the opposite. According to the OED 'You bet' or 'You bet you' are slang expressions meaning 'be assured, certainly'. For instance: "'Can you handle this outfit?' 'You bet,' said the scout." (D.L.Sayers, Lord Peter Views Body, iv. 68). Mark Twain wrote "'I'll get you there on time' - and you bet you he did, too." (Roughing It, xx. 152).So 'bet' is one of those words whose meaning stretches from one idea all the way to its opposite. Drayton's "even bet" between Warwick and the Queen means that he has no idea who will win. In contrast, Twain's "you bet you" is a statement of certainty. In Twain's or Sayers' usage, it's as though uncertainty combines with moral conviction to produce a definite resolution. This is a dialectic in which doubt and determination form decisiveness.John Locke may have had something like this in mind when he wrote:"If we will disbelieve everything, because we cannot certainly know all things; we shall do muchwhat as wisely as he, who would not use his legs, but sit still and perish, because he had no wings to fly." (An Essay Concerning Human Understanding, 1706, I.i.5)The absurdity of Locke's wingless gentleman starving in his chair leads us to believe, and to act, despite our doubts. The moral imperative of survival sweeps aside the paralysis of uncertainty. The consequence of unabated doubt - paralysis - induces doubt's opposite: decisiveness.But rational creatures must have some method for reasoning around their uncertainties. Locke does not intend for us to simply ignore our ignorance. But if we have no way to place bets - if the odds simply are unknown - then what are we to do? We cannot "sit still and perish".This is where the strategy of robustness comes in.'Robust' means 'Strong and hardy; sturdy; healthy'. By implication, something that is robust is 'not easily damaged or broken, resilient'. A statistical test is robust if it yields 'approximately correct results despite the falsity of certain of the assumptions underlying it' or despite errors in the data. (OED)A decision is robust if its outcome is satisfactory despite error in the information and understanding which justified or motivated the decision. A robust decision is resilient to surprise, immune to ignorance.It is no coincidence that the colloquial use of the word 'bet' includes concepts of both chance and certainty. A good bet can tolerate large deviation from certainty, large error of information. A good bet is robust to surprise. 'You bet you' does not mean that the world is certain. It means that the outcome is certain to be acceptable, regardless of how the world turns out. The scout will handle the outfit even if there is a rogue in the ranks; Twain will get there on time despite snags and surprises. A good bet is robust to the unknown. You bet you!An extended and more formal discussion of these issues can be found elsewhere. Full Article betting robustness
l Beware the Rareness Illusion When Exploring the Unknown By decisions-and-info-gaps.blogspot.com Published On :: Thu, 06 Oct 2011 12:14:00 +0000 Here's a great vacation idea. Spend the summer roaming the world in search of the 10 lost tribes of Israel, exiled from Samaria by the Assyrians 2700 years ago (2 Kings 17:6). Or perhaps you'd like to search for Prester John, the virtuous ruler of a kingdom lost in the Orient? Or would you rather trace the gold-laden kingdom of Ophir (1 Kings 9:28)? Or do you prefer the excitement of tracking the Amazons, that nation of female warriors? Or perhaps the naval power mentioned by Plato, operating from the island of Atlantis? Or how about unicorns, or the fountain of eternal youth? The Unknown is so vast that the possibilities are endless.Maybe you don't believe in unicorns. But Plato evidently "knew" about the island of Atlantis. The conquest of Israel is known from Assyrian archeology and from the Bible. That you've never seen a Reubenite or a Naphtalite (or a unicorn) means that they don't exist?It is true that when something really does not exist, one might spend a long time futilely looking for it. Many people have spent enormous energy searching for lost tribes, lost gold, and lost kingdoms. Why is it so difficult to decide that what you're looking for really isn't there? The answer, ironically, is that the world has endless possibilities for discovery and surprise.Let's skip vacation plans and consider some real-life searches. How long should you (or the Libyans) look for Muammar Qaddafi? If he's not in the town of Surt, maybe he's Bani Walid, or Algeria, or Timbuktu? How do you decide he cannot be found? Maybe he was pulverized by a NATO bomb. It's urgent to find the suicide bomber in the crowded bus station before it's too late - if he's really there. You'd like to discover a cure for AIDS, or a method to halt the rising global temperature, or a golden investment opportunity in an emerging market, or a proof of the parallel postulate of Euclidean geometry.Let's focus our question. Suppose you are looking for something, and so far you have only "negative" evidence: it's not here, it's not there, it's not anywhere you've looked. Why is it so difficult to decide, conclusively and confidently, that it simply does not exist?This question is linked to a different question: how to make the decision that "it" (whatever it is) does not exist. We will focus on the "why" question, and leave the "how" question to students of decision theories such as statistics, fuzzy logic, possibility theory, Dempster-Shafer theory and info-gap theory. (If you're interested in an info-gap application to statistics, here is an example.)Answers to the "why" question can be found in several domains.Psychology provides some answers. People can be very goal oriented, stubborn, and persistent. Marco Polo didn't get to China on a 10-hour plane flight. The round trip took him 24 years, and he didn't travel business class.Ideology is a very strong motivator. When people believe something strongly, it is easy for them to ignore evidence to the contrary. Furthermore, for some people, the search itself is valued more than the putative goal.The answer to the "why" question that I will focus on is found by contemplating The Endless Unknown. It is so vast, so unstructured, so, well ..., unknown, that we cannot calibrate our negative evidence to decide that whatever we're looking for just ain't there.I'll tell a true story.I was born in the US and my wife was born in Israel, but our life-paths crossed, so to speak, before we were born. She had a friend whose father was from Europe and lived for a while - before the friend was born - with a cousin of his in my home town. This cousin was - years later - my 3rd grade teacher. My school teacher was my future wife's friend's father's cousin.Amazing coincidence. This convoluted sequence of events is certainly rare. How many of you can tell the very same story? But wait a minute. This convoluted string of events could have evolved in many many different ways, each of which would have been an equally amazing coincidence. The number of similar possible paths is namelessly enormous, uncountably humongous. In other words, potential "rare" events are very numerous. Now that sounds like a contradiction (we're getting close to some of Zeno's paradoxes, and Aristotle thought Zeno was crazy). It is not a contradiction; it is only a "rareness illusion" (something like an optical illusion). The specific event sequence in my story is unique, which is the ultimate rarity. We view this sequence as an amazing coincidence because we cannot assess the number of similar sequences. Surprising strings of events occur not infrequently because the number of possible surprising strings is so unimaginably vast. The rareness illusion is the impression of rareness arising from our necessary ignorance of the vast unknown. "Necessary" because, by definition, we cannot know what is unknown. "Vast" because the world is so rich in possibilities.The rareness illusion is a false impression, a mistake. For instance, it leads people to wrongly goggle at strings of events - rare in themselves - even though "rare events" are numerous and "amazing coincidences" occur all the time. An appreciation of the richness and boundlessness of the Unknown is an antidote for the rareness illusion.Recognition of the rareness illusion is the key to understanding why it is so difficult to confidently decide, based on negative evidence, that what you're looking for simply does not exist.One might be inclined to reason as follows. If you're looking for something, then look very thoroughly, and if you don't find it, then it's not there. That is usually sound and sensible advice, and often "looking thoroughly" will lead to discovery.However, the number of ways that we could overlook something that really is there is enormous. It is thus very difficult to confidently conclude that the search was thorough and that the object cannot be found. Take the case of your missing house keys. They dropped from your pocket in the car, or on the sidewalk and somebody picked them up, or you left them in the lock when you left the house, or or or .... Familiarity with the rareness illusion makes it very difficult to decide that you have searched thoroughly. If you think that the only contingencies not yet explored are too exotic to be relevant (a raven snatched them while you were daydreaming about that enchanting new employee), then think again, because you've been blinded by a rareness illusion. The number of such possibilities is so vastly unfathomable that you cannot confidently say that all of them are collectively negligible. Recognition of the rareness illusion prevents you from confidently concluding that what you are seeking simply does not exist.Many quantitative tools grapple with the rareness illusion. We mentioned some decision theories earlier. But because the rareness illusion derives from our necessary ignorance of the vast unknown, one must always beware.Looking for an exciting vacation? The Endless Unknown is the place to go. Full Article rareness illusion
l Squirrels and Stock Brokers, Or: Innovation Dilemmas, Robustness and Probability By decisions-and-info-gaps.blogspot.com Published On :: Sun, 09 Oct 2011 11:51:00 +0000 Decisions are made in order to achieve desirable outcomes. An innovation dilemma arises when a seemingly more attractive option is also more uncertain than other options. In this essay we explore the relation between the innovation dilemma and the robustness of a decision, and the relation between robustness and probability. A decision is robust to uncertainty if it achieves required outcomes despite adverse surprises. A robust decision may differ from the seemingly best option. Furthermore, robust decisions are not based on knowledge of probabilities, but can still be the most likely to succeed.Squirrels, Stock-Brokers and Their DilemmasDecision problems.Imagine a squirrel nibbling acorns under an oak tree. They're pretty good acorns, though a bit dry. The good ones have already been taken. Over in the distance is a large stand of fine oaks. The acorns there are probably better. But then, other squirrels can also see those trees, and predators can too. The squirrel doesn't need to get fat, but a critical caloric intake is necessary before moving on to other activities. How long should the squirrel forage at this patch before moving to the more promising patch, if at all?Imagine a hedge fund manager investing in South African diamonds, Australian Uranium, Norwegian Kroners and Singapore semi-conductors. The returns have been steady and good, but not very exciting. A new hi-tech start-up venture has just turned up. It looks promising, has solid backing, and could be very interesting. The manager doesn't need to earn boundless returns, but it is necessary to earn at least a tad more than the competition (who are also prowling around). How long should the manager hold the current portfolio before changing at least some of its components?These are decision problems, and like many other examples, they share three traits: critical needs must be met; the current situation may or may not be adequate; other alternatives look much better but are much more uncertain. To change, or not to change? What strategy to use in making a decision? What choice is the best bet? Betting is a surprising concept, as we have seen before; can we bet without knowing probabilities?Solution strategies.The decision is easy in either of two extreme situations, and their analysis will reveal general conclusions.One extreme is that the status quo is clearly insufficient. For the squirrel this means that these crinkled rotten acorns won't fill anybody's belly even if one nibbled here all day long. Survival requires trying the other patch regardless of the fact that there may be many other squirrels already there and predators just waiting to swoop down. Similarly, for the hedge fund manager, if other funds are making fantastic profits, then something has to change or the competition will attract all the business.The other extreme is that the status quo is just fine, thank you. For the squirrel, just a little more nibbling and these acorns will get us through the night, so why run over to unfamiliar oak trees? For the hedge fund manager, profits are better than those of any credible competitor, so uncertain change is not called for.From these two extremes we draw an important general conclusion: the right answer depends on what you need. To change, or not to change, depends on what is critical for survival. There is no universal answer, like, "Always try to improve" or "If it's working, don't fix it". This is a very general property of decisions under uncertainty, and we will call it preference reversal. The agent's preference between alternatives depends on what the agent needs in order to "survive".The decision strategy that we have described is attuned to the needs of the agent. The strategy attempts to satisfy the agent's critical requirements. If the status quo would reliably do that, then stay put; if not, then move. Following the work of Nobel Laureate Herbert Simon, we will call this a satisficing decision strategy: one which satisfies a critical requirement."Prediction is always difficult, especially of the future." - Robert Storm PetersenNow let's consider a different decision strategy that squirrels and hedge fund managers might be tempted to use. The agent has obtained information about the two alternatives by signals from the environment. (The squirrel sees grand verdant oaks in the distance, the fund manager hears of a new start up.) Given this information, a prediction can be made (though the squirrel may make this prediction based on instincts and without being aware of making it). Given the best available information, the agent predicts which alternative would yield the better outcome. Using this prediction, the decision strategy is to choose the alternative whose predicted outcome is best. We will call this decision strategy best-model optimization. Note that this decision strategy yields a single universal answer to the question facing the agent. This strategy uses the best information to find the choice that - if that information is correct - will yield the best outcome. Best-model optimization (usually) gives a single "best" decision, unlike the satisficing strategy that returns different answers depending on the agent's needs.There is an attractive logic - and even perhaps a moral imperative - to use the best information to make the best choice. One should always try to do one's best. But the catch in the argument for best-model optimization is that the best information may actually be grievously wrong. Those fine oak trees might be swarming with insects who've devoured the acorns. Best-model optimization ignores the agent's central dilemma: stay with the relatively well known but modest alternative, or go for the more promising but more uncertain alternative."Tsk, tsk, tsk" says our hedge fund manager. "My information already accounts for the uncertainty. I have used a probabilistic asset pricing model to predict the likelihood that my profits will beat the competition for each of the two alternatives."Probabilistic asset pricing models are good to have. And the squirrel similarly has evolved instincts that reflect likelihoods. But a best-probabilistic-model optimization is simply one type of best-model optimization, and is subject to the same vulnerability to error. The world is full of surprises. The probability functions that are used are quite likely wrong, especially in predicting the rare events that the manager is most concerned to avoid.Robustness and ProbabilityNow we come to the truly amazing part of the story. The satisficing strategy does not use any probabilistic information. Nonetheless, in many situations, the satisficing strategy is actually a better bet (or at least not a worse bet), probabilistically speaking, than any other strategy, including best-probabilistic-model optimization. We have no probabilistic information in these situations, but we can still maximize the probability of success (though we won't know the value of this maximum).When the satisficing decision strategy is the best bet, this is, in part, because it is more robust to uncertainty than another other strategy. A decision is robust to uncertainty if it achieves required outcomes even if adverse surprises occur. In many important situations (though not invariably), more robustness to uncertainty is equivalent to being more likely to succeed or survive. When this is true we say that robustness is a proxy for probability.A thorough analysis of the proxy property is rather technical. However, we can understand the gist of the idea by considering a simple special case.Let's continue with the squirrel and hedge fund examples. Suppose we are completely confident about the future value (in calories or dollars) of not making any change (staying put). In contrast, the future value of moving is apparently better though uncertain. If staying put would satisfy our critical requirement, then we are absolutely certain of survival if we do not change. Staying put is completely robust to surprises so the probability of success equals 1 if we stay put, regardless of what happens with the other option. Likewise, if staying put would not satisfy our critical requirement, then we are absolutely certain of failure if we do not change; the probability of success equals 0 if we stay, and moving cannot be worse. Regardless of what probability distribution describes future outcomes if we move, we can always choose the option whose likelihood of success is greater (or at least not worse). This is because staying put is either sure to succeed or sure to fail, and we know which.This argument can be extended to the more realistic case where the outcome of staying put is uncertain and the outcome of moving, while seemingly better than staying, is much more uncertain. The agent can know which option is more robust to uncertainty, without having to know probability distributions. This implies, in many situations, that the agent can choose the option that is a better bet for survival.Wrapping UpThe skillful decision maker not only knows a lot, but is also able to deal with conflicting information. We have discussed the innovation dilemma: When choosing between two alternatives, the seemingly better one is also more uncertain.Animals, people, organizations and societies have developed mechanisms for dealing with the innovation dilemma. The response hinges on tuning the decision to the agent's needs, and robustifying the choice against uncertainty. This choice may or may not coincide with the putative best choice. But what seems best depends on the available - though uncertain - information.The commendable tendency to do one's best - and to demand the same of others - can lead to putatively optimal decisions that may be more vulnerable to surprise than other decisions that would have been satisfactory. In contrast, the strategy of robustly satisfying critical needs can be a better bet for survival. Consider the design of critical infrastructure: flood protection, nuclear power, communication networks, and so on. The design of such systems is based on vast knowledge and understanding, but also confronts bewildering uncertainties and endless surprises. We must continue to improve our knowledge and understanding, while also improving our ability to manage the uncertainties resulting from the expanding horizon of our efforts. We must identify the critical goals and seek responses that are immune to surprise. Full Article betting innovation dilemma probability proxy property robustness
l The Language of Science and the Tower of Babel By decisions-and-info-gaps.blogspot.com Published On :: Mon, 31 Oct 2011 06:23:00 +0000 And God said: Behold one people with one language for them all ... and now nothing that they venture will be kept from them. ... [And] there God mixed up the language of all the land. (Genesis, 11:6-9)"Philosophy is written in this grand book the universe, which stands continually open to our gaze. But the book cannot be understood unless one first learns to comprehend the language and to read the alphabet in which it is composed. It is written in the language of mathematics." Galileo GalileiLanguage is power over the unknown. Mathematics is the language of science, and computation is the modern voice in which this language is spoken. Scientists and engineers explore the book of nature with computer simulations of swirling galaxies and colliding atoms, crashing cars and wind-swept buildings. The wonders of nature and the powers of technological innovation are displayed on computer screens, "continually open to our gaze." The language of science empowers us to dispel confusion and uncertainty, but only with great effort do we change the babble of sounds and symbols into useful, meaningful and reliable communication. How we do that depends on the type of uncertainty against which the language struggles.Mathematical equations encode our understanding of nature, and Galileo exhorts us to learn this code. One challenge here is that a single equation represents an infinity of situations. For instance, the equation describing a flowing liquid captures water gushing from a pipe, blood coursing in our veins, and a droplet splashing from a puddle. Gazing at the equation is not at all like gazing at the droplet. Understanding grows by exposure to pictures and examples. Computations provide numerical examples of equations that can be realized as pictures. Computations can simulate nature, allowing us to explore at our leisure.Two questions face the user of computations: Are we calculating the correct equations? Are we calculating the equations correctly? The first question expresses the scientist's ignorance - or at least uncertainty - about how the world works. The second question reflects the programmer's ignorance or uncertainty about the faithfulness of the computer program to the equations. Both questions deal with the fidelity between two entities. However, the entities involved are very different and the uncertainties are very different as well.The scientist's uncertainty is reduced by the ingenuity of the experimenter. Equations make predictions that can be tested by experiment. For instance, Galileo predicted that small and large balls will fall at the same rate, as he is reported to have tested from the tower of Pisa. Equations are rejected or modified when their predictions don't match the experimenter's observation. The scientist's uncertainty and ignorance are whittled away by testing equations against observation of the real world. Experiments may be extraordinarily subtle or difficult or costly because nature's unknown is so endlessly rich in possibilities. Nonetheless, observation of nature remorselessly cuts false equations from the body of scientific doctrine. God speaks through nature, as it were, and "the Eternal of Israel does not deceive or console." (1 Samuel, 15:29). When this observational cutting and chopping is (temporarily) halted, the remaining equations are said to be "validated" (but they remain on the chopping block for further testing).The programmer's life is, in one sense, more difficult than the experimenter's. Imagine a huge computer program containing millions of lines of code, the accumulated fruit of thousands of hours of effort by many people. How do we verify that this computation faithfully reflects the equations that have ostensibly been programmed? Of course they've been checked again and again for typos or logical faults or syntactic errors. Very clever methods are available for code verification. Nonetheless, programmers are only human, and some infidelity may slip through. What remorseless knife does the programmer have with which to verify that the equations are correctly calculated? Testing computation against observation does not allow us to distinguish between errors in the equations, errors in the program, and compensatory errors in both.The experimenter compares an equation's prediction against an observation of nature. Like the experimenter, the programmer compares the computation against something. However, for the programmer, the sharp knife of nature is not available. In special cases the programmer can compare against a known answer. More frequently the programmer must compare against other computations which have already been verified (by some earlier comparison). The verification of a computation - as distinct from the validation of an equation - can only use other high-level human-made results. The programmer's comparisons can only be traced back to other comparisons. It is true that the experimenter's tests are intermediated by human artifacts like calipers or cyclotrons. Nonetheless, bedrock for the experimenter is the "reality out there". The experimenter's tests can be traced back to observations of elementary real events. The programmer does not have that recourse. One might say that God speaks to the experimenter through nature, but the programmer has no such Voice upon which to rely.The tower built of old would have reached the heavens because of the power of language. That tower was never completed because God turned talk into babble and dispersed the people across the land. Scholars have argued whether the story prescribes a moral norm, or simply describes the way things are, but the power of language has never been disputed.The tower was never completed, just as science, it seems, has a long way to go. Genius, said Edison, is 1 percent inspiration and 99 percent perspiration. A good part of the sweat comes from getting the language right, whether mathematical equations or computer programs.Part of the challenge is finding order in nature's bubbling variety. Each equation captures a glimpse of that order, adding one block to the structure of science. Furthermore, equations must be validated, which is only a stop-gap. All blocks crumble eventually, and all equations are fallible and likely to be falsified.Another challenge in science and engineering is grasping the myriad implications that are distilled into an equation. An equation compresses and summarizes, while computer simulations go the other way, restoring detail and specificity. The fidelity of a simulation to the equation is usually verified by comparing against other simulations. This is like the dictionary paradox: using words to define words.It is by inventing and exploiting symbols that humans have constructed an orderly world out of the confusing tumult of experience. With symbols, like with blocks in the tower, the sky is the limit. Full Article
l Can We Replay History? By decisions-and-info-gaps.blogspot.com Published On :: Thu, 10 Nov 2011 07:15:00 +0000 After the kids' party games and the birthday cake came the action-packed Steve McQueen movie. My friend's parents had rented a movie projector. They hooked up the reel and let it roll. But the high point came later when they ran the movie backwards. Bullets streamed back into guns, blows were retracted and fallen protagonists recoiled into action. The mechanism that pulls the celluloid film forward for normal showing, can pull the film in the reverse direction, rolling it back onto the feeder reel and showing the movie in reverse.If you chuck a round pebble off a cliff it will fall in a graceful parabolic arch, gradually increasing its speed until it hits the ground. The same pebble, if shot from the point of impact, at the terminating angle and speed, will gracefully and obligingly retrace its path. (I'm ignoring wind and air friction that make things a bit more complicated.)Deterministic mechanisms, like the movie reel mechanism or the law of gravity, are reversible.History is different. Peoples' behavior is influenced by what they know. You pack an umbrella on a trip to the UK. Google develops search algorithms not search parties because their knowledge base is information technology not mountain trekking. Knowledge is powerful because it enables rational behavior: matching actions to goals. Knowledge transforms futile fumbling into intelligent behavior.Knowledge underlies intelligent behavior, but knowledge is continually expanding. We discover new facts and relationships. We discover that things have changed. Therefore tomorrow's knowledge-based behavior will, to some extent, be unpredictable today because tomorrow's discoveries cannot be known today. Human behavior has an inherent element of indeterminism. Intelligent learning behavior cannot be completely predicted.Personal and collective history does not unfold like a pre-woven rug. Human history is fundamentally different from the trajectory of a pebble tossed from a cliff. History is the process of uncovering the unknown and responding to this new knowledge. The existence of the unknown creates the possibility of free will. The discovery of new knowledge introduces indeterminism and irreversibility into history, as explained by the philosophers G.L.S. Shackle and Karl Popper.Nonetheless history is not erratic because each increment of new knowledge adds to the store of what was learned before. Memory is not perfect, either of individuals or groups, but it is powerful. History happens in historical context. For instance, one cannot understand the recent revolutions and upheavals in the Arab world from the perspective of 18th century European revolutions; the historical backgrounds are too different, and the outcomes in the Middle East will be different as well. Innovation, even revolution, is spurred by new knowledge laid over the old. A female municipal official slapped a Tunisian street vendor, Mohamed Bouazizi. That slap crystalized Mr Bouazizi's knowledge of his helpless social impotence and lit the match with which he immolated himself and initiated conflagrations around the Mideast. New knowledge acts like thruster engines on the inertial body of memory. What is emerging in the Mideast is Middle Eastern, not European. What is emerging is the result of new knowledge: of the power of networking, of the mortality of dictators, of the limits of coercion, of the power of new knowledge itself and the possibilities embedded in tomorrow's unknowns.Mistakes are made, even with the best intentions and the best possible knowledge. Even if analysts knew and understood all the actions of all actors on the stage of history, they still cannot know what those people will learn tomorrow and how that new knowledge will alter their behavior. Mistakes are made because history does not unwind like a celluloid reel.That's not to say that analysts are never ignorant, negligent, stupid or malicious. It's to say that all actions are, in a sense, mistakes. Or, the biggest mistake of all is to think that we can know the full import of our actions. We cannot, because actions are tossed, like pebbles, into the dark pit of unknown possible futures. One cannot know all possible echoes, or whether some echo might be glass-shatteringly cataclysmic.Mistakes can sometimes be corrected, but never undone. History cannot be run backwards, and you never get a second chance. Conversely, every instant is a new opportunity because the future is always uncertain. Uncertainty is the freedom to err, and the opportunity to create and discover. Full Article
l Picking a Theory is Like Building a Boat at Sea By decisions-and-info-gaps.blogspot.com Published On :: Sun, 11 Dec 2011 12:14:00 +0000 "We are like sailors who on the open sea must reconstruct their ship but are never able to start afresh from the bottom." Otto Neurath's analogy in the words of Willard V. QuineEngineers, economists, social planners, security strategists, and others base their plans and decisions on theories. They often argue long and hard over which theory to use. Is it ever right to use a theory that we know is empirically wrong, especially if a true (or truer) theory is available? Why is it so difficult to pick a theory?Let's consider two introductory examples.You are an engineer designing a robot. You must calculate the forces needed to achieve specified motions of the robotic arms. You can base these calculations on either of two theories. One theory assumes that an object comes to rest unless a force acts upon it. Let's call this axiom A. The other theory assumes that an object moves at constant speed unless a force acts upon it. Let's call this axiom G. Axiom A agrees with observation: Nothing moves continuously without the exertion of force; an object will come to rest unless you keep pushing it. Axiom G contradicts all observation; no experiment illustrates the perpetual motion postulated by the axiom. If all else is the same, which theory should you choose?Axiom A is Aristotle's law of inertia, which contributed little to the development of mechanical dynamics. Axiom G is Galileo's law of inertia: one of the most fruitful scientific ideas of all time. Why is an undemonstrable assertion - axiom G - a good starting point for a theory?Consider another example.You are an economist designing a market-based policy to induce firms to reduce pollution. You will use an economic theory to choose between policies. One theory assumes that firms face pure competition, meaning that no single firm can influence market prices. Another theory provides agent-based game-theoretic characterization of how firms interact (without colluding) by observing and responding to price behavior of other firms and of consumers.Pure competition is a stylized idealization (like axiom G). Game theory is much more realistic (like axiom A), but may obscure essential patterns in its massive detail. Which theory should you use?We will not address the question of how to choose a theory upon which to base a decision. We will focus on the question: why is theory selection so difficult? We will discuss four trade offs."Thanks to the negation sign, there are as many truths as falsehoods;we just can't always be sure which are which." Willard V. QuineThe tension between right and right. The number of possible theories is infinite, and sometimes it's hard to separate the wheat from the chaff, as suggested by the quote from Quine. As an example, I have a book called A Modern Guide to Macroeconomics: An Introduction to Competing Schools of Thought by Snowdon, Vane and Wynarczyk. It's a wonderful overview of about a dozen theories developed by leading economic scholars, many of them Nobel Prize Laureates. The theories are all fundamentally different. They use different axioms and concepts and they compete for adoption by economists. These theories have been studied and tested upside down and backwards. However, economic processes are very complex and variable, and the various theories succeed in different ways or in different situations, so the jury is still out. The choice of a theory is no simple matter because many different theories can all seem right in one way or another."The fox knows many things, but the hedgehog knows one big thing." ArchilochusThe fox-hedgehog tension. This aphorism by Archilochus metaphorically describes two types of theories (and two types of people). Fox-like theories are comprehensive and include all relevant aspects of the problem. Hedgehog-like theories, in contrast, skip the details and focus on essentials. Axiom A is fox-like because the complications of friction are acknowledged from the start. Axiom G is hedgehog-like because inertial resistance to change is acknowledged but the complications of friction are left for later. It is difficult to choose between these types of theories because it is difficult to balance comprehensiveness against essentialism. On the one hand, all relevant aspects of the problem should be considered. On the other hand, don't get bogged down in endless details. This fox-hedgehog tension can be managed by weighing the context, goals and implications of the decision. We won't expand on this idea since we're not considering how to choose a theory; we're only examining why it's a difficult choice. However, the idea of resolving this tension by goal-directed choice motivates the third tension."Beyond this island of meanings which in their own nature are true or falselies the ocean of meanings to which truth and falsity are irrelevant." John DeweyThe truth-meaning tension. Theories are collections of statements like axioms A and G in our first example. Statements carry meaning, and statements can be either true or false. Truth and meaning are different. For instance, "Archilochus was a Japanese belly dancer" has meaning, but is not true. The quote from Dewey expresses the idea that "meaning" is a broader description of statements than "truth". All true statements mean something, but not all meaningful statements are true. That does not imply, however, that all untrue meaningful statements are false, as we will see.We know the meanings of words and sentences from experience with language and life. A child learns the meanings of words - chair, mom, love, good, bad - by experience. Meanings are learned by pointing - this is a chair - and also by experiencing what it means to love or to be good or bad.Truth is a different concept. John Dewey wrote that"truths are but one class of meanings, namely, those in which a claim to verifiability by their consequences is an intrinsic part of their meaning. Beyond this island of meanings which in their own nature are true or false lies the ocean of meanings to which truth and falsity are irrelevant. We do not inquire whether Greek civilization was true or false, but we are immensely concerned to penetrate its meaning."A true statement, in Dewey's sense, is one that can be confirmed by experience. Many statements are meaningful, even important and useful, but neither true nor false in this experimental sense. Axiom G is an example.Our quest is to understand why the selection of a theory is difficult. Part of the challenge derives from the tension between meaning and truth. We select a theory for use in formulating and evaluating a plan or decision. The decision has implications: what would it mean to do this rather than that? Hence it is important that the meaning of the theory fit the context of the decision. Indeed, hedgehogs would say that getting the meaning and implication right is the essence of good decision making.But what if a relevantly meaningful theory is unprovable or even false? Should we use a theory that is meaningful but not verifiable by experience? Should we use a meaningful theory that is even wrong? This quandary is related to the fox-hedgehog tension because the fox's theory is so full of true statements that its meaning may be obscured, while the hedgehog's bare-bones theory has clear relevance to the decision to be made, but may be either false or too idealized to be tested.Galileo's axiom of inertia is an idealization that is unsupported by experience because friction can never be avoided. Axiom G assumes conditions that cannot be realized so the axiom can never be tested. Likewise, pure competition is an idealization that is rarely if ever encountered in practice. But these theories capture the essence of many situations. In practical terms, what it means to get the robotic arm from here to there is to apply net forces that overcome Galilean inertia. But actually designing a robot requires considering details of dissipative forces like friction. What it means to be a small business is that the market price of your product is beyond your control. But actually running a business requires following and reacting to prices in the store next door.It is difficult to choose between a relevantly meaningful but unverifiable theory, and a true theory that is perhaps not quite what we mean.The knowledge-ignorance tension. Recall that we are discussing theories in the service of decision-making by engineers, social scientists and others. A theory should facilitate the use of our knowledge and understanding. However, in some situations our ignorance is vast and our knowledge will grow. Hence a theory should also account for ignorance and be able to accommodate new knowledge.Let's take an example from theories of decision. The independence axiom is fundamental in various decision theories, for instance in von Neumann-Morgenstern expected utility theory. It says that one's choices should be independent of irrelevant alternatives. Suppose you are offered the dinner choice between chicken and fish, and you choose chicken. The server returns a few minutes later saying that beef is also available. If you switch your choice from chicken to fish you are violating the independence axiom. You prefer beef less than both chicken and fish, so the beef option shouldn't alter the fish-chicken preference.But let's suppose that when the server returned and mentioned beef, your physician advised you to reduce your cholesterol intake (so your preference for beef is lowest) which prompted your wife to say that you should eat fish at least twice a week because of vitamins in the oil. So you switch from chicken to fish. Beef is not chosen, but new information that resulted from introducing the irrelevant alternative has altered the chicken-fish preference.One could argue for the independence axiom by saying that it applies only when all relevant information (like considerations of cholesterol and fish oil) are taken into account. On the other hand, one can argue against the independence axiom by saying that new relevant information quite often surfaces unexpectedly. The difficulty is to judge the extent to which ignorance and the emergence of new knowledge should be central in a decision theory.Wrapping up. Theories express our knowledge and understanding about the unknown and confusing world. Knowledge begets knowledge. We use knowledge and understanding - that is, theory - in choosing a theory. The process is difficult because it's like building a boat on the open sea as Otto Neurath once said. Full Article
l Accidental Education By decisions-and-info-gaps.blogspot.com Published On :: Mon, 20 Feb 2012 06:31:00 +0000 "He had to take that life as he best could, with such accidental education as luck had given him". Henry AdamsI am a university professor. Universities facilitate efficient and systematic learning, so I teach classes, design courses, and develop curricula. Universities have tremendously benefitted technology, the economy, health, cultural richness and awareness, and many other "goods".Nonetheless, some important lessons are learned strictly by accident. Moreover, without accidental surprises, education would be a bit dry, sometimes even sterile. As Adams wrote: "The chief wonder of education is that it does not ruin everybody concerned in it, teachers and taught."An example. I chose my undergraduate college because of their program in anthropology. When I got there I took a chemistry course in my first semester. I was enchanted, by the prof as much as by the subject. I majored in chemistry and never went near the anthro department. If that prof had been on sabbatical I might have ended up an anthropologist.Universities promote lifelong learning. College is little more than a six-pack of knowledge, a smattering of understanding and a wisp of wisdom. But lifelong learning doesn't only mean "come back to grad school". It means perceiving those rarities and strangenesses that others don't notice. Apples must have fallen on lots of peoples' heads before some clever fellow said "Hmmm, what's going on here?".Accidental education is much more than keeping your eyes and mind open (though that is essential). To understand the deepest importance of accidental education we need to enlist two concepts: the boundlessness of the unknown, and human free will. We will then understand that accidental education feeds the potential for uniqueness of the individual.As we have explained elsewhere, in discussing grand unified theories and imagination, the unknown is richer and stranger - and more contradictory - than the single physical reality that we actually face. The unknown is the realm of all possible as well as impossible worlds. It is the domain in which our dreams and speculations wander. It may be frightening or heartening, but taken as a whole it is incoherent, contradictory and endlessly amazing, variable and stimulating.We learn about the unknown in part by speculating, wondering, and dreaming (awake and asleep). Imagining the impossible is very educational. For instance, most things are impossible for children (from tying their shoes to running the country), but they must be encouraged to imagine that they can or will be able to do them. Adults also can re-make themselves in line with their dreams. We are free and able to imagine ourselves and the world in endless new and different ways. Newton's apple brought to his mind a picture of the universe unlike any that had been imagined before. Surprises, like dreams, can free us from the mundane. Cynics sometimes sneer at personal or collective myths and musings, but the ability to re-invent ourselves is the essence of humanity. The children of Israel imagined at Sinai that the covenant was given directly to them all - men, women and children equally - with no royal or priestly intermediary. This launched the concept and the possibility of political equality.The Israelites had no map of the desert because the promised land that they sought was first of all an idea. Only after re-inventing themselves as a free people created equal in the image of God, and not slaves, only after finding a collective identity and mission, only then could they enter the land of Canaan. Theirs wanderings were random and their discoveries were accidental, but their formative value is with us to this day. No map or curriculum can organize one's wandering in the land of imagination. Unexpected events happen in the real world, but they stimulate our imagination of the infinity of other possible worlds. Our most important education is the accidental stumbling on new thoughts that feed our potential for innovation and uniqueness. For the receptive mind, accidental education can be the most sublime. Full Article
l We're Just Getting Started: A Glimpse at the History of Uncertainty By decisions-and-info-gaps.blogspot.com Published On :: Thu, 22 Mar 2012 19:12:00 +0000 We've had our cerebral cortex for several tens of thousands of years. We've lived in more or less sedentary settlements and produced excess food for 7 or 8 thousand years. We've written down our thoughts for roughly 5 thousand years. And Science? The ancient Greeks had some, but science and its systematic application are overwhelmingly a European invention of the past 500 years. We can be proud of our accomplishments (quantum theory, polio vaccine, powered machines), and we should worry about our destructive capabilities (atomic, biological and chemical weapons). But it is quite plausible, as Koestler suggests, that we've only just begun to discover our cerebral capabilities. It is more than just plausible that the mysteries of the universe are still largely hidden from us. As evidence, consider the fact that the main theories of physics - general relativity, quantum mechanics, statistical mechanics, thermodynamics - are still not unified. And it goes without say that the consilient unity of science is still far from us.What holds for science in general, holds also for the study of uncertainty. The ancient Greeks invented the axiomatic method and used it in the study of mathematics. Some medieval thinkers explored the mathematics of uncertainty, but it wasn't until around 1600 that serious thought was directed to the systematic study of uncertainty, and statistics as a separate and mature discipline emerged only in the 19th century. The 20th century saw a florescence of uncertainty models. Lukaczewicz discovered 3-valued logic in 1917, and in 1965 Zadeh introduced his work on fuzzy logic. In between, Wald formulated a modern version of min-max in 1945. A plethora of other theories, including P-boxes, lower previsions, Dempster-Shafer theory, generalized information theory and info-gap theory all suggest that the study of uncertainty will continue to grow and diversify.In short, we have learned many facts and begun to understand our world and its uncertainties, but the disputes and open questions are still rampant and the yet-unformulated questions are endless. This means that innovations, discoveries, inventions, surprises, errors, and misunderstandings are to be expected in the study or management of uncertainty. We are just getting started. Full Article
l I am a Believer By decisions-and-info-gaps.blogspot.com Published On :: Mon, 23 Apr 2012 05:11:00 +0000 There are many things that I don't know. About the past: how my great-great-grandfather supported his family, how Charlemagne consolidated his imperial power, or how Rabbi Akiva became a scholar. About the future: whether I'll get that contract, how much the climate will change in the next 100 years, or when the next war will erupt. About why things are as they are: why stones fall and water freezes, or why people love or hate or don't give a damn, or why we are, period.We reflect about questions like these, trying to answer them and to learn from them. For instance, we are interested in the relations between Charlemagne and his co-ruling brother Carloman. This can tell us about brothers, about emperors, and about power. We are interested in Akiva because he purportedly started studying at the age of 40, which tells us something about the indomitable human spirit.We sometimes get to the bottom of things and understand the whys and ways of our world. We see patterns and discover laws of nature, or at least we tell stories of how things happen. Stones fall because it's their nature to seek the center of the world (Aristotle), or due to gravitational attraction (Newton), or because of mass-induced space warp (Einstein). Human history has its patterns, driven by the will to power of heroic leaders, or by the unfolding of truth and justice, or by God's hand in history.We also think about thinking itself, as suggested by Rodin's Thinker. What is thinking (or what do we think it is)? Is thinking a physical process, like electrons whirling in our brain? Or does thinking involve something transcendental; maybe the soul whirling in the spheres? Each age has its answers.We sometimes get stuck, and can't figure things out or get to the bottom of things. Sometimes we even realize that there is no "bottom", that each answer brings its own questions. As John Wheeler said, "We live on an island of knowledge surrounded by a sea of ignorance. As our island of knowledge grows, so does the shore of our ignorance."Sometimes we get stuck in an even subtler way that is very puzzling, and even disturbing. Any rational chain of thought must have a starting point. Any rational justification of that starting point must have its own starting point. In other words, any attempt to rationally justify rational thought can never be completed. Rational thought cannot justify itself, which is almost the same as saying that rational thought is not justified. Any specific rational argument - Einstein's cosmology or Piaget's psychology - is justified based on its premises (and evidence, and many other things). But Rational Thought, as a method, as a way of life and a core of civilization, cannot ultimately and unequivocally justify itself.I believe that experience reflects reality, and that thought organizes experience to reveal the patterns of reality. The truth of this belief is, I believe, self evident and unavoidable. Just look around you. Flowers bloom anew each year. Planets swoop around with great regularity. We have learned enough about the world to change it, to control it, to benefit from it, even to greatly endanger our small planetary corner of it. I believe that rational thought is justified, but that's a belief, not a rational argument.Rational thought, in its many different forms, is not only justified; it is unavoidable. We can't resist it. Moses saw the flaming bush and was both frightened and curious because it was not consumed (Exodus 3:1-3). He was drawn towards it despite his fear. The Unknown draws us irresistibly on an endless search for order and understanding. The Unknown drives us to search for knowledge, and the search is not fruitless. This I believe. Full Article
l Alone By decisions-and-info-gaps.blogspot.com Published On :: Fri, 11 May 2012 05:46:00 +0000 [S]ince there is an infinity of possible worlds, there is also an infinity of possible laws, some proper to one world, others proper to another, and each possible individual of a world includes the laws of its world in its notion. Gottfried Wilhelm LeibnizOn simple matters we can agree. Water freezes and wood burns. People can agree on social or political issues, though often more from self interest than from reasoned argument.Agreement is rare or flitting on what is good or bad, worthy or worthless, humane or heartless. Are we simply not wise or intelligent or patient or convincing enough to find consensus?Agreement is rare because the realm of possibilities is boundless. Every thought or vision carries a cosmos of variations and extensions. A good idea is one that spawns new good ideas, on and on. We are told that God the creator created man and woman in his image: as creators, to be fruitful and to multiply children, and ideas, and worlds.At first we think that we are the entire world. Then we discover other worlds - things and people - and we think that they are the same as us. Then we discover that they have minds that, like ours, create their own worlds. We learn to communicate with those minds out there. We think that our meanings are their meanings, and this is true for many things, and even for many thoughts. But not for all of them. Then we discover that our deepest feelings are ours alone, and that we have created a continent whose shores are only lapped by waves from distant lands. Full Article
l Why We Need Libraries, Or, Memory and Knowledge By decisions-and-info-gaps.blogspot.com Published On :: Sat, 26 May 2012 06:19:00 +0000 "Writing is thinking in slow motion. We see what at normal speeds escapes us, can rerun the reel at will to look for errors, erase, interpolate, and rethink. Most thoughts are a light rain, fall upon the ground, and dry up. Occasionally they become a stream that runs a short distance before it disappears. Writing stands an incomparably better chance of getting somewhere."... What is written can be given endlessly and yet retained, read by thousands even while it is being rewritten, kept as it was and revised at the same time. Writing is magic." Walter KaufmannWe are able to know things because they happen again and again. We know about the sun because it glares down on us day after day. Scientists learn the laws of nature, and build confidence in their knowledge, by testing their theories over and over and getting the same results each time. We would be unable to learn the patterns and ways of our world if nothing were repeatable.But without memory, we could learn nothing even if the world were tediously repetitive. Even though the sun rises daily in the east, we could not know this if we couldn't remember it.The world has stable patterns, and we are able to discover these patterns because we remember. Knowledge requires more than memory, but memory is an essential element.The invention of writing was a great boon to knowledge because writing is collective memory. For instance, the Peloponnesian wars are known to us through Thucydides' writings. People understand themselves and their societies in part through knowing their history. History, as distinct from pre-history, depends on the written word. For example, each year at the Passover holiday, Jewish families through the ages have read the story of the Israelite exodus from Egypt. We are enjoined to see ourselves as though we were there, fleeing Egypt and trudging through the desert. Memory, recorded for all time, creates individual and collective awareness, and motivates aspirations and actions.Without writing, much collective memory would be lost, just as books themselves are sometimes lost. We know, for instance, that Euclid wrote a book called Porisms, but the book is lost and we know next to nothing about its message. Memory, and knowledge, have been lost.Memory can be uncertain. We've all experienced that on the personal level. Collective memory can also be uncertain. We're sometimes uncertain of the meaning of rare ancient words, such as lilit in Isaiah (34:14) or gvina in Job (10:10). Written traditions, while containing an element of truth, may be of uncertain meaning or veracity. For instance, we know a good deal, both from the Bible and from archeological findings, about Hezekiah who ruled the kingdom of Judea in the late 8th century BCE. About David, three centuries earlier, we can be much less certain. Biblical stories are told in great detail but corroboration is hard to obtain.Memory can be deliberately corrupted. Records of history can be embellished or prettified, as when a king commissions the chronicling of his achievements. Ancient monuments glorifying imperial conquests are invaluable sources of knowledge of past ages, but they are unreliable and must be interpreted cautiously. Records of purported events that never occurred can be maliciously fabricated. For instance, The Protocols of the Elders of Zion is pure invention, though that book has been re-published voluminously throughout the world and continues to be taken seriously by many people. Memory is alive and very real, even if it is memory of things that never happened.Libraries are the physical medium of human collective memory, and an essential element in maintaining and enlarging our knowledge. There are many types of libraries. The family library may have a few hundred books, while the library of Congress has 1,349 km of bookshelves and holds about 147 million items. Libraries can hold paper books or digital electronic documents. Paper can perish in fire as happened to the Alexandrian library, while digital media can be erased, or become damaged and unreadable. Libraries, like memory itself, are fragile and need care.Why do we need libraries? Being human means, among other things, the capacity for knowledge, and the ability to appreciate and benefit from it. The written record is a public good, like the fresh air. I can read Confucius or Isaiah centuries after they lived, and my reading does not consume them. Our collective memory is part of each individual, and preserving that memory preserves a part of each of us. Without memory, we are without knowledge. Without knowledge, we are only another animal. Full Article
l Mathematical Metaphors By decisions-and-info-gaps.blogspot.com Published On :: Sun, 28 Apr 2013 11:25:00 +0000 Theories in all areas of science tell us something about the world. They are images, or models, or representations of reality. Theories tell stories about the world and are often associated with stories about their discovery. Like the story (probably apocryphal) that Newton invented the theory of gravity after an apple fell on his head. Or the story (probably true) that Kekule discovered the cyclical structure of benzene after day-dreaming of a snake seizing its tail. Theories are metaphors that explain reality.A theory is scientific if it is precise, quantitative, and amenable to being tested. A scientific theory is mathematical. Scientific theories are mathematical metaphors.A metaphor uses a word or phrase to define or extend or focus the meaning of another word or phrase. For example, "The river of time" is a metaphor. We all know that rivers flow inevitably from high to low ground. The metaphor focuses the concept of time on its inevitable uni-directionality. Metaphors make sense because we understand what they mean. We all know that rivers are wet, but we understand that the metaphor does not mean to imply that time drips, because we understand the words and their context. But on the other hand, a metaphor - in the hands of a creative and imaginative person - might mean something unexpected, and we need to think carefully about what the metaphor does, or might, mean. Mathematical metaphors - scientific models - also focus attention in one direction rather than another, which gives them explanatory and predictive power. Mathematical metaphors can also be interpreted in different and surprising ways.Some mathematical models are very accurate metaphors. For instance, when Galileo dropped a heavy object from the leaning tower of Pisa, the distance it fell increased in proportion to the square of the elapsed time. Mathematical equations sometimes represent reality quite accurately, but we understand the representation only when the meanings of the mathematical terms are given in words. The meaning of the equation tells us what aspect of reality the model focuses on. Many things happened when Galileo released the object - it rotated, air swirled, friction developed - while the equation focuses on one particular aspect: distance versus time. Likewise, the quadratic equation that relates distance to time can also be used to relate energy to the speed of light, or to relate population growth rate to population size. In Galileo's case the metaphor relates to freely falling objects.Other models are only approximations. For example, a particular theory describes the build up of mechanical stress around a crack, causing damage in the material. While cracks often have rough or ragged shapes, this important and useful theory assumes the crack is smooth and elliptical. This mathematical metaphor is useful because it focuses the analysis on the radius of curvature of the crack that is critical in determining the concentration of stress.Not all scientific models are approximations. Some models measure something. For example, in statistical mechanics, the temperature of a material is proportional to the average kinetic energy of the molecules in the material. The temperature, in degrees centigrade, is a global measure of random molecular motion. In economics, the gross domestic product is a measure of the degree of economic activity in the country.Other models are not approximations or measures of anything, but rather graphical portrayals of a relationship. Consider, for example, the competition among three restaurants: Joe's Easy Diner, McDonald's, and Maxim's de Paris. All three restaurants compete with each other: if you're hungry, you've got to choose. Joe's and McDonald's are close competitors because they both specialize in hamburgers but also have other dishes. They both compete with Maxim's, a really swank and expensive boutique restaurant, but the competition is more remote. To model the competition we might draw a line representing "competition", with each restaurant as a dot on the line. Joe's and McDonald's are close together and far from Maxim's. This line is a mathematical metaphor, representing the proximity (and hence strength) of competition between the three restaurants. The distances between the dots are precise, but what the metaphor means, in terms of the real-world competition between Joe, McDonald, and Maxim, is not so clear. Why a line rather than a plane to refine the "axes" of competition (price and location for instance)? Or maybe a hill to reflect difficulty of access (Joe's is at one location in South Africa, Maxim's has restaurants in Paris, Peking, Tokyo and Shanghai, and McDonald's is just about everywhere). A metaphor emphasizes some aspects while ignoring others. Different mathematical metaphors of the same phenomenon can support very different interpretations or insights.The scientist who constructs a mathematical metaphor - a model or theory - chooses to focus on some aspects of the phenomenon rather than others, and chooses to represent those aspects with one image rather than another. Scientific theories are fascinating and extraordinarily useful, but they are, after all, only metaphors. Full Article
l Customer experience tweaks that boost restaurant results By feeds.feedblitz.com Published On :: Sat, 19 Oct 2019 19:22:35 +0000 Restaurant guest experience depends on more than good food and quick service. The post Customer experience tweaks that boost restaurant results appeared first on Neuromarketing. Full Article Neuromarketing consumer behavior customer experience cx menu design restaurant restaurant menus restaurants
l Decoy Pricing: Did United Airlines Fire Their Behavioral Economist? By feeds.feedblitz.com Published On :: Tue, 29 Oct 2019 11:07:30 +0000 It appears that United Airlines has stopped using a classic decoy pricing approach for in-flight wifi options. The post Decoy Pricing: Did United Airlines Fire Their Behavioral Economist? appeared first on Neuromarketing. Full Article Neuromarketing decoy marketing decoy pricing pricing united airlines
l Brainfluence Now Has An Italian Translation By feeds.feedblitz.com Published On :: Thu, 14 Nov 2019 22:31:05 +0000 Roger Dooley's book Brainfluence has just been released in an Italian translation. The post Brainfluence Now Has An Italian Translation appeared first on Neuromarketing. Full Article Neuroscience and Marketing Books brainfluence italian neuromarketing translations
l Non-Profit Persuasion Lesson from Jay-Z By feeds.feedblitz.com Published On :: Tue, 19 Nov 2019 12:59:07 +0000 Rapper Jay-Z used a classic influence principle for non-profit persuasion. The post Non-Profit Persuasion Lesson from Jay-Z appeared first on Neuromarketing. Full Article Neuromarketing fundraising non-profit nonprofit personalization reciprocation reciprocity rolex
l When Lead Generation Trumps Helping Customers | #FrictionHunter By feeds.feedblitz.com Published On :: Thu, 26 Dec 2019 17:54:40 +0000 Turning a chat request into a lead generation process adds friction and annoys customers. The post When Lead Generation Trumps Helping Customers | #FrictionHunter appeared first on Neuromarketing. Full Article Friction chat help chatbots conversion cro customer experience cx friction lead generation leadgen user experience ux
l How One Simple Strategy Changed the Candy Industry By feeds.feedblitz.com Published On :: Mon, 27 Jan 2020 16:41:38 +0000 A century ago, Edward Noble sold billions of Life Savers in a few years with a different approach to marketing mints. The post How One Simple Strategy Changed the Candy Industry appeared first on Neuromarketing. Full Article Neuromarketing candy convenience customer experience cx edward noble friction
l Sensory Marketing for Intangibles By feeds.feedblitz.com Published On :: Tue, 05 May 2020 12:40:55 +0000 Sensory marketing is possible for intangible products, services, and ideas. Here are examples from Friction by Roger Dooley. The post Sensory Marketing for Intangibles appeared first on Neuromarketing. Full Article Neuromarketing business books business cards friction senses sensory branding sensory marketing touch
l New History of Psychiatry: Melancholy, Madness, Chinese Psychiatry, Psychedelic Therapy, and More By ahp.apps01.yorku.ca Published On :: Tue, 21 Apr 2020 12:59:00 +0000 The June 2020 issue of History of Psychiatry is now online. Full details follow below: “Wild melancholy. On the historical plausibility of a black bile theory of blood madness, or hæmatomania,” Jan Verplaetse. Abstract: Nineteenth-century art historian John Addington Symonds coined the term hæmatomania (blood madness) for the extremely bloodthirsty behaviour of a number of … Continue reading New History of Psychiatry: Melancholy, Madness, Chinese Psychiatry, Psychedelic Therapy, and More → Full Article General
l New JHBS: Mind-Body Medicine Before Freud, Psychology and Biography, Jung and Einstein By ahp.apps01.yorku.ca Published On :: Thu, 30 Apr 2020 12:54:00 +0000 The Spring 2020 issue of the Journal of the History of the Behavioral Sciences is now online. Full details about contributions to this issue follow below. “Practicing mind-body medicine before Freud: John G. Gehring, the “Wizard of the Androscoggin”” by. Ben Harris and Courtney J. Stevens. Abstract: This article describes the psychotherapy practice of physician … Continue reading New JHBS: Mind-Body Medicine Before Freud, Psychology and Biography, Jung and Einstein → Full Article General
l History of Spanish Psychology, 1800–2000 By ahp.apps01.yorku.ca Published On :: Thu, 30 Apr 2020 14:11:00 +0000 AHP readers may be interested in a recent piece on “History of Spanish Psychology, 1800–2000” in the Oxford Research Encyclopedia of Psychology. Full details below. “History of Spanish Psychology, 1800–2000,” by Javier Bandrés. Abstract: In the history of Spanish psychology in the 19th century, three stages can be distinguished. An eclectic first stage was defined … Continue reading History of Spanish Psychology, 1800–2000 → Full Article General
l Review Article – Within a single lifetime: Recent writings on autism By ahp.apps01.yorku.ca Published On :: Thu, 30 Apr 2020 20:23:00 +0000 AHP readers will be interested in a review article now available online from History of the Human Sciences “Within a single lifetime: Recent writings on autism.” Written by Gregory Hollin the piece reviews five recent books on autism. Full Article General
l New Theory & Psychology: Early Critical Theory and Beck’s Cognitive Theory By ahp.apps01.yorku.ca Published On :: Fri, 01 May 2020 12:21:00 +0000 Two articles in the most recent issue of Theory & Psychology may interest AHP readers. Full details below. “How lost and accomplished revolutions shaped psychology: Early Critical Theory (Frankfurt School), Wilhelm Reich, and Vygotsky,” by Gordana Jovanovi?. Abstract: On the occasion of recent centenaries of revolutions in Europe (1917, 1918–19), this article examines, within a … Continue reading New Theory & Psychology: Early Critical Theory and Beck’s Cognitive Theory → Full Article General
