Category Archives: Science

generating knowledge

ABCs of Climate Change change

Consider this observation from a policy perspective piece in the New York Times.

But there has not been a huge public outcry to endorse new climate change policy. Polls consistently show that while a majority of Americans accept that climate change is real, addressing it ranks at the bottom of voters’ priorities.

You see the ABC, the Attitude Behavior Consistency, or in this case, the ABnotC, the Attitude Behavior not Consistent. Under many circumstances attitudes are consistent with behavior – you do what you feel and you feel what you do. And, we know that when attitudes and behaviors are inconsistent, that can produce Dissonance which nobody wants. We are highly motivated to be ABC when possible.

The Climate Change ABC we observe in the NYTimes quote is a problem of a different order. As we’ve seen with a lot of good experimental research exactly focused on Climate Change attitudes and beliefs, we find that for most Other Guys, their attitudes are weakly held and change with the slightest variation in the Local. Make a room warmer and Other Guys believe there’s more Climate Change; make a room cooler and they don’t.

Soft attitudes like that produce the ABnotC in the quoted paragraph. Other Guys poll strongly about Climate Change attitudes and beliefs, but when you poll them about behaviors, Climate Change policy moves drop to the bottom. Other Guy attitudes about Climate Change are so weakly held that when asked about political actions, other attitude issues like economics, jobs, immigration, gay rights, and so on, pop higher and stronger.

I’ll ask you now to reflect on this graphic from the ELM chapter in the Primer.

ELM Outcomes

Persuasion change can be assessed four ways: Magnitude, Persistence, Resistance, and Prediction. How much change? How long does the change last? Does the change resist counter-attacks? Does the change drive future action?

And, you’ll note from the graphic, a comparison between the two routes, Central or Peripheral with each of these change outcomes. While either an Argument or Cue based approach can produce the same Magnitude of change, you see differences between the routes on Persistence, Resistance, and Prediction.

Now, combine this persuasion knowledge with that original New York Times quote. Other Guys have favorable attitudes about Climate Change, but those attitudes do not persist, resist, and as we clearly see in the quote, do not predict action. The implication is apparent. Climate Change changers have achieved Peripheral Route, Cue-based change. All of the changed attitudes and beliefs about Climate Change are weak, contradictory, and vague in the minds of Other Guys.

If you are a Climate Change changer, you might understand this line of analysis and are probably explaining the outcome like this. The deniers are lying liars who are confusing Other Guys with those lying lies. No wonder Other Guys show ABnotC rather than ABC!

You may believe that if you wish, but such thinking both violates the Rules and fails a basic understanding of persuasion principles. Blaming the opposition for your persuasion failure violates the Rule:

Great Persuaders Don’t Need Kindness from Strangers

If you think that deniers are killing your case that means you are worse at persuasion than they are and that you can only be successful in persuasion when you have no competition. We’d all be professional athletes or actors winning all the awards if guys like LeBron James or Meryl Streep weren’t around, right?

Worse than the Rule violation, is the misunderstanding of persuasion principles. Other Guys do not necessarily develop weak attitudes because of competition and conflict between information sources. They primarily develop weak attitudes because they’ve been exposed to Cue-based Peripheral Route persuasion plays.

While Climate Change changers think they have been using science as the foundation of their persuasion, the persuasion outcomes contradict that perspective. If indeed the Climate Change changers had taken Other Guys down the Central Route with High WATT processing of strong Arguments based in science, then you would . . . what? Right. Look back at the ELM graphic. You would achieve attitude change that was persistent, resistant, and predictive. And that quote from the New York Times explicitly contradicts that conclusion.

Look more carefully at the persuasion plays from Climate Change changers and you see, not science as Argument, but science as Cue. You only need to see two words to catch this distinction: Scientific Consensus. Those two words have become the persuasion short hand, the headline, for basic Climate Change persuasion. Scientific Consensus.

As we’ve noted before, Scientific Consensus is not an Argument, but a Cue. The assertion that 97% of experts agree is not crucial information about the science of how climate change happens, its impact on humanity, or how humanity should respond. It is only a Cue that points to Authority, Dr. Doctor, Phd.

As long as Climate Change changers in particular and muggles in general miss this difference between an Argument and a Cue and the WATTage difference each requires, then you will always find a source like the New York Times making observations about your persuasion like the quote that opened this post. Everyone agrees with you, but no one will do anything about it. The persuasion failure is fundamental and begins with the source.

The practical lesson is . . . theoretical! If you don’t master the principles of persuasion then you will fail. Forget your passion or the importance of the issue or how many Fellow Travelers you can find or how much resource you’ve got. Bad persuasion begins with error and blunders on from there.

When your persuasion produces change that doesn’t produce action, you are failing.

Data, Big; Analytics, Big; Persuasion?

Persuasion is in the details, but not in the minutia, and most of the Big Data with Big Analytics is minutia. All that Big Minutia allows you to make bigger persuasion mistakes. Like this.

Office Max Big Data Car Wreck

In the confused stream of building Big Data with Big Analytics someone entered that car wreck fatality in a database and off it went into Big Persuasion. It happens.

Such incidents are inevitable—part of the cost of doing business in collecting and collating information on millions of individuals, said Steven Sheck, owner of customer-data provider On rare occasions he has seen obscenities find their way into mailing addresses, likely entered by angry customer-service representatives during a contentious telephone call.

For this specific case, no one knows how it happened.

OfficeMax said it doesn’t know how the information got there.

“We would like nothing more than to tell the world what happened,” said a spokeswoman for the Naperville, Ill., chain, which merged last year with rival Office Depot Inc. “We don’t know what happened yet. We haven’t been told. It was not our data and we don’t have access to the original information.”

Think about this for a moment. You’ve got the smartest technology run by the smartest people in the history of the planet with more data and more analytics than ever, and yet you cannot detail how the details are collected, entered, databased, shared, or analyzed. Consider the Rule:

If You Can’t Count It, You Can’t Change It.

Normally we apply that Rule to understand the impact side of persuasion, but you can move back upstream in the persuasion Cascade with this Rule, too. If you can’t count your persuasion plays, you can’t control them! Here we see that Big Data with Big Analytics can’t even count itself. We’ve seen this lack of control in Big Data as with my hyphenated last name or the big feet of Facebook or the wildly untrue data profiles of Other Guys. Big Data with Big Analytics makes a lot of stupid mistakes that cannot be controlled, predicted, or explained.

While I do not operate with a palantir from Sauron, I do cast a wide search for information about persuasion, particularly scientific information, information that is generalizable knowledge with practical impact. And, I’ve yet to find a reasonable literature that scientifically tests Big Data with Big Analytics to determine whether it changes anything, how big that Windowpane is, and how the change occurs. Almost everything we know about Big Data with Big Analytics is only persuasive: Selling sand and ice to Sauds and Aleuts. The cold hearted counting of a persuasion scientist is not easily available.

You know why?

Big Data with Big Analytics doesn’t work for persuasion. In its own way Big Data with Big Analytics is exactly like those trendy, stylish, and useless activity bracelets the tragically hip and worried well wear to collect the physical activities of their daily lives down to the calorie in Personal Big Data with Pretty Picture Big Analytics.

FitBit Bracelets

Hey, stupid. You eat too much or you move too little. You need Big Data with Big Analytics to know that? And chances are great that if you are a Digital Aesthete wearing one of those bracelets, you don’t need the damn thing anyway.

Do you see the Bolivian Banks here? A few very smart werewolves have packaged faux science in a name – Big Data – or a bracelet – FitBit – and sold a bucket of steam. The persuasion play is the Authority Cue and you know this is all a Cue because we’ve noted the absence of a reliable scientific literature on these inventions and the presence of no effect and little control in their application. Lots of Other Guys go Low WATT, observe the trappings of Expertise or Science or Authority, and hit the TACT without thinking.

I understand why so many Other Guys glide down the Peripheral Route with FitBit, but can the Guys running Office Max be this stupid, thoughtless, and gullible? What’s great about this is that peace and prosperity has created such a large cushion that Other Guys can blunder like this and still survive. You wonder where bubbles come from?

As I’ve noted frequently on the Persuasion Blog this is the greatest time in the history of persuasion to wear a white lab coat, flash a Pretty Picture infographic, and call yourself scientific. Persuasive Science cannot fail big enough, often enough, or obviously enough to kill that Cue in this Local. A lot of Other Guys will remain easy, ripe, and luscious for the beat of the coldest heart in human thought and action: Science.

Kids, the dangerous 1% are not that wealthy 1% despised of the 99%, but the 1% who operate beyond good and evil with persuasion. They get more than your money.

a Cool Table Play with Your Tax Dollars At Work

If you are old or extremely hip, you’ll recall the Golden Fleece award from Senator William Proxmire, the late Democratic Senator from Wisconsin. Proxmire devised a clever way to attract media attention with his Fleece awards, given regularly at press conferences and aimed at exposing what he thought were foolish examples of spending tax dollars. An infamous example revealed a Department of Justice study that questioned why prisoners wanted to get out of jail. While the award was somewhat tongue-in-cheek, it helped make the point that your tax dollars buy some unusual goods and services. Plus, it put the Senator in front of cameras and in a good light. Jeepers, who can complain about an elected official mocking government waste?

Pivot on the idea of spotlighting government spending, but turn from the cost side to the benefit side: the Golden Goose Award! Another Democratic Congressman, this time a Representative, has developed a tactic to garner press attention, but this time to honor government funded research that produced benefits to society! Who can complain about your tax dollars at work that actually work? And better still, Proxmire never created an concrete icon for his award, but the Goose herders have.

Golden Goose Awards

Now. Follow the details.

While Representative Jim Cooper (D-TN) started this idea, he’s going way beyond Proxmire’s tactic of earning favorable media attention for himself. He’s built an interesting Cool Table for the Golden Goose Award.

The organizations sponsoring the Golden Goose Award — which include the American Association for the Advancement of Science (AAAS, publisher of ScienceInsider), the Association of American Universities, and the Progressive Policy Institute — hope to award it annually starting this fall. Nominations will be reviewed by an eight-member selection committee that includes Bruce Alberts, the editor-in-chief of Science, and Nobel Prize-winning physicist Burton Richter as well as university research officials.

So. The guys who benefit from government funding – like the members of AAAS or AAU – pick the winners of the Golden Goose Award and then the guys who provide the government funding announce those winners. No one who actually provides the tax dollars (like you) has anything to say about this award. Just the guys who spend your taxes and the guys who get your taxes.

A government official is trying to make himself look good by cherry picking winners given to him by the fruit farmers who get subsidies from that official. Gee. No conflict of interests in this Cool Table. Better still this Cool Table is built and served in good Sicilian style: as a cold dish.

Alan Leshner, who leads the American Association for the Advancement of Science, was once a target of a Golden Fleece when studying why rats use exercise wheels. (The answer: To regulate body composition — the same reason people run.) Speaking to a group of scientists and legislators, Leshner said he suspects his project wasn’t the only one unfairly ridiculed by the Wisconsin senator.

“I’m sure each of you could think of Golden Fleece recipients who could go ‘Na-na-na-na-na-na’ today,” he said.

See all the persuasion and little of the science. Proxmire invented a clever play that permitted him to look good and responsible, spotlighting government waste, while doing nothing to stop the waste. Cooper, the AAAS, and fellow travelers take the play and move it to a revolving Cool Table play that extols the virtues of Golden research while hiding the conflicts of interests between those who give subsidies and those who receive them pretending all the while to be independent parties.

By comparison, Proxmire’s Golden Fleece award was a pretty obvious piece of persuasion while the current Golden Goose award hides the persuasion in plain sight. The Goose is a double-inside job, like a bank owner hiring bank robbers to cover bad losses.

Let’s get out of here on a Rule.

You Cannot Persuade a Falling Apple.

P.S. Jeepers, who knew that scientists were so thin skinned they can’t take public criticism about their work? Especially with tax dollars. Somehow recipients of tax funded programs think the money is earned income rather than welfare, whoops, a grant. The Fed alone gives out annually over $130 billion a year in research and development funding and requires little public accounting beyond filling out paperwork (which the unversity grant office handles, anyway). Welfare queens and unemployment cheats get greater scrutiny than profs on grants.

P.P.S. Chase down Daniel Greenberg’s books on politics, science, and money. This Wiki is a good start. You’ll find a lot of vampires, panthers, and werewolves in white lab coats.

P.P.P.S. Bankers hiring robbers to steal as a cover for bad losses? That’s The Getaway with Steve McQueen and Ali McGraw!


P.P.P.P.S. Who’d want an award that looks like and is called a goose? And, you get the goose for laying eggs. Yeah. Paint it gold and that makes it like a Nobel.

a Climate for Failure with Cool Tables

Climate Change changers provide a compelling, useful, and on-going case study of persuasion failure. Everyone knows the sky is falling and knows why the sky is falling and how to stop the sky from falling, yet no one is doing anything to stop the sky from falling. This can only occur if you are lousy at persuasion. (Or lousy at science, but let’s concede that for the moment. The sky is falling, we know why, and we can stop it, but we don’t.) Why this persuasion failure?

We’ve looked at numerous examples in the Persuasion Blog, but they tend to be specific and focused examples that ignore the broader sweep and scope of Climate Change changers. I’ve now found a helpful source that traces the Local of Climate Change changers almost from the beginning through at least 2012. The authors are participant-observers, that is, both academic researchers trying to understand the Other Guys while also being part of the Other Guys themselves. They believe in Climate Change and they are also curious about how the thing works, or in this case, doesn’t. They provide that sweep and scope in a qualitative analysis of this persuasion case. Let’s begin at their end.

In closing, our study contributes to understanding why, despite the widespread agreement on the urgency of mitigating climate change and of developing adaptation mechanisms, powerful actors still seem unwilling and unable to subscribe to a single course of action and to provide an effective solution.

Thus, these insider researchers, who’ve participated in most of the major UN sponsored meetings, believe that the Climate Change changers have failed. They have not persuaded key Other Guys to do anything useful for solving the problem. So, in this research report, published in a peer review journal, people who are qualified observers (and believers) report on their observations of the major source of Climate Change persuasion, the various United Nations groups, the players working in that context, and the characteristics of that Local. Consider this foundational observation.

Hardy and Maguire (2010) argued that field-configuring events can catalyze change because they provide discursive spaces not normally available: they are temporally bounded, special moments in the life of a field and facilitate interactions among field members that do not usually interact.

Translated into practical persuasion this means people combine into large transnational units that can change the world through the use of communication (discursive spaces that facilitate interaction) among members with deadlines (temporally bounded, special moments). More compactly: Cool Tables with time limits.

While transnational units exhaust the universe for communication Locals (unless E.T. is out there), you can still apply this idea to any setting where all the Other Guys can be divided into smaller segments of groups. In the Fed, I lived in a Local segmented by branch of government (Executive, Legislative, or Judicial), then within branch, different Agencies (Defense, Commerce, Labor, HHS, and so on), then within any Agency, many different Centers, Institutes, and Offices, and on and on with the Fed organizational chart. Even if you are living in the Local called a Mom and Pop business, you can segment by customers, suppliers, and so on. In other words, the transnational nature of this Local is big, but still just different groups of Other Guys in the Local.

You then construct Cool Tables and populate them with representatives from the various segments. Now add time limits for their interactions. And, while they are communicating, they are communicating in discursive spaces which means everyone gets their turn at the microphone while everyone else (theoretically) listens. Such interaction will cause everyone to understand everyone else, discover areas of agreement, and through the pressure of known and shared deadlines, will create action. While not made explicit in this paper, I also believe the central motivating force behind all this is that irrefutable, irrevocable, and irresistible science. The Apple is Falling.

I’ve seen this work before.

Just as I was joining NIOSH in the late 1990s, they had completed a nationwide series of town hall meetings with anyone remotely interested in workplace health and safety. From these meetings, NIOSH developed a list of specific areas for research which had widespread concern and support. They refined both the items and their wording by forming content committees who discussed a specific area in depth with those Other Guys most concerned about it. From this iterative Cool Table operation emerged NORA, the National Occupational Research Agenda.

NIOSH leadership then took NORA to the President and Congress and got the best kind of change you can count: Funding. NIOSH got the funding because of the Cool Table operation. Other Guys who participated in the Cool Table town hall meetings or committee work called the President or their Congressional representatives and persuaded for both NORA in general and their specific area in particular.

The people behind the play knew what already existed, but let the Other Guys on the Cool Table discover it for themselves in public. This process not only let the Cool Table show off, but also built a natural constituency to advocate, support, and work the research area. The Cool Table also functioned as a reliable source of public knowledge and its distribution, so that over time almost everyone with even a minimal interest in workplace health and safety knew about the Cool Table and its operations. You can use the Cool Table as a sleeper hold, as I often recommend, but you can also use it to make things happen.

So, you can combine large and diverse groups of Other Guys, glide them into discursive spaces with plenty of time at the microphone while a clock is running and you will get both ideas and action that then leads to the big change you want to count.

It. Does. Work.

Why not with Climate Change changers? The researchers offer four detailed observations explaining why things with the UN Climate Change changers have failed so far. We’ll take them one at a time.

. . . we find that field-configuring events over time ceased to be interactionally open and temporally bounded as diverse actors with vested interests entered the field, power coalitions shifted, and the events became platforms for issues not strictly related to emission reduction. Under such conditions, the deliberate staging of the Copenhagen high-stakes event in 2009 to induce a sense of urgency in the climate negotiations prevented institutional change and resulted in an ongoing delay of substantive policy decisions.

Stated in persuasion terms, the discursive space became so open and so crowded that nothing got done. When planners realized this, they gambled on a “high stakes” Cool Table meeting in 2009 at Copenhagen that forced everyone to either work together . . . or not, as it turned out. Self interest usually beats Other interest.

Realize that Cool Tables should operate with tight control of who gets in. This quote explains that the UN process lost that control and just about anyone who was both noisy and rude could push into the Cool Table. Sure, there’s the dynamic tension here of being open and democratic versus enforcing rules from an open and democratic process. The UN changers failed to keep the Cool Table closed and defined as they practiced eternal open discursive spaces.

Now, this.

Because an overarching authority is missing in transnational fields, rules, norms, and understandings are continuously (re)negotiated and often highly ambiguous to include diverse actors and logics (Djelic & Quack, 2011).

And we know why the UN changers failed to keep the Cool Table closed and defined. Nobody had sufficient power or persuasion to enforce any interaction rules in the open discursive spaces. Even after the Cool Table first met and defined rules, no one enforced them and worse still, the Cool Table got bigger and bigger with more frequent rule violations and abuse of open discursive spaces. The consequences here are both obvious and destructive. Yet, no one did anything about it. Why?

I take recourse to the Rule of There Are No Laws and you see that here. Why did no one in this UN change process cowboy up and enforce rules, discipline, and focus? Who knows? The UN is always haunted with a lack of power whether in terms of guns and money or political legitimacy. It lacks sovereignty. But, even past that, if you’ve watched enough John Wayne movies, you know that one guy can stand up in the crowd, enforce justice, and things work out. Why has there been no one guy or even on small group of guys who rode herd on the rest to enforce the rules everyone had made?

And, it’s not like this oversight requires a horse, a gun, and the Duke. During the NORA process, NIOSH leadership had some power with money and access, but nothing decisive. However, that leadership controlled those town hall meetings and committees and locked down entrance and exit. They persistently kept to the public rules of NORA and enforced them personally, not with money or access. They just ruled both formally and informally the way effective group leaders (and persuaders) do. Apparently no single person or group in the UN process has ever operated like this. Stated another way, there’s no leadership in the UN Climate Change changer process.

So, here we are in our open discursive spaces, jibber-jabbering without fear of consequence, eating time while watching the clock count down, each pursuing our individual interest. Guess what happens?

. . . our findings suggest that the effects of field-configuring events are closely tied to emotions, so that analyzing such events can enrich recent efforts to understand the emotional dimension of institutional work (Voronov & Russ, 2012). Ritualistic performances afford shared emotional experiences and are often deliberately crafted to that end (Dacin, Munir, & Tracey, 2010); social movements partly gain their mobilization potential from emotions such as passion and feelings of solidarity (Flam & King, 2005; Goodwin, Jasper & Polletta, 2001; Goodwin, 2007). At the same time, our study has shown that heightened emotionality can also obstruct change under specific field conditions.

While certainly true of human nature, this observation damns the UN change process as little more than a pecking party. In the midst of doing science-based public policy, the UN change process permitted emotionality to dominate the discursive space. Of course, people will get fired up on big issues that personally involve them. That’s known and given. Any change process that does not recognize and control this only indicts its own incompetence. Here you see the flip side of the Wisdom of the Crowd. Crowds tend to encourage emotionality as they rampage down either the Peripheral Route or the Biased Central Route.

The Cool Table devolved into the Mob. An elite Mob. A scientific Mob. A sincere, passionate, and committed Mob. But a Mob.

When you have open discursive spaces and no one enforcing any kind of rules, you will soon get the Crowd at the Cool Table. Anyone who has worked with groups of humans at any age knows that groups without enforced norms of conduct will devolve into source material for the next version of Lord Of The Flies. No cohesion. No focus. No product. Just a lot of discursive open space filled with self interest and emotion.

And, especially when you point the Cool Table in this direction.

The field of climate policy is an extreme case of a transnational field, because the need to substantially reduce greenhouse gas emissions not only mobilizes governments, international and nongovernmental organizations (NGOs), private sector actors, and research institutes all around the world (Orr, 2006), but also requires that millions of organizations and individuals change their production and consumption patterns, which implies a changed economic system for a threat that lies largely in the future (Giddens, 2009; Levy & Egan, 2003).

We arrive at the Ground Zero for this case study failure. This is the TACT statement. This is what we want all the Other Guys not at the Cool Table to do. The Target Action Context and Time. The Who does What Where and When.

Can you believe the scope and range of this TACT? It is absurd on the face of it, a massive leap of faith while doing science. Gee. Imagine that it is difficult to get 6 billion people to agree on the same threat and same solution that involves changed national and international economic systems? I realize that there are also much more specific TACTs in the various UN IPCC statements, but the general structure is both so vague and so wide as to strain common sense. Who thinks like this?

The cluelessness of this orientation to the TACTs exposes the wide ranging incompetence and inexperience of the UN Climate Change changers. They think they have irrefutable science that will motivate and discipline Cool Table representatives to restrain their human nature, emotional responding, and self-interested biases, play fair and nice with everyone else, and convince 6 billion Other Guys to change the foundations of their economies.

Of course, this error is not unique to Climate Change changers, but is common among those we know as the Sinceres. While Sinceres are authentic and often motivated to make you and your world a better place, all of their activity only presents, defends, or justifies themselves and their Sincerity. It almost never focuses upon or produces a change anyone can count in those Other Guys who need Sincere help. When you are Sincere, you are also Certain which makes you a double persuasion muggle.

The description of the people and their communication at these UN open discursive spaces provides an excellent illustration of Sincerity in action. It is nothing but irony to behold authentic experts joined together by science and torn apart by persuasion. Even with the Falling Apple in their hands, they cannot resist the persuasion gravity of the Fallen Apple as they fill precious time and space with their Sincerity at the expense of saving the Other Guys from a falling sky.

Read the Rules and pick the violations that seem most relevant, poignant, or destructive. These seem most obvious to me.

All Bad Persuasion Is Sincere.

If You Can’t Succeed, Don’t Try.

It’s about the Other Guy, Stupid.

Persuasion Is Strategic or It Is Not.

Drive with Science, Putt with Poetry.

You Cannot Persuade a Falling Apple.

If You Can’t Count It, You Can’t Change It.

All People Always Resist Significant Change.

Persuaders Can Either Be Famous or Effective, But Not Both.

Great Persuaders Don’t Need Rich Uncles, Kindness from Strangers, or Third Party Vote Splitters.

Past the Rule violations, please catch the lessons with this applied Cool Table. That play is extremely effective with large and diverse groups of Other Guys. You can capture a small number, put them on a Cool Table with rules, enforce those rules, and that Cool Table can produce what you want. They will discover what you already know, form alliances, generate commitment, publicize you and your idea, product, or service, and act as a persuasion agent on your behalf. (And, alternatively, you can use a Cool Table to distract idiots who are in your way. Same principles of operation, just a different persuasion goal.)

Here we see Climate Change changers trying the Cool Table play, but only for their own Sincerity. The absence of control and rules, the vague and nebulous TACTs, and rampant human nature destroy the application, but not the principle. Failure proves the foolishness of the muggle, not the persuasion play.

Schüßler, E., Rüling, C.-C., and Wittneben, B. (2014): On melting summits: The limitations of field-configuring events as catalysts of change in transnational climate policy. Academy of Management Journal, 57, 140-171.

Cut and paste this link to a preprint of the paper as of April 2014.

a Gedankenexperiment on WATTage and Tooth Fairy Tales

Imagine this thought experiment.

You grab a humongous convenience sample of Other Guys to complete a Tooth Fairy Tale self report survey on the life and death importance of sitting or drinking soda pop, whatever. Just pick your favorite Tale and its survey. Now, randomly . . . stop, don’t panic. Take a deep breath. It’s okay. Randomization cannot kill you. Really. Here. Take this pill. Feeling better now?

We very slowly and carefully and while taking deep breaths randomize this very large convenience sample of Other Guys who are taking a survey on life and death into three groups. With the first group, we just do the normal Tooth Fairy Tale. With the second group, we do something that increases their WATTage. With the third group we do something that decreases their WATTage. Read the ELM/HSM literature and pick your favorite WATTage manipulation and run it.

Then everyone takes the survey.

Let the mess of life continue and count the bodies as they hit the floor and the national database of death certificates. Wait as long as you want since this is a Gedankenexperiment and what you imagine you can do – which is pretty much a Tooth Fairy Tale; goodness, I never realized that Gedankenexperiment can be a synonym for Tooth Fairy Tale. Except for the experiment part because that needs randomization and . . . hold on! Here’s your pill!


On the first large convenience sample of Other Guys, go ahead and do all that Stat Boy and Girl adjusting and de-biasing and whatevering you do to find the level of statistical significance you most enjoy. Now, run that same final analytic model on the other two groups, High WATT and Low WATT, without making any new adjustments or de-biasing techniques. Just replicate the model from the original Tooth Fairy Tale group on the two WATTage groups.

We have three different Results: Standard Fairy Tale, High WATT Fairy Tale, and Low WATT Fairy Tale.

Raise your hand if you think the results of the three identical analyses will be within sampling error (statistical significance, right?) of each other.

If you raised your hand, please contact me immediately.

I have an exciting research opportunity for NIH funding that is going to be announced in the next funding cycle and have learned through my vast network of colleagues in the Fed (you can take the boy out of the Fed, but you can’t take the Fed out of the boy!). I also have similar knowledge and contacts in the venture capital world for another exciting funding opportunity. Just deposit $12,583 in a Bitcoin account to be named later.

If you didn’t raise your hand, let’s think.

If these Fairy Tale surveys are accurately measuring what Other Guys are doing, it is interesting to consider what difference WATTage might make on the measurement. Would the Low WATT or the High WATT Fairy Tale be most similar to the Standard Fairy Tale? Or would each group be different (at least with the Tooth Fairy standard of statistical significance) from each other? Would all three be within sampling error and produce what even a Tooth Fairy would have to confess is the same thing?

A Tooth Fairy has to raise its hand because if the manipulated thoughtfulness of the Other Guy makes any difference then the fundamental science beneath the telling of Fairy Tales is revealed for its absence. Variation in WATTage must not affect the results because that means all published Tooth Fairy Tales are just that, tooth fairy tales.

My bet would be that Low WATT conditions would be most similar to the Standard Fairy Tale and that the High WATT conditions would produce results so null and void that even with a million cases, nothing would even be statistically significant, must less a Staggering effect size. Of course, if you ran re-adjustments and re-de-biasing on the WATTage groups, you could re-invent a Tooth Fairy Tale. But, that’s changing the physics of the Gedankenexperiment and in a Gedankenexperiment that’s not allowed. You have to do a different Gedankenexperiment to accomplish that fantasy!

My argument is that Tooth Fairy Tales arise not only from those modeling games with different “adjustments” to cases and variables or from the ruthless protection of statistical significance against any other criterion of evaluation, but from the Low WATT setting in which the data are collected.

The less Other Guys think, the more Tooth Fairies know!


Science as Bad Persuasion

You will not find a better example.

Bisexual Science Activism

That image and description comes courtesy of the Science home page for the online New York Times. And the article details how a particular group of advocates is spending time in the musty and dusty depositories of research libraries to uncover the truth, the persuasive truth, of their cause. Of course, the science itself could care less what any advocate thinks of it. The Apple falls or it doesn’t. So we have only and yet again another example of persuasive science.

I would most often play the Dynamic Tension game here between Falling and Fallen Apples with a careful look at each force, inspecting the lift properties of the wing with the thrust properties of the engine to understand whether and how the thing will fly. But I’m beginning to see this tension in a new light.

Whether you achieve lift with science and persuasion is less interesting now than this Rule-bound thought:

Great Persuaders Don’t Need Kindness From Strangers.

You can’t swing a dead cat nowadays without finding science-based advocacy as if science can prove past objection and democracy what society should do. Advocates seem to think they can hasten or shortcut the long persuasion process of achieving their Heaven on Earth with a few citations to the peer review literature using science as a type of Kindness from Strangers. Stated another way lazy persuasion seeks science.

The topic that began this post is an apt illustration. I’ve argued before that as an example of effective persuasion you need look no farther than the gay and lesbian community, especially compared to other groups seeking social change. While I’m sure you can find examples of gay and lesbian panthers quoting from the Journal of Sex Archives, in the main they hit their societal TACTs through smart, careful, and persistent persuasion of an old fashioned flavor.

Now with another group of advocates, those seeking something related to bisexuality, you see, instead of old fashioned persuasion working both sides of the legislative aisle to get the needed votes to hit the TACT, PR in pop press outlets declaiming science. Sure, the PR get Exposure in the Cascade, but among the Other Guys who count here, counting the science is not persuasive. I’d argue the same point with climate change, lifestyle change, just about any form of progressive change. Most are simply lazy with their persuasion and want a hammer to hit the TACT, so they grab science thinking it has a handle.

A Rule dawns on me.

All Bad Persuasion Is Scientific.

Persuasive Science for Brain Games

You either have to be British or a compulsive reader to know this, but here’s the kind of science that the vampires at Lumosity and the rest of that brood will love.

Cognitive Myths

A European research team proves that old people do not experience cognitive decline from aging, but because they have too many memories! Here’s how the first sentence of the Abstract gives it up.

As adults age, their performance on many psychometric tests changes systematically, a finding that is widely taken to reveal that cognitive information-processing capacities decline across adulthood. Contrary to this, we suggest that older adults’ changing performance reflects memory search demands, which escalate as experience grows.

The researchers knowingly use a computer metaphor to explain the mechanics here. Build a huge database and the computer slows down whenever it has to seek, search, or save that database. Mere size kills processing speed. With a computer. And, so the researchers argue, too with people. As you age, your database gets bigger and it requires more time to access and employ. The researchers then design and test several interesting computer simulations of learning, databasing, and accessing, and discover exactly what they know – computers that learn more have bigger databases and that produces slower processing. Your mind isn’t getting older, baby, your memory is getting bigger!

What a fabulous and persuasive science. Never observe Other Guys doing anything, just simulate their behavior in computer algorithms that produce exactly what you want them to produce. If you read the literature created from the Four HorsePersons of the iPostModern Apocalypse – epidemiology, economics, evolution, and environmental studies – you see the persuasive science. You don’t have to observe or manipulate anything in reality, just make models that exactly reproduce reality, down to as many decimal points as it takes to tell the Tooth Fairy Tale. Then, argue that everyone else who employed random selection or assignment to controlled conditions with comparison and careful counting did not do science because it doesn’t fit the models of reality you’ve proven! Such thinking allows conclusions like this.

The results reported here indicate that older and younger adults’ performance in psychometric testing are the product of the same cognitive mechanisms processing different quantities of information: Older adults’ performance reflects increased knowledge, not cognitive decline.

Now, if you cannot see the persuasion implications of this assertion for Lumosity and other Brain Traps, I’m throwing you out of the werewolf pack. If true, the assertion means exactly that people need to be playing Brain Games so that they become more efficient and effective processors of all that data they acquire with age and, presumably, experience. Just add a new metaphor to the old metaphor and you can count some change, baby.

Start with that old metaphor of mind and brain as computer software and hardware. That proves it’s the bigger database, baby. Then switch the metaphor to mind and brain as a muscle. That proves you need to exercise your mind and brain just like your pecs and quads! Gee. Instead of buying new computers or iGizmos with faster processors and operating systems, why don’t you just exercise your old device?

Funny how metaphors work when you think about them.

See all the foolishness and the persuasion. The science is silly because it eats the menu when it pretends that the model is the reality when the model is just a map you’ve drawn that you can sell to reviewers and trusting Other Guys of a certain age. While you can model mind behavior with math (why no citations to Professor Estes?) that’s what you do after you’ve done the science to get the data with randomization, control, comparison, and counting, not before.

But, the persuasion here is fabulous for the aforementioned Other Guys of a certain age. This makes sense and requires none of that ridiculous reading of something called a research literature. Good Grief. These researchers actually can talk to real people about what’s really going on in that aging body and brain and mind. Of course. My mind and brain is exactly like an app and an iGizmo! And, of course, my mind and brain is exactly like a muscle that needs exercise!

Tell Me A Story works with Tooth Fairy Tales, too. Begin with the General Semantics Persuasion Play©™® and the rest is narrative.

Ramscar, M., Hendrix, P., Shaoul, C., Milin, P. and Baayen, H. (2014). The Myth of Cognitive Decline: Non-Linear Dynamics of Lifelong Learning. Topics in Cognitive Science.

doi: 10.1111/tops.12078

P.S. The New York Times was surprisingly slow to pick up this story. The research paper was published online on Jan 13, 2014, then first picked up in the media about a week later. And a week after that the Times provided its first notice and stupidly adored it along with most of the commenters. Man, talk about a Bolivian Bank here. Easy, ripe, and luscious.

P.P.S. Read Tim Salthouse’s work.

P.P.P.S. But see the continuing effort with persuasive science for this Bolivian Bank.

P.P.P.P.S. Last one. Vampires, panthers, werewolves and all those who are beyond the perimeter of good and evil! Aim this at the under 50 crowd who are scared to death watching their parents. Those kids will fall for this play without any effort on your part while their parents either can’t understand it or know it won’t work.

Nudging in Living Color Yet Again

About 2 years ago we looked at a colorful Nudge aimed at persuading people to select healthier foods in a cafeteria. Combining color codes (green dots for good food, red dots for bad food and yellow food for okay food) and choice architecture (making red food hard to reach and green food easier), the researchers tested a practical Nudge in the real world. The preliminary results after 3 months showed Small and contradictory outcomes. I’ll requote myself.

Roughly speaking the Phase 1 Central Route intervention produced about a 11% decrease (Small Windowpane) in Red food items and about a 7% increase (half a Small Windowpane) in Green food items. The Phase 2 Nudge produced another 4% decrease in Red food items and, this isn’t good, a 2% decrease in Green food items. Clearly very Small Windowpanes here, but statistically significant because you have over 4,000 cases in a repeated measures design which provides power out the wazoo.

Now, the research team is back with the same Nudge, but with 2 year follow up data instead of that 3 month data we looked at in 2012. Here’s their Figure for all the purchases of red, yellow, or green foods over 2 years.

Nudging in the Cafeteria

While there is statistically significant variation in these lines (and thousands of cases in a repeated measures design makes trivial Windowpanes open as statistically significant), you can see a simple pattern. Green went up a little with the color labeling, then stayed right there for 2 years; red when down a little with the color labeling, then stayed right there for 2 years; yellow moves up maybe a little and wanders around for 2 years. Yet, here’s how the authors describe this Figure.

The results of this study provide strong evidence that a simple traffic-light labeling and choice architecture intervention can improve healthy food and beverage choices of a diverse population over a sustained period of time . . .

The results of this study were unable to separate out the effects of the labeling and the choice architecture because both interventions were incorporated into the cafeteria as permanent changes.

I’d like to disagree with both statements and with many of the same arguments I raised in the earlier post 2 years ago. This is not “strong” evidence. It’s a one shot prospective study of a cafeteria a Massachusetts General Hospital! Talk about a topic friendly environment. You are a fish swimming in the sea called progressive health policy. Note that half of the food sales were already in the green category before the Nudge even began! As I noted before, try doing this colorful out of reach Nudge on food trucks serving construction workers on job sites in greater Boston and tell me what happens.

I also take issue with their inability to separate out the effects of labeling with color from the out of reach choice architecture. The Figure directly contradicts that assertion because as the Figure shows, the colorful labels were applied alone before the out of reach Nudge (points 1 and 2 in the Table). You can see that much of the change in red or green purchases occurred within those first two time periods and that most all the variation in time periods 3 to 8 just wanders around a straight line. In other words, the simple Cue of color produced almost all of the change in this fish bowl and the out of reach Nudge did virtually nothing.

The researchers evade this point by reporting comparisons in green, yellow, or red purchase from Baseline to One Year or to Two Years. They could easily do the same comparison to Baseline for Time Period 1 and 2, but they do not because it shows all the action is from the color Cue and nothing from the out of reach Nudge.

But even this nitpicking point should not obscure the overblown discussion of this limited intervention. Calling this a Nudge may make the research appear new, cutting edge, or innovative, but the name doesn’t change the numbers. Count the change with color and you find a simple Authority Cue (based on trusted science) that makes an absolute change of less than 5 percentage points, one half of a Small Windowpane and even that estimate is generous because there’s only one month for Baseline; you know if you had 6 months of Baseline data it would be higher and lower with a bit of random variation. So, go to Harvard Health and affix color dots and you’ll get this. Try it on a construction site and tell me what you get . . . after you untie yourself from nearest tree or utility pole.

And, I’ve got to harp on that failure to analyze the two different time periods of the intervention, color labels, then the out of reach Nudge. This is just plain bad science. It misleads practitioners who simply read the Intro and Discussion and take it all on faith. People think that something called a Nudge exists and makes a big difference with Other Guys when it is nothing but a bucket of steam relabeled as vapor.

The color Cue is providing the change here and that persuasion play is as old as water and heat. If you trust the source doing the color coding, then the color becomes a reliable indicator of crucial information. But, realize that the Cue depends first upon trusting the source of the label, then the color variation. There is no news here with that finding.

But, to deliberately combine the color Cue with that Nudge and say that both plays make a difference is the bucket of vapor. It fools people into thinking they must invent barriers like reach or placement – a Nudge – when the evidence here shows that those barriers make no difference. And, if you want to be perverse here, you can read that Figure of outcomes as an indictment of the Nudge. The color Cue clearly moved the dial from Baseline with both green and red purchases in the desired direction, but then they added that damn Nudge and the trend stopped immediately. It is reasonable to argue that if they had just let the color Cue alone continue, the trend lines could have persisted in the correct direction.

And you see the practical problem with persuasive science. It may create a publication or a grant or a presentation for a vampire, but it trades on scientific credibility and trust. When practitioners believe researchers who play like this, they end up with empty buckets and no change to count and not because they did a lousy intervention, but because they trusted werewolves. I get this persuasion angle when vampires do persuasive science to make money on games like Lumosity or diversity training on “unconscious bias” with the Implicit Attitudes Test or even to push policy through politics as with climate change or menu labeling. Buyer beware and all that.

But Nudging as science is only persuasion.

Lillian Sonnenberg, Emily Gelsomin, Douglas E Levy, Jason Riis, Susan Barraclough, Anne N Thorndike. (2013). A traffic light food labeling intervention increases consumer awareness of health and healthy choices at the point-of-purchase. Preventive Medicine (Impact Factor: 3.5). 07/2013.


An RCT for Lumosity!

Through dumb luck, I encountered a news report on a randomized controlled trial of cognitive training on older adults. The news report heralded the research as more evidence that doing various cognitive tasks for memory, reasoning, and speed of processing slows the inevitable cognitive decline of aging. And, best of all, the news report ended with an advertisement for . . . can you believe it? . . . Lumosity! I reloaded the page and fortunately a different ad appeared which means the Lumosity ad was truly dumb luck. However, the new ad related to Alzheimer’s! (A Peitho nomination to the ad service for scanning the page contents before assigning an ad.)

I chased down the paper and read it and understand why the news report was positive. The paper was positive, too! And, as near as I can tell, persuasively positive. If you actually read the Methods and Results, you will find a different story than the Discussion. Begin with good science.

Over 10 years ago a research team enrolled healthy older adults (over 70) in a randomized controlled trial. The trial began with nearly 700 people each assigned to Control (just testing, no training) or one of three cognitive training interventions for Memory, Reasoning, or Speed of Processing. Training ran for 5-6 weeks and was conducted in small group of 10 people in 60-75 minute sessions. The training was followed by a couple of booster sessions. All participants were regularly tested with standard peer review measures of memory, reasoning, speed of processing, and also a daily living activities scale over the course of the 10 years.

So. A large cohort of healthy older people get randomized to one of four conditions then gets regular tests on their progress for 10 years. Let’s begin with the good news from the researchers.

In the ACTIVE trial, 10 to 14 weeks of organized cognitive training delivered to community-dwelling older adults resulted in significant improvements in cognitive abilities and better preserved functional status than in nontrained persons 10 years later. Each training intervention produced large and significant improvements in the trained cognitive ability. These improvements dissipated slowly but persisted to at least 5 years for memory training and to 10 years for reasoning and speed-of-processing training.

Here’s the Table of outcomes with d effects circled (click to enlarge).

RCT for Lumosity Table 2

Orient. The top row heads the four conditions from Memory to Reasoning to Speed to Control. The left column heads the outcome measures for memory, reasoning, speed, and then the activities of daily life at the bottom.

Notice the diagonal of circled effect sizes. In each row, the circled effect size should be larger than the others and if you hit all three like that you’ve done a nice test of the discriminant validity of the interventions. Memory training should increase memory more than Reasoning, right? Reasoning training should increase reasoning more than Speed training, right? And so on. Well, the Memory training fails, the Reasoning training is Small which is not clinically significant, and the Speed training is Large which means it worked.

Details. Always details.

The Speed training involves visual perception and how quickly and accurately you can scan a visual field and find information. It’s an useful skill while driving, for example. As this nice Wiki entry describes, Useful Field of View is a life changing skill, particularly for aging drivers. And, it’s nice for finding information on medicine bottles! Or navigating the damn remote control buttons! But, it is a perceptual skill not a cognitive skill. Sure, both perception and cognition involve brain and mind function, but they are different.

So, the result of this RCT confirms a bunch of prior research on Speed, or Useful Field of View, and doesn’t say anything that we didn’t already know. When people practice perceptual skills, they get better, even if they are older.

Now, the Memory and Reasoning results. Again and forever, the key problem with aging and cognition is memory. That is the bottleneck, the chokepoint, the center of gravity. If you cannot improve memory, you are not making an important and practical difference. And nobody has done any good science demonstrating practical improvements (at least Medium Windowpanes in experimental designs with lots of replication) in memory as people age. Right now all the science demonstrates about memory and age is this: Age kills memory.

You might remember the really interesting basic research on moving memories in mice with the Optogenetics Persuasion Play®™©. That research demonstrated you can externally manipulate memory with laser hits on neurons. And, maybe someday we’ll be able to manipulate human memory in a similar fashion and either preserve, repair, or rewire memory so that whatever you lose with age you can regain with lasers. Any day now!

As this new research disappointingly demonstrates with its numbers, we still cannot stop the effect of age on memory. Now, with Reasoning we do get a Small Windowpane in an experimental design and over 10 years. I’ll call this a real effect, but not a practical effect. While you may not be rolling downhill as fast, you are still rolling downhill and much faster than when you were a kid, rolling uphill with ease. In other words, the loss from age is so great compared to your training that a Small benefit is probably not noticed.

Finally, we get to that activities of daily life scale which is a self report of the activities you can do in your daily life. The Windowpanes are Small+. The scoring is a bit complicated (they created a composite score based on several different tests). That composite ranges from 0 to 38 with (I think) 0 being the best and 38 the worst. Note that all the conditions at Baseline begin with very low means, averaging around 1 which means (again if I correctly understand the composite construction and scoring) everyone was able to do virtually all of life’s daily tasks without trouble. Over 10 years, everyone’s scores got worse, to about an average of 4 points on that 0-38 range. You see the effect sizes in the Table with all training groups showing Small+ Windowpanes against the control.

A couple of points on this activities of daily life.

First, the reported effects for all training conditions are pretty consistent and make it look like doing anything where you get people together in small groups doing something for 10 hours will produce an effect on daily living. Hey, merely to participate in the training requires you to get out of the house, get to the training site, hang out and interact with others for an hour or so and do this several times. That’s a lot of skill building and socializing and light exercising compared to staying in the house in your sweatpants wondering when your kids will visit. In other words, the cognitive training type makes no difference on daily life, but getting out to participate in a randomized controlled trial does. That’s quite a different conclusion.

Second, realize that the absolute score in activities for all conditions after 10 years ranges from 3.3 to 4.5 on a 38 point scale! Everyone is at the very low end of the scale meaning they are all doing most of the activities of daily life without trouble. There’s just not much there, there, with any of the training.

Now, the researchers do an unusually good job of noting qualifications, limitations, and weaknesses of the outcomes in the Discussion, but persist with a much more positive headline. Consider these two key paragraphs from Discussion.

In the ACTIVE trial, 10 to 14 weeks of organized cognitive training delivered to community-dwelling older adults resulted in significant improvements in cognitive abilities and better preserved functional status than in nontrained persons 10 years later. Each training intervention produced large and significant improvements in the trained cognitive ability. These improvements dissipated slowly but persisted to at least 5 years for memory training and to 10 years for reasoning and speed-of-processing training. This is the first demonstration of long-term transfer of the training effects on cognitive abilities to daily function.

And then.

In summary, ACTIVE was the first multisite clinical trial to test the effects of cognitive training interventions on cognitive abilities and daily function. Results at 10 years demonstrate that cognitive training has beneficial effects on cognitive abilities and on self-reported IADL function. These results provide support for the development of other interventions, particularly those that target multiple cognitive abilities and are more likely to have an effect on IADL performance. Such interventions hold the potential to delay onset of functional decline and possibly dementia and are consistent with comprehensive geriatric care that strives to maintain and support functional independence. If interventions that could delay onset of functional impairment by even 6 years were introduced, the number of people affected by 2050 would be reduced by 38%,[48] which would be of great public health significance.

And, here’s how it looked on at least one media source.

Utah News on ACTIVE trial

You could put it that way, I guess, but that’s a lot of persuasion over a little science. That training on Useful Field of View clearly worked and with obvious impact. You could watch older adults driving a car, for example. One group got the training, the other didn’t. With this effect size you’d have no trouble identifying which group got the training and which didn’t. But, this is old news, as even the public Wiki entry notes. And, while the training does involve the brain and the mind, it is more perceptual than cognitive.

We see that distinction in the results with the Memory and Reasoning training. Memory training produces no difference. None. Age kills memory. And, the effect with Reasoning training is statistically detectable at Small, but I don’t think an outside observer could look at two groups of adults doing tasks at a bank or Walmart and tell you accurately which adults got trained in Reasoning and which didn’t, given this effect size. So, the way most people think of cognition and aging – with memory and reasoning – finds little good news here.

And, finally the activities of daily life . . . all conditions were somewhat better than control, but all had healthy absolute scores with little practical difference between the training groups and control. If there is any effect, the results support an effect for Getting Out Of The House as much as Training Memory, Reasoning, or Speed Of Processing.

Yet, the headline pitch is persuasion while wearing a white lab coat. My concern here is false hope for everyone involved. These kinds of cognitive training don’t work because of how aging works and everyone is doing their level best to pretend otherwise. The only people who benefit are the vampires at Lumosity (and others) and maybe some panthers angling for the next grant application. Until we can change brain function over age, no cognitive training will make a difference. It’s like trying to exceed the speed of light or to run in a straight line after spinning in a tight circle with your head held down.

Of course, you cannot overlook the Local Bolivian Bank called Aging America. Good grief, I can see the opportunities every morning as I look at my face in the mirror. Stop this relentless destruction! Hey, combine worry, fear, and pain with a mirror and you’re gonna do a lot of persuasion.

Rebok, G. W., Ball, K., Guey, L. T., Jones, R. N., Kim, H.-Y., King, J. W., Marsiske, M., Morris, J. N., Tennstedt, S. L., Unverzagt, F. W., Willis, S. L. (2014), Ten-Year Effects of the Advanced Cognitive Training for Independent and Vital Elderly Cognitive Training Trial on Cognition and Everyday Functioning in Older Adults. Journal of the American Geriatrics Society.

doi: 10.1111/jgs.12607

P.S. A fine point: Nearly 50% of the population failed to complete a 10 year project. Imagine that with a group starting at age 70? The researchers, to their everlasting credit, ran the analyses with “intention-to-treat,” meaning they included the drop-outs in all groups. This inevitably wreaks havoc on statistical analysis. You’ve got an RCT, so you don’t need to “adjust” the data in Tooth Fairy fashion, but with high and variable attrition rates, you will get predictably lumpy data.

I think intention-to-treat is the best solution, but it does make things beguiling. I guarantee you that if you excluded all or some drop-outs, the results would change. What’s the truth here? Intention-to-treat replicates the Local that Other Guys inhabit. If you want to run a practical persuasion play that helps Older Other Guys save cognitive resources, then you’ve got to count the drop-outs and run intention-to-treat. If you want to sell more tickets to Lumosity, you will play games with attrition to make things look better just like the Tooth Fairies do. The researchers here played it scientific by my lights.

Jared B Jobe, David M Smith, Karlene Ball, Sharon L Tennstedt, Michael Marsiske, Sherry L Willis, George W Rebok, John N Morris, Karin F Helmers, Mary D Leveck, Ken Kleinman. (2001). Active: A cognitive intervention trial to promote independence in older adults, Controlled Clinical Trials, Volume 22, Issue 4, August 2001, Pages 453-479.

DOI: 10.1016/S0197-2456(01)00139-8.

Buffett Twerks Bracketology

If you are groovy, gear, and fab today you are smart and bright, an Other Guy who knows how to count the change . . . as long as there’s no math. You read Nate Silver’s 538 website for the statistical truth on sports, science, politics, life, whatever. Silver and that Big Data with Big Analytics Journalism tells you the story before it happens with the story behind it, making a little money along the way (from ESPN??? When did anyone read ESPN for news about life and science and politics?).

And then along comes Warren Buffett, the Oracle of Omaha.

Buffett famously made an offer to Big Data with Big Analytic brights to make their March Madness picks for the men’s NCAA basketball tournament. Pick them all and win a billion bucks!

So. Hit a Big Data with Big Analytics website like Silver’s 538 and you’re on your way!


Buffett Twerks Big Data

Within the first three days of the tournament every one of the 10 million entrants held busted brackets. Think about that. Over 10 million people using the best pop press statistical science available got killed in three days of a three week tournament. Big Data. Big Analytics. Yeah, baby, we’re in the Third Millennium.

Buffett generated millions of dollars of free advertising with this offer, most of it benefiting Quicken Loans who served as the source for entering the contest. And, it also helped Yahoo, which functioned as the web portal for online submission of the brackets.

Here’s the persuasion twerk.

Lots of pop press muggles offer statistical science (like Nate Silver) who, in theory, should be giving everyone a great chance at actually winning this bet. However, the persuasion panther, Warren Buffett, made them all look stupid, by making a fool’s offer that over 10 million Other Guys fell for. Who truly knows how the count the change here? An old codger like Warren Buffett or the New New Thing like Nate Silver?

Buffett and Quicken Loans made an offer of $1 billion dollars – just an offer – and got millions of dollars of free publicity. Guys like Silver provided statistical science that helped bust 10 million bets in three days.

I’d argue that Buffett understands both the Falling Apples and the Fallen Apples. He knows how to count the change on bracketology and how to make an offer 10 million Other Guys cannot refuse. And Buffett put his money where his count is. If anyone had hit the winner, Buffett would have paid out a billion of his own dollars. And, he’s still going to pay out at least one million to the 20 best brackets.

Mr. Buffett may be one of the best counting panthers in the history of persuasion.