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What Meritocracy looks like in the US and elsewhere?

Why Poor kids who do everything right don’t do better than rich kids who do everything wrong

This propaganda that “America is the land of opportunity“, is it just for some more than others?

In large part, inequality starts in the crib, in the socio-political system

Rich parents can afford to spend more time and money on their kids, and that gap has only grown the past few decades.

Economists Greg Duncan and Richard Murnane calculate that, between 1972 and 2006, high-income parents increased their spending on “enrichment activities” for their children by 151% in inflation-adjusted terms, compared to 57% for low-income parents.

By Matt O’Brien October 18, 2014Poor Grads, Rich DropoutsSource: Data from Richard Reeves and Isabel Sawhill

It’s not just a matter of dollars and cents. It’s also a matter of letters and words.

Affluent parents talk to their kids three more hours a week on average than poor parents, which is critical during a child’s formative early years.

That’s why, as Stanford professor Sean Reardon explains, “rich students are increasingly entering kindergarten much better prepared to succeed in school than middle-class students,” and they’re staying that way.

It’s an educational arms race that’s leaving many kids far, far behind.

It’s depressing, but not nearly so much as this:

Even poor kids who do everything right don’t do much better than rich kids who do everything wrong.

Advantages and disadvantages tend to perpetuate themselves.

You can see that in the above chart, based on a new paper from Richard Reeves and Isabel Sawhill, presented at the Federal Reserve Bank of Boston’s annual conference, which is underway.

Specifically, rich high school dropouts remain in the top about as much as poor college grads stay stuck in the bottom — 14 versus 16%, respectively. Not only that, but these low-income strivers are just as likely to end up in the bottom as these wealthy ne’er-do-wells. Some meritocracy

What’s going on? Well, it’s all about glass floors and glass ceilings.

Rich kids who can go work for the family business — and, in Canada at least, 70 % of the sons of the top 1 percent do just that — or inherit the family estate don’t need a high school diploma to get ahead.

It’s an extreme example of what economists call “opportunity hoarding.” That includes everything from legacy college admissions to unpaid internships that let affluent parents rig the game a little more in their children’s favor.

But even if they didn’t, low-income kids would still have a hard time getting ahead.

That’s, in part, because they’re targets for diploma mills that load them up with debt, but not a lot of prospects.

And even if they do get a good degree, at least when it comes to black families, they’re more likely to still live in impoverished neighborhoods that keep them disconnected from opportunities.

It’s not quite a heads-I-win, tails-you-lose game where rich kids get better educations, yet still get ahead even if they don’t—but it’s close enough.

And if it keeps up, the American Dream will be just that.

Note: Kids of struggling and hard working parents learn to save money and appreciate the value of hard work. Kids of very rich families fail to learn the value of money or work hard when young.

Unless the rich kid  go to work for his parents’ business and are given countless second chances, he is unable to make it on his own.

It is not the rich parents fault as much as their inability to convince the kid, who see wealth of his family surrounding him, in the house and things coming his way the easy way, that the notion of hard work is not believable.

Which machine learning algorithm should I use? How many and which one is best?

Note: in the early 1990’s, I took graduate classes in Artificial Intelligence (AI) (The if…Then series of questions and answer of experts in their fields of work) and neural networks developed by psychologists. 

The concepts are the same, though upgraded with new algorithms and automation.

I recall a book with a Table (like the Mendeleev table in chemistry) that contained the terms, mental processes, mathematical concepts behind the ideas that formed the AI trend…

There are several lists of methods, depending on the field of study you are more concerned with.

One list of methods is constituted of methods that human factors are trained to utilize if need be, such as:

Verbal protocol, neural network, utility theory, preference judgments, psycho-physical methods, operational research, prototyping, information theory, cost/benefit methods, various statistical modeling packages, and expert systems.

There are those that are intrinsic to artificial intelligence methodology such as:

Fuzzy logic, robotics, discrimination nets, pattern matching, knowledge representation, frames, schemata, semantic network, relational databases, searching methods, zero-sum games theory, logical reasoning methods, probabilistic reasoning, learning methods, natural language understanding, image formation and acquisition, connectedness, cellular logic, problem solving techniques, means-end analysis, geometric reasoning system, algebraic reasoning system.

Hui Li on Subconscious Musings posted on April 12, 2017 Advanced Analytics | Machine Learning

This resource is designed primarily for beginner to intermediate data scientists or analysts who are interested in identifying and applying machine learning algorithms to address the problems of their interest.

typical question asked by a beginner, when facing a wide variety of machine learning algorithms, is “which algorithm should I use?”

The answer to the question varies depending on many factors, including:

  • The size, quality, and nature of data.
  • The available computational time.
  • The urgency of the task.
  • What you want to do with the data.

Even an experienced data scientist cannot tell which algorithm will perform the best before trying different algorithms.

We are not advocating a one and done approach, but we do hope to provide some guidance on which algorithms to try first depending on some clear factors.

The machine learning algorithm cheat sheet

Flow chart shows which algorithms to use when

The machine learning algorithm cheat sheet helps you to choose from a variety of machine learning algorithms to find the appropriate algorithm for your specific problems.

This article walks you through the process of how to use the sheet.

Since the cheat sheet is designed for beginner data scientists and analysts, we will make some simplified assumptions when talking about the algorithms.

The algorithms recommended here result from compiled feedback and tips from several data scientists and machine learning experts and developers.

There are several issues on which we have not reached an agreement and for these issues we try to highlight the commonality and reconcile the difference.

Additional algorithms will be added in later as our library grows to encompass a more complete set of available methods.

How to use the cheat sheet

Read the path and algorithm labels on the chart as “If <path label> then use <algorithm>.” For example:

  • If you want to perform dimension reduction then use principal component analysis.
  • If you need a numeric prediction quickly, use decision trees or logistic regression.
  • If you need a hierarchical result, use hierarchical clustering.

Sometimes more than one branch will apply, and other times none of them will be a perfect match.

It’s important to remember these paths are intended to be rule-of-thumb recommendations, so some of the recommendations are not exact.

Several data scientists I talked with said that the only sure way to find the very best algorithm is to try all of them.

(Is that a process to find an algorithm that matches your world view on an issue? Or an answer that satisfies your boss?)

Types of machine learning algorithms

This section provides an overview of the most popular types of machine learning. If you’re familiar with these categories and want to move on to discussing specific algorithms, you can skip this section and go to “When to use specific algorithms” below.

Supervised learning

Supervised learning algorithms make predictions based on a set of examples.

For example, historical sales can be used to estimate the future prices. With supervised learning, you have an input variable that consists of labeled training data and a desired output variable.

You use an algorithm to analyze the training data to learn the function that maps the input to the output. This inferred function maps new, unknown examples by generalizing from the training data to anticipate results in unseen situations.

  • Classification: When the data are being used to predict a categorical variable, supervised learning is also called classification. This is the case when assigning a label or indicator, either dog or cat to an image. When there are only two labels, this is called binary classification. When there are more than two categories, the problems are called multi-class classification.
  • Regression: When predicting continuous values, the problems become a regression problem.
  • Forecasting: This is the process of making predictions about the future based on the past and present data. It is most commonly used to analyze trends. A common example might be estimation of the next year sales based on the sales of the current year and previous years.

Semi-supervised learning

The challenge with supervised learning is that labeling data can be expensive and time consuming. If labels are limited, you can use unlabeled examples to enhance supervised learning. Because the machine is not fully supervised in this case, we say the machine is semi-supervised. With semi-supervised learning, you use unlabeled examples with a small amount of labeled data to improve the learning accuracy.

Unsupervised learning

When performing unsupervised learning, the machine is presented with totally unlabeled data. It is asked to discover the intrinsic patterns that underlies the data, such as a clustering structure, a low-dimensional manifold, or a sparse tree and graph.

  • Clustering: Grouping a set of data examples so that examples in one group (or one cluster) are more similar (according to some criteria) than those in other groups. This is often used to segment the whole dataset into several groups. Analysis can be performed in each group to help users to find intrinsic patterns.
  • Dimension reduction: Reducing the number of variables under consideration. In many applications, the raw data have very high dimensional features and some features are redundant or irrelevant to the task. Reducing the dimensionality helps to find the true, latent relationship.

Reinforcement learning

Reinforcement learning analyzes and optimizes the behavior of an agent based on the feedback from the environment.  Machines try different scenarios to discover which actions yield the greatest reward, rather than being told which actions to take. Trial-and-error and delayed reward distinguishes reinforcement learning from other techniques.

Considerations when choosing an algorithm

When choosing an algorithm, always take these aspects into account: accuracy, training time and ease of use. Many users put the accuracy first, while beginners tend to focus on algorithms they know best.

When presented with a dataset, the first thing to consider is how to obtain results, no matter what those results might look like. Beginners tend to choose algorithms that are easy to implement and can obtain results quickly. This works fine, as long as it is just the first step in the process. Once you obtain some results and become familiar with the data, you may spend more time using more sophisticated algorithms to strengthen your understanding of the data, hence further improving the results.

Even in this stage, the best algorithms might not be the methods that have achieved the highest reported accuracy, as an algorithm usually requires careful tuning and extensive training to obtain its best achievable performance.

When to use specific algorithms

Looking more closely at individual algorithms can help you understand what they provide and how they are used. These descriptions provide more details and give additional tips for when to use specific algorithms, in alignment with the cheat sheet.

Linear regression and Logistic regression

Linear regressionLogistic regression

Linear regression is an approach for modeling the relationship between a continuous dependent variable [Math Processing Error]y and one or more predictors [Math Processing Error]X. The relationship between [Math Processing Error]y and [Math Processing Error]X can be linearly modeled as [Math Processing Error]y=βTX+ϵ Given the training examples [Math Processing Error]{xi,yi}i=1N, the parameter vector [Math Processing Error]β can be learnt.

If the dependent variable is not continuous but categorical, linear regression can be transformed to logistic regression using a logit link function. Logistic regression is a simple, fast yet powerful classification algorithm.

Here we discuss the binary case where the dependent variable [Math Processing Error]y only takes binary values [Math Processing Error]{yi∈(−1,1)}i=1N (it which can be easily extended to multi-class classification problems).

In logistic regression we use a different hypothesis class to try to predict the probability that a given example belongs to the “1” class versus the probability that it belongs to the “-1” class. Specifically, we will try to learn a function of the form:[Math Processing Error]p(yi=1|xi)=σ(βTxi) and [Math Processing Error]p(yi=−1|xi)=1−σ(βTxi).

Here [Math Processing Error]σ(x)=11+exp(−x) is a sigmoid function. Given the training examples[Math Processing Error]{xi,yi}i=1N, the parameter vector [Math Processing Error]β can be learnt by maximizing the Pyongyang said it could call off the talks, slated for June 12, if the US continues to insist that it give up its nuclear weapons. North Korea called the military drills between South Korea and the US a “provocation,” and canceled a meeting planned for today with South Korea.of [Math Processing Error]β given the data set.Group By Linear RegressionLogistic Regression in SAS Visual Analytics

Linear SVM and kernel SVM

Kernel tricks are used to map a non-linearly separable functions into a higher dimension linearly separable function. A support vector machine (SVM) training algorithm finds the classifier represented by the normal vector [Math Processing Error]w and bias [Math Processing Error]b of the hyperplane. This hyperplane (boundary) separates different classes by as wide a margin as possible. The problem can be converted into a constrained optimization problem:
[Math Processing Error]minimizew||w||subject toyi(wTXi−b)≥1,i=1,…,n.

A support vector machine (SVM) training algorithm finds the classifier represented by the normal vector  and bias  of the hyperplane. This hyperplane (boundary) separates different classes by as wide a margin as possible. The problem can be converted into a constrained optimization problem:

Linear and kernel SVM charts

When the classes are not linearly separable, a kernel trick can be used to map a non-linearly separable space into a higher dimension linearly separable space.

When most dependent variables are numeric, logistic regression and SVM should be the first try for classification. These models are easy to implement, their parameters easy to tune, and the performances are also pretty good. So these models are appropriate for beginners.

Trees and ensemble trees

A decision tree for prediction model.

Decision trees, random forest and gradient boosting are all algorithms based on decision trees.

There are many variants of decision trees, but they all do the same thing – subdivide the feature space into regions with mostly the same label. Decision trees are easy to understand and implement.

However, they tend to over fit data when we exhaust the branches and go very deep with the trees. Random Forrest and gradient boosting are two popular ways to use tree algorithms to achieve good accuracy as well as overcoming the over-fitting problem.

Neural networks and deep learning

Neural networks flourished in the mid-1980s due to their parallel and distributed processing ability.

Research in this field was impeded by the ineffectiveness of the back-propagation training algorithm that is widely used to optimize the parameters of neural networks. Support vector machines (SVM) and other simpler models, which can be easily trained by solving convex optimization problems, gradually replaced neural networks in machine learning.

In recent years, new and improved training techniques such as unsupervised pre-training and layer-wise greedy training have led to a resurgence of interest in neural networks.

Increasingly powerful computational capabilities, such as graphical processing unit (GPU) and massively parallel processing (MPP), have also spurred the revived adoption of neural networks. The resurgent research in neural networks has given rise to the invention of models with thousands of layers.

A neural network

Shallow neural networks have evolved into deep learning neural networks.

Deep neural networks have been very successful for supervised learning.  When used for speech and image recognition, deep learning performs as well as, or even better than, humans.

Applied to unsupervised learning tasks, such as feature extraction, deep learning also extracts features from raw images or speech with much less human intervention.

A neural network consists of three parts: input layer, hidden layers and output layer. 

The training samples define the input and output layers. When the output layer is a categorical variable, then the neural network is a way to address classification problems. When the output layer is a continuous variable, then the network can be used to do regression.

When the output layer is the same as the input layer, the network can be used to extract intrinsic features.

The number of hidden layers defines the model complexity and modeling capacity.

Deep Learning: What it is and why it matters

k-means/k-modes, GMM (Gaussian mixture model) clustering

K Means ClusteringGaussian Mixture Model

Kmeans/k-modes, GMM clustering aims to partition n observations into k clusters. K-means define hard assignment: the samples are to be and only to be associated to one cluster. GMM, however define a soft assignment for each sample. Each sample has a probability to be associated with each cluster. Both algorithms are simple and fast enough for clustering when the number of clusters k is given.


A DBSCAN illustration

When the number of clusters k is not given, DBSCAN (density-based spatial clustering) can be used by connecting samples through density diffusion.

Hierarchical clustering

Hierarchical partitions can be visualized using a tree structure (a dendrogram). It does not need the number of clusters as an input and the partitions can be viewed at different levels of granularities (i.e., can refine/coarsen clusters) using different K.


We generally do not want to feed a large number of features directly into a machine learning algorithm since some features may be irrelevant or the “intrinsic” dimensionality may be smaller than the number of features. Principal component analysis (PCA), singular value decomposition (SVD), andlatent Dirichlet allocation (LDA) all can be used to perform dimension reduction.

PCA is an unsupervised clustering method which maps the original data space into a lower dimensional space while preserving as much information as possible. The PCA basically finds a subspace that most preserves the data variance, with the subspace defined by the dominant eigenvectors of the data’s covariance matrix.

The SVD is related to PCA in the sense that SVD of the centered data matrix (features versus samples) provides the dominant left singular vectors that define the same subspace as found by PCA. However, SVD is a more versatile technique as it can also do things that PCA may not do.

For example, the SVD of a user-versus-movie matrix is able to extract the user profiles and movie profiles which can be used in a recommendation system. In addition, SVD is also widely used as a topic modeling tool, known as latent semantic analysis, in natural language processing (NLP).

A related technique in NLP is latent Dirichlet allocation (LDA). LDA is probabilistic topic model and it decomposes documents into topics in a similar way as a Gaussian mixture model (GMM) decomposes continuous data into Gaussian densities. Differently from the GMM, an LDA models discrete data (words in documents) and it constrains that the topics are a priori distributed according to a Dirichlet distribution.


This is the work flow which is easy to follow. The takeaway messages when trying to solve a new problem are:

  • Define the problem. What problems do you want to solve?
  • Start simple. Be familiar with the data and the baseline results.
  • Then try something more complicated.
  • Dr. Hui Li is a Principal Staff Scientist of Data Science Technologies at SAS. Her current work focuses on Deep Learning, Cognitive Computing and SAS recommendation systems in SAS Viya. She received her PhD degree and Master’s degree in Electrical and Computer Engineering from Duke University.
  • Before joining SAS, she worked at Duke University as a research scientist and at Signal Innovation Group, Inc. as a research engineer. Her research interests include machine learning for big, heterogeneous data, collaborative filtering recommendations, Bayesian statistical modeling and reinforcement learning.

Is Improvisation in Jazz a conversation? And how the brains work?

Does the brain works in the same way for all kinds of languages?

For the better part of the past decade, Mark Kirby has been pouring drinks and booking gigs at the 55 Bar in New York City’s Greenwich Village.

The cozy dive bar is a neighborhood staple for live jazz that opened on the eve of Prohibition in 1919.

It was the year Congress agreed to give American women the right to vote, and jazz was still in its infancy.

Nearly a century later, the den-like bar is an anchor to the past in a city that’s always changing.

ADRIENNE LAFRANCE published in The Atlantic this Feb. 19 2014:

How Brains See Music as Language

A new Johns Hopkins study looks at the neuroscience of jazz and the power of improvisation.

For Kirby, every night of work offers the chance to hear some of the liveliest jazz improvisation in Manhattan, an experience that’s a bit like overhearing a great conversation.

“There is overlapping, letting the other person say their piece, then you respond. Threads are picked up then dropped. There can be an overall mood and going off on tangents.”

Brain areas linked to meaning shut down during improvisational jazz interactions: this music is syntactic, not semantic.A member of the Preservation Hall Jazz Band performs at the New Orleans Jazz and Heritage Festival in New Orleans. (Gerald Herbert/AP)

The idea that jazz can be a kind of conversation has long been an area of interest for Charles Limb, an otolaryngological surgeon at Johns Hopkins. Limb, a musician himself, decided to map what was happening in the brains of musicians as they played.

He and a team of researchers conducted a study that involved putting a musician in a functional MRI machine with a keyboard, and having him play a memorized piece of music and then a made-up piece of music as part of an improvisation with another musician in a control room.

What researchers found:

1. The brains of jazz musicians who are engaged with other musicians in spontaneous improvisation show robust activation in the same brain areas traditionally associated with spoken language and syntax.

Improvisational jazz conversations “take root in the brain as a language,” Limb said.

“It makes perfect sense,” said Ken Schaphorst, chair of the Jazz Studies Department at the New England Conservatory in Boston. “I improvise with words all the time—like I am right now—and jazz improvisation is really identical in terms of the way it feels. Though it’s difficult to get to the point where you’re comfortable enough with music as a language where you can speak freely.”

2. Along with the limitations of musical ability, there’s another key difference between jazz conversation and spoken conversation that emerged in Limb’s experiment.

During a spoken conversation, the brain is busy processing the structure and syntax of language, as well the semantics or meaning of the words.

But Limb and his colleagues found that brain areas linked to meaning shut down during improvisational jazz interactions: this kind of music is syntactic but it’s not semantic.

Music communication, we know it means something to the listener, but that meaning can’t really be described,” Limb said. “It doesn’t have propositional elements or specificity of meaning in the same way a word does. So a famous bit of music—Beethoven’s dun dun dun duuuun—we might hear that and think it means something but nobody could agree what it means.”

So if music is a language without set meaning, what does that tell us about the nature of music?

3. “The answer to that probably lies more in figuring out what the nature of language is than what the nature of music is,” said Mike Pope, a Baltimore-based pianist and bassist who participated in the study.

When you’re talking about something, you’re not thinking about how your mouth is moving and you’re not thinking about how the words are spelled and you’re not thinking about grammar.

With music, it’s the same thing.” Many scientists believe that language is what makes us human, but the brain is wired to process acoustic systems that are far more complicated than speech.

Pope says even improvisational jazz is built around a framework that musicians understand. This structure is similar to the way we use certain rules in spoken conversation to help us intuit when it’s time to say “nice to meet you,” or how to read social clues that signal an encounter is drawing to a close.

4. “In most jazz performances, things are Not nearly as random as people would think,” Pope said. “If I want to be a good bass player and I want to fill the role, idiomatically and functionally, that a bass player’s supposed to fulfill, I have to act within the confines of certain acceptable parameters. I have to make sure I’m playing roots on the downbeat every time the chord changes. It’s all got to swing.”

5. But Limb believes his finding suggests something even bigger, something that gets at the heart of an ongoing debate in his field about what the human auditory system is for in the first place.

“If the brain evolved for the purpose of speech, it’s odd that it evolved to a capacity way beyond speech. So a brain that evolved to handle musical communication—there has to be a relationship between the two. I have reason to suspect that the auditory brain may have been designed to hear music and speech is a happy byproduct.”

Back in New York City, where the jazz conversation continues at 55 Bar almost every night, bartender Kirby makes it sound simple:

“In jazz, there is no lying and very little misunderstanding.”

Overwhelming power of prosecutors in US justice system.

When a kid commits a crime, the US justice system has a choice: prosecute to the full extent of the law, or take a step back and ask if saddling young people with criminal records is the right thing to do every time.

In this searching talk, Adam Foss, a prosecutor with the Suffolk County District Attorney’s Office in Boston, makes his case for a reformed justice system that replaces wrath with opportunity, changing people’s lives for the better instead of ruining them

Patsy Z and TEDxSKE shared a link.

A prosecutor vision for a better justice|By Adam Foss

Adam Foss. Juvenile justice reformer

By shifting his focus from incarceration to transforming lives, Adam Foss is reinventing the role of the criminal prosecutor. Full bio

The following are my opinions, and do not reflect the opinions or policies of any particular prosecutor’s office. 

I am a prosecutor. I believe in law and order. I am the adopted son of a police officer, a Marine and a hairdresser. 

I believe in accountability and that we should all be safe in our communities. I love my job and the people that do it. I just think that it’s our responsibility to do it better.

By a show of hands, how many of you, by the age of 25, had either acted up in school, went somewhere you were specifically told to stay out of, or drank alcohol before your legal age?  

How many of you shoplifted, tried an illegal drug or got into a physical fight, even with a sibling?

how many of you ever spent one day in jail for any of those decisions?

How many of you sitting here today think that you’re a danger to society or should be defined by those actions of youthful indiscretion?

When we talk about criminal justice reform, we often focus on a few things, and that’s what I want to talk to you about today.

But first I’m going to give you a confession on my part.

I went to law school to make money. I had no interest in being a public servant, I had no interest in criminal law, and I definitely didn’t think that I would ever be a prosecutor.

Near the end of my first year of law school, I got an internship in the Roxbury Division of Boston Municipal Court

I knew of Roxbury as an impoverished neighborhood in Boston, plagued by gun violence and drug crime.

My life and my legal career changed the first day of that internship. I walked into a courtroom, and I saw an auditorium of people who, one by one, would approach the front of that courtroom to say two words and two words only: “Not guilty.”

They were predominately black and brown. And then a judge, a defense attorney and a prosecutor would make life-altering decisions about that person without their input. They were predominately white.

As each person, one by one, approached the front of that courtroom, I couldn’t stop but think: How did they get here? I wanted to know their stories. And as the prosecutor read the facts of each case, I was thinking to myself, we could have predicted that. That seems so preventable… not because I was an expert in criminal law, but because it was common sense.

Over the course of the internship, I began to recognize people in the auditorium, not because they were criminal masterminds but because they were coming to us for help and we were sending them out without any.

My second year of law school I worked as a paralegal for a defense attorney, and in that experience I met many young men accused of murder. Even in our “worst,” I saw human stories.

And they all contained childhood trauma, victimization, poverty, loss, disengagement from school, early interaction with the police and the criminal justice system, all leading to a seat in a courtroom.

Those convicted of murder were condemned to die in prison, and it was during those meetings with those men that I couldn’t fathom why we would spend so much money to keep this one person in jail for the next 80 years when we could have reinvested it up front, and perhaps prevented the whole thing from happening in the first place.

My third year of law school, I defended people accused of small street crimes, mostly mentally ill, mostly homeless, mostly drug-addicted, all in need of help. They would come to us, and we would send them away without that help. 

They were in need of our assistance. But we weren’t giving them any. Prosecuted, adjudged and defended by people who knew nothing about them.

The staggering inefficiency is what drove me to criminal justice work. The unfairness of it all made me want to be a defender. The power dynamic that I came to understand made me become a prosecutor.

I don’t want to spend a lot of time talking about the problem. We know the criminal justice system needs reform, we know there are 2.3 million people in American jails and prisons, making us the most incarcerated nation on the planet.

We know there’s another 7 million people on probation or parole, we know that the criminal justice system disproportionately affects people of color, particularly poor people of color.

And we know there are system failures happening everywhere that bring people to our courtrooms. But what we do not discuss is how ill-equipped our prosecutors are to receive them.

When we talk about criminal justice reform, we, as a society, focus on three things. We complain, we tweet, we protest about the police, about sentencing laws and about prison. We rarely, if ever, talk about the prosecutor.

In the fall of 2009, a young man was arrested by the Boston Police Department. He was 18 years old, he was African American and he was a senior at a local public school. He had his sights set on college but his part-time, minimum-wage job wasn’t providing the financial opportunity he needed to enroll in school.

In a series of bad decisions, he stole 30 laptops from a store and sold them on the Internet. This led to his arrest and a criminal complaint of 30 felony charges. The potential jail time he faced is what stressed Christopher out the most. But what he had little understanding of was the impact a criminal record would have on his future.

I was standing in arraignments that day when Christopher’s case came across my desk. And at the risk of sounding dramatic, in that moment, I had Christopher’s life in my hands. 

I was 29 years old, a brand-new prosecutor, and I had little appreciation for how the decisions I would make would impact Christopher’s life. Christopher’s case was a serious one and it needed to be dealt with as such, but I didn’t think branding him a felon for the rest of his life was the right answer.

For the most part, prosecutors step onto the job with little appreciation of the impact of our decisions, regardless of our intent. Despite our broad discretion, we learn to avoid risk at all cost, rendering our discretion basically useless.

History has conditioned us to believe that somehow, the criminal justice system brings about accountability and improves public safety, despite evidence to the contrary.

We’re judged internally and externally by our convictions and our trial wins, so prosecutors aren’t really incentivized to be creative at our case dispositions, or to take risks on people we might not otherwise. We stick to an outdated method, counterproductive to achieving the very goal that we all want, and that’s safer communities.

Yet most prosecutors standing in my space would have arraigned Christopher. They have little appreciation for what we can do. Arraigning Christopher would give him a criminal record, making it harder for him to get a job, setting in motion a cycle that defines the failing criminal justice system today.

With a criminal record and without a job, Christopher would be unable to find employment, education or stable housing.

Without those protective factors in his life, Christopher would be more likely to commit further, more serious crime.

The more contact Christopher had with the criminal justice system, the more likely it would be that he would return again and again and again — all at tremendous social cost to his children, to his family and to his peers. And, ladies and gentlemen, it is a terrible public safety outcome for the rest of us.

When I came out of law school, I did the same thing as everybody else. I came out as a prosecutor expected to do justice, but I never learned what justice was in my classes — none of us do. None of us do.

And yet, prosecutors are the most powerful actors in the criminal justice system. Our power is virtually boundless.

In most cases, not the judge, not the police, not the legislature, not the mayor, not the governor, not the President can tell us how to prosecute our cases.

The decision to arraign Christopher and give him a criminal record was exclusively mine. I would choose whether to prosecute him for 30 felonies, for one felony, for a misdemeanor, or at all. I would choose whether to leverage Christopher into a plea deal or take the case to trial, and ultimately, I would be in a position to ask for Christopher to go to jail. 

These are decisions that prosecutors make every day unfettered, and we are unaware and untrained of the grave consequences of those decisions.

One night this past summer, I was at a small gathering of professional men of color from around the city. As I stood there stuffing free finger sandwiches into my mouth, as you do as public servant —  I noticed across the room, a young man waving and smiling at me and approaching me. 

And I recognized him, but I couldn’t place from where, and before I knew it, this young man was hugging me. And thanking me. “You cared about me, and you changed my life.” It was Christopher.

 I never arraigned Christopher. He never faced a judge or a jail, he never had a criminal record. Instead, I worked with Christopher; first on being accountable for his actions, and then, putting him in a position where he wouldn’t re-offend.

We recovered 75 percent of the computers that he sold and gave them back to Best Buy, and came up with a financial plan to repay for the computers we couldn’t recover. 

Christopher did community service. He wrote an essay reflecting on how this case could impact his future and that of the community. He applied to college, he obtained financial aid, and he went on to graduate from a four-year school.

After we finished hugging, I looked at his name tag, to learn that Christopher was the manager of a large bank in Boston. Christopher had accomplished — and making a lot more money than me —

He had accomplished all of this in the six years since I had first seen him in Roxbury Court. I can’t take credit for Christopher’s journey to success, but I certainly did my part to keep him on the path.

There are thousands of Christophers out there, some locked in our jails and prisons. We need thousands of prosecutors to recognize that and to protect them.

An employed Christopher is better for public safety than a condemned one. It’s a bigger win for all of us. In retrospect, the decision not to throw the book at Christopher makes perfect sense. When I saw him that first day in Roxbury Court, I didn’t see a criminal standing there. I saw myself — a young person in need of intervention.

As an individual caught selling a large quantity of drugs in my late teens, I knew firsthand the power of opportunity as opposed to the wrath of the criminal justice system. Along the way, with the help and guidance of my district attorney, my supervisor and judges, I learned the power of the prosecutor to change lives instead of ruining them.

And that’s how we do it in Boston. We helped a woman who was arrested for stealing groceries to feed her kids get a job.

Instead of putting an abused teenager in adult jail for punching another teenager, we secured mental health treatment and community supervision.

A runaway girl who was arrested for prostituting, to survive on the streets, needed a safe place to live and grow — something we could help her with.

I even helped a young man who was so afraid of the older gang kids showing up after school, that one morning instead of a lunchbox into his backpack, he put a loaded 9-millimeter. 

We would spend our time that we’d normally take prepping our cases for months and months for trial down the road by coming up with real solutions to the problems as they presented.

Which is the better way to spend our time? How would you prefer your prosecutors to spend theirs?

Why are we spending 80 billion dollars on a prison industry that we know is failing, when we could take that money and reallocate it into education, into mental health treatment, into substance abuse treatment and to community investment so we can develop our neighborhoods?

why should this matter to you? Well, one, we’re spending a lot of money.

Our money. It costs 109,000 dollars in some states to lock up a teenager for a year, with a 60 percent chance that that person will return to the very same system. That is a terrible return on investment.

Number two: it’s the right thing to do. If prosecutors were a part of creating the problem, it’s incumbent on us to create a solution and we can do that using other disciplines that have already done the data and research for us.

Number three: your voice and your vote can make that happen. The next time there’s a local district attorney’s election in your jurisdiction, ask candidates these questions.

One: What are you doing to make me and my neighbors safer?

Two: What data are you collecting, and how are you training your prosecutors to make sure that it’s working? And

Three: If it’s not working for everybody, what are you doing to fix it? If they can’t answer the questions, they shouldn’t be doing the job.

Each one of you that raised your hand at the beginning of this talk is a living, breathing example of the power of opportunity, of intervention, of support and of love. While each of you may have faced your own brand of discipline for whatever malfeasances you committed, barely any of you needed a day in jail to make you the people that you are today — some of the greatest minds on the planet.

Every day, thousands of times a day, prosecutors around the United States wield power so great that it can bring about catastrophe as quickly as it can bring about opportunity, intervention, support and yes, even love. 

Those qualities are the hallmarks of a strong community, and a strong community is a safe one. If our communities are broken, don’t let the lawyers that you elect fix them with outdated, inefficient, expensive methods.

Demand more; vote for the prosecutor who’s helping people stay out of jail, not putting them in.

Demand better. You deserve it, your children deserve it, the people who are tied up in the system deserve it, but most of all, the people that we are sworn to protect and do justice for demand it.

We must, we must do better

You’re Not Dumb.

Are you doing your due diligence to acquire comprehensive knowledge of cultures, civilization, nature, environment, communication…?

Are you prepared with the subject matter before you compete in school studies?

This may surprise you, but Sal Khan used to skip classes at MIT. (Very normal behaviour if you never joined team sports or served in the military)

Khan, perhaps the best-known teacher in the world today,|By Kim Lachance Shandrow

Lectures were too long and boring: “I found it much more valuable to learn the material at my own time and pace”

“I learned a lot more going into the computer lab or the science lab or the circuits lab, fiddling with things and playing and getting my hands dirty.” (That’s called training your experimental mind in education methods)

Patsy Z shared this link TEDxBarcelona

“Whoever you are, wherever you are. You only have to know one thing: you can learn anything.”

Khan Academy Founder: No, You’re Not Dumb. Anyone Can Learn Anything.

That same renegade spirit of independence and innovation, of learning on your own terms and on your own time, is still the heart and soul of Khan Academy. The “revolutionary controversial” online learning platform that this 38-year-old math whiz engineer singlehandedly founded 10 years ago.

What began as a handful of tutoring videos, the former hedge fund analyst uploaded to YouTube to help his cousins with their algebra homework. The platform mushroomed into a massive digital classroom for the world.

To date, the free, non-profit learning hub has delivered more than 580 million of Khan’s straightforward video lessons on demand, with students completing around 4 million companion exercises on any given day.

The Academy is in the midst of a growth spurt offline as well, with an excess of 1 million registered teachers around the globe incorporating the supplemental teaching tool into their classrooms.

We recently caught up with Khan, who discussed how his own education shaped his passion project, his belief that anyone can learn anything and what’s next for Khan Academy, online and off.

How did you develop a passion for education? Who inspired you?

Education has helped me a lot. My father’s side of the family was very active in education.

My parents separated when I was two and then my father passed away. I never really knew that side of the family. But, when I got to know my father’s side branch, they’re intensely academic.

My mother’s side of the family, they’re more the artists. We have a lot of dancers and singers who don’t fit with certain stereotypes that they’re all engineers and they’re all super invested in math.

I went to a fairly normal, middle of the road public school in a suburb of New Orleans, but it gave me huge opportunities. I had a lot of friends there who were just smart as I am.

They seem to learn things just as fast, but they’re hitting walls in algebra class and chemistry class.

That’s when I started questioning the notion of mastery-based learning. It wasn’t completely obvious to me then, but I just knew something was off.

You often say that anyone can learn anything. Why do you think that?

If you’re doing well in school you can have one of two things: You can say, “Oh, well, I have the DNA for doing it. Or you can say, “No, my brain was able to tackle it. I had the right mindset.” I saw those ideas in action early in high school.

Also, I tutored others as part of this math honors society I was in. I noticed that if you tutored people the right way, engaged with them the right way, they would improve.

I saw C and D students all of the sudden do very, very well and become some of the best math students in the state.

Then I go to college at MIT and I saw a lot of people struggle there, too, mainly because they aren’t adequately prepared. It was the same thing.

It was clear to me that it wasn’t intelligence at play, it was much more preparation. The people who did well were the people who saw the material for the third time, had a lot of rigor and didn’t have any gaps in their knowledge.

The people who really struggled were the folks who weren’t familiar with the material and didn’t have a super solid grasp. It has nothing to do with some type of innate intelligence.

How are you taking Khan Academy out from behind the Internet and into the real world?

We piloted a program called LearnStorm in the Bay Area (of San Francisco,California) last year. We’re expanding it to three to five other areas this Spring.

We hope it will function nationwide by 2017. It goes beyond the core skill work we do on Khan Academy, tying it into monthly challenges that are intended to be done in a physical environment, in your math class with your teacher.

LearnStorm came from the idea of we can create these great experiences online that are aligned with standards that are really good for students and they correlate with success metrics, but you need the the students to engage with them.

On our own, we can create a lot of neat game mechanics and all sorts of things on the site, but nothing beats having physical people who are part of your life, especially your teachers, your school and your peers, involved in your learning.

More recently, we worked with Disney Pixar to bridge the disconnect between what students learn about math and science at school and tackling creative challenges in the real world with an initiative called Pixar in a Box.

Our relationship with Pixar makes it very clear that math, science, creativity and storytelling aren’t separate things. They can all happen together.

Why the recent pivot to a growing list of local, offline projects when you originally set out to be a digital classroom for the world?

This isn’t the first time we’ve branched out offline. From day one, I immediately reached out to teachers to see if they’d want to use Khan Academy and to get their feedback on our features. In 2010, we started with the Los Altos school district here in Northern California.

Plus, there’s a whole teacher resources section on Khan Academy, so we’ve always had this dimension.

What’s different now isn’t us working with a handful of classrooms in a very high-touch way. It’s us being able to work with many more teachers and, frankly, they’re able to do a lot of the heavy lifting around mindset, meta cognition, getting students into it, and we provide the tools.

When we say that our vision statement is a free, world-class education for anyone anywhere, it doesn’t mean that it’s just going to all happen through our software, through our content.

As an organization, we view it as part of our mission to up how we interface with all of the other incredible stakeholders in this ecosystem, especially teachers and schools, to figure out how we educate students together, not just all from one site.

What will the classroom of the future look like and how will Khan Academy play a role?

You won’t need lectures in class any more. Those can happen on students’ own time. Using exercises, students can progress at their own pace, like how the Khan academy software works.

Instead, in-class time can be spent having peer-to-peer socratic dialogues, case-based discussions, programming and project based learning.

Why can’t teachers co-teach and mentor each other?

Why separate students by perceived ability or age?

Can’t you benefit from older students mentoring younger students? When classrooms are not one pace, when it’s all not lectured-based, it opens up all sorts of possibilities.

What’s the next big tech innovation in education, even bigger than the Internet?

Virtual reality, though my gut says it’s going to be about 10 years before we see major potential here. It’s very early right now. I can imagine that in about a decade, when you come to Khan Academy, you’ll literally feel like you’re in a virtual place of learning and in a community.

You’ll see people walking around in a virtual world. Who knows? I don’t know if that’s in 10 or 20 years, but I think that’s going to happen.

Aside from virtual reality integration, what else is on the horizon for Khan Academy?

We’re going to be available in all of the world’s major languages on all of the major platforms, whether it’s a cheap smartphone or an Oculus Rift. The more the better. We’re working on translating all of our resources into more than 36 languages, with thousands of volunteers helping us subtitle videos.

Are any new subjects in the works? Topics outside of the traditional academic realm, like, say, yoga and meditation perhaps?

No, nothing like that at the moment, although I do love yoga. We already have a lot of material in physics and chemistry and biology, but we want to really nail those core academic subjects.

Expect to see a lot from us in history and civics over the next year, along with interesting things around grammar, writing and programming.

What advice do you have for entrepreneurs who hope to be as astronomically successful as you

I cringe at the term “astronomically successful,” because it sure doesn’t feel like I am. As for advice, though, I think every entrepreneur should know what they’re getting into, that there are moments of extreme stress and pain that aren’t so obvious sometimes when you read about startups in the press.

Still, all entrepreneurs go through it. You need to be prepared for it and know that it’s normal when you’re in the midst of it.

The transcript that follows has been edited for clarity and brevity.


How a great conversation is like a game of catch

A TED talk. Jul 19, 2016

How a great conversation is like a game of

As a radio host, Celeste Headlee has engaged in her fair share of discussions, and she’s thought a lot about how to bring out the best in a conversational counterpart.

When you play catch, you have to do an equal number of catches and throws, right? It’s not possible to play catch with somebody and throw more than you catch, for the most part.

Because then you’d just be throwing baseballs at them, which is not nice. This is the exact same ratio as a healthy conversation — you’re going to catch as much as you throw.

you’re going to talk 50% and listen 50%, and we don’t generally have that balance in our conversations.

Here’s the best way to start a conversation that you’re worried might end in an argument.

There’s a great study out of Harvard in which researchers discovered that talking about yourself actually activates the same pleasure centers in your brain as sex and cocaine.

That means it’s very pleasurable to us to talk about ourselves and what we like. You could walk away from a conversation like that and feel fantastic about it.

But remember — talking about yourself makes you feel fantastic. So you may have just walked away from a conversation in which you talked about yourself — that was awesome! — and the other person is walking away going, “Good god, that person would not stop talking about themselves.”

It’s a totally different perception, so you’ve got to remember you’re playing catch — find the balance.

How do you go beyond small talk to have a meaningful conversation with somebody?

Not every single conversation that you have is going to be in-depth and serious. And that’s okay! You should relax.

Eventually, while you’re sitting there talking small talk, something’s going to pique your interest, or something’s going to catch their interest, or they’re going to say, “Wait, what did you just say?” Or, “Why is it that way?”

And someone’s going to ask a question, and it’s going to lead you further into deeper subject matter. So it will happen, if there’s something there to talk about. Otherwise, be on your way — let it go.

What about that awkward silence when you don’t know what to say next?

By the time that you’re thirsty, you’re already dehydrated. So by the time you’ve reached an awkward silence, something’s already gone wrong. But it’s not too late!

Very often, an awkward silence comes because either you weren’t listening or they weren’t listening, and therefore, you guys have kind of meandered off-topic to where you’re at the opposite ends of a football field.

The way to fix that is to say, “You know what, I’m sorry, I got totally distracted. Where did we start? Can you help me out here? I was just following a train of thought about Cheetos, and I got totally lost.”

What should you do when it is very clear from body language that the other person is not listening?

End it. Again with the game of catch.

That’s the equivalent of me taking a ball and throwing it over my shoulder instead of to you. Why would you want to keep playing? You have to have an equal partner in a conversation. Otherwise, walk away.

You make the case that all experiences are not equal. Are you saying that empathy is not useful in a conversation?

What should people do instead?

People always push back on this topic. I’m not a psychiatrist or a psychologist, but I believe that most of us are motivated by empathy. You’re with your friend, and you want to say, “Oh, I do understand you, because I’ve been through something similar.”

But the truth is, you haven’t — you haven’t been through something the same.

You maybe have gone through something kind of similar, but the fact of the matter is that you’re a different person from your friend.

So even if it was the exact same experience, even if you both almost went down on the Titanic, the way you experienced that is completely different. And these situations are most likely totally different.

Although it feels to you like you’re reaching out and giving empathy, what’s happening is that you’re talking about yourself again.

So you shouldn’t say, “I know how you feel”?

That’s the worst. You don’t know how they feel. They’re confiding in you, and all they want you to do is listen to them and say, “Wow, that sounds awful. There’s no way for me to understand what you’re going through, but you tell me what you need.”

What do you think is stopping people from having better, more meaningful conversations?

The elephant in the room is obviously polarization, and this is true not just in the United States, but I think Brexit and the migrant crisis in Europe tell us that it’s happening all over the world.

Oftentimes we’ll enter into a conversation, and somebody will say, “I’m voting for Trump in the fall.” Conversation over. You immediately say, “Nothing this person says is something I want to listen to, they have nothing to teach me,” and you end the conversation.

And if the conversation does continue, you’re not actually listening to them.

That’s what is often ending conversations now.

We have stopped talking to people that we disagree with. We basically want to be able to curate and edit our conversations the same way that we curate and edit our social media. If we’re talking to somebody that we don’t want to hear from, we want to unfollow them like we do on Twitter.

The problem with that is that everybody knows something that you don’t. And so if you are stopping all of those conversations and only speaking with people who have similar experiences and opinions, you’re not going to grow, ever, and you won’t change your mind or your opinion.

They used to tell us, don’t talk about religion and politics. The problem today is that everything is religion and politics.

So what’s the best approach to start a conversation that you know might end up in an argument?

First of all, a lot of conversations end in arguments these days. But when I’m sitting down with somebody, especially somebody with whom I absolutely don’t agree, I sit down and I think through, “Okay, what if they’re right?”

Let’s think about what would change, and how my mind would change, if they are right and I am wrong. And as they start to tell me things, as long as they’re not completely made-up facts, I ask myself what it would mean if they’re right. And then I ask them too. I say, “Okay, let’s say you’re right. What does that mean?” And try to get inside what they’re thinking.

For instance, a lot of people ask me how to talk to Donald Trump supporters. It is a great question.

But here’s the thing: there’s an anger there among people — not just people who support Trump, but people who support Bernie Sanders, or the people who voted for Britain to leave the EU.

There is an anger there, and it could be fascinating and engaging and compelling to figure out where that is coming from. That’s not always going to be the case, and there are going to be conversations you have to walk away from.

But if you’re going to have an argument with someone, the best way to do it is with an open mind, assuming that that person can teach you something, and that you’re not there to teach them.

What should you say if you unintentionally offend someone during a conversation?

You say, “I’m really sorry, I did not in any way, shape, or form intend to offend you. I may be inarticulate, but let me try to explain what I thought I was saying, and then you tell me what you think I’m saying, and maybe we can understand one another.” That’s it, that’s all that you say. Be honest.

Is there a quick way to help a friend to stop obsessing about a negative topic?

It’s difficult to address specific situations, since context is so important. In broad strokes, though, people often repeat themselves when they feel as though they haven’t been heard. For example, when we tell our kids something important and they don’t acknowledge that they’ve heard, we’ll keep repeating it until they say, “Okay! I got it, Mom!”

The same things happen often in the workplace.

So, try telling your friend that you think you understand what he or she is saying: “Let me tell you what I’m hearing and you tell me if I’m getting it wrong.”

Then you can offer to brainstorm to find solutions. If he or she’s not open to that, then be honest. Say, “You’re telling me the same things over and over. I can tell you’re very upset, but we can also move forward from here.”

How can you turn a one-way conversation into a dialogue?

You can’t, really. There’s a couple of reasons for a one-way conversation. Sometimes it’s that the person is shy, and in that case, that’s totally fixable, you can draw somebody out, usually by finding out what they like, or self-deprecation is good.

I usually tell a joke or a story about something I’ve done that was really stupid — and I have a wealth of those examples. But if somebody isn’t in the mood to talk, you can’t fix that.

And here’s the thing that people are always surprised that I say: it is totally okay to not have a conversation. Having a real conversation takes energy, and it takes focus, and sometimes you just don’t have that kind of energy to give. That’s totally fine — don’t have the conversation, enjoy the silence.

So if you’re feeling like you really want to have a conversation and the other person isn’t matching that energy, you just need to let them have their time, and find somebody else who is ready.

What about when people really don’t seem to want to listen, but just want to talk about themselves and their experiences?

I’ve found that it’s good to very kindly address this head-on. Say, “It’s so great to hear all that. Can I tell you a little about what I’ve been doing?” Or any version of that.

Don’t assume that person is just trying to dominate the conversation. Give them the benefit of the doubt, because we all talk about ourselves too much. If you try to improve the conversation and they are resistant, then just accept that your conversations with that person will be brief and unsatisfying.

Just like a game of catch, you need two participants who are willing to take turns.

How do you get others to open up as much as you are opening up?

You can’t, really. For instance, when you’re opening up, is it mostly because you’re telling them about your experiences? Are you talking a lot about yourself, and not giving them an opening to talk about themselves?

Are you in any way, shape or form shutting down the conversation? In other words, does that person say, “Oh, you know, I had something similar happen to me the other day, it was really, really interesting,” and you say, “Oh, no, no, no, it wasn’t like that,” and then you go back to what it was you were talking about.

There are a million reasons why the person that you’re talking to may not be opening up. But often, it’s because you’ve shut the door in one way or another. The fact of the matter is it’s probably not them, it’s probably you.

So what if a conversation has run its course? How do you gracefully exit a conversation?

You gracefully exit by saying, “I need to go; it’s been so great to talk to you, and I’ll see you in a couple days.” Or you say, “You know what? I have too much on my mind, I’m really sorry, it’s been great to talk to you, and I’ll see you again in a couple weeks, but I’m going to head back.”

Or — what happens to me, because I have adult ADD all the time — “I can’t keep my mind on this conversation, I am so sorry, it has nothing to do with you, but I’m going to go sit in my office and try to gather my thoughts.” Don’t lie. No white lies! Just be honest, and gracious and nice, not condescending, and just end the conversation.

This is an edited version of a conversation took place at TEDSummit 2017 (see below). Moderated by TED’s Janet Lee, it includes questions from Facebook and from commenters on Celeste’s TED Talk, 10 ways to have a better conversation.

Note: A graduating girl could Not suffer talking to me for a good reason. Once, I started asking her pertinent questions about her thesis and the conversation lasted for hours and we were both very pleased of this quality time.

Another Open Letter to French President Macron

Deuxième lettre ouverte au Président Macron :
Où est l’image satellite du port de Beyrouth ?

Par Hassan Hamadé : Écrivain et journaliste libanais – Membre du Conseil national de l’audiovisuel (CNA)

1er octobre 2020, par Comité Valmy

Monsieur le Président,

Je souhaite commencer par vous féliciter chaleureusement pour votre franchise. Je n’ai pas été déçu que vous soyez allé directement au cœur du sujet, lequel n’a nul besoin de fioritures pour dissimuler sa vérité, vu que cette vérité est la raison directe ayant fait de vous le gagnant de la mission au Liban. J’entends par là : le problème posé par les armes de la Résistance.

Il ne vous a pas fallu longtemps pour avouer ouvertement cette première moitié de ce qui vous intéresse au Liban ; l’autre moitié se résumant à votre obsession de gagner des contrats s’appropriant ce qui reste de la richesse de l’État et du peuple.

Des richesses passant du port martyr de Beyrouth à son aéroport menacé du même sort, à l’électricité, à l’eau, au téléphone cellulaire, aux infrastructures et, bien sûr, à ce que la terre et les eaux du Liban contiennent de pétrole et de gaz, là où le géant de l’énergie, la société Total, occupe le devant de la scène.

Mis à part ces deux préoccupations majeures, votre discours [1] sur la dimension humanitaire, réformatrice et éthique de votre mission au Liban est resté dans les limites de sa fonction de maquillage et d’un semblant d’élégance.

Ceux qui attendaient le contraire de votre part ont été désagréablement surpris. C’est leur problème car dans le dictionnaire des États, les promesses n’ engagent que ceux qui y croient.

Outre les félicitations, il nous faut discuter ensemble, chacun à partir de son camp, de la question de l’affrontement direct avec les forces qui s’opposent à la campagne coloniale destructrice désignée par « printemps arabe ».

Pour rappel, Monsieur le Président, cette expression avait déjà été utilisée par les gouvernements français il y a 172 ans, lorsqu’ils avaient affirmé que la création de la sinistre mission « Baudicour » [2] serait le début du printemps des peuples. Mission qui consistait à déraciner les maronites libanais de leurs terres et à les transférer en Algérie.

Conformément à votre habitude des raccourcis, votre conférence de presse du 27 septembre 2020 est venue confirmer vos déclarations annoncées quelques heures avant votre deuxième visite au Liban, le 1er septembre 2020.

C’est ainsi que vous avez ajouté une zone d’ombre encore plus dense dans l’espace des relations libano-françaises ; autrement dit, une nouvelle ambiguïté qui s’ajoute aux précédentes déjà évoquées [3] et qui mène à une lecture différente du devenir des relations entre nos deux pays, loin de la propagande entourant le mythe d’amour et de tendresse pour le Liban.

Cette fois, vous nous avez rappelés une époque supposée révolue, étant donné qu’aujourd’hui vous nous apparaissez plutôt proche d’un haut-commissaire.

Cependant, avec moins de pouvoirs que vos prédécesseurs à ce poste, car leur référence était Paris, tandis que votre véritable référence se situe quelque part dans le « Nouveau Monde ».

Cela ne vous est absolument pas étranger. Vous êtes le tenant d’une démarche politique ayant opté pour une France européenne, plutôt que pour une France française et si vous aviez à choisir entre une Europe européenne et une Europe atlantiste, vous opteriez pour une Europe atlantiste.

Et je n’irai pas jusqu’à dire, comme certains, que vous iriez jusqu’à préférer l’appartenance aux États-Unis à l’appartenance à l’Europe atlantiste.

C’est probablement la raison qui fait qu’à aucun moment vous n’avez abordé la question cruciale de la Résistance qui protège autant qu’elle le peut le Liban du monstre raciste sioniste, alors que vous considérez le manque de respect à la mémoire de la Résistance française comme un péché mortel.

En effet, la résistance à l’occupation et la défense des patries est par principe une question morale, éthique, légale et humaine, toute proche de la sainteté.

Trouvez-vous qu’il est sérieux de parler de la nôtre comme vous l’avez fait ? Pour de nombreux Libanais, votre discours sur la Résistance libanaise est venu comme un coup de poignard en plein cœur.

Peut-être que vous ne l’avez pas voulu. Et, peut-être que vous avez écouté plus qu’il ne le faut vos conseillers et vos amis, lesquels n’ont fait que vous impliquer dans un problème pouvant fortement compromettre la relation historique entre nos deux pays dans le présent et le futur.

Monsieur le Président,

Je n’ai pas été surpris par votre totale indifférence à l’analyse du dossier libanais par le respecté homme d’État français [4], Maurice Couve de Murville.

La différence entre vous porte non seulement sur l’époque, l’expérience et la culture, mais aussi sur l’appartenance. Il était dans la fleur de l’âge lorsqu’il a rejoint le Commandant de la France libre, a travaillé à la radio de la Résistance, est resté proche du Général de Gaulle tout au long de sa vie et a été ministre des Affaires étrangères, puis Premier ministre.

Ce qui explique qu’il ait tenu à ne pas prendre parti face aux querelles des Libanais et donc à ne pas les encourager à détruire leur pays.

Naturellement, à l’époque il n’a pas eu à s’opposer à la résistance naissante qui a expulsé les monstres sionistes de la capitale Beyrouth ; première capitale arabe occupée par l’armée israélienne lorsque le Hezbollah n’était pas encore né. Lequel Hezbollah est néanmoins né de la matrice de cette première résistance triomphante qui a brisé les crocs des monstres sionistes et les a expulsés de Beyrouth que vous avez visité et dans les rues duquel vous vous êtes promené.

Vous êtes censé avoir été informé de ces faits historiques avant d’user d’expressions offensantes contre notre Résistance, abstraction faite de votre position de principe en raison de vos engagements otano-sionistes.

C’est là une atteinte à la dignité de la patrie libanaise, laquelle suppose que vous lui présentiez vos excuses.

Vous avez parfaitement le droit de haïr la Résistance et de la combattre, mais vous n’avez pas le droit de l’offenser alors que vous traitez du sujet libanais au titre de l’amitié.

Imaginez la situation inverse où un Libanais se tiendrait devant vous pour traiter de la sorte la Résistance française. Quelle serait votre réaction ? Je m’attends à ce que vous entriez dans une grande colère ; là aussi, abstraction faite de votre propre opinion sur la Résistance française qui ne concerne que vous.

Et que dire de vos propos prétendant que la Résistance libanaise sème la terreur en Syrie ?

Que cela vous plaise ou non, Monsieur le Président, cette Résistance est le fer de lance de la défense territoriale contre le terrorisme, à commencer par les organisations atlantistes de la terreur, c’est-à-dire Daech, le Front al-Nosra, la Brigade Sultan Mourad, la Harakat Nour al-Din al Zenki et l’ensemble de leurs dérivées bénéficiant globalement du parrainage de votre Organisation du traité de l’Atlantique nord [l’OTAN] et du financement puisé dans les caisses des pays du Golfe, occupés par vos armées atlantistes.

Plus de 170 000 terroristes venus d’Europe et d’autres pays, amenés par votre organisation au cœur de la géographie syrienne pour la déchirer de l’intérieur, menant ainsi la plus monstrueuse des campagnes coloniales que l’histoire ait connues au cours de ses différentes époques. Organisations qui « font du bon boulot », comme l’a dit un jour l’un de vos ministres des Affaires étrangères !

C’est pourquoi vous vous en prenez à la résistance libanaise. C’est peut-être aussi parce qu’elle a énormément contribué à la défense de la présence chrétienne sur la sainte terre syrienne pendant que votre alliance atlantique, laquelle excelle dans la flagellation des peuples et la négation de leurs droits humains les plus élémentaires, travaille jour et nuit à effacer les traces du christianisme de la terre palestinienne du premier révolutionnaire humaniste, Jésus-Christ, et les traces du crime commis le 30 septembre 2000 contre l’enfant Mohammed al-Durah [5], son père, ses frères et ses sœurs.

Et c’est plus probablement encore, Monsieur le Président, la raison qui vous pousse à voir une contradiction incompréhensible entre la résistance du Hezbollah à Israël et son droit d’être un parti respecté au Liban.

Imaginez, là aussi, qu’un Libanais vous dise que toute force française ayant résisté aux nazis perdrait son droit à former un parti politique respecté en France. Serait-ce raisonnable ? Question, évidemment indépendante de votre propre opinion sur le fascisme et le nazisme qui ne concerne que vous.

Tout comme le Christ, le peuple du Christ est persécuté. Le pape Benoît XVI n’a-t-il pas condamné « l’hostilité et les préjugés à l’encontre des chrétiens » en Europe » ?

Lisez, Monsieur le président, son message pour la Journée mondiale de la paix du 1er janvier 2011. Cette même année où vous avez inauguré l’orgie sanguinaire via votre printemps arabe. Dans le quatorzième paragraphe de ce terrible message, le penseur Joseph Ratzinger semble considérer que vos discours au monde manquent de sincérité.

Contentez-vous de lire ce seul paragraphe, votre excellence, car il est fort probable que vous ne soyez pas intéressé par ce genre de lecture.

Lors de votre conférence de presse, alors que je vous observais pendant que vous déversiez vos ressentiments, j’ai senti toute la froideur de vos paroles en dépit de la volubilité de votre langage corporel.

Vous êtes apparu froid et nullement concerné par la requête libanaise qui vous a été personnellement adressée ; celle de fournir une image satellite [6] de la terrible explosion terrestre engendrée par le crime complexe contre l’existence même du Liban. Vos paroles resteront creuses et sans valeur tant que vous éluderez notre demande destinée à savoir qui a dirigé l’explosion hirochimienne contre le port de Beyrouth, pour favoriser le port de Haïfa en Palestine occupée.

Nous voulons la vérité ; la vérité pour le Liban. Nous avez-vous entendus, vous qui vous permettez de nous donner des leçons en insultant nos politiciens voleurs, afin de susciter notre amitié et de gagner notre confiance, tout en continuant à vous entendre avec eux et à dissimuler le coupable ? Il en est toujours ainsi : généralisation, hausse du ton, débats creux aboutissant à la dissimulation du coupable. Une technique, cher Président, qui ne trompe que ceux qui croient aux paroles des États. Où sont donc les images satellite ? Et que cache leur non divulgation ?

Désolé, Monsieur le Président, pour avoir oublié que votre éloquence en matière de transparence, de démocratie et de droits humains n’a d’égale que l’éloquence de vos confrères banquiers lorsqu’ils insistent pour que les clients déposent leur argent et leurs économies dans les coffres de leurs banques, pour qu’une opération de sublimation transforment ensuite leurs dépôts en vapeurs lorsque sonnera l’heure du grand pillage et de la destruction des familles, sous couvert de telle ou telle révolution colorée, comme cela s’est passé et se passe encore au Liban. Choses que ne pouvez ignorer, votre Excellence.

Et c’est peut-être parce que vous maitrisez ce savoir que vous avez complètement ignoré les aveux particulièrement terribles, formulés quelques heures avant votre grande conférence de presse, devant le Congrès américain, par le diplomate américain, David Hale ; un homme d’une grande politesse, un amoureux de la paix et de l’harmonie entre les humains au point d’accompagner les orgies sanguinaires au Liban depuis des décennies. Il a déclaré que son administration avait dépensé et distribué dix milliards de dollars [7] au profit de ceux en qui vous avez confiance au Liban : des organisations non gouvernementales et des inféodés fiables au sein des cercles politiques et des médias menteurs.

Des aveux venus s’ajouter aux déclarations antérieures d’un autre diplomate américain, tout aussi féru des orgies sanguinaires au Liban : le nommé Jeffrey Feltman. Lequel avait affirmé le 8 juin 2010, toujours devant le Congrès américain, que son administration pacifique, qui hait les massacres et les assassinats, avait dépensé un demi-milliard de dollars au cœur du Liban afin de défigurer l’image du Hezbollah [8].

Les oreilles de ces individus, Monsieur le Président, entendent essentiellement vos collègues parmi les banquiers internationaux, tandis que leurs yeux sont tournés vers la Banque centrale libanaise qu’ils se préparent à dépouiller de son droit exclusif d’émettre la monnaie. Pour cela, le prétexte est fin prêt : la Banque du Liban n’étant plus digne de confiance, ce privilège doit être confié à des banques privées.

Mais, puisque les banques privées ont également perdu leur crédibilité avec la complicité du gouverneur de la Banque centrale (l’équivalent d’Edgar Hoover en matière de finances) et des sommités du comité des banques, lesquels passent la moitié de leur temps à Paris loin des projecteurs des patriotes libanais, le privilège doit plutôt être confié à des banques internationales.

Et la « Bank of New York », l’une des plus grande banques, propriétaire de la Réserve fédérale américaine, détient désormais 34% des plus grandes banques libanaises, grâce à une opération furtive de vol mi-2019. Une opération que les médias libanais « libres » ont dissimulée, ces mêmes médias financés par les dix milliards de dollars précités et devenus promoteurs de ladite révolution ; la révolution de l’autodestruction au nom de la lutte contre la corruption.

Est-il possible, Monsieur le Président, que vous ignoriez ce vol généralisé de tout un peuple par les banques !? Il est étonnant que vous ayez pu oublier un fait aussi terrible, exactement comme vous semblez avoir oublié les images satellite, lesquelles faciliteraient grandement la désignation des responsables de l’explosion hirochimienne du port de Beyrouth.

Monsieur le Président,

Il m’est difficile de croire ceux qui prétendent que vous n’êtes pas au courant de tout cela, tout comme il m’est difficile de croire que vous ne sachiez pas que vos avions de l’OTAN brûlent systématiquement des champs de céréales et des cultures de terres fertiles en Syrie, pour que les Syriens meurent de famine pendant que le blocus atlantiste les prive des moyens de combattre l’invasion de la pandémie virale.

Vous qui êtes issu du monde civilisé, transparent, défenseur des droits humains, naturellement et avant tout démocrate, vous devez présenter vos excuses aux Libanais, à nous tous, Monsieur le Président. Ce serait honteux de vous en abstenir. Quant à nous :

Notre Liban est et restera à nous, il n’est pas à vendre. Notre Syrie est et restera à nous. Notre Palestine était et reviendra au peuple du Christ… notre peuple.

Une fois de plus, Monsieur le Président, veuillez accepter mes meilleures salutations.

Hassan Hamadé

Traduction de l’arabe par Mouna Alno-Nakhal

Source : Al-Intichar (Liban)

Notes :

[1][ Conférence de presse du Président Emmanuel Macron sur la situation au Liban. (diffusée en direct le 27 septembre 2020 (vidéo)]
[2][ Le projet Baudicour de 1848]
[3][Première lettre ouverte au Président Macron ; par Hassan Hamadé]
[4] [La crise libanaise et l’évolution du Proche-Orient [Maurice Couve de Murville]
[5][Charles Enderlin & l’affaire Mohammed al-Durah (vidéo)]
[6][Aoun demande à Macron des images aériennes du moment de l’explosion]
[7] [Al-Mayadeen / Hale : nous avons dépensé 10 milliards de dollars pour les forces de sécurité et la société civile libanaises (vidéo)]
[8][Al-Mayadeen / Jeffrey Feltman : Les USA ont dépensé 500 milliards de dollars pour défigurer l’image du Hezbollah (vidéo)]

Evolution theory was known long time before Darwin.

Darwin collected data before coming forward with his knowledge.

The same case with Euler who had Not a shadow of doubt that planet trajectories were elliptical. He still plugged in for years to gather the necessary data to come forward with his proof.

Many scientists start with an intuition and end up retaining the data that match their hypothesis. The common people have to wait for other kinds of scientists to analyse all the data and start a paradigm shift that discard the traditional knowledge.

Un érudit musulman a eu l’idée de l’évolution 1000 ans avant Darwin

Deux pages du Livre des Animaux d'al-Jahiz

Charles Darwin est le père de la théorie de l’évolution, mais avez-vous entendu parler du scientifique irakien Al-Jahiz ?

L’histoire de la théorie de l’évolution remonte loin dans le monde musulman.

La théorie de l’évolution du scientifique britannique Charles Darwin est l’une des pierres angulaires de la science moderne.

L’idée que les espèces changent progressivement au fil du temps grâce à un mécanisme appelé sélection naturelle (adapting to the environment) a révolutionné notre compréhension du monde vivant.

Dans son livre de 1859, De l’origine des espèces, Darwin définit l’évolution comme une “descente avec modification”, démontrant comment différentes espèces émergent d’un ancêtre commun.

Mais il semble que la théorie de l’évolution elle-même ait aussi un ancêtre dans le monde islamique.

La sélection naturelle

Environ 1000 ans avant que Charles Darwin n’écrive un livre sur la façon dont les animaux changent par un processus qu’il appelait “sélection naturelle”, un philosophe musulman vivant en Irak, qui s’appelait Al-Jahiz l’avait déjà précédé.

De son vrai nom Abu Usman Amr Bahr Bahr Alkanani al-Basri, l’histoire se souvient de lui par son surnom, Al-Jahiz, qui signifie quelqu’un dont les yeux semblent sortir de leur orbite.

Timbre représentant le penseur musulman al-Jahiz

Ce n’est pas la façon la plus gentille d’appeler quelqu’un, mais la renommée d’Al-Jahiz perdure grâce à son livre fondateur, Kitab al-Hayawan (Le Livre des animaux).

Il est né en 776 après J.-C. dans la ville de Bassorah, au sud de l’Irak, à l’époque où le mouvement Mutazilah, (Mo3tazalat) une école de pensée théologique qui prônait l’exercice de la raison humaine, gagnait du terrain dans la région.

C’était le sommet de la domination abbasside.

Des travaux de savants ont été traduits du grec à l’arabe et de puissants débats sur la religion, la science et la philosophie ont eu lieu à Bassorah, façonnant l’esprit d’Al-Jahiz et l’aidant à formuler ses idées.

Le papier a été introduit en Irak par des commerçants chinois, ce qui a stimulé la diffusion des idées et le jeune Al-Jahiz a commencé à écrire sur une variété de sujets.

Ses intérêts couvraient de nombreux domaines académiques, y compris la science, la géographie, la philosophie, la grammaire arabe et la littérature.

On pense qu’il a produit 200 livres au cours de sa vie, mais seulement un tiers d’entre eux ont survécu jusqu’à notre époque.

Portrait de Charles Darwin

Le Livre des Animaux

Son œuvre la plus célèbre, The Book of Animals, est conçue comme une encyclopédie présentant 350 animaux, dans laquelle Al-Jahiz présente des idées qui ont une ressemblance frappante avec la théorie de Darwin sur l’évolution.

“Les animaux s’engagent dans une lutte pour l’existence et pour les ressources, pour éviter d’être mangés et pour se reproduire”, écrit Al-Jahiz, “les facteurs environnementaux influencent les organismes à développer de nouvelles caractéristiques pour assurer leur survie, les transformant ainsi en de nouvelles espèces”.

Il ajoute : “Les animaux qui survivent pour se reproduire peuvent transmettre leurs caractéristiques à leur progéniture.”

Il était clair pour Al-Jahiz que le monde vivant était en lutte constante pour sa survie et qu’une espèce était toujours plus forte qu’une autre.

La couverture du magazine satirique français La Petite Lune en 1871

Pour survivre, les animaux devaient avoir des caractéristiques compétitives pour trouver de la nourriture, éviter de devenir eux-mêmes la nourriture de quelqu’un d’autre et se reproduire.

Cela les a forcés à changer de génération en génération.

Les idées d’Al-Jahiz ont influencé d’autres penseurs musulmans qui lui ont emboîté le pas.

Son travail a été lu par des gens comme Al-Farabi, Al-Arabi, Al-Biruni et Ibn Khaldoun.

Le “Père spirituel” du Pakistan, Muhammad Iqbal, également connu sous le nom d’Allama Iqbal, observe l’importance d’Al-Jahiz dans son recueil de conférences publié en 1930, écrivant que “c’est Al-Jahiz qui a souligné les changements dans la vie des animaux à cause des migrations et des changements environnementaux”.

Théorie mahométane (Muslim theory)

La contribution du monde musulman à l’idée d’évolution n’était pas un secret pour l’intellectuel du XIXe siècle en Europe.

En effet, un contemporain de Charles Darwin, le scientifique William Draper, parlait en 1878 de la “théorie mahométane de l’évolution”.

Dessin de quatre espèces de pinsons observés par Darwin aux îles Galápagos

Le naturaliste britannique mérite à juste titre sa réputation de scientifique qui a passé des années à voyager et à observer le monde naturel, et qui a fondé sa théorie avec une précision et une clarté sans précédent pour transformer notre façon de voir le monde.

Mais le journaliste scientifique Ehsan Masood, qui a réalisé une série de documentaires pour la BBC intitulée “Islam et Science”, dit qu’il est important de se souvenir de ceux qui ont contribué à l’histoire de la pensée évolutionnaire.


Il note également que le créationnisme ne semble pas exister en tant que mouvement significatif pendant le IXe siècle en Irak, lorsque Bagdad et Bassora étaient les principaux centres d’enseignement supérieur de la civilisation islamique.

“Les scientifiques n’ont pas passé des heures à examiner des passages de la révélation pour voir s’ils se comparent aux connaissances observées sur le monde naturel”, écrit Ehsan Masood dans un article sur Al-Jahiz dans le journal britannique The Guardian.

“Au lieu de cela, ils sont sortis et ont essayé de découvrir des choses par eux-mêmes.”

En fin de compte, c’est la quête du savoir qui a entraîné la mort d’Al-Jahiz.

On dit qu’à l’âge de 92 ans, alors qu’il essayait de prendre un livre sur une étagère lourde, il s’est effondré sur lui, tuant le philosophe musulman.

« Le monde a besoin de science la science a besoin des femmes »

Process of system/mission analyses? What are the phases?

Written in April 14, 2006

Systems, missions, and products that involve human operators to run, maintain, and keep up-to-date, as societies evolve and change, need to be analyzed at intervals for its consistency with the latest technology advances, people’s expectations, government regulations, and international standards.

To that end, the latest development in the body of knowledge of human physical and cognitive capabilities, along with the latest advancement in the methods applied for analyzing and designing systems have to be revisited, tested, and evaluated for better predictive aptitude of specific human-machine performance criteria.

This article is a refresher tutorial of the necessary sequence of human factors methods offered to analyze each stages in system development.

In general, the basic milestones in system development begin with the exploration concept, demonstration of the concept, validation, full-scale engineering development, testing and debugging for errors and malfunctions, production, and finally operations and support systems for marketing.

Each one of these stages requires the contribution of human factors professionals and experts from the extensive array of methods they dispose of and are trained for, to their vast store of data on human capabilities and limitations, and to their statistical and experimental formation.

Human factors professionals can also contribute to the baseline documentation, instructions, training programs, and operations manuals.

There is a mission for each stage of development concerning the end product of the stage to the next and the sequence follows 7 steps.

The first step is constituted of four analyses requirements; mainly, operational or the projected operations that will confront operators and maintainers, then comparing similar systems in operations and functions, measuring and quantifying the activities involved in the operations, and then identifying the sources of difficulties or critical incidents that may have to be overcome among the interactions of operators and machines.

The second phase is to figure out the flow of functions and the kinds of action/decision or binary choices at each junction of two successive functions. There are no equipments in mind at this phase of analyses.

The third phase is concerned with the types of information necessary to undertake each action identified in the second phase.

The fourth phase is the study of allocating operators to sets of functions and activities and how many operators and skill levels might be needed to fulfill the mission.

The fifth phase is to construct detailed analyses of the required tasks for each activity/function and basically trying to integrate among people, software, and hardware for smooth operations.

The sixth phase might call for an assortment of methods in order to collect detailed data for the network of tasks such as faulty events, mode of failures, the effects or seriousness of the failures, timeline from beginning to ending a task/activity, how the tasks are linked and how often two tasks come to be interacted, simulation techniques whether a computer simulation of virtual real world or prototyping, and eventually conducting controlled experimentations when the previous traditional methods cannot answer specific problems of cause and effects among the variables.

The seventh and final phase in the analysis of a stage of development is to study the sequence of operations and the physical and mental workload of each operator and to finalize the number and capabilities of the crew operating as a team.

The last five phases are time consuming and it is imperative that the first two phases be well planned, analyzed and firm decisions made for the remaining phases in funding, duration of study, and level of details.

In all these phases human factors are well trained to undertake the analyses because they have the knowledge and methods to extract the capabilities and limitations of human operators interacting with the software and hardware so that the design, trade-off studies, and prediction of human performance match the requirements for achieving a mission.

The ultimate output/product of the sequence of analyses becomes inputs to specifications, reviews, and for design guidelines.


Your sense of smell controls what you spend and who you love

Does this means when you lose this sense of smell your spending and falling in love habits are thrown into chaos?

By Georgia Frances King 

Smell is the ugly stepchild of the sense family.

Sight gives us sunsets and Georgia O’Keefe.

Sound gives us Brahms and Aretha Franklin.

Touch gives us silk and hugs.

Taste gives us butter and ripe tomatoes.

But what about smell?

It doesn’t exist only to make us gag over subway scents or tempt us into a warm-breaded stupor.

Flowers emit it to make them more attractive to pollinators. Rotting food might reek of it so we don’t eat it.

And although scientists haven’t yet pinned down a human sex pheromone, many studies suggest smell influences who we want to climb in bed with. (Not a brainer. what of foul breath, sweat, soiled clothes, unclean hair…)

Olivia Jezler studies the science and psychology that underpins our olfactory system.

For the past decade, she has worked with master perfumers, developed fragrances for luxury brands, researched olfactory experience at the SCHI lab at University of Sussex, and now is the CEO of Future of Smell, which works with brands and new technologies to design smellable concepts that bridge science and art.

In this interview, Jezler reveals the secret life of smell. Some topics covered include:

  • how marketers use our noses to sell to us
  • why “new car smell” is so pervasive
  • how indoor air is often more polluted than outdoor air
  • the reason why luxury perfume is so expensive
  • why babies smell so damn good
  • how Plato and Aristotle poo-pooed our sense of smell

This interview has been condensed and edited for clarity.

Quartz: On a scientific level, why is smell such an evocative sense?

Olivia Jezler: Our sense of smell is rooted in the most primal part of our brain for survival. It’s not linked through the thalamus, which is where all other sensory information is integrated: It’s directly and immediately relayed to another area, the amygdala.

None of our other senses have this direct and intimate connection to the areas of the brain that process emotion, associative learning, and memory. (That’s why we don’t dream “smell”)

Why? Because the structure of this part of the brain—the limbic system—grew out of tissue that was first dedicated to processing the sense of smell.

Our chemical senses were the first that emerged when we were single-cell organisms, because they would help us understand our surroundings, find food, and reproduce.

Still today, emotionally driven responses through our senses of taste and smell make an organism react appropriately to its environment, maximizing its chances for basic survival and reproduction.

Beauty products like lotions and perfumes obviously have their own smells. But what businesses use scent in their branding?

It’s common for airlines to have scents developed for them. Air travel is interesting because, as it’s high stress, you want to make people feel connected to your brand in a positive way.

For example, British Airways has diffusers in the bathrooms and a smell for their towels. That way you walk in and you can smell the “British Airways smell.”

It’s also very common in food.

You can design food so that the smell evaporates in different ways. Nespresso capsules, for instance, are designed to create a lot of odor when you’re using one, so that you feel like you’re in a coffee shop.

I’m sure a lot of those make-at-home frozen pizza brands are designed to let out certain smells while they’re in the oven to feel more authentic, too.

That’s an example of the “enhancement of authenticity.” Another example might be when fake leather is made to smell like real leather instead of plastic.

So we got used to the smell of natural things, but then as production became industrialized, we now have to fabricate the illusion of naturalness back into the chemical and unnatural things?

Yes, that’s it. People will feel more comfortable and they’ll pay more for products that smell the way we imagine them to smell.

For example: “new car smell.” When Rolls Royce became more technologically advanced, they started using plastic instead of wood for some parts of the car—and for some reason, sales started going down. They asked people what was wrong, and they said it was because the car didn’t smell the same. It repelled people from the brand. So then they had to design that smell back into the car.

New car smell is therefore a thing, but not in the way we think. It is a mix of smells that emanate from the plastics and interiors of a car.

The cheaper the car, the stronger and more artificial it smells. German automakers have entire olfactory teams that sniff every single component that goes into the interior of the car with their nose and with machines.

The problem then is if one of these suppliers changes any element of their product composition without telling the automaker, it throws off the entire indoor odor of the car, which was carefully designed for safety, quality, and branding—just another added complexity to the myriad of challenges facing automotive supply chains!

Are these artificial smells bad for us?

Designed smells are not when they fulfill all regulatory requirements. This question touches on a key concern of mine: indoor air. Everybody talks about pollution.

Like in San Francisco, a company called Aclima works with Google to map pollution levels block by block at different times of the day—but what about our workplaces? Our homes? People are much less aware of this.

We are all buying inexpensive furniture and carpets and things that are filled with chemicals, and we’re putting them in a closed environment with often no air filtration.

Then there are the old paints and varnishes that cover all the surfaces! Combine that with filters in old buildings that are rarely or never changed, and it gets awful.

When people use cleaning products in their home, it’s also putting a lot more chemicals into the house than before. (You should open your windows after you clean.)

We’re therefore inhaling all these fumes in our closed spaces. In cities like New York, we spend 90% of our time indoors and the air is three times worse than outdoors.

The World Health Organization says it’s one of the world’s greatest environmental health risks.

There are a few start-ups working on consumer home appliances that help you monitor your indoor air, but I am still waiting to see the one that can integrate air monitoring with filtering and scenting.

Manufacturing smell seems to fall into two camps. The first is fabricating a smell when you’ve taken the authenticity out of the product and other brands simply enhance an existing smell. That’s not fake, but it still doesn’t seem honest.

To me they seem like the same thing: Because they are both designed to enhance authenticity.

There’s an interesting Starbucks case related to smell experiences and profits.

In 2008 they introduced their breakfast menu, which included sandwiches that needed to be reheated. The smell of the sandwiches interfered with the coffee aroma so much that it completely altered the customer experience in store: It smelled of food rather than of coffee.

During that time, repeat customer visits declined as core coffee customers went elsewhere, and therefore sales at their stores also declined, and this impacted their stock. The sandwiches have since been redesigned to smell less when being reheated.

This is starting to feel a bit like propaganda or false advertising. Are there laws around this?

No, there aren’t laws for enhancing authenticity through smell. Maybe once people become more aware of these things, there will be. I think it’s hard at this point to quantify what is considered false advertising.

There aren’t even laws for copyrighting perfumes!

This is a reason why everything on the market usually kind of smells the same: Basically you can just take a perfume that’s on the market and analyze it in a machine that can tell you its composition. It’s easily recreated, and there’s no law to protect the original creation. Music has copyright laws, fragrance does not.

That’s crazy. That’s intellectual property.

It is. As soon as there’s a blockbuster, every brand just goes, “We want one like that!” Let’s make a fragrance that smells exactly like that, then lets put it in the shampoo. Put it in the deodorant. Put it in this. Put it in that.

If the perfume smells the same and is made with the same ingredients, why do we pay so much more for designer perfumes?

High fashion isn’t going to make [luxury brands] money—it’s the perfumes and accessories.

What differs is the full complexity of the fragrance and how long it lasts.

As for pricing, It’s very much the brand. Perfume is sold at premium for what it is—but what isn’t?

Your Starbucks coffee, Nike shoes, designer handbags… There can be a difference in the quality of the ingredients, yeah, but if it’s owned by a luxury brand and you’re paying $350, then you’re paying for the brand.

The margins are also really high: That’s why all fashion brands have a perfume as a way of making money. High fashion isn’t going to make them money—it’s the perfumes and accessories. They play a huge, huge role in the bottom line.

How do smell associations differ from culture to culture?

Because of what was culturally available—local ingredients, trade routes et cetera—countries had access to very specific ingredients that they then decided to use for specific purposes.

Because life was lived very locally, these smells and their associations remained generation after generation.

Now if we wanted to change them, it would not happen overnight; people are not being inundated with different smell associations the way they are with fashion and music.

Once a scent is developed for a product in a certain market, the cultural associations of the scent of “beauty,” “well-being,” or “clean” stick around. The fact that smells can’t yet transmit through the internet means that scent associations also keep pretty local.

For example, multinational companies want to develop specific fragrances and storylines for the Brazilian market. Brazilian people shower 3.5 times a day. If somebody showers that much, then scent becomes really important. When they get out of the shower, especially in the northeast of Brazil, they splash on a scented water—it’s often lavender water, which is also part of a holy ritual to clean a famous church, so it has positive cultural connotations.

Companies want to understand what role each ingredient already plays in that person’s life so that they can use it with a “caring” or “refreshing” claim, like the lavender water.

Lavender is an interesting one. In the US, lavender is more of a floral composition versus true lavender. People like the “relaxing lavender” claim, but Americans don’t actually like the smell of real lavender.

On the other hand, in Europe and Brazil, when it says “lavender” on the packaging, it will smell like the true lavender from the fields; in Brazil, lavender isn’t relaxing—it’s invigorating!

In the UK, florals are mostly used in perfumes, especially rose, which is tied to tradition.

Yet in the US, a rose perfume is considered quite old-fashioned—you rarely smell it on the subway, whereas the London Tube smells like a rose garden.

In Brazil, however, florals are used for floor and toilet cleaners; the smell of white flowers like jasmine, gardenia, and tuberose are considered extremely old-fashioned and unrelatable. However, in Europe and North America, these very expensive ingredients are a sign of femininity and luxury.

Traditional Chinese medicine influences the market in China: Their smells are a bit more herbal or medicinal because those ingredients are associated with health and well-being. You see that in India with Ayurvedic medicine as well. By comparison, in the US, the smell of health and cleanliness is the smell of Tide detergent.

Are there smells we can all agree on biologically, no matter where we’re from, that smell either good or bad?

Yes: Body fluids, disease, and rotten foods are biological no-nos.

Natural gas, which you can smell in your kitchen if you leave the gas on by mistake, is in reality odorless: A harmless chemical is added to give gas a distinctive malodor that is often described as rotten eggs—and therefore act as a warning!

The smell of babies, on the other hand? Everybody loves the smell of babies: It’s the next generation.

Do you wear perfume yourself?

I wear tons of perfume. However, if I’m working in a fragrance house or a place where I smell fragrances all the time, I don’t wear perfume, because it then becomes difficult to smell what is being created around me. There is also a necessity for “clean skin” to test fragrances on—one without any scented lotions or fragrances.

Why does perfume smell different on different people? Is it because it reacts differently with our skin, or is it because of the lotions and fabric softeners or whatever other smells we douse ourselves in?

Cancers and diabetes can be identified through body odor.

Generally, it’s our DNA. But there are different layers to how we smell. Of course, the first layer is based on the smells we put on: soaps and deodorants and whatever we use. Then there’s our diet, hydration level, and general health.

An exciting development in the medical world is in diagnostics: Depending upon if we’re sick or not, we smell different.

Cancers and diabetes can be identified through body odor, for instance. Then on the most basic level, our body odor is linked to the “major histocompatibility complex” (MHC), which is a part of the genome linked to our immune system. It is extremely unique and a better identifier than a retinal scan because it is virtually impossible to replicate.

Why don’t we care more about smell?

The position that our sense of smell holds is rooted in the foundation of Western thought, which stems from the ancient Greeks. Plato assigned the sense of sight as the foundation for philosophy, and Aristotle provided a clear hierarchy where he considered sight and hearing nobler in comparison to touch, taste, and smell.

Both philosophers placed the sense of smell at the bottom of their hierarchy; logic and reason could be seen and heard, but not smelt.

The Enlightenment philosophers and the Industrial Revolution did not help, either, as the stenches that emerged at that time due to terrible living conditions without sewage systems reminded us of where we came from, not where we were headed.

Smell was not considered something of beauty nor a discipline worth studying.

It’s also a bit too real and too closely tied to our evolutionary past. We are disconnected from this part of ourselves, so of course we don’t feel like it is something worth talking about.

As society becomes more emotionally aware, I do think smell will gain a new role in our daily lives.

This article is part of Quartz Ideas, our home for bold arguments and big thinkers.




December 2020

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