The Seesaw

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I am sitting on a seesaw with my past. As long as I can put Hitler, or Mengele, or the gaping mouth of my loss on the opposite seat, then I am somehow justified, I always have an excuse. That’s why I’m anxious. That’s why I’m sad. It’s not that I’m wrong to feel anxious and sad and afraid. It’s not that there isn’t real trauma at the core of my life. And it’s not that Hitler and Mengele and every other perpetrator of violence or cruelty shouldn’t be held accountable for the harm the cause. But if I stay on the seesaw, I am holding the past responsible for what I choose to do now. 

Auschwitz survivor Edith Eva Eger in her book The Choice

Stale and ineffective

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Organizations are created by their founders to serve vibrant, living purposes. but all too often the founding purposes fade and what finally get served are the purposes of institutional self-enhancement. It happens in hospitals to the detriment of patients, in schools to the detriment of students, in businesses to the detriment of shareholders and customers, end in government to the detriment of taxpayers. It is rarely the result of evil intent: it happens because memes triumph over ends, form triumphs over spirit, and the turf syndrome conquers all.

John W. Gardner, On Leadership

When the dream of childhood ends

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For most people it is the demands of life which harshly put an end to the dream of childhood. If the individual is sufficiently well prepared, the transition to a professional career may take place smoothly. But if he clings to illusions that contradict reality, then problems will surely arise. No one takes the step into life without making certain presuppositions—and occasionally they are false. That is, they may not fit the conditions into which one is thrown. It is often a question of exaggerated expectations, of under-estimation of difficulties, of unjustified optimism or of a negative attitude.

CG Jung, Modern Man in Search of a Soul

Make friends who don’t see you as a professional object

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It makes me feel good when a person I meet for the first time recognizes me as a columnist for The Atlantic rather than as some random guy—but can easily become a barrier to the formation of healthy friendships, which we all need. By self-objectifying in your friendships, you can make it easier for your friends to objectify you.

This is why having friends outside your professional circles is so important. Striking up friendships with people who don’t have any connection to your professional life encourages you to develop nonwork interests and virtues, and thus be a fuller person. The way to do this goes hand in hand with recommendation No. 1: Don’t just spend time away from work; spend it with people who have no connection to your work. 

You are not your job, and I am not mine. Take your eyes off the distorted reflection, and have the courage to experience your full life and true self.

Arthur C. Brooks writing in The Atlantic

Not all encouragement is the same

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Praising or criticizing outcomes tends to lead to a fixed mindset. Tell me I'm good at science and I'll start to think my skills are innate; tell me I'm terrible at math and I'll begin to believe there's no hope for me. 

Praising effort and application tends to lead to a growth mindset. Praise me for working hard on a project and I'll begin to believe that effort makes anything possible. Praise me for hanging in there even though I initially failed, and I'll begin to believe that perseverance makes eventual achievement possible. Praise me for taking a risk, and I'll begin to believe that trying new things--especially things I'm not good at--is a natural step on the road to achievement.

Jeff Haden writing in Inc.

The Gospel of Work

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The decline of traditional faith in America has coincided with an explosion of new atheisms. Some people worship beauty, some worship political identities, and others worship their children. But everybody worships something. And workism is among the most potent of the new religions competing for congregants. 

What is workism? It is the belief that work is not only necessary to economic production, but also the centerpiece of one’s identity and life’s purpose; and the belief that any policy to promote human welfare must always encourage more work. 

Derek Thompson writing in The Atlantic

Leading with Empathy

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Leaders can demonstrate empathy in two ways. First, they can consider someone else’s thoughts through cognitive empathy (“If I were in his/her position, what would I be thinking right now?”). Leaders can also focus on a person’s feelings using emotional empathy (“Being in his/her position would make me feel ___”). But leaders will be most successful not just when they personally consider others, but when they express their concerns and inquire about challenges directly, and then listen to employees’ responses.

Leaders don’t have to be experts in mental health in order to demonstrate they care and are paying attention.

Tracy Brower writing in Forbes

Data Science articles from Oct. 2021

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DOD looks to civilian workforce to close technology gaps

Junk Algorithms

OpenAI attempts to summarize two recent KDnuggets posts

A new machine learning optimization technique

The state of undergraduate Bayesian education with recommendations

Commercial remote sensing companies “pivoting marketing efforts away from the NRO and instead focusing on direct sales to other US national security customers”

The value of “small data” approaches: transfer learning, data labeling, artificial data generation, Bayesian methods and reinforcement learning

‘Small Data’ are crucial to machine learning

The US satellite imagery industry readies for the NRO’s Electro-Optical Commercial Layer program—an open competition for satellite imagery products

NGA is planning to begin testing out the concept of using a “data lakehouse” to begin breaking down the walls between where data is managed at the agency

Why the Air Force’s First Software Chief is calling it quits

Masking use of graph neural networks

A case for holding tech companies responsible for their algorithms

CodeNet (and similar projects) are paving the way for Natural Language Coding  

The US Senate is considering bill that would force the military to introduce key performance indicators measuring how effectively it used AI in operations

The problem with p-hacking is not the “hacking,” it’s the “p” 

An Inconvenient Truth About AI: the ghost in the machine is essential (for now) 

Neural networks: structure, types, and possibilities

Is Machine Learning an Art, a Science or Something Else?

Junk Algorithms

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Despite the weight of scientific evidence to the contrary, there are people selling algorithms to police forces and governments that claim to ‘predict’ whether someone is a terrorist or a pedophile based on the characteristics of their face alone. Others insist their algorithm can suggest changes to a single line in a screenplay that will make a movie more profitable at the box office. Others boldly state — without even a hint of sarcasm — that their algorithm is capable of finding your one true love.

There's a trick you can use to spot the junk algorithms. I like to call it the Magic Test. Whenever you see a story about an algorithm, see if you can swap out any of the buzzwords, like ‘machine learning’, ‘artificial intelligence’, and ‘neural network’, and swap in the word magic. Does everything still make grammatical sense? Is any of the meaning lost? If not, I'd be worried that it's all nonsense. Because I'm afraid — long into the foreseeable future —  we are not going to ‘solve world hunger with magic’  or  ‘use magic to write the perfect screenplay’ any more than we are with AI. 

Hannah Fry, Hello World