46 Matching Annotations
  1. Jul 2020
    1. he suggests that a “low-testing” black student and a “high-testing” white student may simply be demonstrating “different kinds of achievement rather than different levels of achievement.”

      What does this even mean?

    2. He argues that the idea of black underachievement lends support for anti-black policies, which in turn help perpetuate the conditions that inspire speeches like his

      This is a poor argument. It’s like saying food is bad because some people get food poisoning or eat too much.

    3. Kendi’s position has radical implications: in ruling out criticism of black culture or black behavior, it stipulates that any problems must be either fictional or the result of contemporary discrimination.

      This is the main issue with Kendi’s viewpoint, it’s overly simplistic.

    4. In his view, the pioneering black sociologist W. E. B. Du Bois was propping up racist ideas in 1897, when he condemned “the immorality, crime, and laziness among the Negroes.” So, too, was Barack Obama, when, as a Presidential candidate in 2008, he decried “the erosion of black families.” Although Obama noted that this erosion was partly due to “a lack of economic opportunity,” he also made an appeal to black self-reliance, saying that members of the African-American community needed to face “our own complicity in our condition.” Kendi saw statements like these as reflections of a persistent but delusional idea that something is wrong with black people.

      Kendi is infantilizing us. His viewpoint suggests that black people have zero agency and need white people to stop being racist in order to succeed. It’s like he’s saying the absence of racism will magically make everything great.

    1. Critical Race Theory acts like anyone who disagrees with it must do so for racist and white supremacist reasons, even if those people are black.

      This is a Kafka trap.

    2. Critical Race Theory believes science, reason, and evidence are a “white” way of knowing and that storytelling and lived experience is a “black” alternative.

      This tells me everything I need to know about critical race theory.

    1. If you object to any of the “feedback” that DiAngelo offers you about your racism, you are engaging in a type of bullying “whose function is to obscure racism, protect white dominance, and regain white equilibrium.”

      And this is a Kafka trap.

    1. The following month, another YA author, Kosoko Jackson, likewise pulled his debut novel after a Twitter mob savaged it for featuring “privileged” protagonists and casting a Muslim character as a villain. Ironically, Jackson, who is black and gay, had worked as a “sensitivity reader” for publishing houses, screening manuscripts for just such politically incorrect content, and on Twitter, like Zhao, he had waged identitarian turf wars. “He was Robespierre,”
    2. In January 2019, debut author Amélie Wen Zhao found herself the subject of such intense criticism—largely for making slavery a feature of her fictional world—that she pulled her YA fantasy novel, Blood Heir
    1. The letter reads as a caustic reaction to a diversifying industry — one that’s starting to challenge institutional norms that have protected bigotry.

      Isn’t it important to make sure that in the pursuit of justice we don’t create new injustices. If we do, aren’t we no better than those we’re fighting against?

    2. Manuscripts for books written by nonwhite authors are not given such leniency.

      This is true. It is also not a valid criticism of the Harper’s letter. It’s more whataboutism. It’s like saying that because group A has fewer problems than group B, group A has no right to complain.

    3. The content of the letter also does not deal with the problem of power: who has it and who does not.

      This is a fair question to ask. It seems like the Harper’s letter does address power though, indirectly. The group doing the canceling is a nameless collective and the concern is that power has shifted to a mass mob. That seems fine as long as the mob’s morality is aligned with yours. But what about when it is not?

    1. Wholly new forms of encyclopedias will appear, ready made with a mesh of associative trails running through them, ready to be dropped into the memex and there amplified.

      This sounds a lot like the personal knowledge management apps we have today, like Notion and Roam Research.

    2. Our ineptitude in getting at the record is largely caused by the artificiality of systems of indexing. When data of any sort are placed in storage, they are filed alphabetically or numerically, and information is found (when it is) by tracing it down from subclass to subclass. It can be in only one place, unless duplicates are used; one has to have rules as to which path will locate it, and the rules are cumbersome. Having found one item, moreover, one has to emerge from the system and re-enter on a new path.The human mind does not work that way. It operates by association.

      This describes why the bidirectional links in note-taking apps like Roam Research are so useful.

    3. The machines for higher analysis have usually been equation solvers. Ideas are beginning to appear for equation transformers, which will rearrange the relationship expressed by an equation in accordance with strict and rather advanced logic.

      Mathematica is probably one of the best example of this.

    1. Frank Luntz stumbled on much the same concept
    2. most words and phrases are actually defined not by a single dictionary description, but rather two distinct attributes

      S.I. Hayakawa's Language in Thought and Action has a great discussion of this.

    3. Russell Conjugation (or “emotive conjugation”)
    1. Our membership inference attack exploits the observationthat machine learning models often behave differently on thedata that they were trained on versus the data that they “see”for the first time.

      How well would this work on some of the more recent zero-shot models?

    1. Essentialists have a representational theory of truth. They believe that a statement is true when it represents the state of reality accurately.Pragmatists have an instrumental theory of truth. They believe that a statement is true when it works — that the only way we can know if something is true is if, by acting according to it, the world reacts in the way we expect it to. 

      As described here, these two viewpoints are not opposites.

    2. Essentialists think about truth in a very specific way. They think that a statement is true when it reflects something essential about the way reality is organized. They think truth is defined as a relationship between a statement and a state of the world.

      This view is in line with science.

    1. It turns out that there's this very broad equivalence between the kinds of computations that different kinds of systems do. That realization makes the question of the human condition a little bit more poignant, because where we might say, "There's one thing we've got—we're special, we've got all this intelligence and all these things which nothing else can have." But that's not true. There are all these different systems of nature that are pretty much equivalent in terms of their computational, or for that matter, intellectual, capabilities.

      Wolfram’s principle of computational equivalence, applied to the human brain and AI.

    1. What contemporary and ancient meditators have always known, however, is that while the hype may be warranted, the practice is not all peace, love, and blissful glimpses of unreality. Sitting zazen, gazing at their third eye, a person can encounter extremely unpleasant emotions and physical or mental disturbances.

      In the yogic tradition, people didn’t generally dive into meditation. They first prepared their body and minds through other means. There’s a reason why Patanjali set dhyan, which is generally translated as meditation, as the seventh limb of yoga in the Yoga Sutras.

    1. data leakage (data from outside of your test set making it back into your test set and biasing the results)

      This sounds like the inverse of “snooping”, where information about the test data is inadvertently built into the model.

    1. Healing that injury means closing racial gaps.

      This is obviously wrong, as there is no reason to think that any two groups will ever have 100% equal outcomes.

      The only way that equal outcomes would be possible for any two groups of people would be for every member of the group to make identical choices, in a level playing field. And even that would not be enough, since identical choices is no guarantee of identical results.

    2. The injury of that wrong determines present outcomes.

      It would have been better for Robinson to say that it affects present outcomes.

    1. Why does solar energy rely upon photovoltaic cells? Wouldn’t it be more efficient to use mirrors to focus the sun’s rays on a water tank to produce steam which could in turn run a generator?

      Morocco does this, but with molten salt. https://en.wikipedia.org/wiki/Ouarzazate_Solar_Power_Station

    1. The federal government recommended against face coverings for the public in March, with some public-health officials positing that they may even cause more harm than good.

      Ben Thompson at Stratechery has a great article on the details of what happened here.

  2. Jun 2020
    1. One need arose quite commonly as trains of thought would develop on a growing series of note cards. There was no convenient way to link these cards together so that the train of thought could later be recalled by extracting the ordered series of notecards. An associative-trail scheme similar to that out lined by Bush for his Memex could conceivably be implemented with these cards to meet this need and add a valuable new symbol-structuring process to the system.

      This reminds me of of how the Roam Research app has implemented bidirectional links and block references.

    2. We refer to a way of life in an integrated domain where hunches, cut-and-try, intangibles, and the human "feel for a situation" usefully co-exist with powerful concepts, streamlined terminology and notation, sophisticated methods, and high-powered electronic aids.

      This sounds a lot like Rheingold's tools for thought.

    1. Alan Kay has famously described Lisp as the “Maxwell’s equations of software”

      As a physicist, this got me interested in Clojure.

  3. Sep 2017
    1. And so the most powerful country in the world has handed over all its affairs—the prosperity of its entire economy; the security of its 300 million citizens; the purity of its water, the viability of its air, the safety of its food; the future of its vast system of education; the soundness of its national highways, airways, and railways; the apocalyptic potential of its nuclear arsenal—to a carnival barker who introduced the phrase grab ’em by the pussy into the national lexicon. It is as if the white tribe united in demonstration to say, “If a black man can be president, then any white man—no matter how fallen—can be president.” And in that perverse way, the democratic dreams of Jefferson and Jackson were fulfilled.

      This is probably an excellent summary of the article.

    2. The dent of racism is not hard to detect in West Virginia. In the 2008 Democratic primary there, 95 percent of the voters were white. Twenty percent of those—one in five—openly admitted that race was influencing their vote, and more than 80 percent voted for Hillary Clinton over Barack Obama. Four years later, the incumbent Obama lost the primary in 10 counties to Keith Judd, a white felon incarcerated in a federal prison; Judd racked up more than 40 percent of the Democratic-primary vote in the state. A simple thought experiment: Can one imagine a black felon in a federal prison running in a primary against an incumbent white president doing so well?

      This reminds me of a line from Chris Rock’s Bigger and Blacker special:

      There still ain’t a white guy in here who would trade places with me — and I’m rich

    3. Moreover, to accept that whiteness brought us Donald Trump is to accept whiteness as an existential danger to the country and the world. But if the broad and remarkable white support for Donald Trump can be reduced to the righteous anger of a noble class of smallville firefighters and evangelicals, mocked by Brooklyn hipsters and womanist professors into voting against their interests, then the threat of racism and whiteness, the threat of the heirloom, can be dismissed. Consciences can be eased; no deeper existential reckoning is required.

      White guilt?

    1. Part of the wild success of the Silicon Valley giants of today — and what makes their stocks so appealing to investors — has come from their ability to attain huge revenue and profits with relatively few workers.Apple, Alphabet (parent of Google) and Facebook generated $333 billion of revenue combined last year with 205,000 employees worldwide. In 1993, three of the most successful, technologically oriented companies based in the Northeast — Kodak, IBM and AT&T — needed more than three times as many employees, 675,000, to generate 27 percent less in inflation-adjusted revenue.The 10 most valuable tech companies have 1.5 million employees, according to calculations by Michael Mandel of the Progressive Policy Institute, compared with 2.2 million employed by the 10 biggest industrial companies in 1979. Mr. Mandel, however, notes that today’s tech industry is adding jobs much faster than the industrial companies, which took many decades to reach that scale.

      It seems like this would certainly contribute to wealth inequality, since the majority of today's tech workforce is more well-educated than the industrial employees of decades past (who then shared in their employer's rise).

  4. Aug 2017
    1. So this transforms how we do design. The human engineer now says what the design should achieve, and the machine says, "Here's the possibilities." Now in her job, the engineer's job is to pick the one that best meets the goals of the design, which she knows as a human better than anyone else, using human judgment and expertise.

      A post on the Keras blog was talking about eventually using AI to generate computer programs to match certain specifications. Gruber is saying something very similar.

    1. Since Clojure uses the Java calling conventions, it cannot, and does not, make the same tail call optimization guarantees. Instead, it provides the recur special operator, which does constant-space recursive looping by rebinding and jumping to the nearest enclosing loop or function frame. While not as general as tail-call-optimization, it allows most of the same elegant constructs, and offers the advantage of checking that calls to recur can only happen in a tail position.

      Clojure's answer to the JVM's lack to tail call optimization

    1. Program synthesis consists in automatically generating simple programs, by using a search algorithm (possibly genetic search, as in genetic programming) to explore a large space of possible programs. The search stops when a program is found that matches the required specifications, often provided as a set of input-output pairs. As you can see, is it highly reminiscent of machine learning: given "training data" provided as input-output pairs, we find a "program" that matches inputs to outputs and can generalize to new inputs. The difference is that instead of learning parameter values in a hard-coded program (a neural network), we generate source code via a discrete search process.

      This suggests that one could eventually just write unit tests and the program generator could handle the rest, at least for relatively simple things.

    1. “Programming is like thinking about thinking. And debugging is a close approximation of learning about learning.” When you program, you translate your thoughts into executable form. Debugging your program is close to debugging your thoughts.
    2. The thrill of programming, for me, is found more in the exploration of ideas than in the joy of controlling machines.

      This is something that I can relate to. I tend to program as I learn a subject that I eventually want to write real programs for, as an aide to understanding. It helps me grok how things work in the new domain. It also helps me retain the new information.

    1. As these digital tools find their way into medical rooms, and they become digitally ready, what happens to the digitally invisible? What does the medical experience look like for someone who doesn't have the $400 phone or watch tracking their every movement? Do they now become a burden on the medical system? Is their experience changed?

      This is such an important question. An extreme version of this reminds me of things I've read in dystopian science fiction stories. This could create an underclass.

    1. Even after decades of affirmative action, black and Hispanic students are more underrepresented at the nation’s top colleges and universities than they were 35 years ago

      I wish this article had also looked at how much a given underrepresented group's graduation rate has changed as well (for the same group of schools). Even if a group's enrollment in top colleges has gone down, the data could show that a given group's graduation rate from those same colleges has increased over the same time period. Info on changes in enrollment and graduation rate would be so much more informative than studying each statistic alone.

    1. “Sankofa” teaches us that we must go back to our roots in order to move forward. That is, we should reach back and gather the best of what our past has to teach us, so that we can achieve our full potential as we move forward. Whatever we have lost, forgotten, forgone, or been stripped of can be reclaimed, revived, preserved, and perpetuated.

      Another interpretation of Sankofa.

    1. taking from the past what is good and bringing it into the present in order to make positive progress through the benevolent use of knowledge

      Sankofa

  5. Aug 2015
    1. I asked him if, by the same logic, a man with the background of Darren Wilson would be inherently less effective in North County. McCarthy bristled. “Watch what you’re using for the definition of ‘effective,’ ” he said. “I can do my job down there, but you’re not getting the maximum use of my resources.” What would be lost? The ability to communicate easily, he replied. I reminded him that he considered communication to be the most important skill in law enforcement. Wasn’t Wilson’s confrontation with Brown, on some level, about communication? Would an encounter with Brown really have played out in the same manner for McCarthy? He insisted that he would have acted just as Wilson had. I then asked him to consider the initial moment of contact, when Wilson and Brown were still talking. “It might not have escalated to that point,” McCarthy conceded, uneasily. Later, he added, “There is likelihood that it could’ve avoided that confrontation—the escalation of that confrontation.” But he felt that such speculation was pointless.

      This part is very interesting. It seems one of the things this article does is juxtapose McCarthy and Wilson, vis a vis their communication styles.

    2. In 2009, Wilson got a job in Jennings, a town on Ferguson’s southeastern border, where ninety per cent of the residents are black and a quarter of the population lives below the poverty line. “I’d never been in an area where there was that much poverty,” Wilson said. Interacting with residents, he felt intimidated and unprepared. A field-training officer named Mike McCarthy, who had been a cop for ten years, displayed no such discomfort. McCarthy, a thirty-nine-year-old Irish-American with short brown hair and a square chin, is a third-generation policeman who grew up in North County. Most of his childhood friends were African-American. “If you just talk to him on the phone, you’d think you’re talking to a black guy,” Wilson said. “He was able to relate to everyone up there.” Wilson said that he approached McCarthy for help: “Mike, I don’t know what I’m doing. This is a culture shock. Would you help me? Because you obviously have that connection, and you can relate to them. You may be white, but they still respect you. So why can they respect you and not me?” McCarthy had never heard another officer make such an honest admission of his own limitations. At the same time, he sensed a fierce determination: “Darren was probably the best officer that I’ve ever trained—just by his willingness to learn.”

      This Darren Wilson sounds like someone with the makings of a good police officer, someone who cares about the people in the community where he works. What happened to this guy?