It Is Useless To Resist Us!

Book report: Deep Work by Cal Newport

(link to book) I read this a while ago as part of a reading group at work. Quite a bit of the content resonated with me – I’ve always found concentration on my task to be both important and rewarding, but it’s getting harder and harder to achieve these days.

Things that I thought worthy enough to bookmark:

• The Monastic Philosophy: Schedule long periods of time time for your deep work, and isolate yourself during that time. Go physically far away from all people and distractions.
• The Bimodal Philosophy: Alternate between deep work (in periods of at least one full day) and interaction with distractions. The distractions can give you ideas and check your thinking.
• The Rhythmic Philosophy: This is Seinfeld’s “Don’t break the chain” thing. Keep a calendar on your wall, and check off every day you achieve a period of deep work, and try not to break the chain. This helps develop a habit and helps you remember to set aside time for deep work every day.
• The Journalistic Philosophy: Fit in short periods of deep work whenever you get the chance. Just sit down and do it – it doesn’t matter if you’re going to be interrupted in 20 minutes. You’ll still make some progress, and that’s better than none.
• The Grand Gesture: If you’re finding it difficult to concentrate in your normal surroundings, make a change of scene specifically for working on something you need to do. Take a mini working vacation, with luxuries, in another city and work there.
• Some useful disciplines:
  • Focus only on the most important thing.
  • Focus on the “lead measures”. Lag measures are your progress on the task so far. Lead measures are your new behaviors that will help you progress better.
  • Keep a compelling scorecard. Competition, even if it’s just with yourself, is motivating.
• Idleness is important. You need downtime, relaxation and entertainment to be energized and creative. Learn to decide when you’re crossing into laziness without berating yourself for it. Sometimes you even need to do nothing at all (not even entertainment) for a while too – it leads naturally to meditation.
• Change your perspective – instead of taking focus breaks from distraction, take breaks from focus for distraction. (This is really hard if your workplace is full of work-related distraction, as mine is.)
• Schedule your internet use both at home and at work.
• Meditate productively – occupy yourself physically and let your mind wander around your tasks. For example, I like to take a 30-minute walk after lunch every day, and I tend to think about work-related things during this time. It really helps organize my thoughts and make decisions.
• Be aware of looping. If you keep going over the same thoughts over and over, When you detect a loop, concentrate on the next step.
• Structure your deep thinking time. Identify variables and tasks, and know what your next step is.
• Consider the means by which you select your work tools (this mainly means online and software tools):
  • The Any-Benefit approach. We tend to default to using a tool if it benefits us at all, but lately this is being exploited in ways that distract us – notably by social media and web advertising.
  • The Craftsman approach. Adopt a tool only if its positive impacts substantially outweigh the negatives.
  • Identify the main high-level goals in your personal and professional lives, then list the two or three most important activities that will help you achieve those goals. Evaluate your current tools on how well they help you with these activities, and look for replacements if any are found wanting.
• Spring cleaning: Pack everything up, uninstall all your software and log off from all your online accounts. Then unpack, reinstall or log back in the things you actually need during your work week. Get rid of everything still packed away after that.
• Don’t use the Internet for entertainment. One click leads to another and eats up all your personal time.
• “Drain the Shallows”: If you can clear your schedule of meetings, brainless work and other interruptions, you’ll be able to concentrate more and get more done.
  • Schedule every minute of your day. This means block off time for deep work, and block off time for petty things like email.
  • Answer this question: “What is the project represented by this email/interruption, and what is the most interruption-free way of successfully completing it?”
  • Make it your default policy to not respond to email, and write your emails in such a way that the default action of the recipient is to not respond.

If you struggle with productivity at work or at home, have distraction and concentration problems, or just want to get stuff done, it’s worth your time to read this book.

Book report: Thinking Fast and Slow by Daniel Kahneman

(Link)

One of the most important books I’ve ever read. It gives insight into how our minds work and why we fall prey to as many errors of judgement as we do.

Kahneman observes that our mental reactions to situations can be categorized into two groups, fast and slow, and that the fast ones are both more influential and more prone to error.

The fast system, which he calls system 1, does things like distinguish between near and far objects, identify the direction of sounds, auto-complete common phrases, make and identify facial expressions, read tone of voice, answer the most familiar math problems (2+2), read easy words, do familiar tasks like riding a bike or driving a car under easy circumstances, and comprehend stereotypes.

The slow system, system 2, does things that require attention, such as: Get ready to start in a race, pay attention to particular people in a crowd, search for things meeting a description, recall memories that require searching, do familiar physical tasks under unusual circumstances, keep your foot out of your mouth, count more than a few instances of a thing, compare lists of attributes, do difficult math or evaluate logical reasoning. System 2 is a very limited resource, which is why it’s difficult to pat your head and rub your belly at the same time.

For my own future reference, I decided to itemize his findings here:

1. It’s difficult or impossible to do more than one system 2 task at the same time; you can’t do a multi-digit multiplication while dealing with dangerous traffic. This is why you don’t see the guy in the gorilla suit while counting ball passes. (p.23)
2. System 2 tasks require effort that we prefer to avoid. It’s a noticeable mental effort. Most of the time system 2 will just rubber-stamp suggestions from system 1. (p.24)
3. Your pupils dilate and your heart rate increases slightly when working on system 2 tasks. The pupil response is body language that can give away your level of interest to someone trying to sell you something. (p.32)
4. You’re more likely to make bad decisions or put your foot in your mouth while system 2 is occupied. (p.41)
5. Low blood glucose makes high cognition tasks harder. People are more likely to make hasty decisions when hungry. (p.43)
6. System 1 performs memory associations and is responsible for the priming effect. (ch.4)
   • IMPORTANT NOTE: there have been some replicability problems with chapter 4 of this book. The author may have fallen victim to some of the same overconfidence fallacies he documents.
7. Tasks that cause cognitive strain, such as reading a poorly legible font, make you more accurate but less intuitive and creative. (p.60)
8. Cognitive ease, or anything that makes our associative machinery run more smoothly, can cause bias by making it easier to reach a conclusion that is primed than a conclusion that is true. (ch.5) This is one of the mechanisms of propaganda: repetition. This is also why using simpler language makes speakers appear more credible to some.
9. Norms shape a lot of our thinking and are what we draw on to explain behavior we witness when an external explanation isn’t available. For example, norms make it possible to tell a simple story with abstract shapes by moving them in ways that mimic the human body language for different emotions. Norms are also very easily changed by our experiences, and therefore are very likely to be wrong. (ch.6)
10. Our brains are highly optimized for jumping to conclusions, and it saves a lot of time and effort, but it’s risky when the cost of being wrong is high. (ch.7)
11. The Halo Effect is a form of jumping to conclusions, in which we are likely to judge someone favorably based on irrelevant favorable impressions of them in other contexts. It’s also why first impressions carry the most weight. There are techniques for avoiding halo effect bias in some circumstances, such as blinding yourself to earlier impressions by anonymizing the data you’re presently evaluating. (p.82-84)
12. What You See Is All There Is (WYSIATI) fallacy: Coherence-seeking system 1 and lazy system 2 combine to cause judgments based on available evidence, without making much effort to seek additional relevant evidence or even to notice that relevant evidence might be missing. This causes lots of kinds of biased judgement, including overconfidence, framing effects and base-rate neglect. (p.86-88)
13. System 1 deals well with tasks such as averaging or comparing similar objects, but not with things like summing or judging the relative impact of numbers. This is why statistics so easily mislead. System 1 likes things that can be mapped to intensity in some way. This is also why we judge people by their faces – system 1 maps certain facial features to intensities of important attributes such as dominance and competence. (ch.8)
14. We often unconsciously answer difficult questions by answering a simpler proxy question and then using an intensity scale to map that answer back to the original question. For example, when asked how much money you would be willing to contribute to help clean oil-soaked seabirds, there is no obvious mapping from oily birds to money so you might instead ask yourself what the emotional impact of the birds’ condition is on you, then use that intensity to judge how much money to give. This effect can be exploited easily by first priming you to have a more intense reaction to the question. (ch.9)
15. The Law of Small Numbers: Small sample sizes produce more remarkable results, because they are more likely to generate sampling biases. This is one way you can get two studies of the same thing reaching contradictory conclusions. Faith in small numbers is what causes belief in winning streaks in sports and gambling. (ch.10)
16. The Anchoring Effect: Exposure to an intensity can bias your answer to a completely unrelated question. For example, first being asked “Was Ghandi older or younger than 144 when he died?” will cause people to give higher answers to the subsequent question “How old was Ghandi when he died?”, and hearing temperatures mentioned that you recognize as being warm or cool will make it easier to recognize words related to summer or winter, respectively. This is a form of priming and can be used to bias surveys. (ch.11)
17. Availability (easier recall of recent information) biases our decisions. (ch.12)
18. Our evaluation of risk depends on the choice of measure used when presenting the statistics, including the choice of what the measure is compared to. This is why it’s so easy to be misled by death statistics; they’re rarely presented with enough comparative context, and this is usually done deliberately to produce bias. (ch.13)
19. Base rate neglect: We perform our own unconscious statistical sampling of other people, and this is called stereotyping. In some circumstances stereotypes can be usefully accurate, but often they are misleading and we’re not good at recognizing when. (ch.14)
20. Conjunction fallacy: People tend to favor more specific explanations even though they are always less probable than less specific ones. Another form of this is a tendency to favor a smaller uniform set over a larger disparate one (example: a smaller dinnerware set was valued higher than a larger one that contained everything in the smaller one and more plus some broken pieces.) (ch.15)
21. Statistical results with a causal interpretation have a much stronger impact on our evaluation than pure statistics, even when the statistics suggest the causal interpretation is wrong. In other words, humans are terrible at Bayes’ theorem. Also, we love generalizing from small samples but are unwilling to go the other way and assume general rules apply to specific cases. (ch.16)
22. Regression to the mean: We mistakenly believe in “streaks” of good or bad luck or performance and assume they will continue. It’s always a safer bet that things will return to the average, but we never bet that way and when we’re wrong we tend to mis-attribute the reason. (ch.17)
23. Hindsight bias: If a predictions actually happens, we retroactively assign it a higher probability and will tend to erroneously assign more of the responsibility to personal attributes than to luck. We tend to say mistakes should have been obvious after the fact, when they were not. (ch.18)
24. Illusion of validity / skill: Having a poor record of prediction does not shake our faith in our ability to predict. Example: Stock market analysts who consistently predict worse than random chance are still considered to be doing a good job. We reward luck as if it were skill. A coherent story feels better than chance. (ch.20)
25. We value intuition more than we should. Despite negative reactions, the right algorithm can always produce good decisions at a higher rate than humans. (ch.21)
26. The way to avoid the Planning Fallacy (unrealistically optimistic project estimates) is to use statistics about similar cases: how many of them fail, and how long does success typically take? The fallacy comes from having an insider’s view and not knowing the unknown unknowns. Past data gives you a partial outsider’s view. (ch.23)
27. Humans rarely reason based on expected value (economics) but on perceived value (prospect theory). Wealth change has a greater effect on our happiness than absolute value. Amount of change as a percentage is more important than the absolute value of the change. Context matters, as does priming. (ch.25)
28. Most people are risk-averse when it comes to gain, but risk-seeking when it comes to avoiding loss (prospect theory, loss aversion). (ch.26)
29. The Endowment Effect: Owning a good increases its value to you. Your sell price for something you value is typically much higher than the maximum price you would pay to get it. Another way of putting it is that you may not care what you get until you get it. (ch.27)
30. Decision weights: Probabilities close to zero or close to 100% are curved differently from the rest of the range. 5% is seen as a huge improvement over 0% (experimentally, it has been weighted at 13%). 95% is seen as vastly inferior to 100% (experimentally, 95% is felt as valuable as 79%). (ch.29)
31. The Fourfold Pattern (ch.29):
    • High probability produces a certainty effect.
    • High probability of gains produces risk aversion, fear of disappointment, and willingness to accept unfavorable settlements. (Bernoulli’s theory fits this quadrant)
    • High probability of losses produces risk-seeking, hope of avoiding loss, and rejection of favorable settlements.
    • Low probability produces a possibility effect. (fighting losing battles)
    • Low probability of gains causes risk-seeking, hope of large gains, and rejection of favorable settlements. (lotteries benefit here)
    • Low probability of losses causes risk aversion, fear of large loss, and acceptance of unfavorable settlements. (insurance benefits here)
32. We overestimate the probability of unlikely events and over-weight them in our decision making. (ch.30)
33. Denominator neglect: Larger numbers given for the numerator and denominator of a probability can have more effect on our decision than the probability they represent. (8/100 is more popular than 1/10 even though the latter is better.) (ch.30)
34. Vivid or well understood events are over-weighted relative to their probability in our decision making. This is why the “poster child” concept works. (ch.30)
35. We weight the pain of loss more than the pleasure of gain. Losing $1 feels as bad as gaining $2 feels good; even an economist won’t make that bet unless they can make the same bet many times to get the expected return of 50 cents per bet.  (ch.31)  This 2:1 weighting applies in multiple contexts. (ch.32)
36. The Disposition Effect: We want to close each transaction with a gain, rather than an average gain. This leads to the Sunk Cost Fallacy, which mistakenly uses existing investment in a failure to justify more investment in the same. (ch.32)
37. Exposure to a wider context can affect your decisions even if the extra information is irrelevant. (ch.33)
38. Framing matters: “Team A won” is very different from “Team B lost”. Costs are not losses. Gain is not the opposite of loss. (ch.34)
39. We rate the painfulness of an experience by the difference between its peak and its end. The duration is largely irrelevant. Our experiencing self is different from our remembering self. (ch.35)
40. The Focusing Illusion: Nothing is as important as you think it is when you’re thinking about it. Your emotional context at the time greatly affects your answers to questions about feelings. (ch.38)

Summary of the characteristics of system 1 (reproduced from p.105):

• Generates impressions, feelings, and inclinations. When endorsed by system 2 these become beliefs, attitudes and intentions.
• Operates automatically and quickly, with little or no effort, and no sense of voluntary control.
• Can be programmed by system 2 to mobilize intention when a search pattern is detected.
• Executes skilled responses and intuitions, after being trained.
• Creates a coherent pattern of activated ideas in associative memory.
• Links cognitive ease to illusions of truth, pleasant feelings, and reduced vigilance.
• Distinguishes the surprising from the normal.
• Infers and invents causes and intentions.
• Neglects ambiguity and suppresses doubt.
• Is biased to believe and confirm.
• Exaggerates emotional consistency (halo effect).
• Focuses on existing evidence and ignores absent evidence (WYSIATI).
• Generates a limited set of basic assessments.
• Represents set by norms and prototypes, and does not integrate.
• Matches intensities across scales.
• Computes more than intended (mental shotgun effect).
• Sometimes substitutes easier questions for difficult ones.
• Is more sensitive to changes than to states (prospect theory).
• Over-weights low probabilities.
• Shows diminishing sensitivity to quantity.
• Responds more strongly to losses than to gains (loss aversion).
• Frames decision problems narrowly and in isolation.

 

What I’ve Been Reading

The Heritage Universe quintilogy by Charles Sheffield

A very fun adventure series set against the common background trope of a mysterious vanished alien civilization having left amazing and incomprehensible toys behind for the younger civilizations to puzzle over. The arc follows a gang of human and alien characters with a healthy mix of motivations as they get caught up in events that lead to some answers about the long-vanished Builders.

The first two books in this series don’t stand well on their own, but they work well in the context of the overall arc. At first I didn’t like that Summertide didn’t really reveal anything about the Builders, and then I didn’t like that Divergence revealed too much too quickly, but later books damped those oscillations retroactively.

I like the creative variety in alien forms and civilizations presented here; they seem to fit well. I also like the quietly implied moral present in the reason for the Builders leaving their artifacts lying around: Cooperation is better than conquest.

One thing I didn’t like was the complete silence about the fate of the Zardalu in the latter part of the series. Here’s this ruthless, menacing race whose subjects hated them so much they attempted genocide against them, and everyone has been happy thinking the Zardalu have been dead for thousands of years. Now they’re making a comeback but were discovered while in a position of weakness, and… nothing.  Some time was bought by convincing the Zardalu that they’re in danger of being stepped on by other races grown more powerful in the interim, but they have to eventually figure out that’s not the case.  No governments have taken any initiative to contain, protect or negotiate with the Zardalu, and their ambassador became little more than a thug and plot device to help the plot in the fifth book.  This better be addressed in future books.

The setting of this series is one of the most MOO-like I’ve encountered. It could also potentially make for several good movies or a TV series.

 

The Complete Fiction of H.P. Lovecraft

As mentioned in previous posts I’ve been on a quest to read all of Lovecraft’s stories. One story I was having a hard time finding was The Dream-Quest of Unknown Kadath, which based on the implications of other stories sounded like it might be one of the most epic. It was, but it was also disappointing in a few ways – the silliness with the cats being first and foremost.  It was a good story, but I enjoyed At the Mountains of Madness more.

I was delighted to find a handful of other stories in this volume that I had not previously read.

 

Free Will by Sam Harris

A short, easy read about the experimental evidence that suggests free will is an illusion, and what it implies for our justice system and for our thoughts about choice and self-determination.  I found it a fun and easy read and it extended my awareness of the matter a little by exploring some implications I hadn’t thought of.

 

God Is Not Great by Christopher Hitchens

I’ve been meaning to read this for a while but it became more opportune when I discovered the audiobook version was on YouTube.

This is a book I’ve been thinking for a long time needs to exist, and I’m glad someone else went to the trouble of writing it so I don’t have to. And that he then read it to me in his nice accent. See the wikipedia article at the title link above for detailed information on the content, but suffice to say he enumerates most of the major things about religion that bother me, and adds more I wasn’t aware of.

Can we abolish this supernatural nonsense now, please?

 

Schild’s Ladder by Greg Egan

A well-written and interesting hard SF story about a galaxy-threatening accident and the scramble to mitigate it. Less tiresome and more engrossing than some of Egan’s more exposition-heavy, visualization-taxing efforts.

I found it odd that the titular construct played only a tiny role in the story.

The best part of this story, in my opinion, was the interesting model of future human sexuality presented. This is a future where humans are heavily bioengineered and have gotten over their gender-induced hangups. Children do not have genitalia nor do lone adults unless they want to for some odd reason. When two or more people start to develop romantic attachments with each other, their hormonal systems negotiate via pheromones and initiate the growth of appropriate combinations of sex organs based on the emotional dynamics of the relationship. Under this system non-consensual sex is very difficult and sex hormones are less likely to poison rationality.

 

Pushing Ice by Alastair Reynolds

Quite enjoyed this. It’s a story of survival, discovery and human politics over deep time. But more than anything else it ends as a setup for one or possibly two sequels that I hope will prove as engrossing if they’re ever written.

I require a character in the sequel to use the phrase, “Let’s caul ass!”

 

Hold Still by Sally Mann

A few years ago, on impulse, I started a collection of books by and about controversial photographers with some half-baked idea of making a study of what gets fussbudgets wound up. So far I only have a couple of autobiographies in the collection, and this is the most recently written of them. I decided to read one to see how one of these photographers reacted to the fuss over her work.

If you don’t know, Sally Mann has several series of photographs that have drawn some flak, but the biggest noise came from nude photos of her own children. She was accused of everything from poor taste to abuse of trust to child pornography.

She seems to have been more naive than photographers would be today (partly thanks to her example), and was taken by surprise by the reaction. She even went to the point of taking her kids and all of her photos of them to an interview with an FBI investigator, and was assured that none of her work was illegal but that she should expect some trouble with stalkers. Sadly, that did come to pass but not as badly as you might fear.

But that story was only a tiny part of the content of this book. This is the story of her life, interweaving the distant history of her family back to her great-grandparents, her unbelievably film-like growing up in the Southern USA – as in “Suthan” – the complex racial situation there that she was oblivious to until adulthood and now has complex feelings about, and her relationships with horses, dogs, men, her children, the land, photography and other artists. It’s all a lot more fascinating than you might expect, and for me it was a window into a very alien lifestyle.

 

ReWork by Jason Fried and David Heinemeier Hansson

This is a fast and easy read; it’s a collection of one-page theses that each attempt to justify a one-sentence quip about how to run a workplace. It came up in the book club at work, which is why I read it.

While I actually agree with a lot of what they say, this book irritates me because it’s written in a very cocksure style. Reading between the lines – and sometimes not between them – the authors are saying, “We ignored conventional wisdom in the following ways and created a small business that happened to be famously successful at the time we decided to publish this book, so therefore we are qualified to assert that this is the Right Way To Do Things.” Even if they’re right, nobody likes braggarts. Actually, especially if they’re right.

There are a few items in this book that I strongly disagree with, though sometimes it’s the presentation that I disagree with. As an example, in the section titled “Build a Rockstar Environment / Skip the Rock Stars” they assert that instead of trying to recruit star talent, employers should try to create a work environment that naturally boosts everyone’s productivity. I think these two things are orthogonal and they’re presenting them in a false dichotomy. It is simultaneously true that the work environment affects everyone’s productivity and that some people are inherently more productive than others. You should do both – create a good environment AND try to hire good people.

 

Convergent thoughts about mortality at different scales

A thing I ponder frequently is the ultimate fate of the universe and the life within it. The universe is full of beauty and elegance, but those things are useless without minds to appreciate them. Therefore sentience should be maximized in duration and variety.

But we are unsure whether it’s possible for sentience to exist forever. We still don’t know for sure how the universe will develop over long time scales. Most of the current theories imply that the universe has a finite useful lifetime after which sentience is no longer possible; for example, even if the universe itself continues forever, it is likely the case that protons decay and that no new matter is created, and therefore the matter inside the universe will not exist forever. No matter, no minds.

Therefore it behooves all sentience to study this problem and try to find some means of indefinite survival.

A new thought occurred to me today: Suppose it were eventually proven that sentience cannot exist forever? Suppose this universe will eventually reach zero utility, suppose it’s impossible to move to another universe, and even suppose we can’t even leave a permanent record behind.

Well, then sentience itself would collectively face the same decision that young individuals have (mostly unconsciously) faced until recent generations: Live with this depressing and uncomfortable truth, or develop some sort of systematic insanity to make it more palatable?

When I was young, I learned that death exists and that despite best attempts, nobody has yet managed to avoid it. Thus far, living has been 100% fatal – what a rip-off! Perhaps this problem might be solved in the future, but at the time that was a far-out science fiction idea and there was no hope of it happening in my expected lifetime.

Many people of my generation and previous generations found this a pretty bitter pill. Some dealt with it via various forms of insanity: Denial by ignoring the problem entirely; the softly suicidal acceptance of death’s inevitability; the misanthropic (or even murderous if it inspires activism) belief that death is a good thing and should be preserved as is, or the baseless assumption of various kinds of immortality that don’t require bodies.

After ignoring it for a while, I chose to throw in with the group that faces the existence of death without accepting it. The Something Must Be Done crowd.

Fortunately, younger generations are less bound to make this choice. We have now realized that “death by old age” is not actually a thing; it’s just a term of convenience that means someone was killed by some combination of diseases that were incurable at the time and often too complex to bother sorting out precisely after the fact.

We’ve also realized that we are made of software-controlled microscopic protein factories, that these cells and their DNA programs are bloated and inefficient due to their evolutionary origin, and that we should therefore be able to both improve them and improve their aggregate products (us). We’re currently reverse-engineering the software that makes us and learning to improve it and write our own new versions. I am certain that, barring interference, this will lead to radical life extension and eventually a solution to the problem of finite expected lifespans (in the absence of accident, murder or suicide, of course). I have no idea when though; some generations, including mine, may be disappointed.

 

So here’s where the interesting parallel exists: At the individual level we’ve had to wrestle with the difficult problem of mortality in the face of the certainty of its existence so far, but now science is starting to give us some hope of a reprieve.  At the level of sentience itself we, as the only example thereof we’re currently aware of, don’t know if mortality is certain and will have to do the science to find out. It’s not a perfect dovetail since at the small scale we’re moving from an assumed certainty to uncertainty and possibly to the opposite certainty, whereas at the large scale we know we’re uncertain and are trying to establish either certainty.

But if it does turn out to that finiteness of mind is certain then we’ll have to make that same choice between insanities collectively. I wonder what that will look like; I suspect it will result in large sections of the civilized universe living wastefully and dangerously.

Language Really Is a Virus

I’ve always bought into the idea that language shapes our thoughts and enables us to do more with our brains, but there is evidence that it is much more profoundly true than I ever suspected. Have a listen to this great Radiolab episode:

http://www.radiolab.org/story/91725-words/

What we think of as humanity is language, not genes. Thanks to genes we have brains that can process complex languages and spread the language virus to other brains, but without the language we might not even be people at all – just clever animals. If you had never learned a language, not only would you not be the same person but you might not even be aware you exist.

Humanity is self-replicating, self-modifying software running on an independently self-replicating squishy hardware platform.

I think this explains why infants undergo a radical mental restructuring in their first couple of years, and tend to not remember anything before that.  They’re going from native, animal processing mode to being driven by an interpreted language.

This also contributes some explanation to why there can be such radical cultural differences and lack of understanding between peoples who speak different languages.

I hereby require everyone to learn a computer programming language. Then we can be the same species.