Category Archives: complexity

Book: Range: Why Generalists Triumph in a Specialized World

In his new book, Range: Why Generalists Triumph in a Specialized World, David J. Epstein investigates the significant advantages of generalized cognitive skills for success in a complex world. We’ve heard and read many praises for narrow expertise in both humans and AIs (Watson, Alpha Go, etc.). In both humans and AIs, however, narrow+deep expertise does not translate to adaptiveness when reality presents novel challenges, as it does constantly. 

As you ingest this highly readable, non-technical book, please add your observations to the comments below. 

Syntegration: The key to innovation

This TED talk discusses how tech innovation is driven by those with diverse experience that syntegrate a variety of genres instead of specialists that are limited to a few. They call it ‘lateral’ thinking but that term sets up a dichotomy with hierarchical thinking, which the syntegral approach is certainly much more than. The hierarchical complexity approach would limit that way of thinking merely to what it calls horizontal complexity, again missing the boat entirely of the sort of cross-paradigmatic thinking involved in syntegration, aka hier(an)archical synplexity.

History of complexity science

Here’s an interesting infographic of the main concepts and thinkers in complexity science across time. Notice S. Kauffman is slated in the 1980s column, suggesting the graphic depicts when influential thinkers first make their marks. 

https://www.art-sciencefactory.com/complexity-map_feb09.html

‘Neurosexism’ debated

Neuroscientist Larry Cahill takes issue with a Feb 2019 Nature favorable book review of Gina Rippon’s The Gendered Brain: The New Neuroscience That Shatters The Myth Of The Female Brain.

Cahill’s response prompted an interview by Medium Neuroscience writer Meghan Daum.

Scientific findings have a way of upsetting apple carts, especially when we consider our oft-demonstrated human capacity to bend science to advantage some power-coveting groups over others.

Valid research amply shows there are real differences in male and female neuroanatomy and functions. Honest science must follow the evidence where it leads. Clearly, any discovered differences cannot be allowed to justify unequal social or economic opportunities or treatment. Cahill compares the situation to genetics. That people differ genetically in a vast number of ways cannot be taken as cause to misstate scientific findings or preclude further learning about genetics.

There are times and circumstances in which certain research approaches must be blocked for humane or other reasons but that is a different argument than denying the findings of a body of research because they are uncomfortable or inconvenient.

Thoughts?

Ideas of Stuart Kauffman

If you are familiar with complex systems theorist Dr. Stuart Kauffman’s ideas you know he covers a broad range of disciplines and concepts, many in considerable depth, and with a keen eye for isomorphic and integrative principles. If you peruse some of his writings and other communications, please share with us how you see Kauffman’s ideas informing our focal interests: brain, mind, intelligence (organic and inorganic), and self-aware consciousness.

Do you find Kauffman’s ideas well supported by empirical research? Which are more scientific and which, if any, more philosophical? What intrigues, provokes, or inspires you? Do any of his perspectives or claims help you better orient or understand your own interests in our focal topics?

Following are a few reference links to get the conversation going. Please add your own in the comments to this post. If you are a member and have a lot to say on a related topic, please create a new post, tag it with ‘Stuart Kauffman,’ and create a link to your post in the comments to this post.

the evolution of synergy

Good quick summary of some of Deacon’s ideas. Deacon: “We need to stop thinking about hierarchic evolution in simple Darwinian terms. We need to think about it both in terms of selection and the loss of selection or the reduction of selection. And that maybe it’s the reduction of selection that’s responsible for the most interesting features” (9:40).

Running on escalators

Ideally, automation would yield a Star Trek reality of increasing leisure and quality of choice and experience. Why isn’t this our experience? An article on Medium offers insight into why this is not occurring on any significant scale.

Evolved behavioral strategies explained by the prisoner’s dilemma damn the majority of humans to a constant doubling down. We exchange the ‘leisure dividend’ (free time) granted by automation for opportunities to outcompete others.

Apparently, the sort of reciprocal social learning that could lead us to make healthy choices with our leisure opportunities depends on us and our competitors being able to mutually track our outcomes across consecutive iterations of the ‘game’. That ‘traceability’ quickly breaks down with the complexity inherent in vast numbers of competitors. When we conclude that any viable competitor may use her leisure dividend to further optimize her competitive position, rather than to pause to enjoy her life, we tend to do the same. Each assumes the other will sprint ahead and so chooses to sprint ahead. Both forfeit the opportunity to savor the leisure dividend.

The prisoner’s dilemma shows that we (most humans) would rather be in a grueling neck-and-neck race toward an invisible, receding finish line than permit the possibility a competitor may increase her lead.

Any strategy that’s so endemic must have evolutionary roots. Thoughts?

Vibration: A new theory of consciousness

Article in Scientific American. One point. The article sees energetic fields underlying matter as if they are separate things, one the cause of the other. Whereas a naturalistic, postmetaphysical view might be that they mutually entail and co-generate each other within an ecological frame. The cause/effect frame still clings to a form of dualism.

Applying artificial intelligence for social good

This McKinsey article is an excellent overview of this more extensive article (3 MB PDF) enumerating the ways in which varieties of deep learning can improve existence. Worth a look.

The articles cover the following:

  • Mapping AI use cases to domains of social good
  • AI capabilities that can be used for social good
  • Overcoming bottlenecks, especially around data and talent
  • Risks to be managed
  • Scaling up the use of AI for social good

The Singularity is Near: When Humans Transcend Biology

Kurzweil builds and supports a persuasive vision of the emergence of a human-level engineered intelligence in the early-to-mid twenty-first century. In his own words,

With the reverse engineering of the human brain we will be able to apply the parallel, self-organizing, chaotic algorithms of  human intelligence to enormously powerful computational substrates. This intelligence will then be in a position to improve its own design, both hardware and software,  in a rapidly accelerating iterative process.

In Kurzweil's view, we must and will ensure we evade obsolescence by integrating emerging metabolic and cognitive technologies into our bodies and brains. Through self-augmentation with neurotechnological prostheses, the locus of human cognition and identity will gradually (but faster than we'll expect, due to exponential technological advancements) shift from the evolved substrate (the organic body) to the engineered substrate, ultimately freeing the human mind to develop along technology's exponential curve rather than evolution's much flatter trajectory.

The book is extensively noted and indexed, making the deep-diving reader's work a bit easier.

If you have read it, feel free to post your observations in the comments below. (We've had a problem with the comments section not appearing. It may require more troubleshooting.)