Information technologist, knowledge management expert, and writer. Academic background in knowledge management, social and natural sciences, information technologies, learning, educational technologies, and philosophy. Married with one adult child who's married and has a teenage daughter.
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.
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.
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.
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.
Team Human by Douglas Rushkoff investigates the impacts of current and emerging technologies and digital culture on individuals and groups and seeks ways to evade or extract ourselves from their corrosive effects.
After you read the book, please post your thoughts as comments to this post or, if you prefer, as new posts. There are interviews and other resources about the book online. Feel free to recommend in the comments those you find meaningful. Also, the audiobook is available through the Albuquerque Public Library but may have a long wait queue (I’m aiming for a record number of ‘q’s in this sentence).
Please use the tag and/or category ‘Rushkoff’ in your new posts. Use any other tags or categories you want. To access categories and tags while composing a post, click ‘Document’ at the top of the options area on the right side of the editing page.
Any comments you add to this post should inherit the post’s categories and tags. Add any additional ones as you like.
Last, this site includes a book reviews app for registered site members. To use it, log in and select Review under the New menu.
We propose ‘multi-level evolution’, a bottom-up automatic process that designs robots across multiple levels and niches them to tasks and environmental conditions. Multi-level evolution concurrently explores constituent molecular and material building blocks, as well as their possible assemblies into specialized morphological and sensorimotor configurations. Multi-level evolution provides a route to fully harness a recent explosion in available candidate materials and ongoing advances in rapid manufacturing processes.
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?
Psychologist Robert Epstein, the former editor of Psychology Today, challenges anyone to show the brain processing information or data. The IP metaphor, he says, is so deeply embedded in thinking about thinking it prevents us from learning how the brain really works. Epstein also takes on popular luminaries including Ray Kurzweil and Henry Markram, seeing both exemplifying the extremes of wrongness we get into with the IP metaphor and the notion mental experience could persist outside the organic body.
Age-at-death forecasting – A new test predicts when a person will die. It’s currently accurate within a few years and is getting more accurate. What psychological impacts might knowing your approximate (± 6 months) death time mean for otherwise healthy people? Does existing research with terminally ill or very old persons shed light on this? What would the social and political implications be? What if a ‘death-clock’ reading became required for certain jobs (elected positions, astronauts, roles requiring expensive training and education, etc.) or decisions (whom to marry or parent children with, whether to adopt, whether to relocate, how to invest and manage one’s finances, etc.)?