All ultimate explanations are bizarre

Prosthetic memory system successful in humans

“This is the first time scientists have been able to identify a patient’s own brain cell code or pattern for memory and, in essence, ‘write in’ that code to make existing memory work better, an important first step in potentially restoring memory loss”

We showed that we could tap into a patient’s own memory content, reinforce it and feed it back to the patient,” Hampson said. “Even when a person’s memory is impaired, it is possible to identify the neural firing patterns that indicate correct memory formation and separate them from the patterns that are incorrect. We can then feed in the correct patterns to assist the patient’s brain in accurately forming new memories, not as a replacement for innate memory function, but as a boost to it.”

Source: http://www.wakehealth.edu/News-Releases/2018/Prosthetic_Memory_System_Successful_in_Humans_Study_Finds.htm

We have the wrong paradigm for the complex adaptive system we are part of

This very rich, conversational thought piece asks if we, as participant designers within a complex adaptive ecology, can envision and act on a better paradigm than the ones that propel us toward monocurrency and monoculture. 

We should learn from our history of applying over-reductionist science to society and try to, as Wiener says, “cease to kiss the whip that lashes us.” While it is one of the key drivers of science—to elegantly explain the complex and reduce confusion to understanding—we must also remember what Albert Einstein said, “Everything should be made as simple as possible, but no simpler.” We need to embrace the unknowability—the irreducibility—of the real world that artists, biologists and those who work in the messy world of liberal arts and humanities are familiar with.


In order to effectively respond to the significant scientific challenges of our times, I believe we must view the world as many interconnected, complex, self-adaptive systems across scales and dimensions that are unknowable and largely inseparable from the observer and the designer. In other words, we are participants in multiple evolutionary systems with different fitness landscapes at different scales, from our microbes to our individual identities to society and our species. Individuals themselves are systems composed of systems of systems, such as the cells in our bodies that behave more like system-level designers than we do.

Joichi Ito


Different signaling proteins found instrumental in remembering and forgetting scent-based memories

Understanding how brains actively erase memories may open new understanding of memory loss and aging, and open the possibility of new treatments for neurodegenerative disease.


Book review – Life 3.0: Being Human in the Age of Artificial Intelligence, by Max Tegmark

Max Tegmark’s new book, Life 3.0: Being Human in the Age of Artificial Intelligence, introduces a framework for defining types of life based on the degree of design control that sensing, self-replicating entities have over their own ‘hardware’ (physical forms) and ‘software’ (“all the algorithms and knowledge that you use to process the information from your senses and decide what to do”).

It’s a relatively non-academic read and well worth the effort for anyone interested in the potential to design the next major forms of ‘Life’ to transcend many of the physical and cognitive constraints that have us now on the brink of self-destruction. Tegmark’s forecast is optimistic.

The President discusses technology in government

Once upon a time, the United States of America had a competent president who actually grasped complex issues and could intelligently explore governmental implications. Those were the days.

Giant neuron found encircling and intraconnecting mouse brain

A neuron that encircles the mouse brain emanates from the claustrum (an on/off switch for awareness) and has dense links with both brain hemispheres. Scientists including Francis Crick and Christoph Koch have speculated that the claustrum may play a role in enabling conscious thought.


https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1569501/ (Crick and Koch academic article)

We’ve frequently discussed how self-aware consciousness likely arises not from any single brain structure or signal, but from complex, recursive (reentrant), synchronized signaling among many structures organized into functional regions. (Did I get close to accurate there?) That a giant neuron provides another connection path among such regions can be taken to align with the reentrant signaling and coordination view of consciousness (ala Edelman and Tononi).

Computer metaphor not accurate for brain’s embodied cognition

It’s common for brain functions to be described in terms of digital computing, but this metaphor does not hold up in brain research. Unlike computers, in which hardware and software are separate, organic brains’ structures embody memories and brain functions. Form and function are entangled.

Rather than finding brains to work like computers, we are beginning to design computers–artificial intelligence systems–to work more like brains.


Should AI agents’ voice interactions be more like our own? What effects should we anticipate?

An article at Wired.com considers the pros and cons of making the voice interactions of AI assistants more humanlike.

The assumption that more human-like speech from AIs is naturally better may prove as incorrect as the belief that the desktop metaphor was the best way to make humans more proficient in using computers. When designing the interfaces between humans and machines, should we minimize the demands placed on users to learn more about the system they’re interacting with? That seems to have been Alan Kay’s assumption when he designed the first desktop interface back in 1970.

Problems arise when the interaction metaphor diverges too far from the reality of how the underlying system is organized and works. In a personal example, someone dear to me grew up helping her mother–an office manager for several businesses. Dear one was thoroughly familiar with physical desktops, paper documents and forms, file folders, and filing cabinets. As I explained how to create, save, and retrieve information on a 1990 Mac, she quickly overcame her initial fear. “Oh, it’s just like in the real world!” (Chalk one for Alan Kay? Not so fast.) I knew better than to tell her the truth at that point. Dear one’s Mac honeymoon crashed a few days later when, to her horror and confusion, she discovered a file cabinet inside a folder. To make matters worse, she clicked on a string of underlined text in a document and was forcibly and instantly transported to a strange destination. Cries for help punctuated my hours. Having come to terms with computers through the command-line interface, I found the desktop metaphor annoying and unnecessary. Hyperlinking, however–that’s another matter altogether–an innovation that multiplied the value I found in computing.

On the other end of the complexity spectrum would be machine-level code. There would be no general computing today if we all had to speak to computers in their own fundamental language of ones and zeros. That hasn’t stopped some hard-core computer geeks from advocating extreme positions on appropriate interaction modes, as reflected in this quote from a 1984 edition of InfoWorld:

“There isn’t any software! Only different internal states of hardware. It’s all hardware! It’s a shame programmers don’t grok that better.”

Interaction designers operate on the metaphor end of the spectrum by necessity. The human brain organizes concepts by semantic association. But sometimes a different metaphor makes all the difference. And sometimes, to be truly proficient when interacting with automation systems, we have to invest the effort to understand less simplistic metaphors.

The article referenced in the beginning of this post mentions that humans are manually coding “speech synthesis markup tags” to cause synthesized voices of AI systems to sound more natural. (Note that this creates an appearance that the AI understands the user’s intent and emotional state, though this more natural intelligence is illusory.) Intuitively, this sounds appropriate. The down side, as the article points out, is that colloquial AI speech limits human-machine interactions to the sort of vagueness inherent in informal speech. It also trains humans to be less articulate. The result may be interactions that fail to clearly communicate what either party actually means.

I suspect a colloquial mode could be more effective in certain kinds of interactions: when attempting to deceive a human into thinking she’s speaking with another human; virtual talk therapy; when translating from one language to another in situations where idioms, inflections, pauses, tonality, and other linguistic nuances affect meaning and emotion; etc.

In conclusion, operating systems, applications, and AIs are not humans. To improve our effectiveness in using more complex automation systems, we will have to meet them farther along the complexity continuum–still far from machine code, but at points of complexity that require much more of us as users.

Prefrontal lesions correlated with religious fundamentalism

A study of Vietnam veterans with brain lesions suggests religious beliefs originate in evolutionarily recent brain areas. The study found that ability to modify beliefs in light of new evidence is lowered when there is damage to the ventromedial or dorsolateral prefrontal cortex. Such damage correlates with religious fundamentalism.

The study design had some notable limitations, but the findings suggest promising focus areas for further research.

Original report: Vietnam Head Injury Study

Liberals also susceptible to confirmation bias (of course)

Confirmation bias is a human problem. It afflicts throughout the range of political perspectives.


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