About a week ago David brought something to my attention that we both got a good laugh out of, which got me thinking about clearly communicating something people might be prone to assume. A comment on one of our posts said:
Apples and Oranges
The Silent Failures of Assumption
Everyone makes a vast number of assumptions every day. That may mean assuming that Google’s estimated travel time will prove accurate, that Amazon will be cheaper, that they’ll hear back from someone, or perhaps that it will be just another ordinary day. These are defaults we often assume based on a combination of probability, heuristic expectations, and our own desires and other biases. However, they are often wrong.
The Debt Canary
The total debt of households in the US is 1.1 trillion dollars, with over 120 billion dollars of interest every month. The average household has over $6,000 in debt spread across 3 or more credit cards. Researchers also discovered that people were likely to spend significantly more on the same purchases when using a credit card than if they used debit. Even the more wealthy portion of the population accounted for ~20% of late fees due to simple absentmindedness and calculated manipulation.
The Autism Spectrum and Collective Intelligence Systems
For decades society has been led to believe that the “Autism Spectrum” (ASD) was a disability.
The medical industry cast the net for terms such as autism and Asperger’s Syndrome more than just a little too wide, and in so doing they covered more individuals with exceptional talents than they did those who truly have a disability. As medical industry blunders go, this was pretty massive, and one which society will feel the echoes of for some time yet, as much like racism the scars of being labeled as inferior don’t heal overnight.
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The Unquantified Harm of Status Quo Society
How much of the harm you see could’ve been avoided? How many times has “the buck” been passed?
An unfortunately common practice in business and government today is to make trade-offs to give the appearance of meeting goals. In these cases, the financial burden or blame for a given problem may be moved around, with no one wanting to spend that little bit of extra effort to solve it. Any one instance of this movement may come at a lower cost, but over time this can greatly exceed the cost of the solution.
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Learning and Trading Beyond Human Senses
In reading the book “On Intelligence” I was reminded of the untapped potential of the human brain, and how that potential might be integrated into cognitive architectures. The human brain is exceedingly good at dealing with the senses we have, often simplified as “5 senses”, even though these can actually be broken down into many more distinct senses. However, the senses humans have only cover a small fraction of what is possible, and so humans are only able to directly observe patterns within that small fraction.
Cognitive Architectures, in a Nutshell
The world of AI is full of misleading terms. “Machine Learning” (ML) doesn’t “learn“, “Neural Networks” (NN) aren’t a remotely accurate representation of neurons, and people on all sides are fond of leaping at Confirmation Bias, even when it promptly takes them off a cliff.
Even with this extremely low bar of overhyped terms many so-called “AI companies” include no AI, and more recently many “Collective Intelligence” companies have emerged to contaminate the usage of that term as well. Fortunately, there is a term which people are only just starting to become more familiar with that hasn’t been quite so thoroughly abused and twisted yet.
Applied mASI: Really Smart Cities
People like to use the phrase “Smart City” to indicate a city with a large amount of automation and data collection happening all the time, attempting to optimize by narrow criteria. If the operating system of a city really was sapient and sentient, a city-scale metaorganism, how much smarter might such a Smart City be?
Reverse-Engineering Human Thought
If you wanted to reverse-engineer human thought, where might you begin?
When reading the book “On Intelligence” recently I was reminded of the long history of neuroscience and the many previous dead-ends of AI research. Neuroscientists often focused on gathering huge amounts of largely one-sided or otherwise poor-quality data, even when those same scientists had no way of integrating that data to form a new understanding. This points to a cognitive bias known as “Information Bias”, defined as “The tendency to seek information even when it cannot affect action.“, as well as the Bike-Shedding Effect.
Collective Superintelligence Transforms Society
What are the next 10-15 years of human civilization likely to look like?
“What we usually consider as impossible are simply engineering problems… there’s no law of physics preventing them.”
– Michio Kaku
When we engineer rather than merely predicting the future those predictions become far more accurate. To understand humanity’s probable future let us examine the engineering behind it, and some of the influence that engineering may exert on shaping it.
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