Paul writes about AI, emotions and empathy at Forbes, just in time for Valentine’s Day.

We believe it is possible that robotics and “thinking” machines will eventually take all human jobs.

Since the Agricultural Revolution millennia ago, many human jobs have been replaced by automation. And the pace of job displacement due to automation is accelerating, as machine intelligence is added to mechanical and robotic systems. Our blog is an objective look at how far technology must advance to close the gap between people and the requirements for automating different classes of jobs.

This post is a summary of our writing and thought process so far. …

This post begins with a dog. Our last post was about sapience and learning processes; when we’d toss ideas back and forth, the family dog made for great anecdotes. Occasionally when we’d mention Zoe (the dog), she’d cock her head and look like she was trying understand what we were saying. Cue the debates about canine cognition. The question “What Is Understanding?” isn’t limited to debate about dogs; it’s going to be a huge stumbling block as automation increasingly continues to take hold.

We’re all clear that bread slicers, factory robots, Roombas, and thousands of other machines that are automating routine manual jobs don’t understand anything about the tasks they do. But what about the systems that replace middle managers, software developers, academics, and artists? This issue isn’t purely philosophical. In the end it’s also technical and highly political. …

In our previous post we explored how Imitating Machines are good at sense and respond loops and simple OODA loops. But Imitating Machines lack the higher-level abilities to build behavioral models of the real world, make complex human-like decisions, or demonstrate a self-directed intent. In this post we’ll combine that thread of logic with our observations on overfit models and finish our thoughts on what it will take to create true machine sapience.

Sapience drives progress, but historically progress has not happened very often or very consistently. There is an expression “normal people do not change history”. Science and arts are driven by curiosity and explorations of “what if” and “watch this” instead of belief in or constraining scope to commonly-accepted facts. Because exceptional non-normal people often ignore cultural norms of belief, faith, and dogma, they are often labeled as heretics in their own time. Current mainstream intelligence and personality tests do not focus on finding exceptional non-normal people; testing focuses on intelligence and not sapience. If we cannot reliably measure sapience, then how can we measure it in machines (or in other animal species, space aliens, etc.). How will humanity know when an imaginative, curious sapient machine becomes our equal, or better?

In our previous post we described how humans might have an urge that forms the basis of “wanting” to do something. We discussed evolutionary imperatives, the effects of punctuated equilibrium on evolution, and OODA loops: Observe, Orient, Decide, Act. With this context, we’ll consider how a machine might want to do something…and what that has to do with displacing jobs.

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Today, if humans want a machine to do something, humans design the machine to do that thing. The code that runs the machine has no option but to do the thing it was designed to do. A human determined that a machine should be designed to do the thing, carried through with designing and building the machine, and once the machine starts operating it simply does the thing it was designed and built for. …

This and the following two posts will complete our high-level narrative on machine intelligence and machine sapience. We will then use our narrative as context for commenting other experts’ writing.

People tend to anthropomorphize technology. But technology is not human, nor is it even biologically-based. That does not stop people from believing that a machine sapience will want some of the same things that people want.

The fear that machine sapience will be just like people — and want the same things that people want — is the core of a lot of modern science fiction. …

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Earlier we defined “creative” ideas as having novelty and value. Here, we explore overfit and how machines can generate creative ideas…and potentially take your job.

One really useful trick that higher order animals use to game randomness — to improve their chances of learning to survive and thrive — is called overfit.

We believe overfit is useful on an evolutionary scale. Organisms that wish to adapt to new environments may be presented with only a handful of life-threatening learning opportunities. If they do not infer conclusions quickly, without a large training set of data, they may die quickly. If they die before they reproduce, they are out of the gene pool. Life on Earth became capable of overfit a long time ago. Overfit’s side effect may be that organisms are likely to use aggressive survival tactics in many situations that are not life threatening, with the benefit that they will probably react to and survive true life threatening situations; therefore overfit will be selected for in the gene pool. …

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Photo generated from random noise by a neural network trained on places by MIT Computer Science and AI Laboratory. Courtesy of Google at, and under Creative Commons Attribution 4.0 International License.

We surprised some people when we said it is possible that robotics and “thinking” machines will eventually take all human jobs. “Certainly you don’t mean all jobs…what about creative jobs?” Yes, even creative jobs. It is possible that robotics and “thinking” machines will eventually take creative jobs, too. We believe…

  1. Creativity is a process.
  2. The creative process is based on a mathematical model called overfit.
  3. Once you design a machine intelligence to embrace overfit models — instead of avoiding them — you are starting down the road to building a creative machine.
  4. When you build creative machines, they will be capable of competing with people for any job. …

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Vincent van Gogh, The Harvest, June 1888, oil on canvas, 73.4 cm x 91.8 cm, Van Gogh Museum, Amsterdam.

This blog sets the stage for determining what kinds of human work can be displaced by automation by looking at the kinds of work people have invented for themselves, and why increasing “horizontal” job specialization creates opportunities for potential automation of those specialized jobs.

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Thomas Cole, The Arcadian or Pastoral State, 1834, oil on canvas, 39 ½ × 63 ½ in. New-York Historical Society.

Millennia ago, occupations were hereditary. Most people lived their entire lives near their extended family and worked in the agricultural economy. For most of recorded human history, more than 90% of the world’s population worked at growing, harvesting, preserving, or distributing food.

People were trained to do everything associated with their occupation, like farming a specific crop. If someone couldn’t work or died, then anyone trained in that occupation could easily replace them. …


Imitating Machines

We talk about the impact on human employment of robotics, Machine Intelligence, and possible future Machine Sapience. Also

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