SynapticNulship

Apparently a concept I developed in my spare time in 2009, which I dubbed “posthuman factors,” is very similar to some guy’s PhD dissertation in 2010 in which he also used the term posthuman factors. (And I don’t mean everything in his dissertation, but there’s a lot of overlap.)

I recently learned of this through a Wikipedia article I discovered (created in April 2011 by user Nikiburri) called “Posthuman factors.” It has a good summary:

In general, posthuman factors addresses the intersection of design practices that includes (1) the design of posthumans, (2) designing for such posthumans, especially in safe and sustainable ways, and (3) designing the design methodologies that will supersede human-centered design (i.e., “posthuman-centered design”, or the processes of design that posthumans employ).

Interestingly, it cites my IEET article “Why You Should Care About (Post)Human Factors,” published Jan 8, 2010, yet claims that posthuman factors was first “articulated” by Dr. Haakon Faste in his Jan 2010 doctoral dissertation “Posthuman Factors: How Perceptual Robotic Art Will Save Humanity from Extinction.”

Most likely we were both thinking about it and writing about it at around the same time (one would assume that, as with my articles mentioned above, the writing actually started in 2009). And then there are whatever projects that lead to this particular synthesis of concepts; e.g. in my case it connects at least as far back to my attempt to describe an interface point of view for future human/robot/posthuman/etc. interactions (“Would You Still Love Me If I Was A Robot?“).

But the Wikipedia pages are a bit annoying. The Posthuman factors page has a link to a wikipedia page for Haakon Faste (created by the same user Nikiburri) which informs us that he is a leading figure in the field of posthuman factors and that he coined the term in 2010. Well, guess what—I posted my article “Do We Need a Posthuman Factors Discipline?” in December 2009 on my blog, so I guess that means I coined it first.

But it’s nice to know that I started a new field. And I’m pleased that at least one other person is thinking about these issues.

“Nothing New Under the Sun” is the title of Robert Silverberg’s column for the June 2011 issue of Asimov’s Science Fiction Magazine. Although the sobering thought that humanity keeps repeating certain types of mistakes is not one I particularly relish, it should be discussed.

Crowd Stupidity

“Anyone taken as an individual is tolerably sensible and reasonable — as a member of a crowd he at once becomes a blockhead.”

—Schiller as quoted by Bernard Baruch as quoted by Robert Silverberg

Silverberg shares some excerpts from the mid-1800s book Extraordinary Popular Delusions and the Madness of Crowds, written by Scottish lawyer / journalist Charles Mackay.

Silverberg compares the South-Sea Bubble disaster to the Internet dot com bubble, specifically failed companies such as Webvan (bankrupt in 2001), Boo.com (broke in 2000) and Flooz.com (died in 2001).

England’s South-Sea Bubble so long ago was not blamed, according to Mackay, on the general public’s avarice, lust of gain, etc. Instead, like with the recent economic crash of 2008, the “evil” bankers and executives are blamed. The collective insanity of a nation seems to be a major factor though. Perhaps it does take a cunning plan to fool the masses, but it also requires the masses to act idiotically as they urgently try to consume or become rich or whatever.

My intention in this post is not to get into the issues of blame for economic bubbles, but to note the special ability for a normally intelligent person to become less so in the context of a group.

Another popular delusion of humankind’s past is fortune telling, e.g. via astrology. Unfortunately, it’s still quite popular. As Mackay wrote:

Leaving out of view the oracles of pagan antiquity and religious predictions in general, and confining ourselves solely to the persons who, in modern times, have made themselves most conspicuous in foretelling the future, we shall find that the sixteenth and seventeenth centuries were the golden age of these impostors. Many of them have been already mentioned in their character of alchymists. The union of the two pretensions is not at all surprising. It was to be expected that those who assumed a power so preposterous as that of prolonging the life of man for several centuries, should pretend, at the same time, to foretell the events which were to mark that preternatural span of existence.

Of course, most transhumanists would exactly like to do the same thing that those alchemists promised, which is to live for centuries (at least). And transhumanists are quite often found foretelling events or repeating the foretellings of popular writers. I recommend that transhumanists, including me, be all the more alert to traditional delusions dressed in sexy technolust clothes.

Crowd Intelligence

“We find that whole communities suddenly fix their minds upon one object, and go mad in its pursuit; that millions of people become simultaneously impressed with one delusion, and run after it, till their attention is caught by some new folly more captivating than the first. ”

—Charles Mackay

Humans are social animals, surely there must be overall benefits to group intelligence? Well, even our relatives the chimps have group stupidity—they will keep copying the behavior of a leader even if a better strategy appears and they will copy the behavior of the dominant group member even if it results in less rewards than another way that they also learned.

But what about the so-called “wisdom of crowds?” Well, we don’t always have wisdom or higher intelligence emerging from groups because the system has to be set up correctly. The main criteria that James Surowiecki listed in his book The Wisdom of Crowds are:

• Diversity of opinion
• Independence
• Decentralization
• Aggregation

So, first every person should ideally have some private information or ideas that aren’t shared with the others. Second, people don’t allow others in the group to determine their opinions or decisions. Third, people don’t have to be stuck in a closed central structure of wisdom, they can draw from local knowledge and wisdom. Fourth, there has to be a part of the system that compiles judgements into a decision.

And it is not necessarily easy to achieve all four of those criteria for a given problem and a given group.

The Future of Madness

“Pretend to be mad? Who would notice a madman around here?”
—Capt. Blackadder (from Blackadder Goes Forth, which takes place in the trenches of World War 1)

Robert Silverberg’s essay presents the solemn attitude that humanity keeps on repeating its old mistakes. It sounds like a cliché (although perhaps not a popular enough one); in fact Silverberg says one falls back on clichés in this context. Is the adage of Alphonse Karr that Silverberg quotes, “The more things change, the more they remain the same,” really a behavior of the humanity system?

It’s been said that a true science fiction story is one in which the world is irreversibly changed by the end of the story. But can that happen in real life? Transhumanists very much want to instantiate science fiction’s promises. And it seems like certain technologies have transformed everything, such as the Internet.

Perhaps national delusions, group idiocy, Ponzi schemes, witch hunts, economic bubbles, and so on, are not actually a concern for us in the long run. But, let’s explore the premise that they are, just in case.

So, what would be some therapies for humankind’s collective insanity? One obvious answer for a transhumanist is of course to change the very nature of our intelligence, and that can be at an individual level and/or in networked assistance via computer systems, etc. But, what if we were to imagine reducing madness today, using today’s infrastructure?

Philosopher Daniel Dennett had a concept he called “Super Snopes.” Snopes.com is the popular debunking database which explains the truths and lies behind urban myths, chain emails, etc. Super Snopes would be some sort of more massive collection of truth utilizing the power of the Internet, and which would counter the misinformation on the Web.

But Snopes, and maybe even a Super Snopes (if that’s even possible), don’t really address the serious delusions which can last for years. And how does one even know they have subscribed to a delusion if everybody they talk to (or follow) is deluded in the same way? What would motivate a person to even participate in a (Super) Snopes?

Perhaps one glimmer of hope is that the Internet and social media allow different groups to communicate. Never are all people in the world under the exact same delusion. So if the people of sufficient difference were able to trade criticism in a way that overcame our primitive tribal nature, major delusions could be stopped before total disaster.

I suspect we have just begun to tap the power of constant global connections and social media. As Clay Shirky points out, we have a “cognitive surplus” of billions of hours per year that’s largely been used to watch television. In this century some of that time has shifted from passive consumption of media to video games (especially massively multiplayer games) and to actual content creation such as with Wikipedia and of course blogs.

Yet the memes that run rampant are often not about debunking or skepticism, they are simply viral without regards to truth. Our system presently allows simple amplification of normal human social emotions and behaviors. It doesn’t take much cognitive power to go along with bandwagons: repeating—and buying into—what everybody else says on Twitter or Facebook to a major news event. And of course, as it always has been with news, the social news gives the same attention to celebrity gossip and cat photos as it does to natural disasters and national revolutions. And the lifetime of a meme or popular event can be extremely short lived.

So, we have this powerful worldwide networked community, but could it be used for the good of groups? Could it be used at longer time scales, e.g. to stop a decade-long delusion?

Could we evolve our social web so that humankind (or at least those online) are constantly keep ahead of the game when it comes to tricks and delusions?

Also published in H+ Magazine.

Science comedian Brian Malow has made a video containing neither comedy nor science:

When Robots Attack! Should We Fear a Singularity?

And yes, I realize I shouldn’t have even bothered to watch it once I realized it was for a mainstream news outlet, but several people in my Twitter lists were tweeting it.

Unfortunately, this video turned out not to be for nerds or anyone who has ever thought about future robots or the Singularity.  This video is for mainstream sheep.  The only glimmer of hope was when he started pursuing the thread of asking why humans have this tendency to punish themselves in robot stories with a father figure or in the manner of Frankenstein.  After a couple seconds of that we’re dropped back into cliché city with “robot uprisings.”

The Roomba is mentioned—and then—holy shit, iRobot makes military robots too!  OMG!  Wait…everybody knows that already.  Big deal.  I guess Time readers/watchers are really behind the…times.  And sure, I’m not being fair—Time readers may not have heard of every robot company, after all.  Thank goodness this video shows Big Dog and Robonaut, two unrelated robots made by other companies, wedged in between the iRobot clips while Malow lobs the old joke at us that the cleaning robots will decide to kill humans.

Sure, it’s supposed to be funny.  But it’s not, because it’s unoriginal and out of date and/or not real enough (some humor is effective because it’s so close to the truth).  As William Zinsser said of humor writers:

They’re not just fooling around.  They are as serious in purpose as Hemingway or Faulkner—in fact, a national asset in forcing the country to see itself clearly.

Occasionally I do see a humor piece on the web that achieves this, sometimes even from big places like Cracked.com or The Onion.

Partly, it’s just a matter of taste.  Surely some people found Malow’s robot/singularity video funny; after all, millions of people out there paid money to see Meet the Fockers and Little Fockers.  Millions of people…laughing when they’re told to at tired jokes and clichés.

Of course, maybe it’s too difficult to be funny with robots—you have to be creative and you’re not sure what your target audience will grok.  But, please, if you’re going to make yet another joke about the “robot uprising,” at least make it a new joke.

If you think I’m biased against people making fun of robots or my company, think again: The Daily Show beat Malow to the punch and made fun of iRobot in 2009 (“Roombas of Doom“), and it was much funnier than Malow’s attempt, although still very far removed from reality:

So why do I even bother ranting about mainstream tropes and lack of creativity?  Well, the problem is it’s infecting even those not in the mainstream.  Almost every person, even if they are scientists or engineers, seems to be obligated to mention AI overlords and robot uprisings as if there are no possible other hooks available.  Every single military robot related article I have seen on the Internet mentions Terminator.  It’s as if the bulk of our culture has been reduced to a mere handful of common concepts, and more and more people are being sucked into this pit of mental inbreeding.

Cross-posted with Science 2.0.

Transhumanists are into improvements, and many talk about specific problems, for instance Nick Bostrom. However, Bostrom’s problem statements have been criticized for not necessarily being problems, and I think largely this is why one must consider the problem definition (see step #2 below).

Sometimes people talk about their “solutions” for problems, for instance here in H+ Magazine. But in many cases they are actually talking about their ideas of how to solve a problem, or making science-fictional predictions. So if you surf the web, you will find a lot of good ideas about possibly important problems—but a lot of what you find will be undefined (or not very well defined) problem ideas and solutions.

These proposed solutions often do not attempt to find root causes or assume the wrong root cause. And finding a realistic complete plan for solving a problem is rare.

8D (Eight Disciplines) is a process used in various industries for problem solving and process improvement. The 8D steps described below could be very useful for transhumanists, not just for talking about problems but for actually implementing solutions in real life.

Transhuman concerns are complex not just technologically, but also socioculturally. Some problems are more than just “a” problem—they are a dynamic system of problems and the process for problem solving itself is not enough. There has to be management, goals, etc., most of which is outside the scope of this article. But first one should know how deal with a single problem before scaling up, and 8D is a process that can be used on a huge variety of complex problems.

Here are the eight steps of 8D:

1. Assemble the team
2. Define the problem
3. Contain the problem
4. Root cause analysis
5. Choose the permanent solution
6. Implement the solution and verify it
7. Prevent recurrence
8. Congratulate the team

More detailed descriptions:

1. Assemble the Team

With an initial, rough concept of the problem, a team should be assembled to continue the 8D steps. The team will make an initial problem statement without presupposing a solution. They should attempt to define the “gap” (or error)—the big difference between the current problematic situation and the potential fixed situation. The team members should all be interested in closing this gap.

The team must have a leader; this leader makes agendas, synchronizes actions and communications, resolves conflicts, etc. In a company, the team should also have a “sponsor”, who is like a coach from upper management. The rest of the team is assembled as appropriate; this will vary depending on the problem, but some general rules for a candidate can be:

• Has a unique point of view.
• Logistically able to coordinate with the rest of the team.
• Is not committedd to preconceived notions of “the answer.”
• Can actually accomplish change that they might be responsible for.

The size of an 8D team (at least in companies) is typically 5 to 7 people.

The team should be justified. This matters most within an organization that is paying for the team, however even a group of transhumanists out in the wilds of cyberspace will have to defend themselves when people ask, “Why should we care?”

2. Define the Problem

Let’s say somebody throws my robot out of an airplane, and it immediately falls to the ground and breaks into several pieces. This customer then informs me that this robot has a major problem when flying after being dropped from a plane and that I should improve the flying software to fix it.

Here is the mistake: The problem has not been properly defined. The robot is a ground robot and was not intended to fly or be dropped out of a plane. The real problem is that a customer has been misinformed as to the purpose and use of the product.

When thinking about how to improve humanity, or even how to merely improve a gadget, you should consider: Have you made an assumption about the issue that might be obscuring the true problem? Did the problem emerge from a process that was working fine before? What processes will be impacted? If this is an improvement, can it be measured, and what is the expected goal?

The team should attempt to grok the issues and their magnitude. Ideally, they will be informed with data, not just opinions.

Just as with medical diagnosis, the symptoms alone are probably not enough input. There are various ways to collect more data, and which methods you use depends on the nature of the problem. For example, one method is the 5 W’s and 2 H’s:

• Who is affected?
• What is happening?
• When does it occur?
• Where does it happen?
• Why is it happening (initial understanding)?
• How is it happening?
• How many are affected?

For humanity-affecting problems, I think it’s very important to define what the context of the problem is.

3. Contain the Problem

Some problems are urgent, and a stopgap must be put in place while the problem is being analyzed. This is particularly relevant for problems such as product defects which affect customers.

Some brainstorming questions are:

• Can anything be done to mitigate the negative impact (if any) that is happening?
• Who would have to be involved with that mitigation?
• How will the team know that the containment action worked?

Before deploying an interim expedient, the team should have asked and answered these questions (they essentially define the containment action):

• Who will do it?
• What is the task?
• When will it be accomplished?

A canonical example: You have a leaky roof (the problem). The containment action is to put a pail underneath the hole to capture the leaking water. This is a temporary fix until the roof is properly repaired, and mitigates damage to the floor.

Don’t let the bucket of water example fool you—containment can be massive, e.g. corporate bailouts. Of course, the team must choose carefully: Is the cost of containment worth it?

4. Root Cause Analysis

Whenever you think you have an answer to a problem, as yourself: Have you gone deep enough? Or is there another layer below? If you implementt a fix, will the problem grow back?

Generally in the real world events are causal. The point of root cause analysis is to trace the causes all the way back for your problem. If you don’t find the origin of the causes, then the problem will probably rear its ugly head again.

Root cause analysis is one of the most overlooked, yet important, steps of problem solving. Even engineers often lose their way when solving a problem and jump right into a fix which later on turned out to be a red herring.

Typically, driving to root cause follows one of these two routes:

1. Start with data; develop theories from that data.
2. Start with a theory; search for data to support or refute it.

Either way, team members must always remember keep in mind that correlation is not necessarily causation.

One tool to use is the 5 Why’s, in which you move down the “ladder of abstraction” by continually asking: “why?” Start with a cause and ask why this cause is responsible for the gap (or error). Then ask again until you’ve bottomed out with something that may be a true root cause.

There are many other general purpose methods and tools to assist in this stage; I will list some of them here, but please look them up for detailed explanations:

• Brainstorming: Generate as many ideas as possible, and elaborate on the best ideas.
• Process flow analysis: Flowchart a process; attempt to narrow down what element in the flow chart is causing the problem.
• Fishikawa: Use a Fishikawa (aka Cause and Effect) diagram to try narrowing down the cause(s).
• Pareto analysis: Generate a Pareto chart, which may indicate which cause (of many) should be fixed first.
• Data analysis: Use trend charts, scatter plots, etc. to assist in finding correlations and trends.

And that is just the beginning—a problem may need a specific new experiment or data collection method devised.

Ideally you would have a single root cause, but that is not always the case.

The team should also come up with various correction actions that solve the root cause, to be selected and refined in the next step.

5. Choose the Permanent Solution

The solution must be one or more corrective actions that solve the cause(s) of the problem. Corrective action selection is additionally guided by criteria such as time constraints, money constraints, efficiency, etc.

This is a great time to simulate/test the solution, if possible. There might be unaccounted for side effects either in the system you fixed or in related systems. This is especially true for some of the major issues that transhumanists wish to tackle.

You must verify that the corrective action(s) will in fact fix the root cause and not cause bad side effects.

6. Implement the Solution and Verify It

This is the stage when the team actually sets into motion the correction action(s). But doing it isn’t enough—the team also has to check to see if the solution is really working.

For some issues the verification is clean-cut. Some corrective actions have to be evaluated with effectiveness, for instance some benchmark. Depending on the time scale of the corrective action, the team might need to add various monitors and/or controls to continually make sure the root cause is squashed.

7. Prevent Recurrence

It’s possible that a process will revert back to its old ways after the problem has been solved, resulting in the same type of problem happening again. So the team should provide the organization or environment with improvements to processes, procedures, practices, etc. so that this type of problem does not resurface.

8. Congratulate the Team

Party time! The team should share and publicize the knowledge gained from the process as it will help future efforts and teams.

Image credits:
1. Inception (2010), Warner Bros.
2. Peter Galvin
3. Tom Parnell
4. shalawesome

Also published in H+ Magazine.