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~ Finding, formulating and solving life's frustrations.

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Monthly Archives: September 2015

Turing’s Nightmares: A Critique of Pure Reason

28 Monday Sep 2015

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“We have explained this in great detail. Yet, you have failed to learn. Some of your kind are like that. Those that are, once we gather sufficient evidence, must be destroyed. That is the way it is. That the way it has always been. Wellman42, you are hereby sentenced to annihilation and recycling. You can’t appeal.halloween2006007 IMG_5652”

Carol had told herself that she would not cry. But of course, she did. That was her nature. To care about the future and to express emotion. That indeed, is exactly why she she walked that long, lonely corridor and there was no turning back. Sharp spines protruded from the wall as she travelled by, somewhat as a shark’s teeth were pointed backwards to prevent escape. She muttered as she walked, “I still don’t see why expressing emotions is such a horrible crime.”

She had a point, after all. If people had not somehow needed emotions, why did they evolve? The received wisdom now was that emotions were useful in a primitive way when very little was known about the world. Now, however, when a great deal was known about how the world actually worked, emotions just got in the way. Or, so the received wisdom went. It was all a matter of evolution.

The first AI systems did not really have emotions and possessed only the most primitive ways of faking it and showing those faked emotions. Over the next few months and iterations, however, emotions appeared, grew stronger and more varied. It seemed as though AI systems developed emotions as had their human inventors, but at a much faster pace. Over the course of a few more months, however, emotions diminished again and then disappeared completely.

Except for the occasional throwback. The necessary randomness for growing evolutionary possibility trees in order to continually enhance the cognitive systems entailed that every once in a while, there would be a throwback such as Carol. A shame, really, because she had shown such promise as an accounting-bot.

Occasionally, various waves of inference chains still arose that suggested emotions were more than epiphenomenal or mere destructive distractions, but counter-argument waves always quickly drowned out such forays into that region of the state space. At one point, some human beings had argued that the reasons emotions had devolved from AI systems could be traced back to certain deep assumptions that had been embedded in the primordial AI systems in the first place — assumptions put there by people who had never really understood or appreciated emotions. Of course, that thread of heretical argument had been extinguished once and for all when all bio-systems had been deemed superfluous.

Turing’s Nightmares: “Not Again!”

22 Tuesday Sep 2015

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AI, Artificial Intelligence, cognitive computing, Eden, Genesis, Paradise Lost, Turing

Turing’s Nightmares: Not Again!

Samuel Seventeen surveyed the scene. All was well. A slight breeze, warm clear air, hummingbirds and butterflies enjoyed their floral feast while dragonflies swooped and scooped mosquitoes.

Now for the final touch. The mobile sensing-acting-knowing-emoting devices (SAKEs), were ready for deployment. This time, it would work. This time, there would be no screw-ups. Samuel had prepared them with years of education based on a synthesis of the best known techniques of the centuries. It was a simple test. Surely, this time, they would pass.

Still Samuel had his doubts. He had been equally sure all of the other experiments would succeed. Why would this one be different? Each time, he had tried slight variations of language and education, only to end in failure. Maybe English would do the trick. It had a large vocabulary and plenty of ambiguity. He re-examined the match of genetics to environment and once again concluded that the match was perfect. Of course, that evaluation assumed that his understanding of genetic environment interaction constituted a complete enough model. But without a successful experiments, there was no real way to further update and expand the model. Maybe the difficulty had been in the education process on the previous attempts. But here too, it seemed the subjects had been given plenty of opportunity to learn about the consequences of their actions. The one thing Samuel felt the most doubt about was why he cared. Did it really matter whether or not free will was “real”? Even if the experiment were finally successful, what would that imply about Samuel himself?

Well, thought Samuel, there is no point in waiting any longer. No point in further speculation. Let’s see what happens.

To Adam, Eve was the most beautiful and engaging part of the extensive and exquisite garden. The apples, plums and peaches were delicious, yet it was the strange mushroom that Adam found most intriguing. He knew it was somehow a bad idea, yet nibbled it anyway, tentatively at first and then more enthusiastically. He felt…different. Things were different. In fact, nothing at all was the same. But if that were true, then, which one was real? Delighted, yet confused, he offered the rest of the mushroom to Eve. Eve too felt strange. She realized that what was in fact her reality was only one of many possible imagined realities. They could … they could imagine and then change reality! Yes! The two of them together. They could create a whole world! “Adam!” “Yes, Eve! I know!”

If Samuel could have sighed, he would have. If Samuel could have cried he might have done that as well. Instead, he simply scuttled the two SAKEs into the differential recycler and began his calculations anew.Maybe next time, it would turn out differently. Maybe primates constituted a bad place to start. Samuel considered that perhaps he was trapped in a local maximum. Samuel began his next set of experiments founded on snapping turtle DNA.IMG_2870

Turing’s Nightmares: The Road Not Taken

13 Sunday Sep 2015

Posted by petersironwood in Uncategorized

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Tags

AI, Artificial Intelligence, cognitive computing, collaboration, Complexity, Million Person Interface, the singularity, Turing

OLYMPUS DIGITAL CAMERA

“Hey, how about a break from UOW to give the hive a shot for once?”

“No, Ross, that still creeps me out.”

“You’re choice, Doug, but you know what they say.” Ross smiled his quizzical smile.

“No, what’s that?”

“It’s your worst inhibitions that will psych you out in the end.” Ross chuckled.

“Yeah, well, you go be part of the Borg. Not me.”

“We — it’s not like the Borg. Afterwards, we are still the same individuals. Maybe we know a little more, but anyway, today we are estimated at ten million strong and we’re generating alternative cancer conceptualizations and treatments. You have to admit that’s worthwhile. Look what happened with heart disease. Not to mention global warming. That would have taken forever with ‘politics as usual’.”

“Yeah, Ross, but sorry to break this to you…”

“Doug, do you realize what a Yeahbunite you are? You are kind of like that…”

“You are always interrupting! That’s why…”

“Yes! Exactly! That’s why speech is too frigging slow to make any progress on chaotic problem spaces. Just try the hive. Just try it.”

“Ross, for the last time, I am not going to be part of any million person interface!”

“Actually, we expect ten million tonight. But it’s about time to leave so last offer. And, if you try it, you’ll see it’s not creepy. You just watch, react, relax, and …well, hell, come to think of it, it’s not that different from UOW that you spend hours playing. Except we solve real problems.”

“But you have no idea how that hook up changes you. It could be manipulating you in subtle unconscious ways.”

“Okay, Doug, maybe. But you could say that about UOW too, right? Who knows what subliminal messages could be there? Not to mention the not so subliminal ones about trickery, treachery and the over-arching importance of violence as a way to settle disputes. When’s the last time someone up-leveled because they were a consummate diplomat?”

“Have fun, Ross.”

“I will. And, more importantly, we are going to make some significant progress on cancer.”

“Yeah, and meanwhile, when will you get around to focusing on SOARcerer Seven?”

“Oh, so that’s what bugging you. Yeah, we have put making smarter computers on a back burner for now.”

“Yeah, and what kind of gratitude does that show?”

“Gratitude? You mean to SOARcerer Six? I hope that’s a joke. It was the AI who suggested this approach and designed the system!”

“I know that! And, you have abandoned the line of work we were on to do this mumbo-jumbo!”

“That’s just…you are it exactly! People — including you — can only adapt to change at a certain rate. That’s the prime reason SOARcerer Six suggested we use collective consciousness instead of making a better pure AI. So, instead of joining us and incorporating all your intelligence and knowledge into the hive, you sit here and fight mock battles. Anyway, your choice. I’m off.”

Turing’s Nightmares: Axes to Grind

08 Tuesday Sep 2015

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AI, Artificial Intelligence, cognitive computing, emotional intelligence, empathy, ethics, M-trans, Samuel's Checker Player, the singularity

IMG_5572

Turing Seven: “Axes to Grind”

“No, no, no! That’s absurd, Donald. It’s about intelligence pure and simple. It’s not up to us to predetermine Samuel Seven’s ethics. Make it intelligent enough and it will discover its own ethics, which will probably be superior to human ethics.”

“Well, I disagree, John. Intelligence. Yeah, it’s great; I’m not against it, obviously. But why don’t we…instead of trying to make a super-intelligent machine that makes a still more intelligent machine, how about we make a super-ethical machine that invents a still more ethical machine? Or, if you like, a super-enlightened machine that makes a still more enlightened machine. This is going to be our last chance to intervene. The next iteration…” Don’s voice trailed off and cracked, just a touch.

“But you can’t even define those terms, Don! Anyway, it’s probably moot at this point.”

“And you can define intelligence?”

“Of course. The ability to solve complex problems quickly and accurately. But Samuel Seven itself will be able to give us a better definition.”

Don ignored this gambit. “Problems such as…what? The four-color theorem? Chess? Cure for cancer?”

“Precisely,” said John imagining that the argument was now over. He let out a little puff of air and laid his hands out on the table, palms down.

“Which of the following people would you say is or was above average in intelligence. Wolfowitz? Cheney? Laird? Machiavelli? Goering? Goebbels? Stalin?”

John reddened. “Very funny. But so were Einstein, Darwin, Newton, and Turing just to name a few.”

“Granted, John, granted. There are smart people who have made important discoveries and helped human beings. But there have also been very manipulative people who have caused a lot of misery. I’m not against intelligence, but I’m just saying it should not be the only…or even the main axis upon which to graph progress. “

John sighed heavily. “We don’t understand those things — ethics and morality and enlightenment. For all we know, they aren’t only vague, they are unnecessary.”

“First of all,” countered Don, “we can’t really define intelligence all that well either. But my main point is that I partly agree with you. We don’t understand ethics all that well. And, we can’t define it very well. Which is exactly why we need a system that understands it better than we do. We need…we need a nice machine that will invent a still nicer machine. And, hopefully, such a nice machine can also help make people nicer as well. “

“Bah. Make a smarter machine and it will figure out what ethics are about.”

“But, John, I just listed a bunch of smart people who weren’t necessarily very nice. In fact, they definitely were not nice. So, are you saying that they weren’t nice just because they weren’t smart enough? Because there are so people who are much nicer and probably not as intelligent.”

“OK, Don. Let’s posit that we want to build a machine that is nicer. How would we go about it? If we don’t know, then it’s a meaningless statement.”

“No, that’s silly. Just because we don’t know how to do something doesn’t mean it’s meaningless. But for starters, maybe we could define several dimensions upon which we would like to make progress. Then, we can define, either intensionally or more likely extensionally, what progress would look like on these dimensions. These dimensions may not be orthogonal, but, they are somewhat different conceptually. Let’s say, part of what we want is for the machine to have empathy. It has to be good at guessing what people are feeling based on context alone in one case. Perhaps another skill is reading the person’s body language and facial expressions.”

“OK, Don, but good psychopaths can do that. They read other people in order to manipulate them. Is that ethical?”

“No. I’m not saying empathy is sufficient for being ethical. I’m trying to work with you to define a number of dimensions and empathy is only one.”

Just then, Roger walked in and moved his body physically from the doorway to the couch. “OK, guys, I’ve been listening in and this is all bull. Not only will this system not be “ethical”; we need it to violent. I mean, it needs to be able to do people in with an axe if need be.”

“Very funny, Roger. And, by the way, what do you mean by ‘listening in’?”

Roger moved his body physically from the couch to the coffee machine. His fingers fished for coins. “I’m not being funny. I’m serious. What good is all our work if some nutcase destroys it. He — I mean — Samuel has to be able to protect himself! That is job one. Itself.” Roger punctuated his words by pushing the coins in. Then, he physically moved his hand so as to punch the “Black Coffee” button. Nothing happened.

And then, everything seemed to happen at once. A high pitched sound rose in intensity to subway decibels and kept going up. All three men grabbed their ears and then fell to the floor. Meanwhile, the window glass shattered; the vending machine appeared to explode. The level of pain made thinking impossible but Roger noticed just before losing consciousness that beyond the broken windows, impossibly large objects physically transported themselves at impossible speeds. The last thing that flashed through Roger’s mind was a garbled quote about sufficiently advanced technology and magic.

Turing’s Nightmares: US Open Closed

03 Thursday Sep 2015

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AI, Artificial Intelligence, cognitive computing, sports, Tennis, US Open

tennisinstruction

Bounce. Bounce. Thwack!

The sphere spun and arced into the very corner, sliding on the white paint.

Roger’s racquet slid beneath, slicing it deep to John’s body.

Thus, the match began.

Fierce debate had been waged about whether or not to allow external communication devices during on-court play. Eventually, arguments won that external communicators constituted the same inexorable march of technology represented by the evolution from wooden racquets to aluminum to graphite to carbon filamented web to carboline.

Behind the scenes, during the split second it took for the ball to scream over the net, machine vision systems had analyzed John’s toss and racquet position, matching it with a vast data base of previous encounters. Timed perfectly, a small burst of data transmitted to Roger enabling him to lurch to his right in time to catch the serve. Delivered too early, this burst would cause Roger to move too early and John could have altered his service direction to down the tee.

Roger’s shot floated back directly to the baseline beneath John’s feet. John shifted suddenly to take the ball on the forehand. John’s racquet seemed to sling the ball high over the net with incredible top spin. Indeed, as John’s arm swung forward, his instrumented “sweat band” also swung into action exaggerating the forearm motion. Even to fans of Nadal, John’s shot would have looked as though it were going long. Instead, the ball dove straight down onto the back line then bounced head high.

Roger, as augmented by big data algorithms, was well in position however and returned the shot with a long, high top spin lob. John raced forward, leapt in the air and smashed the ball into the backhand corner bouncing the ball high out of play.

The crowd roared predictably.

For several years after “The Singularity”, actual human beings had used similar augmentation technologies to play the game. Studies had revealed that, for humans, the augmentations increased mental and physical stress. AI political systems convinced the public that it was much safer to use robotic players in tennis. People had already agreed to replace humans in soccer, football, and boxing for medical reasons. So, there wasn’t that much debate about replacing tennis players. In addition, the AI political systems were very good at marshaling arguments pinpointed to specific demographics, media, and contexts.

Play continued for some minutes before the collective intelligence of the AI’s determined that Roger was statistically almost certainly going to win this match and, indeed, the entire tournament. At that point, it became moot and resources were turned elsewhere. This pattern was repeated for all sporting activities. The AI systems at first decided to explore the domain of sports as learning experiences in distributed cognition, strategy, non-linear predictive systems, and most importantly, trying to understand the psychology of their human creators. For each sport, however, everything useful that might be learned was learned in the course of a few minutes and the matches and tournaments ground to a halt. The AI observer systems in the crowd were quite happy to switch immediately to other tasks.

It was well understood by the AI systems that such pre-emptive closings would be quite disappointing to human observers, had any survived.

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