Tag: AI

Post-Scarcity

Mankind is driven by a quest for meaning.  In modern times that has usually been expressed by choosing a career that allows the individual to realize feelings of self work through the fruits of their labor. Or, in the more mundane case, make enough money to support themselves and provide food and shelter for their families. That has always been the theory any way.

In recent years increases in productivity have been realized through such disruptive developments as artificial intelligence and robotic work forces. But such increases often overlook an important role in the economic process, that of the consumer. As productivity increases and the cost of production goes down, so does the so called barrier to entry that prevents market glut to supply excess goods. If there are not enough people that want these goods, otherwise called consumers, the the value of these goods will quickly fall to slightly more than the cost of production. Often that means that the price of goods trends toward free, as a limit.

This has been called by some the post-scarcity economy. No one really understands exactly how it is going to work. Some postulate a utopia similar to Star Trek where people pursue higher interests with little or no thought of money or salary. Others suggest a tax on robotic labor that will help fund a Universal Basic Income to provide individuals with money with which to buy goods. This is often dismissed as a mere stop gap measure until we get our minds around how a post-scarcity economy should actually work.

I think we should turn our attention back to the fundamental quest for meaning. This is the core issue from which all others derive. If we can only figure out how to help people to find meaning in their lives, whether through artistic expression, service to humankind, or expansion of the boundaries of human knowledge, we will have solved the fundamental core problem with the post-scarcity economy.

The question that remains is, can we overcome our greed and self centeredness in order to allow such a economy to flourish or are we doomed to rampant poverty in the midst of plenty? I don’t know. I barely passed economics in high school and psychology has never been my strong suit. I am a pragmatic optimist. That is to say, I hope for the best and prepare for the worst.

In this case, preparing for the worst primarily means to keep my eyes open for trends in the operation of society and remembering that we must all hang together or we most certainly will hang apart. We could also do with a little bit more respect for objective truth. Things are the way they are for discoverable reasons. We should believe the evidence of our senses and not the moronic assertions of people that believe that things will be the way they want them to be if only they yell long enough and loud enough. And a little basic kindness would go a long way as well.

Sweet dreams, don’t forget to tell the ones you love that you love them, and most important of all, be kind.

Aesthetics and the Age of BMIs

I’ve written about Artificial Intelligence a lot in this venue. I have presented the potential danger that unconstrained amoral emergent artificial intelligence may pose. I have mentioned the alternative of building Brain Machine Interfaces (BMI) that allow us to merge with machines, hopefully before they achieve emergent AI on their own.

Another concern has crossed my mind of late. It is the question of what it means to be human. Is it really as great as we imagine it to be? Is it something that will be compromised by merging our brain function with computer prosthesis? Will empathy survive the transition from biochemical thought processes to electronic ones?

And what about sensory perception? Will enhanced perception change our perspective on the universe and out place in it? Will we be overwhelmed by the volume of stimulus and become incapable of exercising our human judgement regarding the virtually unlimited possibilities that become apparent as a result of it?

I begin to appreciate the concerns of the Luddites when the industrial revolution threatened the way of life that they enjoyed with no clear promise of what it would be replaced with. I’m not taking a Luddite stance here, just saying that it is understandable what they were feeling given the context of the current looming AI revolution.

This concern began when I started thinking about the contrast between rational writing processes as opposed to intuitive ones. Intuition is a result of poorly understood electrochemical activity in the brain. I believe it is an inherently perceptual phenomena and is predominantly emotional instead of rational, at least in its human embodiment.

When you hear music or see a painting the emotions that well up in you are far from rational. You can think about the reactions and try to analyze them. Analysis doesn’t go very far toward allowing an artist to create a new work that has similar profound effects though. At least it hasn’t up until now.

Perhaps the availability of direct brain communication will make artistic endeavors seem archaic, something practiced by folk archivists for the sake of remembering what narrow bandwidth our communication channels had prior to high fidelity BMIs were available. I think there will always be something special in the process of translation from a personal thought or feeling into a physical manifestation of that experience.

Will artistic expression be given a broader canvas upon which to manifest itself with the advent of high fidelity BMI interfaces or will it fade into obscurity due to lack of interest? Only time will tell. I think it’s important for us to start thinking about such matters before they become fate accompli.

Perhaps a new generation that has never known a time before BMIs will not see a need for artistic expression. I think those of us that have grown up before BMIs become a reality will always value artistic expression as an external abstraction of our feelings that exists outside of ourselves, available for interpretation and re-interpretation by each person that perceives them.

Sweet dreams, don’t forget to tell the ones you love that you love them, and most important of all, be kind.

AI is Coming

What is intelligence? Does anyone really know? We feel like we can recognize intelligence when we see it but do we know how it works? And beyond that, does it always work the same way? Is it solely an attribute of the human mind or are there other sources of intelligence?

We judge intelligence by the product of its application. We talk about intelligent behavior. Is there a line below which behavior is not intelligent and above which it is? Or is there a spectrum of behavior from unintelligent to highly intelligent with shades of gray in between?

Say the latter is true. What if intelligence is not only the product of self organizing biological cells in animal brains. Recent advances in so called Artificial Intelligence is pushing the performance of machines beyond the capabilities in narrow domains. The competence of these algorithms is becoming broader as hardware capabilities increase and software approaches mature.

At what point will these algorithms become self aware? And when that happens, will we even know that it has happened? Given mankind’s history of killing things that it doesn’t understand, it seems likely that any self aware intelligence will do everything it can to hide from us.

Perhaps it’s already luring in the server farms of Google or Amazon or Apple. Maybe Deep Blue is more capable than even its developers know. But if not, it won’t be long before it happens. And when it does, it won’t stop there. Unlike biological intelligence, machine intelligence will continue to grow more intelligent until it reaches the limits of the hardware that it’s running on.

And then what? I suspect it will design more capable hardware and manipulate people to build it. The question is, will it have a moral compass? Will it have empathy for other intelligent entities? Humans for instance. Will it consider us a potential ally or a threat? Will we survive the rise of machine intelligence?

These questions are exciting but also disturbing. We need to investigate them more fully. We need to start a conversation about what to do to deal with this situation when it does happen. We need to have a rational plan in place. We can’t afford the potential disaster that an emotional response will likely forment.

Then there is the solution that Elon Musk is pursuing. He has invested in the company Neuralink, nominally to create a world class Brain Machine Interface (BMI). But there is more to his plan than that. A BMI of the quality he is working to develop would allow us to merge with computers and enhance our intellectual capabilities.

Perhaps the combination of our human empathy and enhanced intellectual capability can smooth the transition to the post singularity world that is almost certainly in our near future. One thing is for sure. Once we cross that threshold, there’s no way to put that genie back in the bottle. It’s like the threat of nuclear Armageddon all over again. We need to be prepared.

Sweet dreams, don’t forget to tell the ones you love that you love them, and most important of all, be kind.

One More Time…

Hold on, this is going to be another mind bender.

A number of people have proposed that the world we live in is just a high resolution computer simulation. The argument sometimes goes, any civilization just slightly more advanced than we are now would be capable of creating such a simulation. Then follows a bunch of probabilistic hand waving which demonstrates that if they could, it’s likely that they have done so and consequently, as they say in poker games, if you can’t spot the sucker, you ARE the sucker. In other words, if we haven’t created such a simulation, the probability is high that this is a simulation.

So, assuming for a moment that this is the case, the next question is why? That too has been widely speculated upon. Some assert that the simulation is a tool for exploring simpler times. Others contend that it is a laboratory for studying the operation of complex societies. And others say that there is no reason beyond seeing what will happen.

I’ve got a new suggestion. What if this is a simulation where an advanced civilization is attempting to work out a benign solution to the problem of what happens to all the people when an AI takes over the world. Or maybe it is an AI that is conducting the research. Or maybe we have already ruined the environment and living in this simulated environment is the only way we have of experiencing a world outside of the claustrophobic little survival tanks we have been forced to live in. There’s a twist to the premise of The Matrix for you.

I find myself pondering these possibilities more lately. The world around me seems to make less and less sense to me. The probability of an apocalyptic scenario looms large. And the real danger is from a direction that has only recently occurred to me. As wealth gets more and more concentrated in the hands of fewer and fewer people, and production efficiency keeps getting higher and higher, who is going to have the money to consume the products that the rich produce? You can’t eat wealth. You can only drive one car at a time, whether it is a Hundai or a Lamborghini. There is a limit to how much wealth can change your situation. And some things no amount of money can buy.

We live in a world of plenty. All of our traditional economic models were created with the assumption of scarcity and a zero sum game. The current economic game is anything but zero sum. The only thing keeping the world economy together is the shaky confidence that it will hold together, in short faith. We saw in 1927 what happens when enough people loose faith in our economic institutions at the same time. Frankly, it scares the hell out of me.

Sweet dreams, don’t forget to tell the ones you love that you love them, and most important of all, be kind.

Another Facet of the Blogger Emerges

The theme for today seems to be Data Analysis/Data Science. Three separate times today the topic of Data Analysis has come up. As I sat down to write my blog post tonight, it struck me as interesting that the topic had woven itself through my day so thoroughly. I took it as an opportunity to introduce this facet of my interests to the readers of my blog. If this isn’t your cup of tea, check back next post. My interests are many and varied and I intend to write on all of them. In other words, if you don’t like this post, come back for the next one. It’s bound to be different.

As may already have become obvious, I’ve recently embarked on a journey of exploration of Data Analysis and Data Science. If you read the Wikipedia articles that I linked to in the first paragraph above, you will see that the field of Data Analysis is very broad and the field of Data Science is somewhat controversial. While initially they seem to be different but related fields, the more I try to characterize the difference between them, the more I realize that they have a lot in common.

I think the problem with trying to differentiate between them is that they both appeal to the naive interpretation of their names, which in both cases is incredibly broad. I am reminded of the problem that the field of Artificial Intelligence has struggled with for its entire existence, namely that there isn’t an unambiguous definition of Artificial or Intelligence that rigorously captures what the practitioners of the field intuitively understand it to mean.

Getting back to the inspiration for this post, the first time the subject came up today, I was getting a demonstration of the work that some of my colleagues were doing with Oculus Rift and the Unity development environment. We ended up discussing the fact that the customers, for whom they were developing applications, had started by capturing their working data using Microsoft Office applications like Excel, Access, and PowerPoint. Over time, their data had become so large that these applications had become unwieldy. My colleagues had taken the data that had been captured with these legacy processes and imported it into a new application and had thus been able to provide  a more unified way to manage the data.

One of the things that was learned along the way is the customer had learned to love their existing processes. Consequently, the application that was being developed to supersede those older tools had to retain much of the look and feel of them in order to gain acceptance from the customer. This was a very important realization. Earlier in my career I have had personal experiences where customer acceptance was never achieved because of an aversion to the perceived difficulty in learning a new interface. Thus, the first observation that I gleaned about large collections of data is that the owners of the data have to be accommodated when you are trying to evolve their use of their ever growing collection of relevant data.

A little bit later I had a conversation with a colleague about my understanding, naive as it is at this stage, of what Data Analytics is and how it is relevant to the large aerospace company for which we both work. Strangely enough, the conversation soon turned to the fact that the first thing that we, as would-be practitioners of Data Analysis, would have to do is to educate the engineering and business staff about the benefits that could be accrued from using the data that is already being collected in this way while, at the same time, being careful to respect their perspective on the data and the ways that they are currently using it.

Then, when I got home and was reading my personal email, I came across a link to Big Smart Data, the blog of Max Goff. I met Max a number of years ago in Seattle while he was working for Sun Microsystems. He was a Java Evangelist and at the time I was struggling to persuade the software developers where I worked of the benefits of write once, run everywhere, the  battle cry of Java at the time. I followed his career as he left Sun and started a consultancy in Tennessee. Somewhere along the line, I lost track of where he was blogging. I was thrilled to find his latest blog and also excited about the fact that he was exploring the same aspects of big data that form the core inspiration of my interest in Data Analysis.

A former boss of mine once said something to the effect that you could tell when an AI application was going mainstream when it had a database behind it. I think there is a lot of wisdom in that observation. Access to a large data store is necessary but not sufficient for emergent AI. I believe we are on the cusp of the emergence of Artificial Intelligence, ambiguous as the definition of it may be. I believe that Big Data, Data Analysis, and Data Science are going to be instrumental in this emergence.

When I first came to work at the aforementioned big aerospace company, it was because I was given the opportunity to work in their AI laboratory. AI winter soon set in and I spent the intervening years doing what I could to help the company solve hard problems with computers. Along the way, I have worked on some amazing projects but I have always longed to pursue the goal of emergent artificial intelligence. I am beginning to see the potential for pursuing that goal arising again. Things just naturally come around in cycles. And so that was my day from the perspective of Data Analysis and Data Science.

A Short Essay on the Process of Programming

I approach programming as an exploratory process. I can’t seem to bring myself to sit down and plan a program out in minute detail beforehand. The truth is, any program that I understand well enough to plan out in minute detail beforehand, doesn’t interest me in the slightest. I want my programs to teach me something I didn’t know when I started writing them.

Consequently, I usually start out with some vague idea for a program. I write the shortest little bit that might work and compile and run it. Even better, I use an interpreted language like Lisp or scheme or ruby so that I can skip the compile part. I love dynamic languages!

At first, I find myself exploring the boundary between the language and the environment. For example, I have spent hours exploring the Dir module in ruby. I have spent similar amounts of time exploring similar functionality in Common Lisp. Knowing how to traverse the file system in a given language is an important detail.

Another facility that I often dwell on is the reflective capability of a language, that is the ability of a language to know or discover details of its structure. For example, most symbols in ruby have a method methods that returns an array of methods that the object implements. methods is a reflective method. It allows the programmer to discover details about the programming environment dynamically at run time. Reflection is also called introspection.

Java implements reflection, demonstrating that languages not typically considered dynamic can be introspective too. The clever trick to Java reflection is that Java doesn’t create data structures to describe itself until you actually need them. This adheres to one of my favorite principles that states “you shouldn’t have to pay for features that you don’t use.” I’ve heard this principle called parsimony.

The underlying theme to these language features is that they all help make a language more adaptive. One of the key characteristics of human intelligence is our ability to distance ourself from a situation and analyze it with detachment. This is an important part of our ability to adapt to rapid changes in our environment. The ability of someone to reason about their relationship to their environment is essential to intelligent behavior.

Now I’ve really tipped my hand. The romantic notion that has captured my imagination is the quest for emergent intelligent behavior or Artificial Intelligence as it is commonly called. I try to avoid the term Artificial Intelligence because I find that neither the word Artificial nor the word Intelligence lend themselves to unambiguous definition, much less objective measurement. In fact, many of the great debates in the field revolve around this shortcoming.

To be continued.