Chris Brauer Media Project [BLOG]

Caveat Emptor!! Let the buyer be very aware when they deal with the company Crucial. They are a big market player in portable media storage. I had heard pretty good things about them that led me to buy two Crucial Gizmo 2GB USB drives on the Web. Never again!! While one worked fine the other one came with a cap that wouldn't stay on. Contacted customer service and they insisted on sending a spare cap even though I told them that the cap from the other drive didn't stay on either despite it fitting fine on the other drive. Not surprisingly the new cap wouldn't stay on either. In contacting Crucial again I was informed that "Your cap issue is not covered by your warranty so we would not be able to replace this drive for you" and the fact that the goods arrived with a manufacturer defect in the plastic casing was not their responsibility.

In their words: "The warranty that you have with this module covers you for any drive defect that would stop the drive operating it does not cover any issue with the cap of the module." Oh OK. The manufacturer of the cap takes no responsibility for a defective cap. Genius. All this for a $20 USB drive. It's like this company has never heard of the Internet and that customers are not helpless in the face of gross injustice. Screw you Crucial. Hence this post.

Labels: business, computing

Recent articles in The Economist and Artificial Intelligence in Medicine got me thinking about the transformational potential of intelligent information systems on acts of discretion.

In The Economist, a segment entitled "AI am the law" explores the impact of "smart software" in use in Australia that predicts whether clients have winnable cases in court and assesses applicants likelihood of receiving legal aid. In tests to date the software simulations are accurate 98% of the time in predicting the actual outcomes.

"What the systems still lack is the ability to exercise discretion, and that is not likely to change for the foreseeable future," the author muses.

But these tasks seem ripe for automation, or machine migration. Why send someone through the cost and effort of an application process or court proceedings if the outcomes are so predictable as can be mapped beforehand for reference. The assumption is that the discretion previously used by the gatekeepers to legal aid and court dates was frivolous and surplus. All they were really doing was exercising their right to either pass someone into the process or exclude them. So the starting line for machines in the legal advice industry just got one step closer to the claimants. The discretionary task of passing people on to the next step is gone. Could this herald a threat to all human professions with a corresponding shrinkage in the definitions of when discretion is a necessary element of a decision process.

Sitting in a Holborn Street cafe with Milverton Wallace (if ever there was a man who needed a blog), one of the superstars of the British digerati, he shook his head mightily: "You're talking about any professional activity. Perhaps. Anything without discretion."

But is there a danger that as discretion becomes less prevalent, hunted wherever it lies by thirsty software entrepreneurs and business process re-engineering exercises, that it could face virtual extinction, no pun intended. A good management consultant can process map anything: "Tell me about what you do and how you do it?". The question frames the instrumental terms. Break it down for me baby! I'll draw the charts. Later the charts feed into tables that feed into objects and algorithms whirl. Poof! We found out that we can automate what you do. Surprised?

Lawyers are undoubtedly caught off-guard by the technological developments in their industry, susceptible to early adoption by virtue of the structured syntax and tasks that constitute the majority of their professional activity. These are very early days in the intelligent legal systems game, as it is for virtually every industry, so it is difficult to predict where the discretion line will be drawn in the sand. Anyone for a computer judge?

Regardless we are all familiar with that feeling we get when our fate seems to hang in the hands of another. When for that moment in time it seems as if all hangs on the outcome of the decision. Most can recite experiences with a subjectively villainous or empathetic policeman, parking attendant, secretary, customer, or other. "He really did me a favour!" or "I was like, why is he screwing me?" That's the smoking gun, or at least the puff of smoke that comes with discretion. And life is richer with some of it in play.

Think of the golfer who decides to play the aggressive shot from the bunker even though he knows he is 98% likely to either top or pluck the ball. Or the shopper who, rattled with indecision, decides to buy both pairs of shoes.

More seriously think of the value of "the ability or power to decide responsibly" or the "freedom to act or judge on one's own", both dictionary definitions of discretion. How will decisions on where to use systems that implicitly have no discretion be made? How will we know if conservation services are needed due to the imminent extinction of discretion in professional life. Surely no one is immune. How easy would it be to create the perfect CEO by developing working models from studying all of the decisions of previous successful CEOs? Like Deep Blue beat Kasparov so one day will CEO SIMULATOR X wag a virtual finger menacingly at a reticent Donald Trump: "Your numbers stink. You're fired!"

See this Media Project post for an Introduction to Artificial Intelligence

Labels: computing

Can we ever create a machine that is indistinguishable from a human? Discussions on this topic, already a classic 20th century philosophical and scientific polarizer, promises to be one of the most inspired debates of the 21st century.

The tools necessary to enter into a discourse on this subject at first appear daunting and plentiful. Knowledge of the cognitive sciences, logic theory, proof theory, mathematics and physics would be a good starting point. Follow that-up with an informed firm positioning on the nature/nature discussion, skillful application of formal theories of computation, comfort with design of functioning machines to implement formally specified computations, and knowledge of the philosophical foundations of asyntactic, representational view of the relation of mind to reality, embodied by for example Wittgenstein's Tractatus Logico-Philosophicus, and the opposed neuroscientist intuition that artificial intelligence can be created by modeling the brain, fuzzy logic neural nets working a process of computation not akin to formal deduction. Not stopping there, the social sciences will cry out for among others the inclusion of perspectives of epistemology (Foucault), Chomskian linguistics, and notions of refiguring the body that reject the subjugation of the body to a tool, or machine, at the disposal of consciousness.

Phew! While probing these philosophical avenues can be immensely rewarding they require a certain dedication of subject, an immersion into artificial intelligence as a field of study. This can be thought of more broadly as the study of the science of intelligence that has been a fascination of philosophers from Plato to Hobbes and Leibniz. But this daunting topic is actually accessible to anyone with a healthy curiosity about what makes us human.

The central question is whether mind and intelligence can be defined through a functionalist approach regarding mental processes as discreetly specifiable procedures and mental states as defined by their causal relations with sensory input, motor behavior and other mental states. In other words are our minds nothing more than sophisticated computers that can be simulated in machines? Can machines understand and have cognitive states because such understanding is actually a functional mental process that can be theoretically simulated.

Let's look at a couple of recent examples that have gained some notoriety. Perhaps the most famous example of man vs machine is the 1997 chess match between high-performance computer Deep Blue and reigning World Chess Champion Garry Kasparov. With a dramatic victory in Game 6 Deep Blue took the match 3.5-2.5 and afterwards Kasparov was quoted as saying the machine had "played like God" while its inventors at IBM downplayed there machine capabilities as being stunning at solving chess problems but "less intelligent than even the stupidest human".

So while they took completely different approaches to the game -- Kasparov evaluating two or three positions per second, Deep Blue looking at 200 million per second -- the matches were extremely competitive. And it raises the question of whether Deep Blue actually understands chess. While it primarily uses brute force to evaluate moves it has also been programmed with about 6,000 co-efficients (if-then statements like if your king is in check then protect it) as a kind of grandmaster rule book it is likely that Deep Blue could pass a Chess Turing Test by combining programmable rules with brute force computing.

In asking the question "Can Machines Think?" Alan Turing (Nazi codebreaker, creator of Turing Machines, et al) created an "imitation game" where an interrogator is connected to one person and one machine via a terminal with a soundproof wall in between so both counterparts cannot be seen. The task is to find out which is the machine and which is the human, only by asking questions to each. If the machine can fool the interrogator (the interrogator cannot accurately tell the difference), according to Turing it is intelligent. This test remains relevant in studies of artificial intelligence and The Loebner Prize is an ongoing formal instantiation of the Turing Test (TT) that promises a Gold Medal to any machine that 'passes' the test. None have come close so far but each year the respondents score higher and higher. And we can see by the previous example that as Kasparov felt he was playing God it is unlikely he would have been able to distinguish Deep Blue from a human opponent and thus the machine exhibited chess intelligence, indistinguishable from human chess intelligence.

And if you are just thinking to yourself, "yes, while that is chess, particularly suited to that kind of simulation", researchers in South Korea are working as this is written on robots that address the "essence" of man and have developed a series of artificial chromosomes that will allow robots to feel lusty, and could eventually lead to them reproducing out of a feeling of desire. The italics in the previous sentences are mine because the reality is that these robots are also just working out a combinations of rules and brute force in establishing emotions and feelings through computer code.

In Minds, Brains and Programs, a seminal essay in the field of artificial intelligence, John Searle discarded the Turing Test as a reliable method of assessing intelligence or cognitive understanding by creating an ingenious thought experiment, his Chinese Room analogy, in which an English speaker, knowing no Chinese, blindly follows a set of rules to always give the right answer in Chinese to questions posed in that language. Searle argues that the English speaker can clearly be shown not to understand Chinese even though an outside observer would not be able to differentiate between his responses and those of a fluent Chinese speaker. Hence the Chinese Room argument suggests that just passing a Turing Test does not show understanding and is thus not a good evaluator for artificial intelligence (technically Strong AI).

Few in the discussion of artificial intelligence will deny that it is likely that we will be able to create machines that can pass the Turing Test or even the Total Turing Test (TTT includes sight and thus includes robotics ... imagine the same experiment as the one described in the TT but this time remove the soundproof wall and also allow the interrogator to ask the subjects to physically act out as rerquested, playing golf for example and speaking about it afterwards).

So this extends the debate further into what additional (if any) qualities are part of the human mind. The most typically cited qualities are subjective rather than objective qualities, like free will and sentience as well as 'qualia' like the sound of Beethoven, the sound of waves crashing on a beach (those simulators never quite reproduce it), or the smell of home cooking. So while a machine might smell home cooking and identify it as home cooking, does it really understand what that means?

It is a debate that it unlikely to be resolved conclusively anytime soon. But it is of interest to all of us humans to recognize that as technology, robotics and computing advances so too will opportunities for artificial intelligence. Decide for yourself if there is to be any difference between man and machines and if so how will you tell the difference?

For those interested in further readings or information on more detailed concepts of artificial intelligence email me at blog at chrisbrauer.com. In the meantime the following represents a good starting point for anyone interested in introductory reading on the topic:

The Emperor's New Mind - Roger Penrose
The Philosophy of Artificial Intelligence - Ed. Margaret Boden (including Searle and Turing)
Views into the Chinese Room - Ed. John Preston and Mark Bishop

Labels: computing, science