As algorithms push humans out of the job market, wealth and power might become concentrated in the hands of the tiny elite that owns the all-powerful algorithms, creating unprecedented social and political inequality. Alternatively, the algorithms might themselves become the owners.
Yuval Noah Harari
These algorithms, which I'll call public relevance algorithms, are-by the very same mathematical procedures-producing and certifying knowledge. The algorithmic assessment of information, then, represents a particular knowledge logic, one built on specific presumptions about what knowledge is and how one should identify its most relevant components. That we are now turning to algorithms to identify what we need to know is as momentous as having relied on credentialed experts, the scientific method, common sense, or the word of God.
It's difficult to make your clients understand that there are certain days that the market will go up or down 2%, and it's basically driven by algorithms talking to algorithms. There's no real rhyme or reason for that. So it's difficult. We just try to preach long-term investing and staying the course.
Netflix will know everything. Netflix will know when a person stops watching it. They have all of their algorithms and will know that this person watched five minutes of a show and then stopped. They can tell by the behavior and the time of day that they are going to come back to it, based on their history.
We have a lot of argument about laws but none of it solves the problem. Let's examine what happened, why did we miss the Tsarnaev brothers, why did we miss the San Bernardino couple? It wasn't because we had stopped collected metadata it was because, I think, as someone who comes from the technology world, we were using the wrong algorithms.
We do know that we can set certain algorithms for machines to do certain things - now that may be a simple task. A factory robot that moves one object from here to there. That's a very simple top-down solution. But when we start creating machines that learn for themselves, that is a whole new area that we've never been in before.
Leibniz endeavored to provide an account of inference and judgment involving the mechanical play of symbols and very little else. The checklists that result are the first of humanity's intellectual artifacts. They express, they explain, and so they ratify a power of the mind. And, of course, they are artifacts in the process of becoming algorithms.
As a digital technology writer, I have had more than one former student and colleague tell me about digital switchers they have serviced through which calls and data are diverted to government servers or the big data algorithms they've written to be used on our e-mails by intelligence agencies.
Facebook has become the richest and most powerful publisher in history by replacing editors with algorithms - shattering the public square into millions of personalised news feeds, shifting entire societies away from the open terrain of genuine debate and argument while they make billions from our valued attention.
In 2010, the iPhone was only three years old, and many people still didn't see smartphones as the indispensable digital appendages they are today. Seven years later, virtually everything we do causes us to bleed digital information, putting us at the mercy of invisible algorithms that threaten to consume our freedom.
AI does not keep me up at night. Almost no one is working on conscious machines. Deep learning algorithms, or Google search, or Facebook personalization, or Siri or self driving cars or Watson, those have the same relationship to conscious machines as a toaster does to a chess-playing computer.
Fantasy sports went a long way toward developing the sabermetrics formulas used not only by oddsmakers but general managers in hiring players. So the amateur fantasists ended up creating some of the algorithms that Oakland GM Billy Bean's statisticians used to win games with less salary money available for star players.
The classes of problems which are respectively known and not known to have good algorithms are of great theoretical interest. [...] I conjecture that there is no good algorithm for the traveling salesman problem. My reasons are the same as for any mathematical conjecture: (1) It is a legitimate mathematical possibility, and (2) I do not know.
Many [business] people focus on what is static, black and white. Yet great algorithms can be rewritten. A business process can be defined better. A business model can be copied. But the speed of execution is dynamic within you and can never be copied. When you have an idea, figure out the pieces you need quickly, go to market, believe in it, and continue to iterate.
Beauty is more important in computing than anywhere else in technology because software is so complicated. Beauty is the ultimate defense against complexity. ... The geniuses of the computer field, on the the other hand, are the people with the keenest aesthetic senses, the ones who are capable of creating beauty. Beauty is decisive at every level: the most important interfaces, the most important programming languages, the winning algorithms are the beautiful ones.
Enchanting is not the word that would immediately spring to mind when describing a play that deals with fractal geometry, iterated algorithms, chaos theory and the second law of thermodynamics, but it is a perfect fit for Tom Stoppard's astonishing 1993 play, which is as beautiful as it is brilliant. This is one Stoppard drama that you don't have to be Einstein to understand -- you can feel it as well as think it. (...) Breathtaking, exhilarating and deeply satisfying.
And, in the future, while the dumb show of bohemianism plays itself out in the cookie cutter shape of the politically correct martyr/victim, aesthetic terrorists will not involve themselves in the dubious rewards of celebrity. The best of them will work alone, already a part of the enemy camp, and in chameleon-like style master the fifth-column algorithms to subvert the ancient regime. We won't know them by their name but their compensation will be to affect the outcome of the planet. Until then, there's a lot of work to be done.
A fashionable idea in technical circles is that quantity not only turns into quality at some extreme of scale, but also does so according to principles we already understand. Some of my colleagues think a million, or perhaps a billion, fragmentary insults will eventually yield wisdom that surpasses that of any well-thought-out essay, so long as sophisticated secret statistical algorithms recombine the fragments. I disagree. A trope from the early days of computer science comes to mind: garbage in, garbage out.
Human intellectual progress, such as it has been, results from our long struggle to see things 'as they are,' or in the most universally comprehensible way, and not as projections of our own emotions. Thunder is not a tantrum in the sky, disease is not a divine punishment, and not every death or accident results from witchcraft. What we call the Enlightenment and hold on to only tenuously, by our fingernails, is the slow-dawning understanding that the world is unfolding according to its own inner algorithms of cause and effect, probability and chance, without any regard for human feelings.
Human intellectual progress, such as it has been, results from our long struggle to see things 'as they are, ' or in the most universally comprehensible way, and not as projections of our own emotions. Thunder is not a tantrum in the sky, disease is not a divine punishment, and not every death or accident results from witchcraft. What we call the Enlightenment and hold on to only tenuously, by our fingernails, is the slow-dawning understanding that the world is unfolding according to its own inner algorithms of cause and effect, probability and chance, without any regard for human feelings.
The TMS is evolving into a logistics platform that can handle all nodes, all geographies and all transportation nodes. It's already talking to other applications in the supply chain, like warehouse management, order management and ERP systems. By adding underlying algorithms, a TMS can now understand the relationship between the cost of inventory and the cost of transportation and come up with an optimal solution to answer those questions.
Imagine for a moment that we are nothing but the product of billions of years of molecules coming together and ratcheting up through natural selection, that we are composed only of highways of fluids and chemicals sliding along roadways within billions of dancing cells, that trillions of synaptic conversations hum in parallel, that this vast egglike fabric of micron-thin circuitry runs algorithms undreamt of in modern science, and that these neural programs give rise to our decision making, loves, desires, fears, and aspirations. To me, that understanding would be a numinous experience, better than anything ever proposed in anyone's holy text.
It is raining DNA outside. On the bank of the Oxford canal at the bottom of my garden is a large willow tree, and it is pumping downy seeds into the air. ... spreading DNA whose coded characters spell out specific instructions for building willow trees that will shed a new generation of downy seeds. ... It is raining instructions out there; it's raining programs; it's raining tree-growing, fluff-spreading, algorithms. That is not a metaphor, it is the plain truth. It couldn't be any plainer if it were raining floppy discs.
New technologies, be it the printed encyclopedia or Wikipedia, are not abstract machines that independently render us stupid or smart. As we saw with Enlightenment reading technologies, knowledge emerges out of complex processes of selection, distinction, and judgment-out of the irreducible interactions of humans and technology. We should resist the false promise that the empty box below the Google logo has come to represent-either unmediated access to pure knowledge or a life of distraction and shallow information. It is a ruse. Knowledge is hard won; it is crafted, created, and organized by humans and their technologies. Google's search algorithms are only the most recent in a long history of technologies that humans have developed to organize, evaluate, and engage their world.
Evolution has no foresight. Complex machinery develops its own agendas. Brains - cheat. Feedback loops evolve to promote stable heartbeats and then stumble upon the temptation of rhythm and music. The rush evoked by fractal imagery, the algorithms used for habitat selection, metastasize into art. Thrills that once had to be earned in increments of fitness can now be had from pointless introspection. Aesthetics rise unbidden from a trillion dopamine receptors, and the system moves beyond modeling the organism. It begins to model the very process of modeling. It consumes evermore computational resources, bogs itself down with endless recursion and irrelevant simulations. Like the parasitic DNA that accretes in every natural genome, it persists and proliferates and produces nothing but itself. Metaprocesses bloom like cancer, and awaken, and call themselves I.
But the Turing test cuts both ways. You can't tell if a machine has gotten smarter or if you've just lowered your own standards of intelligence to such a degree that the machine seems smart. If you can have a conversation with a simulated person presented by an AI program, can you tell how far you've let your sense of personhood degrade in order to make the illusion work for you? People degrade themselves in order to make machines seem smart all the time. Before the crash, bankers believed in supposedly intelligent algorithms that could calculate credit risks before making bad loans. We ask teachers to teach to standardized tests so a student will look good to an algorithm. We have repeatedly demonstrated our species' bottomless ability to lower our standards to make information technology look good. Every instance of intelligence in a machine is ambiguous. The same ambiguity that motivated dubious academic AI projects in the past has been repackaged as mass culture today. Did that search engine really know what you want, or are you playing along, lowering your standards to make it seem clever? While it's to be expected that the human perspective will be changed by encounters with profound new technologies, the exercise of treating machine intelligence as real requires people to reduce their mooring to reality.
The theory of phlogiston was an inversion of the true nature of combustion. Removing phlogiston was in reality adding oxygen, while adding phlogiston was actually removing oxygen. The theory was a total misrepresentation of reality. Phlogiston did not even exist, and yet its existence was firmly believed and the theory adhered to rigidly for nearly one hundred years throughout the eighteenth century... As experimentation continued the properties of phlogiston became more bizarre and contradictory. But instead of questioning the existence of this mysterious substance it was made to serve more comprehensive purposes... For the skeptic or indeed to anyone prepared to step out of the circle of Darwinian belief, it is not hard to find inversions of common sense in modern evolutionary thought which are strikingly reminiscent of the mental gymnastics of the phlogiston chemists or the medieval astronomers. To the skeptic, the proposition that the genetic programmes of higher organisms, consisting of something close to a thousand million bits of information, equivalent to the sequence of letters in a small library of one thousand volumes, containing in encoded form countless thousands of intricate algorithms controlling, specifying and ordering the growth and development of billions and billions of cells into the form of a complex organism, were composed by a purely random process is simply an affront to reason. But to the Darwinist the idea is accepted without a ripple of doubt - the paradigm takes precedence!