From Quantum Computing to HCI

What is quantum computing?

At this point of time, we are still relying on digital computing, which basically run on this simple principle: “the bit is on, or the bit is off”. These bits will “grow” into larger forms or structures such as phrases, words, which can represent other type of information like sounds, animations. Although scientists and engineers are surely affording every possible effort to improve the computation densities of a regular personal computer, but it still cannot match a human’s brain. You may ask why?  

The human brain has about 100 billion neurons. With an estimated average of 1000 connections between each neuron and its neighbors, we have nearly 100 trillion connections, each capable of a simultaneous calculation. That's massive parallel processing capability, which is one of the most critical strengths of human thinking.

On the other hand, the weakness is the slow pace for neural circuitry for human beings, and it is about 200 calculations a second. However, with 100 trillion connections, each computing at 200 calculations a second per connection, we will get an unbelievable capacity. Moreover, we do not need to worry about running out of memory, as long as you are willing to spend time in rehearsing information, it will go to long-term memory, as we have around 100 trillion connections. 

Since neural net emulations benefit from both strands of the acceleration of computational power, this capacity will double every twelve months. Thus by the year 2020, it will have doubled about twenty-three times, resulting in a speed of about 20 million billion neural connection calculations per second, which is equal to the human brain. Besides the help from parallel processing, the memory is important as well. Nowadays, the memory circuits are doubling their capacities every 18 months.  

Collectively speaking, Implied by the Law of Accelerating Returns, the exponential growth of computing will prove that shortly in the future, machinery’s thinking power will surpass ours. (I refer to a regular personal computer, not supercomputer)

Different from digital computing, quantum computing has this “qu-bits”, which are zero or one in the meanwhile. The state of a particle will stay “ambivalent” until a process of disambiguation forces the particle to choose which position it should stand at. For example, a stream of photons are about to hit the lake surface at 45 degree. Each individual photon will have to determine whether to bounce off the surface at the same angle, or “dive” into the water. In other words, those photons are too “lazy” until the process pushes them to go on with only one path. The same principles apply to carbon-based neurons.

The series of qu-bits represents simultaneously every possible solution to the problem. For instance, a single qu-bit represents two possible solutions; two linked qu-bits represent four possible answers. A quantum computer with 1,000 qu-bits represents 2^1,000 (this is approximately equal to a decimal number consisting of 1, followed by 301 zeroes) possible solutions at the same time. 

Yes, it is fast, it is like a genius who can handle a complex math problem by counting for every possible combination. In that sense, it is a good tool for decoding encryption.  Dr. Nicolas Gisin found out the "communication" speed in-between a photon pair is way faster than the speed of light. But they are not communicating information; instead, they are passing each other a sort of randomness. If we can convert the randomness into information, we may be able to disentangle the photon pair. Nevertheless, this needs a lot of observations on those photons' decisions.

Do human beings have quantum computing inside brains?

Gödel's famous "incompleteness theorem" has been considered as the most important theorem in mathematics. A corollary of Gödel's theorem is that there are mathematical propositions that cannot be decided by an algorithm. In essence, these Gödelian impossible problems require an infinite number of steps to be solved. Dr. Roger Penrose conjects that machines cannot do what humans can do because machines can only follow an algorithm. An algorithm cannot solve a Gödelian unsolvable problem. But humans can. Hence, in this regard, humans are more advanced. Penrose also suggest that human beings’ consciousness comes from quantum computing and quantum de-coherence. 

Well, there is something inaccurate with Penrose’s conjecture: first, human being can only estimate, yet estimation is not equivalent to knocking down the problem; second, if we own quantum computing capability, currently we do not have it outside ourselves yet, and then how come we know a machine cannot solve Gödelian impossible problems? Plus, if a computing task requires an incredible amount of calculations, the quantum computing may still die under certain circumstances. 

But if a human brain indeed displays quantum computing ability, that means this technique is feasible, thus we need to dig out the mechanism that nurture this special treat, and hopefully “feed” it into another piece of hardware. That is why scientists are busy with inventing high-resolution scanning technology such as Magnetic Resonance Imaging. 

Collectively speaking, we do not know much about our brain, not even a little. We carry such a huge potential that we even dare to imagine; that being said, conducting “Reserve Engineering” on our brain is a possible means to understand those God-given abilities and apply those to machinery.

What is the implication for HCI?

Will quantum computing change the way we write the code? Will it change the way we design the interface?  Are we still having browsers? …

On the other hand, What if a machine can have emotion and personality at that time? They may have “a user experience” based on the feedback that human give. Perhaps they are intelligent enough to figure out whether design can convey a good usability for humans, as they have perception then… Lol, those are just some random thoughts. 

The thing is that quantum computers may only be used to tackle a certain kind of problem that is intractable; the power they carry does not apply across the board. BUT what I am more interested is that: during the process of studying our brain (partially driven by quantum computing), how do the outcomes affect the manner we deploy more or less profound design mechanisms to take full advantage of human thinking capability. Perhaps by the time we get this thing run, out neuron-cognitive structure will change due to computational development rather than biological evolution. I mean, thinking about it, interacting with an agent that is far more intelligent than our brains, should we get better fit by not thinking about hard questions from then on? I don’t know.

Reference:

Kurzweil, R. (1999). The age of spiritual machines: When computers exceed human intelligence. New York: Viking.