Artificial Intelligence is well, artificial. It's all scripted and the robot simply follows a logic path. A scenario in I-Robot where the main character(Will Smith) fell into the water with another small kid. The robot rescued him instead of the kid because analysis worked out that he has a better chance of survival and in that kind of scenario, all AI with the same code/script/design will do the same thing. Human intelligences permit other outcome to such scenario even if we're given the odds of survival.

Self learning robot is still far from reality. Scientist claim they're able to make robot learn by themselves. I take another scenario. A self-learning robot picks up a cube, using sensor and determined it as a cube, what if I remove the programming that was placed inside of it's processor before activation to recognize cube? Well, the bot can take out the encycloped... oh wait, do they even know what a book is?

What's behind the scene that drives human intelligence is something eluded scientist. I don't believe we're anywhere near in developing it, let alone perfecting it. Robots and AI still need the creator, us(humans) to give them the power of thought. The infamous fictional Skynet can be a reality one day, it's dangerous to have too much intelligence(even artificial one) minus the proper amount of humanity backing it up.

A frequently mentioned reason for the likelihood of human-equivalent AI being created within decades rather than longer is the fact that affordable computing power is approaching most estimates of human brain processing power.

100 billion neurons firing at 200 Hz — this is a basic neurological fact. Yes, there are many additional shades of complexity, including dendritic spines, neurotransmitter concentrations, and so on. Still, all of these put together seem to change the estimated computational requirements by no more than 2-3 orders of magnitude.

I can tell that I am speaking with an ideologue when they are unaware of the facts mentioned above, are informed of them, but that information then has no impact whatsoever on their subjective probability estimates of human-equivalent AI being created in the next few decades. Many people seem to act as if computing power has no influence whatsoever.

In contrast, Ray Kurzweil, Hans Moravec, and some other advocates of strong AI have seemingly acted as if computing power is everything — that when we have human-equivalent computing power, we’ll immediately have human-equivalent AI. That is wrong too.

It is easy to take the middle path. Particularly when the notion of human-equivalent computing power being available is combined with neural data from extremely high-resolution brain scans (a brute force argument for the eventual plausibility of human-equivalent AI if there ever was one), critics begin to sound incredulous when they do not revise their probability estimates for AI whatsoever.

One particular confused me that has been making the rounds for decades is the notion that some fundamental breakthrough in computing would be necessary to implement human-equivalent AI. A digital computer can simulate any possible analog signal, as long as it has the computing power — the inverse is not true. This is proven thousands or millions of times daily as old VHS and other magnetic tapes are converted into the digital medium.

If I had a computer faster than most expert estimates of human brain computing power and an extremely high resolution scan of the human brain, the burden of proof would be on the critics to say why I couldn’t create a human-equivalent AI immediately. The objections here tend to circulate around dualism, mysticism, biology-worship, quantum mumbo-jumbo, etc.
Yet, if we had sufficiently high-resolution scanners, we could just copy the brain’s design without understanding it.