Ancient dreams of intelligent machines: 3,000 years of robots
nature.com
nature.com
The authors interchangeably use robots, automata, AI (meaning AGI, I am guessing) — that makes for a confusing read. If they mean AGI, then nothing about how humans dealt with robots will likely prepare us for how to deal with an exponentially fast learning, super smart, intelligence. I would argue that learning from history would be anchoring ourselves to wrong ideas (ideas of incrementalism). To prepare for AGI, we need to think quite differently and radically, in some sense.
Note that Hero is credited, and the date is 10-70 AD, but Hero's contribution was to posit the mechanism by which the theatre worked, which was first described by Philon of Byzantium in the late third century BC! [Source: My thesis, submission deadline 28 September 2018 ;)]
Born too early to explore space
But born just in time to explore the consequences of strong AI!
There's nothing to suggest we know how to create strong AI, or that we will have any idea any time soon. It will most probably take several human generations before we can even get close to anything resembling human intelligence implemented in software or hardware.
Dog-level general AIs barking around?
Dogs have complex social hierarchies and social behaviour, a wide range of emotional responses, they communicate, participate in group tactical hunting activities requiring planning and executing coordinated attacks, they exhibit sexual behaviour, they can learn to respond to audible and visual commands. They are also vastly more agile than the Boston dynamics robots, able to climb three dimensional environments, jump through gaps and swim, and they can practice and independently choose to learn to do these things entirely autonomously.
If that bar was hyperbole, then someone please give me the non-hyperbole version. I honestly don't know what level of detail of such plan people expect to be common knowledge in the imminence of its first success.
>Today, more people die from obesity than from starvation (http://www.ynharari.com/book/homo-deus/)
Also trying to copy mechanisms from the human brain is being done with some success by DeepMind. We are not quite up to running a decent brain simulation yet though.
None of our current or projected theoretical scanning technologies are up to the task. We could capture the state of a dead brain, but that won't get us anywhere, for obvious reasons. Hypothetical invasive techniques would kill the patient long before sufficient data could be collected. Hand-wavey 'nano-probe' solutions are sometimes suggested, but again we have no idea how to design or build such things, and in reality we'd need to capture complete instantaneous snapshot data from every part of every cell of a brain to do it, which is absurd. It's no more valid than star trek technobabble.
That is a question lifted straight from the playbook of the Singularity Institute (MIRI, nowadays) and the like - "we will not know strong AI until it is upon us! We must act now!".
I can tell you what I'd consider a "signal" that strong AI is, well, not imminent but forthcoming: research into actually creating strong AI.
Currently, there is no such research to speak of, not at a practical level. For example, the majority of machine learning scientists are competing to see who can create the best-tuned classifier to solve this or that machine learning dataset. They are not even trying to, say, combine different classifiers into a system that can perform multiple classification tasks, let alone a system that can do that and reason about the objects it's able to classify, etc. All modern AI is as far from general intelligence as it can possibly be.
Without any research focus on strong AI, how is it going to come by? The Singularitarians believe (emphasis on "believe") that it's just going to happen by accident, presumably when some unsuspecting graduate student serendipitously mixes together into just the right kind of deep neural net architecture just the right amount of data and just the right set of hyperparameters.
It is plain to see that this is a fantasy grounded in pipe smoke and wishful thinking and not in any way, shape or form a realistic expectation to hold.
There's the advance of hardware such that it may be possible to run a simulation of a human brain for example. Also as hardware reaches human levels, things like self driving cars start working which leads lots of bright researchers to pile into AI which leads to advances in the algorithms. That stuff is happening now, not in several human generations.
Of course, the Agile Manifesto says you can develop systems without having a requirements specification or detailed design beforehand, but it also says that questions about when it will be done are off-topic.