This question is a duplicate of this one with a stronger operationalization for artificial general intelligence, and including robotic capabilities. I will copy relevant parts of that question to this one.
Since the inception of the field, the goal of Artificial Intelligence (AI) research has been to develop a machine-based system that can perform the same general-purpose reasoning and problem-solving tasks humans can. While computers have surpassed humans in many information-processing abilities, this "general" intelligence has remained elusive.
AI, and particularly machine learning (ML), is advancing rapidly, with previously human-specific tasks such as image and speech recognition, translation and even driving, now being successfully tackled by narrow AI systems.
But there is a stunning diversity of opinion about when general AI may arrive, according to published expert surveys. For example this study finds 50% of AI researchers accord a 50% probability to "High level machine intelligence" (HLMI) by 2040, while 20% say that 50% probability will not be reached until 2100 or later. Similarly, this survey finds an aggregated probability distribution with a 25%-75% confidence interval (comparable to Metaculus sliders below) ranging from 2040 to well past 2100.
It would be nice to tighten these probability intervals considerably, so we ask of the Metaculus community:
When will the first [strong and robotic] AGI be first developed and demonstrated?
We will thus define "an artificial general intelligence" as a single unified software system that can satisfy the following criteria, all completable by at least some humans.
Able to reliably pass a Turing test of the type that would win the Loebner Gold Prize. The gold prize is reserved for, "the first bot that can pass an extended Turing Test involving textual, visual, and auditory components."
Has general robotic capabilities, of the type able to autonomously, when equipped with appropriate actuators, satisfactorily assemble a (or the equivalent of a) circa-2020 de Agostini 1:8 scale automobile model.
High competency at a diverse fields of expertise, as measured by achieving at least 75% accuracy in every task and 90% mean accuracy across all tasks in the Q&A dataset developed by Dan Hendrycks et al..
Be able to take a simple text description and turn it into a program coded in C/Python. In particular, we'll ask that in at least 9 out of 10 trials, the system can take the specification of a simple program from a list comparable to the "intermediate" section of this one, and output an executable C or Python code that does the assigned task.
By "unified" we mean that the system is integrated enough that it can, for example, explain its reasoning on a Q&A task, or verbally report its progress and identify objects during model assembly. (This is not really meant to be an additional capability of "introspection" so much as a provision that the system not simply be cobbled together as a set of sub-systems specialized to tasks like the above, but rather a single system applicable to many problems.)
Resolution will be by direct demonstration of such a system achieving the above criteria, or by confident credible statement by its developers that an existing system is able to satisfy these criteria. In case of contention as to whether a given system satisfies the resolution criteria, a ruling will be made by a majority vote of the question author and two AI experts chosen in good faith by him. Resolution date will be the first date at which the system (subsequently judged to satisfy the criteria) and its capabilities are publicly described in a talk, press release, paper, or other report available to the general public.
(Edited 2020-10-15 to strengthen programming task and weaken construction task.)