Foreword: This post was originally submitted to Lab42 as part of an essay competition. The word count was limited to ~2,500 so there is a substantial amount of information that I have neglected to include. I did not win, so I decided to share it with you all today. Enjoy!

(Briefly) Defining Intelligence

Before attempting to approach (what I’d consider) the fundamental principles of developing human-level artificial intelligence, the term ‘intelligence’ itself must be defined. For the purpose of this essay, and to establish a shared vocabulary, I would like to consider intelligence as “the ability to recognise the significance of acquired information or skills via experience and exposure, in addition to the context it may be applied in”. By this standard, intelligence is not limited to biological systems such as the human brain, nor does it require sentience or an ability to experience qualia. I state this due to the nature of computational theory of mind (when applied to Turing-completeness), implying that an artificial intelligence which imitates human cognition to a highly convincing degree is plausible.

Solving The Alignment Problem

Intuitively, the first and foremost measure to take when considering the development of human-level artificial intelligence should be attempting to solve the alignment problem. Though I do not have a solution, I will provide guiding suggestions and core principles to consider during the creation of such a technology. There are several reasons why alignment is a fundamental issue to tackle; namely to minimise training data bias. A notable example of bias within datasets may be presented as certain ethnicities or races representing a larger demographic of those receiving jail sentences with disregards towards additional context (e.g. judges are more likely to give harsher sentences when their football team loses^[1]). This results in complications by either increasing the likelihood of erroneous predictions or actions, however, as long as bias and inaccuracies can be reduced (and tailored to align with human values) in the lead up to the development of human-level artificial intelligence, then more focus and resources can be shifted to other issues such as preventing black boxes within self-improving AI systems.

Should an artificial intelligence demonstrate itself to be equally intelligent as humans, it has likely already surpassed th...

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