MétaCan
Menu
Back to cohort
Record W4380083100 · doi:10.1016/j.techum.2023.05.004

Re-creating the world - On necessary features for the creation of AGI

2023· article· en· W4380083100 on OpenAlex
Oliver Li

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNew Techno Humanities · 2023
Typearticle
Languageen
FieldComputer Science
TopicComputability, Logic, AI Algorithms
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsConsciousnessReflexivityAnthropocentrismEpistemologyRelevance (law)Cognitive scienceRealization (probability)Computer scienceRelation (database)Artificial general intelligenceArtificial intelligencePsychologySociologyPhilosophyEnvironmental ethicsMathematicsPolitical scienceSocial science

Abstract

fetched live from OpenAlex

In this paper I identify and discuss a number of features that I argue are necessary for the realization of AGI. As a preliminary step, common definitions of AGI are presented in respect to their understanding of mind, intelligence, and consciousness. I show that, despite the amazing performance of artificial systems, at present they are still far from exhibiting AGI, and I identify some of their central short-comings. Secondly, inspired by research within the philosophy of mind, embodiment and situatedness, I suggest a number of features that I deem necessary for a mind. I then investigate the possible objection against the relevance of these features namely that they are overly anthropocentric or biocentric. I further discuss aspects of these features in relation to their transfer to artificial systems with the goal of creating an artificial mind. I finally conclude that self-reflexivity and the re-creation of the world as an inner world should be strongly focused upon if one wishes to create an artificial mind or artificial consciousness. However, I also issue a warning about some well-known risks when creating AGI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.895
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.293
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it