Evidence map›Paper›PMID 40069265›Full record

ArticleScientific reports2025

Navigating artificial general intelligence development: societal, technological, ethical, and brain-inspired pathways.

Raghu Raman, Robin Kowalski, Krishnashree Achuthan, Akshay Iyer, Prema Nedungadi

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Artificial Intelligence Across the Drug Development Lifecycle.Medical sciences (Basel, Switzerland) · 2026
    Review
  4. Article
  5. Article
  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Raghu RamanAmrita School of Business, Amrita Vishwa Vidyapeetham, Amritapuri, Amritapuri, Kerala, 690525, India. raghu@amrita.edu.
Robin KowalskiCollege of Behavioral, Social and Health Sciences, Clemson University, Clemson, SC, 29634, USA.
Krishnashree AchuthanCenter for Cybersecurity Systems and Networks, Amrita Vishwa Vidyapeetham, Amritapuri, Amritapuri, Kerala, 690525, India.
Akshay IyerDepartment of Microbiology and Immunology, University of Miami, Miller School of Medicine, Miami, FL, 33136, USA.
Prema NedungadiAmrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, Amritapuri, Kerala, 690525, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examines the imperative to align artificial general intelligence (AGI) development with societal, technological, ethical, and brain-inspired pathways to ensure its responsible integration into human systems. Using the PRISMA framework and BERTopic modeling, it identifies five key pathways shaping AGI's trajectory: (1) societal integration, addressing AGI's broader societal impacts, public adoption, and policy considerations; (2) technological advancement, exploring real-world applications, implementation challenges, and scalability; (3) explainability, enhancing transparency, trust, and interpretability in AGI decision-making; (4) cognitive and ethical considerations, linking AGI's evolving architectures to ethical frameworks, accountability, and societal consequences; and (5) brain-inspired systems, leveraging human neural models to improve AGI's learning efficiency, adaptability, and reasoning capabilities. This study makes a unique contribution by systematically uncovering underexplored AGI themes, proposing a conceptual framework that connects AI advancements to practical applications, and addressing the multifaceted technical, ethical, and societal challenges of AGI development. The findings call for interdisciplinary collaboration to bridge critical gaps in transparency, governance, and societal alignment while proposing strategies for equitable access, workforce adaptation, and sustainable integration. Additionally, the study highlights emerging research frontiers, such as AGI-consciousness interfaces and collective intelligence systems, offering new pathways to integrate AGI into human-centered applications. By synthesizing insights across disciplines, this study provides a comprehensive roadmap for guiding AGI development in ways that balance technological innovation with ethical and societal responsibilities, advancing societal progress and well-being.

Indexed as

Artificial IntelligenceBrainDecision MakingHumansArtificial general intelligenceBrain inspiredEthical AIEthicsHuman-like AIResponsible AIStrong AISuperintelligenceTopic modelingWeak AI

Identifiers

PMID40069265
PMCPMC11897388

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.