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Record W4399171646 · doi:10.18260/1-2--46057

Sacrificing Safety in the Name of Innovation: the OceanGate Titan Disaster

2024· article· en· W4399171646 on OpenAlexaboutno aff
Daniel Marchant, Danny Marchant

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpace exploration and regulation
Canadian institutionsnot available
Fundersnot available
KeywordsTitan (rocket family)AstrobiologyComputer scienceComputer securityBusinessPhysics

Abstract

fetched live from OpenAlex

Abstract In 2023, the OceanGate Titan submersible embarked on a mission to visit the Titanic, ending in a catastrophic implosion and the loss of all five souls on board. Despite successful missions descending to the Titanic before, OceanGate and founder Stockton Rush repeatedly ignored warnings, had an insufficient pressure depth testing plan, oversimplified the submersible's design, and sacrificed safety in the name of innovation. Design choices such as a carbon fiber hull and oversimplified controls were chosen and made the company appear to be on the cutting edge of new maritime technology. However, these critical choices would end up being detrimental to the Titan's final voyage. While accident reports remain ongoing, early reports have shown that the most likely outcome of the Titan was the cracking of its hull, which had previously experienced problems and had not undergone a rigorous amount of testing, as should be required for an ocean floor expedition submarine. Final accident reports will likely further characterize how the lack of proper equipment and testing had decreased the Titan's chance of success. Regardless of the true catastrophic failure the Titan experienced, the company's ambitions to conquer the frontier of deep-sea exploration resulted in poor ethical standards. The Titan also serves as a modern parallel to the ship it was intent on exploring; the Titanic notoriously sank due to an iceberg, as the ship had been poorly tested in rough conditions. In the growing age of extreme adventures, OceanGate's lack of proper testing and overconfidence in its engineering resulted in a culture that was socially responsive to meet demand but lacking in social responsibility. Ethical standards must be established and enforced for start-ups who push the envelope in extreme environments to foster a spirit that emphasizes discovery while prioritizing safety. Additionally, countries must collaborate to ensure basic, proper regulations can be enforced in international spaces, such as the mid-Atlantic, to prevent more disasters at sea. The OceanGate disaster can be used as a valuable lesson to educate the future leaders of engineering. Cultural vitality and social responsiveness must come from the design of the technology itself rather than the dreams and ideas of one person. This shift encourages a collaborative engineering community during design and development to provide a diverse range of perspectives. Emerging leaders in technology must serve as role models for those who endeavor new technology and must demonstrate responsible and ethical engineering while still striving for innovation. Additionally, sound engineering choices benefit society as a whole. Had OceanGate not sunk, the American and Canadian coast guards would not have spent millions attempting to locate the submarine on the ocean floor. Another key influence the Titan sinking has had is the new perception of danger among the public about deep sea exploration, which has generally changed the public opinion to become opposed to important private company missions that could serve as a great benefit to science in the future. By learning from the OceanGate disaster, future society can benefit by producing and maintaining an ethical, educational, and inventive exploration industry, both at sea and beyond.

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.

How this classification was reachedexpand

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.016
GPT teacher head0.268
Teacher spread0.252 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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