ArticleScience and engineering ethics2020
The Boeing 737 MAX: Lessons for Engineering Ethics.
Article in Science and engineering ethics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- Explanations for failures in designed and evolved systems.PNAS nexus · 2025Article
- Application of component failure physics for the reliability assessment of an autonomous braking system.Scientific reports · 2024Article
- Employee Grievance Redressal and Corporate Ethics: Lessons from the Boeing 737-MAX Crashes.Science and engineering ethics · 2024Article
- Inpatient EHR User Experience and Hospital EHR Safety Performance.JAMA network open · 2023Article
- Exceeding the Ordinary: A Framework for Examining Teams Across the Extremeness Continuum and Its Impact on Future Research.Group & organization management · 2023Article
- Repentance as Rebuke: Betrayal and Moral Injury in Safety Engineering.Science and engineering ethics · 2022Article
- Sustained software development, not number of citations or journal choice, is indicative of accurate bioinformatic software.Genome biology · 2022Article
- AI bias: exploring discriminatory algorithmic decision-making models and the application of possible machine-centric solutions adapted from the pharmaceutical industry.AI and ethics · 2022Article
- From driverless dilemmas to more practical commonsense tests for automated vehicles.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The crash of two 737 MAX passenger aircraft in late 2018 and early 2019, and subsequent grounding of the entire fleet of 737 MAX jets, turned a global spotlight on Boeing's practices and culture. Explanations for the crashes include: design flaws within the MAX's new flight control software system designed to prevent stalls; internal pressure to keep pace with Boeing's chief competitor, Airbus; Boeing's lack of transparency about the new software; and the lack of adequate monitoring of Boeing by the FAA, especially during the certification of the MAX and following the first crash. While these and other factors have been the subject of numerous government reports and investigative journalism articles, little to date has been written on the ethical significance of the accidents, in particular the ethical responsibilities of the engineers at Boeing and the FAA involved in designing and certifying the MAX. Lessons learned from this case include the need to strengthen the voice of engineers within large organizations. There is also the need for greater involvement of professional engineering societies in ethics-related activities and for broader focus on moral courage in engineering ethics education.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.