Provable AI Ethics and Explainability in Medical and Educational AI Agents: Trustworthy Ethical Firewall
Round 1
Reviewer 1 Report
Comments and Suggestions for Authors
This article tried to explain that should be a Provable AI Ethics and Explainability in Next-Generation Med-2 ical and Educational AI agents: Trustworthy Ethical Firewall.
AI area is new in medicine end AI ethics is a concept that is after first step – ethics in AI medical use is proven. The author tried very easy to to propose a novel conceptual framework—termed the Ethi-80 cal Firewall Architecture—that embeds mathematically provable ethical constraints di-81 rectly into the core decision-making processes of high-stakes AI systems in medicine and 82 education. By integrating formal verification methods, cryptographic immutability, and 83 emotion-analogous escalation protocols, the framework is designed to ensure that AI sys-84 tems operate in a transparent, auditable, and inherently safe manner.
But this aspect should be used every where when AI is USED.
The ethics in Medicine is an old concept, that why GCP (good clinical practice) already statutes this. GCP is not remembered in this area, and HELSINKI Declaration is forgot.
The author should remember about these classical aspects in his/her article.
In the same time, we know already about INFORM CONSENT, this is other aspect very important in ethics.
All rationales that are attributed to a AI Machine in the area of ethics are made using some human algorithms after some PROFESSIONAL SOCIETIES in Endocrinology, Orthopedics etc . That is the main reason – AI machine is already a concept used after an INFORM CONSENT IS SIGNED, and in mathematics/algorithms the place of ethic is strange.
The methodology is adequate and well expressed. But the rationale is weak.
The rationale of AI ethics is weak, sorry.
The references are carefully chosen, from impact journals. They are updated, from the last 5-8 years, in the area of AI and ethic.
They constitute a real support for the text of the article.
Figures and tables are very easy to understand, presenting a rational of ethics of AI inside of AI. But real, ethics should be BEFORE AI.
Comments on the Quality of English Languagea good English to read
Author Response
Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsDear author,
Thank you for allowing me to read your paper. Here are my thoughts:
The introduction provides a good starting point but could enhance its depth by including more detailed background information and relevant references to better situate the study.
The research design seems to effectively target the study's objectives, particularly in its examination of the Ethical Firewall within AI applications.
I think you could improve the methods section with more thorough descriptions to clarify the processes used, particularly regarding the Ethical Firewall architecture. This would make it easier for others to replicate the study.
I think the results could be presented in a clearer manner, possibly by incorporating more explicit charts or data to strengthen the arguments and facilitate understanding.
The conclusions align well with the results and reflect the study's initial goals.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThe article sounds very promising when it states that it “shifts from post hoc explainability to architecturally enforced morality”. The introduction, however, needs to provide more details on how this is achieved in practice.
The first mention of “Ethical Firewall Architecture” leaves it unclear whether it is the proposed approach or an existing approach. The use of the verb “centers” is confusing.
What are the “emotion-analogous escalation protocols”? What are the mathematically provable ethical constraints? Explain in the first use of such terms, by giving examples. Bring a brief version of 2.3 earlier in the introduction.
A paragraph that clearly states the contributions of the paper is missing after the definition of the paper's goals.
Ethical principles like “do no harm” are oversimplified. They often require deeper interpretations since they may depend on subjective factors and ethical trade-offs (see for example the trolley problem in autonomous vehicles). While deontic logic provides useful tools for encoding rules, it still has limitations in handling such dilemmas. Such restrictions must be mentioned.
Such ideas are extremely ambitious since formal verification techniques are challenged by complex, real-world scenarios with uncertainty and unpredictable behaviors.
The immutability of ethical proofs is a good step towards responsible AI, but cannot solve the aforementioned issues.
Applying SCMs in real-world problems is challenging, and needs to adapt to evolving data patterns and scale up. The scalability of causal reasoning within AI systems creates additional obstacles. See Felin & Holweg (2024)
Felin, T., & Holweg, M. (2024). Theory is all you need: AI, human cognition, and causal reasoning. Strategy Science, 9(4), 346-371.
Also check the following articles on bias detection and mitigation:
Sarridis, I., Koutlis, C., Papadopoulos, S., & Diou, C. (2023, September). Towards fair face verification: An in-depth analysis of demographic biases. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases (pp. 194-208). Cham: Springer Nature Switzerland.
The visualization of Figure 1 is very helpful and represents the approach well. There is an error in Figure 1 in the description of Layer 2: The formal ethical specification is mentioned twice and the Cryptographically immutable ethical core is missing.
What is missing from section 2 are a few more details on how the proposed approach can be applied to actual real-world problems, using specific examples of tasks and solutions, that will make the approach more specific and realistic.
Figure 2, although a bit more graphical than necessary, well displays the proposed solution paths. However, it is not clear how the proposed solution, which includes human reviewers, can scale up to the myriads of solutions and decisions that are developed on a monthly basis. This cognitive limitation is stated but no solutions are discussed.
Apart from the shiny graphic, Figure 3 does not bring something new to the field.
There is a subsection missing in section 4 that explains how the EFA architecture components guarantee the three core components of trustworthy AI.
The example mentioned in 4.5 is interesting and could be used as a motivating and driving example from the beginning to the end of the paper.
My overall comment is that the manuscript presents an approach without performing a literature review on existing frameworks and without a case study that would facilitate the precise description of the framework parameters. As a result the approach remains very high level ignoring implementation challenges.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsA good article, improved after review - ers observations.
Improved, readable and a step forward for the science.
We have a contribution in this area that could be mentioned - if the authors consider, ofcourse. https://doi.org/10.3390/healthcare12151502
Author Response
Thank you, we hwve referenced the paper on the lines 91-93
Recent studies have demonstrated the impact of structured ethical frameworks on enhancing the safety and transparency of healthcare AI systems.
Reviewer 3 Report
Comments and Suggestions for AuthorsThe authors have significantly revised the manuscript and improved it a lot. They also answered all my comments.
Given the limitations of the approach that have been highlighted in this revised version, I would suggest the authors slightly revise the newly added sentence in section 1.2 to include the limits of the proposed approach.
"In this paper, a novel framework is proposed, the Ethical Firewall Architecture, which is designed to guarantee that every decision made by an AI is accompanied by an irrefutable, verifiable proof of ethical compliance. This architecture represents the original contribution to the field of AI ethics."
Author Response
Thank you, I have revised the sentence as recommended. Here is a revised version in Section 1.2 that incorporates the limitations of the proposed approach:
"In this paper, a novel framework is proposed, the Ethical Firewall Architecture, which is designed to guarantee that every decision made by an AI is accompanied by an irrefutable, verifiable proof of ethical compliance, while acknowledging that such guarantees are contingent on the framework's ability to address real-world complexities, including scalability, emergent value conflicts, and the inherent limitations of formal verification techniques."
