# Framework for Assessing Ethical Aspects of Algorithms and Their Encompassing Socio-Technical System
## 4 Results
### Proposed Ethical Framework
#### 4.1.2 Non-Maleficence
For example, it should be clear under which circumstances humans are allowed to intervene or question the algorithm. **Deliberate misuse (misuse):**: To prevent deliberate misuse, sufficient security measures should be in place. **Underuse:**: To prevent underuse, it is important to get important stakeholders to see the importance of the algorithm. No Misuse Can Be Made of the Algorithm: Now and in the FutureAs mentioned before, the future may bring developments such as new technology, new data, or newly found security vulnerabilities that may provide new opportunities for misuse. Therefore, it is important to anticipate certain developments and to establish a protocol for regular re-evaluation. No Misuse Can Be Made of the Algorithm: Algorithm Is SecureAn important vulnerability of an algorithm is its data. Sensitive data may be attractive for exploitation by others, so it is important to secure the access to the data and to possibly anonymize or encrypt it. The threat not only comes from outside: also users of the algorithm may misuse the data (accidentally or not), hence it is important to provide access to only the data that they need and/or by logging access to data. Furthermore, the algorithm itself may be the target of misuse: people (from inside or outside) may, for example, attempt to replace the algorithm with an altered one. No Misuse Can Be Made of the Algorithm: Algorithm Will Be kept up to DateAs circumstances may change, in the organization or with the subjects of the algorithm, it is important to keep it up-to-date. First, the data itself needs to be kept up-to-date. Protocols for this purpose should be in place, such as a regular request to subjects of the algorithm to update their information. Incorrect data poses a risk that the algorithm produces incorrect results leading to incorrect decisions. Second, for a learning algorithm, it may need regular retraining with training data that supplements recent cases. In general, data quality and the algorithm's behavior should be monitored. Furthermore, all protocols and monitoring should be documented. Algorithm Is Developed by Skiful, Rational and Responsible PeopleDevelopers of an algorithm and the designers of the entire socio-technical system have a significant responsibility. They should be sufficiently skiful as to not make mistakes with, for example, security measures. They should also be rational to be able to make objectively justified decisions and to document these properly. They should also be responsible being aware of potential risks and threats and feeling a duty to prevent them. Defining a code of conduct may be desirable. Finally, thorough testing and validation should be standard. Standards and checklists for the development and use of algorithms have been or are being developed. It is of utmost importance that these are known and are applied. For example, many algorithms developed for diagnosis and prognosis of COVID-19 reviewed by (2020) were found to be not usable for clinical use, which their developers could have determined themselves if they would have used the CLAIM checklist (2020). Only professionals Can Access the Data Bound by Transparent Protocols  
Only professionals should be able to access data and only on a need-to basis, especially data in decrypted form and keys needed for decryption or coupling of data sources. The IEEE Global Initiative on Ethics of Autonomous and Intelligent System states that access should be granted on a case-by-case basis [45]. As a preventive measure, the group of people with the ability to access the full data should be kept to a minimum. Access permissions should be well-document as well as the protocols governing the provision of permissions. IEEE Global Initiative also recommends that a regulatory body oversees the entire process of using and maintaining algorithms [45].