# Framework for Assessing Ethical Aspects of Algorithms and Their Encompassing Socio-Technical System
## 4 Results
### Who the Stakeholders Are and How They Are Affected Is Clear
#### Algorithm Is Transparent  
According to the IEEE Global Initiative on Ethics of Autonomous and Intelligent System, transparency of an algorithm means that one should be able to determine how and why an algorithm came to a certain outcome, for example, why someone is considered a fraud risk [45]. There are three reasons why transparency is important according to the Dutch Ministry of Justice and Security: gaining trust, facilitating verification and help, and it can lead to improved adherence to rules and regulations.  
The field of 'Explainable AI' develops and studies methods and techniques for being able to explain the reasoning and outcomes of algorithms, notably learning algorithms. There are two main categories: post hoc explanation and transparency by design. The former takes the algorithm (mostly) as a black box whose and attempts to explain a certain outcome (local explanation) or full reasoning of the algorithm (global explanation). The latter provides for the development or learning of an algorithm whose reasoning is directly understandable (white box), which typically involves the loss of some accuracy compared to black box algorithms. [PERSON] shows in their book \"Thinking, Fast and Slow\" that humans are not good at making unbiased objective decisions and already very simple easily explainable algorithms such as weighing several independently assessed criteria can already significantly improve their decision making [48].  
Note that full transparency to all stakeholders may not be desirable. For example, knowing the full reasoning of a fraud detection algorithm may give fraudsters an undesirable opportunity to find ways to prevent detection. Transparency to some stakeholders is, however, important for verifying the correctness of the outcomes of the algorithm and whether or not it is biased is some way. Furthermore, not every part of the reasoning of an algorithm needs to be transparent; it may suffice that it is testable. As an analogy, we do not understand fully how the eye and brain allow humans to recognize objects and faces, yet we trust a witness when they have seen something or someone, because through test and time we know the reliability our visionary system. Additionally, the training process of a learning algorithm can often not be explained, because it is similarly ill-understood, but also here we trust it through rigorous testing and validation. The comparison with human learning, recognition and reasoning also makes clear that alternative solutions without the use of algorithms and based solely on humans are not fully transparent nor devoid of bias and error either. Therefore, one should not over-criticize algorithms, but strive for improvement of transparency and performance compared to a fully human-based solution. The Dutch Ministry of Justice and Security states that the focus of information provision should be on describing the goal of the algorithm, which criteria and rules the decision was based on, and the sources of data that are used including their quality and how they are combined [50].  
Transparency not only pertains to the algorithm itself, but also on the rest of the socio-technical system. The protocols, procedures, rules, and regulations should also be transparent. It should be clear who can access certain data, who is responsible and for what (for example, when a data breach occurs) and what should be done when something goes wrong. It is also advisable to have exit and change protocols and protocols for what to do when the algorithm produces unexpected outcomes. Note that a well-thought through and transparent design of the socio-technical system the algorithm is embedded in, can be very instrumental for its acceptance. It became very clear in our analysis of the SyRI case (see Section 5.1) that the public outcry was mostly directed not at the algorithm itself but at the flaws and intransparency of the rest of the socio-technical system.