Module 4: Explainable AI (XAI)
LESSON 4.6: SITUATION AWARE EXPLAINABILITY (SAX)
In the scope of the AI4Gov project, our aim is to push the boundaries of XAI to cope with the challenges existing in business processes (BP) and to produce reliable and faithful explanations about decisions and outcomes of BP executions. Situation aware eXplainability (SAX) are evolutionary XAI techniques applied to BPs that aim at tackling the shortcomings of contemporary XAI techniques when applied to BPs as aforementioned. More specifically, a situation-aware eXplanation is a causal sound explanation that takes into account the process context in which the explanandum occurred, including relevant background knowledge, constraints, and goals. A situation-aware explanation can also help ensure that the explanation is relevant and informative to the user.
To understand this definition, let’s unfold it to its ingredients:
- Context in Explanation
Finding an adequate explanation requires, in many cases, understanding the situational conditions in which specific decisions were made during process enactments. Frequently, explanations cannot be derived from ``local'' inference (i.e., current undergoing task or decision in a business process) but require reasoning about situation-wide contextual conditions relevant to the current step as derived from some actions in the past. Context aims to make the explanation richer, including knowledge elements that were originally implicit or part of the surrounding system, yet affected the choices that have been made during process execution. - Sound Explanations
A sound explanation is an explanation that is both true and valid. The former dimension of being true means that the explanation accurately and faithfully represents the domain and the occurrences in that domain, implying that reliance on its insights and actions derived from it can be reliably projected onto the environment it is anticipated to explain. The latter dimension of being valid means that, intrinsically, its reasoning mechanism is guaranteed to ensure its output was logically derived from its premises. - Causal Sound Explanation
In addition to being sound, and to include contextual information, a situation-aware explanation should be causal. A causal sound explanation is an explanation that not only satisfies the criteria for sound explanation, but also provides an account of why the explanandum occurred. This includes the assurance that concluded explanations are entailed from the basic causal dependencies and temporal relationships that link between the different occurrences in the process domain. - Causal Dependency
We consider two occurrences as being causally dependent when the occurrence of the former is explaining WHY the latter has occurred. More concretely, per our view, being related in a way that manipulating the timely occurrence of the former also entails some changes in the timely occurrence of the latter, and not vice versa. - Temporal Relationship
A temporal relationship is just an order relationship of the time axis between any two events such that we can determine which precedes the other in time