# Computational Accountability in MAS Organizations with ADOPT
## 3 Computational Accountability in Organizational Settings  
Different research communities have dealt with the topic of accountability, such as [28; 29; 30; 31; 32; 33; 34; 35; 36]. While its main features remain relatively static, definitions vary in approach, scope and understanding in different communities. The cause of such variability lies with its socio-cultural nature and is one of the main reasons for the lack of a comprehensive support for the realization of accountability frameworks in current socio-technical systems. Accountability's most general definition refers to the assumption of responsibility for decisions and actions that a principal, individual or organization has towards another party. In other words, principals must account for their behavior to another when put under examination. The concept is inherently social, and provides a mechanism by which entities constrain one another's behavior [17]. The previously cited examination is usually carried out by an investigative entity, a forum of auditors [37; 38]. The process can be divided into three main phases: (1) The forum receives all information regarding the principals' actions, effects, permissions, obligations and so on that led to the situation under scrutiny; (2) the forum contextualizes actions to understand their adequacy and legitimacy; and finally, (3) the forum passes judgment on agents with sanctions or rewards. Our goal consists of automating the entire process for use in multiagent organizations, although we will presently leave out the sanctioning piece of the third phase due to its domain-specific application. With the term _computational accountability_, we mean the abilities, realized via software, to trace, evaluate and communicate accountability, in order to support the interacting parties and to help solve disputes. In modern organizations, in particular, accountability determination can be a way to obtain feedback useful to evaluate and possibly improve the processes put in place and, eventually, the overall structure, too. Accountability determination is an extremely complex task, as the following example highlights. **Example 1**. : _[PERSON] and [PERSON] are a painter and a bricklayer, called by [PERSON] for estimating the cost of renovating a room. The walls in the room are very old and for this reason, before being painted, they should be spackled. Since the prices seem reasonable, [PERSON] decides to hire both [PERSON] and [PERSON] with the following work plan. Firstly, [PERSON] should spackle the walls and [PERSON] should paint them white afterwards. Come execution time, [PERSON] decides to use a new variety of dark-colored spackle, since he has an open tin of it and he had not received any precise instruction from [PERSON]. The following day, when [PERSON] finds the dark colored walls she realizes she will not be able to satisfy the commitment she made with [PERSON] because, in order to do a nice job, she will have to use twice as much paint as expected. This simple example shows many challenges brought about when trying to tackle accountability in a computational way. Let us suppose the agreement between [PERSON] and [PERSON] was somehow formalized (for example, with a contract). [PERSON] is unable to fulfill her contract with [PERSON]. Should the simple fact that she made a commitment, which is now impossible for her to fulfill, cause a computational system to conclude she is accountable for the failure? Clearly, conditions have changed since the original room inspection. One may argue that contextual conditions, constituting the prerequisites for [PERSON] for the execution of the work, should have been formalized. In the real world, however, contextual conditions that hardly change over time are presumed implicitly stipulated even when they are not formalized. How could [PERSON] foresee that [PERSON] would have used a particular kind of spackle while the great majority of the briclayers use white ones? Is, then, [PERSON] accountable?