Understanding Wikipedia

Adherence to a reasonable level of understandability would prevent an organization from deliberately obfuscating financial information in order to mislead users of its financial statements. The preceding concepts do not mean that complex information should be excluded from the financial statements. For example, the concepts related to pensions and derivatives are not easy to understand. In these situations, apply the understandability concept as much as possible, but still present the required information. As shown in Table 5.17, the ATD Detail viewpoint received an average score of 6.8, while each of the other viewpoints received an average score above eight. These scores indicate good understandability of the ATD viewpoints, considering that the case study participants spent only 40 min (as described in Table 5.15) on learning the viewpoints.

The literature on artificial intelligence (AI) or machine learning (ML) in mental health and psychiatry lacks consensus on what “explainability” means. Given the differing usage and intended meaning of the term “explainability” in AI and ML, we propose instead to approximate model/algorithm explainability by understandability defined as a function of transparency and interpretability. These concepts are easier to articulate, to “ground” in our understanding of how algorithms and models operate and are used more consistently in the literature. We describe the TIFU (Transparency and Interpretability For Understandability) framework and examine how this applies to the landscape of AI/ML in mental health research. If we develop and deploy AI/ML models, ensuring human understandability of the inputs, processes and outputs of these models is essential to develop trustworthy systems fit for deployment. Any company primarily runs on the funds of shareholders and directors are the people who manage those funds with the intention to generate profits.

Understandability definition

To reason about probabilistic causation in Markov chains, [985] combines standard PCTL model checking [584] with statistical hypothesis testing. Causality  The notion of causality has been extensively studied in philosophy, social sciences, and artificial intelligence (e.g., [971–974]). Most prominent, causality is understood as a binary relation over events that declare the constraints for an event C to be cause of another event E (the effect). These rely on the concept of counterfactual dependencies [975], stating that E would not have happened if C had not happened before.

It is the responsibility of directors to prepare financial statements and shareholders can assess the performance of their directors by reviewing these statements. The concept of understandability aids this very need of the fund providers of the company. Basically the concept suggests that the financial statements prepared by directors must be clear and explicit for their users. They must be presented in such a way that the users do not get confused or deluded.

Definition

Employers and employees relate to each other by engaging in standardized language that is understandable for the benefit of company productivity. Map the semantic link network of sentences into the semantic link network of concepts. David was going to deal with the metrics for FRG internal and external quality characteristics (according to ISO/IEC , ISO, 2003a, and ISO/IEC , ISO, 2003b), in particular I/O utilization, memory utilization, and response time. Sean restricted himself to quality in use metrics (according to ISO/IEC ; ISO, 2004), namely FRG task efficiency. After negotiation, David agreed not to discuss I/O utilization and memory utilization; whereas Sean agreed to discuss response time instead of task efficiency because this external quality metric was understandable to him.

• Changeability and Extensibility—When an abstraction “exposes” or “leaks” implementation details through its public interface, the clients of the abstraction may depend directly upon its implementation details.
• They are usually provided as error traces or in a tree-like structure to guide through the systems source code or operational behavior.
• Reliability—When two abstractions have identical names, a confused developer may end-up using the wrong abstraction.
• Causality-based approaches that analyze counterexamples and extract user-understandable visualizations have been suggested only recently [992,993].
• Probabilistic causation attempts to provide criteria for the stochastic evidence to treat C as a cause for another event E.

Initially, David considered also the Database Subsystem (DBS) and the Hardware Subsystem (HWS) as relevant artifacts, because the quality of FRG depended on their characteristics. Sean, however, only dealt with FRG because he did not see the other components https://turbo-tax.org/tax-software-survey/ of the system. As a result of negotiation, David agreed not to discuss DBS and HWS with Sean. David (the Developer) and Sean (the Business Stakeholder) negotiated the quality of the software component called Financial Report Generator (FRG).

Bounded Contexts: Manage the Understandability of Your Systems (DDD Australia)

Information is reasonably understood by users with a basic knowledge of accounting. Changeability and Extensibility—When an abstraction “exposes” or “leaks” implementation details through its public interface, the clients of the abstraction may depend directly upon its implementation details. This direct dependency makes it difficult to change or extend the design without breaking the client code. Understandability—If a hierarchy is created unnecessarily, it complicates the design. Some have backgrounds in medicine and public health and rely on WHO for technical information. They need information that is easy to understand in order to understand health risks and take appropriate actions.

Understandability—One of the main objectives of the principle of encapsulation is to shield clients from the complexity of an abstraction by hiding its internal details. However, when internal implementation details are exposed in the case of a Leaky Encapsulation smell, the public interface of the abstraction may become more complex, affecting its understandability. Understandability, within the context of workplace communication, refers to the exchange of information in verbal and written terms to facilitate workplace understanding and information. Company success is determined by the reciprocity of ideas and the definitive manner in which they are expressed.

Timely

Extensibility—Consider Example 2 wherein the number of types in a hierarchy can grow exponentially when new combinations need to be supported in the design. This complicates the design and increases the effort required to support new combinations. This is the British English definition of understandable.View American English definition of understandable. Strategies, standards, and supporting resources to make the Web accessible to people with disabilities. Understandability boundaries are separations that look at how concepts in our system are understood together (or autonomously). As a result, David reconsidered his judgment and changed it from good to satisfactory.

This does not mean that complex data must be excluded from these statements, but this data must be explained enough, so that even the users possessing considerably less accounting or business knowledge could understand and interpret it easily. Additionally too much use of jargon must be avoided and where possible intricate terms and statements must be substituted with easy to understand language. The use of proper headings, graphs, formats etc. can also make the statements more legible. Counterexamples and witnesses  During design-time, the cause for a violation of a system property is of utter interest for debugging the system. Counterexamples are likely to contain an event that causes the property violation. They are usually provided as error traces or in a tree-like structure to guide through the systems source code or operational behavior.

WorkplaceTesting Explains Understandability

If the system is poorly designed and overly complex, people not involved in the original design of the system require additional time before they are able to make significant contributions to the project. In addition, their contributions are likely to further complicate the architecture because identifying the most effective way to implement a specific feature is difficult without a solid understanding of the overall architecture. Unfortunately, without intimate access to implementation details, this characteristic is very hard to determine. The CLOZE

method is used as a measure of understandability with audiences of

differing accounting sophistication to measure the predictability of the

narrative and to demonstrate inter‐group and inter‐formulae

distinctions. This concept is very important as the understandability of the information provided in financial statements is necessary for many reasons. It promotes attributes like comparability and consistency within financial statements that raise their relevance.