Related Experiment Video
Updated: May 14, 2025
11:53
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
Published on: October 14, 2017
11.5K
Protocol for implementing the nested model for AI design and validation in compliance with AI regulations.
Akshat Dubey1, Zewen Yang2, Aleksandar Anžel2
1Center for Artificial Intelligence in the Public Health Research (ZKI-PH) at Robert Koch Institute, Nordufer 20, 13353 Berlin, Germany; Department of Mathematics and Computer Science, Freie Universität Berlin, Arnimallee 14, 14195 Berlin, Germany.
STAR Protocols
|April 12, 2025
Summary
This study introduces a nested model protocol for developing and validating artificial intelligence (AI) systems, ensuring compliance with AI regulations and ethical standards. The protocol guides AI application design and validation across multiple layers for robust and regulated AI development.
Area of Science:
- Computer Science
- Artificial Intelligence
- Regulatory Science
Background:
- Developing artificial intelligence (AI) systems requires adherence to evolving AI regulations.
- Ensuring ethical and technical requirements are met during AI development is crucial.
- A structured protocol is needed for AI system validation in regulated environments.
Purpose of the Study:
- To present a protocol for implementing a nested model for AI system development and validation.
- To outline steps for defining AI regulations and associated requirements.
- To detail procedures for designing and validating AI applications across multiple layers.
Main Methods:
- Defining regulations and ethical/technical requirements based on research questions.
- Designing AI applications with a focus on domain, data, model, and prediction layers.
- Validating AI applications through a user-interactive front-end interface across different layers.
Main Results:
- A comprehensive protocol for nested model implementation in AI development.
- A framework for aligning AI system design with regulatory and ethical standards.
- A method for validating AI applications across domain, data, model, and prediction layers.
Conclusions:
- The presented nested model protocol facilitates the development and validation of AI systems in compliance with AI regulations.
- This protocol provides a structured approach to address ethical and technical requirements in AI.
- The layered design and interactive interface enhance the usability and robustness of AI validation.
Related Concept Videos
01:03Data Validation
4.8K
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
Nursing assessment guides are generally based on holistic models rather than medical...
4.8K
01:26Modeling in Therapy
34
Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
34
01:56Ethics in Research
22.8K
Today, scientists agree that good research is ethical in nature and is guided by a basic respect for human dignity and safety. However, this has not always been the case. Modern researchers must demonstrate that the research they perform is ethically sound.
22.8K
02:16Stereotype Content Model
13.9K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
13.9K
01:12Observational Learning
102
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
102
01:14Steps in the Modeling Process
149
Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...
149