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Version control, prototyping, secure development practices, and engineering processes.
Also in Engineering & Development
Designing and implementing appropriate workflows and organizational structures for developing AI systems
Software development and project management (Dennehy & Conboy, 2018) DevOps (Gall & Pigni, 2021) MLOps (Mäkinen et al., 2021)
Reasoning
Establishes development workflows and organizational structures for building AI systems systematically.
AI development
Coordinated and accountable AI development operations is key to sustainable AI development in organizations. The Head of AI should ensure that the organization designs and implements 6) appropriate workflows and processes for its AI-related data acquisition, permitting, and analytics operations, including approvals and signoffs, and 7) appropriate workflows and processes for its algorithm development and AI system development operations, including approvals and signoffs. 8) The workflows and processes should align with the organization's values and risk tolerance.
2.1.3 Policies & ProceduresAI operations
Coordinated and accountable AI operations are key to sustainable AI use in organizations. The Head of AI should ensure that the organization designs and implements 1) appropriate workflows and processes for AI system operations, including approvals and signoffs, and 2) appropriate workflows and processes for AI retirement, including approvals and signoffs. 3) The workflows and processes should align with the organization's values and risk tolerance.
2.1.3 Policies & ProceduresAI governance integration
AI systems are tools that serve business or operational purposes. AI system governance overlaps with business and operational, data, IT system, and governance and strategic governance. AI system governance should be integrated and aligned with other organizational governance processes. The Head of AI should ensure that AI governance is integrated with other organizational governance processes.
2.1.3 Policies & ProceduresAI System
Ensuring that the AI system is developed, operated, and monitored in alignment with the organization’s strategic goals and values.
2.1.3 Policies & ProceduresAI System > AI system repository and AI ID
Coordinated AI development, operation, and use are essential to organizations' sustainable AI operations. All organizations using AI systems should operate an AI system repository. The repository should 1) identify all AI systems the organization is developing, operates, uses, or has retired, 2) assign them a unique identifier, 3) contain the relevant documents the organization has produced or received on the AI system.
2.1.3 Policies & ProceduresAI System > AI system pre-design
Once an organization initiates an AI system development project, it should perform a preliminary pre-design of the system. The Head of AI (T54) should ensure that the organization 1) enters the AI system into the AI repository (T1), 2) assesses whether the AI system can align with the organization's values and risk tolerance, 3) initiates the development processes and assigns roles and responsibilities, 4) identifies and documents the planned AI system's key features and design constraints.
2.1.3 Policies & ProceduresAI System > AI system use case
Identifying and understanding the intended use case of an AI system and its other possible uses is key to sustainable AI development and use. The use case affects the system's regulatory environment and may have significant reputational risk implications. The AI System Owner (T55) should ensure that the organization defines and documents 1) the intended use case of the AI system and 2) the possible other uses of the AI system. The AI System Owner should ensure that the use case definition aligns with the organization's values and risk tolerance. The AI System Owner should ensure that the organization takes adequate measures to prevent inappropriate AI system misuse.
2.1.3 Policies & ProceduresAI System > AI system user
People in organizations use AI systems. Some AI systems make decisions that directly or indirectly affect humans and their rights and obligations (affected persons). Sustainable AI system development and use require that the organization is conscious of who is using the AI system and whose rights and obligations it may affect. The organization should define and document 1) the intended AI system user organizations and human users, 2) the intended affected persons, and 3) possible other users and affected persons. The AI System Owner (T55) should ensure that the user definitions align with the organization's values and risk tolerance.
2.1.3 Policies & ProceduresAI System > AI system operating environment
AI systems are embedded in the business and organizational environment. This environment typically consists of technological and social elements. The operating environment is a key driver of AI system impacts. The organization should define and document 1) the intended business or operational model and environment of the AI system, 2) the intended IT environment the AI system is embedded in and interacts with, 3) the other intended AI systems the AI system interacts with.
2.1.3 Policies & ProceduresPutting AI Ethics into Practice: The Hourglass Model of Organizational AI Governance
Mäntymäki, Matti; Minkkinen, Matti; Birkstedt, Teemu; Viljanen, Mika (2022)
The organizational use of artificial intelligence (AI) has rapidly spread across various sectors. Alongside the awareness of the benefits brought by AI, there is a growing consensus on the necessity of tackling the risks and potential harms, such as bias and discrimination, brought about by advanced AI technologies. A multitude of AI ethics principles have been proposed to tackle these risks, but the outlines of organizational processes and practices for ensuring socially responsible AI development are in a nascent state. To address the paucity of comprehensive governance models, we present an AI governance framework, the hourglass model of organizational AI governance, which targets organizations that develop and use AI systems. The framework is designed to help organizations deploying AI systems translate ethical AI principles into practice and align their AI systems and processes with the forthcoming European AI Act. The hourglass framework includes governance requirements at the environmental, organizational, and AI system levels. At the AI system level, we connect governance requirements to AI system life cycles to ensure governance throughout the system's life span. The governance model highlights the systemic nature of AI governance and opens new research avenues into its practical implementation, the mechanisms that connect different AI governance layers, and the dynamics between the AI governance actors. The model also offers a starting point for organizational decision-makers to consider the governance components needed to ensure social acceptability, mitigate risks, and realize the potential of AI.
Build and Use Model
Training, fine-tuning, and integrating the AI model
Deployer
Entity that integrates and deploys the AI system for end users
Unable to classify
Could not be classified to a specific AIRM function
Primary
6.5 Governance failure