Governing bodies of organizations using artificial intelligence systems are required to establish accountability within the organisation to uphold a responsible approach to the implementation, operation, and management of AI systems. A governance framework provides a conceptual structure by which the current and future use of artificial intelligence is directed and controlled to create value and manage risk. At the centre of an artificial intelligence governance framework is the assignment of decision-making authority and accountability of individuals for the decisions they make, particularly when these decisions impact the organisation's plans, internal policies, external obligations, strategic objectives, value creation, and broader stakeholder needs and expectations.

An artificial intelligence governance framework comprises 3 tiers:

• at the Board level: directors Evaluate, Direct and Monitor the performance of artificial intelligence against plans, internal policies, external obligations, strategic objectives, and broader stakeholder needs and expectations.
• at the Management Level: management Plans, Organises, Directs, and Controls to effectively and efficiently leverage artificial intelligence resources and drive value creation, stakeholder benefits and continuous improvement.
• at the Operational Level: activities are performed, controlled, supervised, and checked in alignment with business objectives.

An artificial intelligence system is defined by the nature, scope, and context of the processing. This influences the governance arrangements used to direct and control key activities to ensure the performance expected by the stakeholders is delivered.

Description

Artificial intelligence systems take many different forms and require different degrees of governance. This Governance of Artificial Intelligence course will address:

• Governance of decision-making by AI systems 
  • Authority and responsibility are delegated to people throughout an organization
  • Decision-making is aligned to the organizational objectives
• Govern value creation (i.e. prioritise purposes - consider the implications on the organisation of any new tool, technique, or technology being introduced.)
• Governance oversight of AI 
  • governance mechanisms (e.g. charter, policies, etc.) are in place to ensure the appropriate use of AI
    • roles and responsibilities are assigned
    • chain of responsibility
    • accountability for decision-making to translate governance direction into the strategy and associated objectives required to achieve desired levels of sustainable performance and long-term viability
    • authority and potential delegation of authority are clearly defined and agreed upon both within the organization and, where applicable, between different parties in any value chain
    • adequate human oversight is in place while using AI
    • any human using Al or responsible for the use of AI has an appropriate understanding of the AI system being used
  • monitor the development and implementation of organisational and governance policies and management of associated tasks, services and products set by the organization, in order to adapt to changes in internal or external circumstances and ensure the effective, efficient, and acceptable use of AI within the organisation
• Govern data use (i.e. quality, quantity, risk, constraints on use, system of internal control)
• Govern culture, values, and ethical outcomes
• Govern compliance:
  • mandatory (e.g. AI, data governance and data protection legislation and
  • voluntary (e.g. ISO, industry bodies, policy forums)
• Govern the management of risk – effect of uncertainty on objectives - optimisation.

Course details

This two-day course ends with a short quiz. This is necessary to confirm knowledge transfer to the attendee.

This in-person classroom course takes place in Dublin, Ireland on the advertised dates.

Cancellation/Refund Policy

The organiser reserves the right to cancel a training event, at any time prior to the actual start of the course. In such circumstances, participants will be advised as soon as possible by telephone or email, and the purchaser will be entitled to a full refund of the course fee, or the course fee can be credited towards a future course, at the purchaser’s choice. Any repayment will be by the same method as the payment. The organisers will not be responsible for any loss or expenses incurred by the participant or purchaser, howsoever arising, irrespective of the length of notice given.

Cancellation by the participant

Notice of a training participant’s intention to cancel a course registration must be made in writing (letter, fax or email), and in good time. In such cases, participants will have the option of nominating a replacement to attend in their place. Participants whose cancellation request is received more than 10 working days prior to the start date of the training course will receive a full refund or credit. Participants whose cancellation request is received less than 10 working days prior to the start date of the training course will be charged 100% of the full fee. Participants who fail to attend the course will be charged 100% of the full fee.

Payment

Payment terms are strictly 30 days from the date of invoice or prior to course commencement, whichever comes earliest. A place on the course is not guaranteed until payment in full has been received.

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