Strategic Plan

AI KR Strategists

Analysis

Direction

Vision

Work performed and works created for each AI value proposition is clearly and transparently documented and measured.

Mission

To be responsible and accountable for the selection, development, application and management of Knowledge Representation (KR) for Artificial Intelligence (AI).

Scorecard

Perspective	Goals	Objectives	Performance Indicators			Commentary
	Goal Strategic Plan	Objective Algorithms
		Objective Ontology
	Goal Applications
	Goal Requirements
	Goal Glossaries
	Goal Risks	Objective Bias
		Objective Consequences
		Objective Control
		Objective Data
		Objective Governance
		Objective Intellectual Property	KPI Existing rights
			KPI Created Rights
			KPI Protected works
			KPI Disputes raised
			KPI Disputes resolved
		Objective Privacy
		Objective Security
	Goal Compliance
	Goal Ethics	Objective Accountability
		Objective Autonomy
		Objective Confidentiality
		Objective Veracity
	Goal Robustness
	Goal Outcomes
	Goal Algorithm Evaluation	Objective Classification	KPI Precision Recall
			KPI Accuracy
			KPI Confusion Matrix
			KPI Per-class accuracy
			KPI Log-Loss
			KPI AUC-ROC Curve
			KPI F-measure
			KPI NDCG
			KPI Regression Analysis
			KPI Quantiles of Errors
			KPI "Almost correct" predictions
		Objective Trustworthiness
	Goal KR Objects

Goals

Strategic Plan

Goal Statement: Document the vision, values, goals, objectives for one or more AIKR objects

An AI KR Object may be :

• an algorithm (example - enable an entity to determine consequences; a set of instructions that provide the ability to monitor and/or move the environment; the rules that are used to change/manipulate/interpret data)
• an ontology (which has a set of ontological commitments) See Goal - Ontological Statements (provides sufficient definition to allow measurement to be performed)
• an Intelligent Reasoning (fragmentary) Theory, such as,
  • deduction,
  • induction,
  • abduction,
  • by analogy,
  • probabilistic,
  • case-based 
• a Reasoning Mechanism (computational environment), such as,
  • natural language processer,
  • rules engine,
  • machine learning
• a Vocabulary (medium of human expression)

Objectives:

• Ontology
• Algorithms

Applications

Goal Statement: Understand the potential applications of AI to business strategies.

Requirements

Goal Statement: Identify which areas of the requirements warrant AI solutions versus which can be achieved with other types of solutions

Glossaries

Goal Statement: Employ definitions from one or more glossaries when explaining AIKR object audit data, veracity facts and (human, social and technology) risk mitigation factors

So that (business) people more readily understand the value that the glossaries bring.

Risks

Goal Statement: Identify and mitigate risks and known threats

A guiding principle is that AIKR systems must mitigate risks.

Objectives:

• Consequences
• Data
• Bias
• Security
• Control
• Intellectual Property
• Privacy
• Governance

Compliance

Goal Statement: Ensure AI Systems comply with all applicable laws and regulations, such as, provision audit data defined by a governance operating model

Compliance policies and procedures ensure that a planned change to a KR Object usage will comply with applicable laws/regulations during the identification, development, documentation, testing, validation, implementation, modification, use and retirement lifecycle

Ethics

Goal Statement: Ensure AI Systems adhere to principles of ethics

Objectives:

• Autonomy
• Veracity
• Accountability
• Confidentiality

Robustness

Goal Statement: Ensure AI Systems are designed to handle uncertainty and tolerate perturbation from a likely threat perspective, such as, design considerations incorporate human, social and technology risk factors

Outcomes

Goal Statement: Track AIKR object performance outcome via KPI (Key Performance Indicator) based on supervised learning models measurements

Algorithm Evaluation

Goal Statement: Evaluate Algorithms

Assess how well Algorithm results match actual outcomes to determine

• how sensitive inferences made are to the parameters and
• the proportion of observations made were accurately predicted.

When needed the algorithmic impact assessments will also identify cause and effect of any biases.

Objectives:

• Trustworthiness
• Classification

KR Objects

Goal Statement: Evaluate KR Object Performance

KR Object oversight mechanisms will define how performance measurements are used via human-in-the-loop, human-on-the-loop, and human-in-command approaches