Skip to Main Content

Artificial Intelligence at Ringling

Ringling College's Recommended AI Tools, Press Releases, and Policies Regarding AI and the AI Certificate Program

About this Document

Framework for AI Fluency (Practical Summary Document), Version 1.0
The Framework for AI Fluency summarized in this document has emerged from an ongoing research collaboration between Prof. Rick Dakan from the Ringling College of Art and Design, Florida, and Prof. Joseph Feller from the Cork University Business School, University College Cork, Ireland. Dakan and Feller’s work explores the intersection between (1) Human Creativity and Innovation, (2) Generative AI technologies (GenAI), and (3) Learning & Teaching in Higher Education. 

The framework has also been (and continues to be) informed by the ongoing design and delivery of student courses, as well as faculty seminars and workshops, at both the Ringling College of Art and Design and the Cork University Business School, in the 2023/2024 and 2024/2025 Academic Years.  A scientific paper presenting the development of the framework, and discussing its intellectual roots and implications in full, is currently in preparation. 

This document presents a summary of the framework simply as a practical tool that is designed to inform discourse and practice in higher education on curriculum and assessment design, academic policy setting, student employability and career coaching, and similar topics in the context of AI (and particularly GenAI) digital disruption. 

Although primarily aimed at higher education, we imagine that the framework in this form will also benefit other educational levels, and indeed organizations more widely addressing the challenges and opportunities of GenAI.

Framework Overview

The Framework for AI Fluency describes two different aspects of Human/AI interaction (Fig 1). 

  1. First, it describes three core AI modalities, which primarily reflect the functional role(s) played by the AI tool.
  2. Second, it describes four core AI competencies, which primarily reflect human capabilities and efforts in the context of these modalities.

Figure 1: Overview of the Framework for AI Fluency

Core AI Modalities

Core AI Modalities (“The 3 A’s”)

The three core AI Modalities are fundamentally concerned with the functional role(s) played by the AI tool. These modalities represent distinct approaches to integrating AI (particularly GenAI) into creative and problem-solving tasks. Each modality encompasses various aspects of human-AI collaboration, such as the degree of autonomy granted to AI systems. The selection of an appropriate modality depends on the specific requirements of the task, the capabilities of the AI systems, the desired balance between human creativity and AI assistance, and other factors.

Modality 1: Automation (AI Performs Human-Defined Task) 
  • AI performs tasks independently, but based on direct human instructions (e.g. in response to a prompt).
  • This modality is particularly useful for improving the efficiency of repetitive, time-consuming, or data-intensive tasks. 
  • Requires clear task definition and quality control measures.
  • Examples: Emails, summaries, social media posts, basic coding.
Modality 2: Augmentation (AI and Human Perform Task Collaboratively)
  • AI and human collaborate towards an end goal, defining and executing tasks iteratively.
  • This modality focuses on enhancing human creativity rather than replacing it.
  • Involves a dynamic interplay between human and AI contribution.
  • Examples: Writing stories, essays, research papers, complex coding tasks.
Modality 3: Agency (Human Configures AI to Perform Tasks Independently)
  • Human configures AI to independently perform future tasks (including for others) on behalf of the user.
  • This modality defines the characteristics and future behavior of an AI, rather than a specific task.
  • Requires sophisticated understanding of AI capabilities and limitations.
  • Examples: Interactive game characters, tutors, chatbots.

Core AI Competencies

Core AI Competencies (“The 4 D’s”)

The four core competencies (Fig 2) describe the interconnected human skills, knowledge and values that enable effective and responsible AI use in creative and professional contexts.

Figure 2: Core AI Competencies

Delegation - Creative vision and selection of the right AI tools and techniques to realize that vision.
Delegation refers to the ability to identify when and how to use AI tools and modalities effectively in creative and problem-solving processes. It involves understanding the capabilities and limitations of various AI technologies and making informed decisions about when to use AI for automation, augmentation, or independent agent-mediated experiences.

Subcategories

a) Goal and Task Awareness:

  • Envisioning an effective goal for a project.
  • Understanding the nature and requirements of the task(s) towards the defined goal.
  • Ability to analyze and deconstruct a task into AI, human, and collaborative components.
  • Necessary for effective integration of AI into creative workflows.

b) Platform Awareness:

  • Understanding the capabilities and limitations of current AI tools.
  • Knowledge of various AI platforms and their specific strengths and limitations  in relation to the project’s goal.
  • Ability to evaluate AI tools based on project requirements, budget, operational and regulatory needs.
  • Necessary for selecting the optimal AI tools for specific tasks.

c) Task Delegation:

  • Balancing AI assistance with human creativity throughout a project to best realize the creative vision.
  • Deciding on the appropriate AI modality (Automation, Augmentation, Agency) given the task and platform characteristics.
  • Assigning project tasks to human and AI tools appropriately.
  • Necessary for successful collaboration between human and AI in creative processes.

Description - Effectively describing a vision and/or tasks to prompt useful AI behaviors and outputs. 
Description encompasses the skills needed to effectively communicate ideas, requirements, constraints, and other aspects of creative visions to AI systems. It involves crafting clear, specific, and well-structured prompts (using a wide range of prompting techniques) and other elements that guide and enable AI tools to produce desired behaviors and outputs.

Subcategories:
a) Product Description:

  • Prompting to define desired output.
  • Ability to clearly articulate desired characteristics, features, and qualities of the final AI-generated output.
  • Skill in translating creative vision into explicit, AI-understandable terms.
  • Crucial for guiding AI tools to produce results aligned with the creator's intentions.

b) Process Description:

  • Dialogic prompting to produce effective iterative collaboration.
  • Ability to engage in dynamic, back-and-forth communication with AI tools.
  • Skill in breaking down complex tasks into a series of smaller, manageable prompts.
  • Essential for guiding AI through multi-step creative processes aligned with the human collaborator.

c) Performance Description:

  • Directive prompting to define future AI behaviors and enable positive user experience.
  • Ability to define how AI-generated content or systems should behave or interact with users.
  • Skill in anticipating user needs and translating them into guidelines for AI behavior.
  • Critical for enabling future AI-driven behaviors that are aligned with the human’s vision and values. 

Discernment - Accurately assessing the usefulness of AI outputs 
Discernment involves the critical evaluation of AI-generated outputs, understanding their quality, relevance, potential biases, and other salient characteristics. It also includes the ability to iterate and refine the collaborative process with AI tools.

Subcategories:
a) Product Discernment:

  • Evaluating output quality and identifying ways to improve it.
  • Ability to critically assess the quality, relevance, and effectiveness of AI-generated content.
  • Skill in identifying strengths and weaknesses in AI outputs.
  • Crucial for maintaining high standards in AI-assisted creative work.

b) Process Discernment:

  • Assessing if the human-AI collaborative dynamic is fruitful or not and how to improve it.
  • Ability to evaluate the effectiveness of the human-AI collaborative process.
  • Skill in identifying which aspects of human-AI interactions are most beneficial and where improvements can be made.
  • Essential for optimizing the use of AI tools in creative collaborative work.

c) Performance Discernment:

  • Evaluating if AI-driven independent behaviors enable positive user experiences and how to better direct the AI to improve outcomes.
  • Ability to assess the effectiveness of AI systems in independent, user-facing scenarios.
  • Skill in gathering and interpreting human feedback to refine and ensure intended AI-driven behaviors and experiences.
  • Essential for designing user experiences aligned with the project's vision and values. 

Diligence - Taking responsibility and vouching for final products created using AI 
Diligence refers to the responsible use of AI, including ethical considerations, transparency about AI use, and taking accountability for the final products created with AI assistance.

Subcategories:
a) Creation Diligence:

  • Responsible use of AI tools, maintaining ethical and legal best practices, awareness of biases, flaws, stakeholder impacts, and other externalities
  • Understanding and applying ethical principles throughout the AI-assisted creative process.
  • Ability to identify and mitigate potential biases and ethical risks in AI-generated content.
  • Crucial for ensuring responsible and socially conscious use of AI in creative work.

b) Distribution Diligence:

  • Transparency and accountability when distributing the end product.
  • Skill in clearly communicating the extent of AI involvement in creative work.
  • Understanding of legal and ethical guidelines for AI-generated content distribution.
  • Essential for maintaining trust and integrity when distributing AI-assisted creative work.
     

Diligence Statement

Diligence Statement: In the creation of this document, we used Claude 3.5 Pro to assist in text creation and refinement. We affirm that all AI-generated content underwent thorough vetting, editing, and curation by the human co-authors. The final document accurately reflects our understanding, expertise, and intended meaning. While AI tools were instrumental in the writing process, we maintain full responsibility for the content, its accuracy, and its presentation. This disclosure is made in the spirit of transparency and to acknowledge the evolving role of AI in content creation and other intellectual work.