Redefining AI's Horizon: Purposeful Intelligence as the True Competitive Edge
By Gwylym Pryce-Owen
In the quiet chambers of ancient scriptoria, monks laboured over illuminated manuscripts, blending ink and insight to preserve knowledge across generations. Their work was not mere transcription; it was a deliberate act of shaping meaning, ensuring that ideas endured with clarity and intent.
Today, as we navigate the digital expanse, agentic AI echoes this endeavour, promising systems that act independently, adapt dynamically, and handle intricate tasks. These agents hold immense potential, from streamlining operations to enhancing decision-making. However, amid the excitement of their autonomy, a fundamental inquiry arises: What if the key to unlocking AI's full business potential lies not in escalating complexity, but in refining our understanding of its core objectives?
Philosophy Eats AI
This essay posits that surpassing agentic algorithms requires embracing philosophy as AI's transformative core, elevating it from efficient executors to instruments of deliberate, value-driven progress. Building on the MIT Sloan Management Review article "Philosophy Eats AI" by Michael Schrage and David Kiron, we examine how teleology (purpose), epistemology (knowledge), and ontology (representation) reshape AI.
Teleology: The Question of Purpose
Agentic AI masters methods and mechanics, but often lacks a defined "why." What overarching goal guides its actions? In a business setting, this could manifest as an agent prioritising immediate throughput while overlooking sustainability, potentially leading to scenarios where short-term gains undermine long-term viability.
Philosophy prompts us to specify AI's telos explicitly. For example, if a company's vision includes employee empowerment alongside productivity, teleological alignment might steer agents toward collaborative roles.
Epistemology: The Nature of Knowledge
Agentic AI constructs "insights" from data patterns, mimicking reason via associations. However, this pattern-bound approach differs from human rationality's boundaries, raising questions about validity. Without epistemological scrutiny, agents could conflate superficial links with deep understanding, risking errors like overreliance on outdated data.
Ontology: The Framework of Reality
Agentic AI abstracts reality into categories, but ontological oversights can skew perceptions. An agent in healthcare might categorise patients as data sets, missing nuances like cultural contexts. By refining ontologies, businesses could enable agents to handle multifaceted realities.
Our Consultancy Roadmap
Our AI consultancy pursues this through a forward-looking roadmap designed to explore and refine these concepts in practice:
- Phase One: Philosophical Discovery (4–6 weeks) - Uncover implicit philosophies in AI efforts
- Phase Two: Teleological Framing (6–8 weeks) - Articulate AI's purposes, aligning with organizational values
- Phase Three: Epistemic and Ontological Enhancement (8–12 weeks) - Integrate knowledge validation and layered reality models
- Phase Four: Iterative Exploration (Ongoing) - Pilot implementations with continuous monitoring
In sum, transcending agentic AI calls for philosophy's integrative power. By clarifying purpose, validating knowledge, and enriching representation, AI evolves into purposeful intelligence, potentially driving lasting edges.
Looking to transform your AI strategy with purposeful intelligence? My consultancy offers tailored roadmaps and implementation plans to align your AI with business goals. DM me on LinkedIn to explore my services.