The Missing Piece in the Use of Generative AI in Business: The Role of Wisdom
Dr. Justin B. Rose, CWDP
Father | ΔΙ Learning | Director | Chief AI Workforce Strategist | Instructional Designer | Industry & Business Optimization Consultant | Workforce Development Professional | Author | Prompt Engineer | Professor
The rapid advancement of generative AI has undeniably transformed the business landscape, offering unprecedented tools for automation, creativity, and decision-making (Akhtar, 2024, Capgemini Research Institute, 2023). However, amid the excitement and the often-necessary focus on responsible AI and ethical use, there is a crucial element that is frequently overlooked: wisdom. While intelligence and knowledge are critical components of AI’s capabilities, the wisdom required to guide these tools, both on an individual and collective level, is the missing piece that can make or break the ethical integration of AI into our lives (Wilson & Daugherty, 2019).
Intelligence, Knowledge, and Wisdom: A Brief Recap
To understand the gap in the use of generative AI, it’s essential first to distinguish between intelligence, knowledge, and wisdom, both in humans and AI.
Intelligence refers to the ability to process information, learn from it, and apply it in problem-solving. In AI, intelligence manifests as the machine’s capability to analyze data, recognize patterns, and perform tasks that typically require human cognition (Singla, Sukharevsky, Yee, and Chui, 2024). For instance, AI can process vast amounts of data at incredible speeds, making it highly intelligent in terms of computational power.
Knowledge, on the other hand, is the information that intelligence draws upon. In humans, knowledge comes from experience, education, and cultural context. In AI, knowledge is derived from the data it’s trained on, encompassing everything from historical records to real-time updates. AI systems like GPT-4 have access to a vast repository of human knowledge, which they use to generate content, answer questions, and perform complex analyses (Capgemini Research Institute, 2023).
Wisdom, however, is a more nuanced and inherently human trait. It is the ability to make sound judgments based on knowledge and experience, often considering ethical implications and long-term consequences. Wisdom involves understanding not just what can be done, but what should be done, and why. While AI can simulate decision-making processes, it lacks the intrinsic ability to apply wisdom in the same way humans do.
Wisdom, Responsible AI, and Ethics: Understanding the Differences
While wisdom, responsible AI, and ethics are all related concepts, they differ significantly in their application and scope.
Wisdom is about making sound judgments and decisions that take into account not only the immediate outcomes but also the broader implications and long-term effects. It is rooted in experience and reflective thinking, guiding actions that are not only effective but also morally and ethically sound. Wisdom in AI use involves understanding when and how to apply AI tools in a way that aligns with human values, societal good, and long-term sustainability (Koestler, 1967).
Responsible AI focuses on the creation and deployment of AI systems in ways that are fair, transparent, and accountable. It involves ensuring that AI systems do not perpetuate biases, cause harm, or operate in ways that are opaque or unaccountable. Responsible AI is about setting up frameworks, guidelines, and best practices that govern the ethical use of AI technologies. This might include developing explainable AI systems, ensuring that users understand how decisions are made, and implementing safeguards to prevent misuse (Singla et al., 2024).
Ethics, on the other hand, refers to the moral principles that govern behavior. In the context of AI, ethics encompasses the values and standards that should guide the development and use of AI systems. Ethical AI involves ensuring that AI technologies respect human rights, dignity, and autonomy. It includes considerations such as privacy, fairness, and the potential societal impacts of AI. Ethical AI development ensures that AI systems do not reinforce existing social inequalities or create new ones (Capgemini Research Institute, 2023).
The Philosophical Angle: The Role of Wisdom in AI’s Future
The philosophical discussion surrounding the role of wisdom in AI use is not new; it has deep roots in both literature and philosophical inquiry. Arthur Koestler’s concept of the “Ghost in the Machine,” introduced in his 1967 book, The Ghost in the Machine, challenges the idea that human consciousness is merely a byproduct of physical processes. Koestler’s work emphasizes the complexity of human consciousness and the dangers of reductionist thinking that ignores the intricacies of the human mind. When we consider the rise of generative AI, Koestler’s ideas prompt us to reflect on the inherent limitations of AI and the necessity of wisdom in its application (Koestler, 1967).
Generative AI, despite its advanced capabilities, operates purely on algorithms and data processing. It lacks the self-awareness, empathy, and moral reasoning that are essential components of human wisdom. Koestler’s “Ghost in the Machine” reminds us that AI, no matter how sophisticated, cannot replicate the full spectrum of human thought and judgment. This is why the human element—our capacity for wisdom—remains indispensable in guiding AI’s use (Kar, Varsha, and Rajan, 2023).
Furthermore, concerns about the intersection of human and machine intelligence have been vividly depicted in works like William Gibson’s Neuromancer and the Matrix trilogy. These narratives, while often seen as cautionary tales within the cyberpunk genre, explore profound philosophical questions about the relationship between humans and technology. They question what happens when technology surpasses human control or when the line between human consciousness and machine intelligence becomes blurred.
While these works are fictional, the underlying concerns they raise are relevant to our current discourse on AI. They caution against the unreflective embrace of technology without considering the ethical implications and the potential loss of human autonomy. In the context of AI in business, these concerns translate into the need for a balanced approach—one that leverages AI’s capabilities while ensuring that human wisdom remains at the forefront of decision-making (Koestler, 1967).
The wisdom discussed here is not just about making ethical choices but about recognizing the limitations of AI and the irreplaceable value of human experience and judgment. As Koestler’s work suggests, there is more to human consciousness than can be captured by machines. Similarly, the dystopian warnings in Neuromancer and the Matrix encourage us to carefully consider the path we take with AI, ensuring that it enhances rather than diminishes our humanity.
In summary, the philosophical framework provided by these works underscores the need for wisdom in the integration of AI. It’s not enough for AI to be intelligent or knowledgeable; it must be guided by human wisdom that understands the broader implications of its use. By maintaining this perspective, we can ensure that AI serves as a tool to augment human capabilities, rather than becoming a substitute for the deeply human qualities that define our moral and ethical landscapes.
Applying Wisdom on an Individual and Collective Level
On an individual level, wisdom in the use of AI requires self-awareness, ethical judgment, and a commitment to the broader impact of one’s actions. Professionals using AI tools should be vigilant about the context in which they deploy these tools, ensuring that their use aligns with both personal and organizational values (Wilson & Daugherty, 2019). For example, an employee using AI to streamline their work should also consider the potential risks, such as data privacy issues or the possibility of AI reinforcing existing biases. The 2010 “Flash Crash” serves as a stark reminder of the importance of human oversight in AI-driven processes. Here, high-frequency trading algorithms contributed to a sudden and extreme drop in the U.S. stock market, underscoring the need for wisdom in balancing AI's speed with careful human judgment.
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This self-awareness can be likened to the realist in the parable who adjusts their path based on a clear understanding of the forest. Just as the realist navigates the forest with awareness of both obstacles and opportunities, individuals must navigate AI use with an understanding of its power and limitations.
On a collective level, organizations and societies must foster an environment where wisdom is prioritized alongside intelligence and knowledge. This can involve creating policies that encourage thoughtful AI use, providing education and training on the ethical implications of AI, and developing systems that require human oversight in AI-driven processes (Capgemini Research Institute, 2023). For example, companies might establish guidelines that mandate human review of AI-generated decisions in areas like hiring, lending, or content moderation. Companies like Google have established AI ethics committees to evaluate potential impacts before deploying new AI technologies, demonstrating how wisdom can guide responsible AI development (Wilson & Daugherty, 2019).
Conclusion: Integrating Wisdom into AI’s Future
The integration of generative AI into business and society is a double-edged sword. It offers incredible opportunities for innovation and efficiency, but it also poses significant ethical and practical challenges. The missing piece in this puzzle is wisdom, both at the individual level, where professionals must make informed, ethical decisions about how they use AI, and at the collective level, where organizations and societies must establish frameworks that promote wise AI use.
In the end, the success of AI in business will not be measured solely by its intelligence or the breadth of its knowledge but by the wisdom with which it is deployed. By embracing wisdom, we can ensure that AI serves as a force for good, enhancing human capabilities without compromising our values or ethical standards. Just as the realist in the forest sees the path clearly and adjusts accordingly, we must approach AI with a clear vision of its potential and its pitfalls, guiding its use with the wisdom that only humans can provide.
References:?
Akhtar, Z. B. (2024). Unveiling the evolution of generative AI (GAI): A comprehensive and investigative analysis toward LLM models (2021–2024) and beyond. Journal of Electrical Systems and Information Technology, 11(22). https://doi.org/10.1186/s43067-024-00145-1
Capgemini Research Institute. (2023). Harnessing the value of Generative?
Koestler, Arthur (1967). The Ghost in the Machine (1990). Penguin Group. ISBN 0-14-019192-5.
Kar, A. K., Varsha, P. S., & Rajan, S. (2023). Unravelling the impact of generative artificial intelligence (GAI) in industrial applications: A review of scientific and grey literature. Global Journal of Flexible Systems Management, 24, 659-689. https://doi.org/10.1007/s40171-023-00356-x
Singla, A., Sukharevsky, A., Yee, L., & Chui, M. (2024). The state of ai in early 2024: Gen ai adoption spikes and starts to generate value. McKinsey & Company. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai?
Wilson, J., & Daugherty, P. (2019). How humans and ai are working together in 1,500 companies. Harvard Business Review. https://hbr.org/2018/07/collaborative-intelligence-humans-and-ai-are-joining-
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