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Physical development involves growth and changes in the body and brain, the senses, motor skills, and health and wellness. Cognitive development involves learning, attention, memory, language, thinking, reasoning, and creativity. To that extent the industrial revolution is about extension of our physical possibilities and AI is about extension of our cognitive possibilities. While there are differences, the similarities between physical and cognitive behavior can be seen in many areas of human experience. Examples are:
- Sequential action: Whether learning a complex skill or performing a mental task, both require breaking down the process into a sequence of smaller, manageable steps.
- Representational changes: Making changes to become more efficient involves developing these representations to guide and refine actions.
If AI in human beings is at the mind level and not at the power level, can AI heighten Personal Agility? If so, how? It may be possible that the Personal Agility Light House™ Model (PALH TM) can help. Our model is about how we behave in this ever-changing environment. Therefore, our mindset and changes in the thoughts and thought process is the extrapolation that AI can extend to our PALHTM model and vice versa. For example, out of the seven agilities in the PALHTM model, Learning agility (continuous growth), Cerebral agility (remove impediments on the spot), Political agility (transparency for organizational growth), Change agility (relearning ourselves to improve competencies), Emotional agility (treat others with deference), Education agility (feel the pain points of others) and finally, Outcomes agility (commit to excel in the outcome that is foreseen). However, the problem is that the pace of the development of AI is very fast. Therefore, as of now the AI agents can influence / change reality, meaning it has significantly impacted our perception of the world and ourselves. This is a particularly important aspect as all technological inventions so far help us to manage the current reality, but AI can change this reality on its own. But Large Language Models does not change reality, only AI agents can. AI agents are a type of artificial intelligence (AI) system that can understand and respond to customer inquiries without human intervention. Money transfer in bank accounts is an example. Agent builders relying on natural language processing ( NLP) and machine learning (ML) can continuously improve our individualized learning experiences as we can self-learn (Learning agility). This is unlike AI that needs to be fed by humans for tasks. This is because AI is a broad term for making machines humanlike, while ML is a specific branch of AI focused on analyzing data. ML is a methodology within AI.
On the flip side of the coin, through the agent, information could be changed into a good or bad or fraudulent content leading to maybe misunderstanding. This could result in beneficial or adverse action. Cerebral agility needs to come in here. For cerebral agility to be deployed fully, Change agility needs to surface. This calls for an individual to relearn in multiple ways. One example is getting comfortable with AI which is an enhancement of human brain power. From this point of view, AI may help accelerate our learning. Going along that vein, Artificial General Intelligence (AGI) has not picked up enough momentum because it is human‑level intelligence AI capable of performing the full spectrum of cognitively demanding tasks with proficiency comparable to, or surpassing, that of humans. Therefore, as the Deloitte, rightly point out (https://youtu.be/f1JA4_UFyns), the human touch cannot be replicated. Therefore, for hone Emotional agility, humans play a huge part.
Among the many subfields of AI, five stand out due to their profound influence and potential: Machine Learning (ML), Natural Language Processing (NLP), Computer Vision, Robotics, and Expert Systems. Amongst the 5 levels of AI the role of humans are still profound. For example, competencies such as transparency need to change to align with Political agility. Only then will people make confident decisions with recommendations that can be understood and trusted. Whereas Outcomes agility paves the way to get to a desired outcome as the outcome is influenced by AI, not outcome itself. As such, it is a hype to think that AI can change life exponentially as this gives too much hope or emphasis on a growing evolution. This could be because there is money behind this endeavor, which seems huge, which cater for very high opportunities for companies. Nevertheless, according to an IBM (https://lnkd.in/e7-AVjvu), “Surveyed CEOs say roughly one-third (31%) of the workforce will require retraining and/or reskilling over the next three years, while 65% say their organization will use automation to address skill gaps.” This calls for Education agility where one puts on the shoes of another to know the challenges of another.
In summary, the questions remains - Can AI accelerate or decelerate a person’s personal agility? AI can accelerate personal agility by enhancing learning, decision-making, and adaptation. AI can also serve as a powerful personal tool, offering tailored insights and automating routine tasks so we can focus on more complex, strategic thinking. On the other hand, while AI offers benefits, it is not a replacement for human judgment or connection. To use AI responsibly, ethical considerations needs to be put in place. For example:
- Data privacy: Use AI tools with strong data protection policies to safeguard your personal and sensitive information. (Political agility)
- Human oversight: Humans have to make critical decisions as AI can perpetuate biases present in its training data. (Emotional agility)
- Purposeful use: Avoid over-reliance on AI leveraging it as a supportive tool to enhance, rather than replace, genuine human interaction and self-reflection. (Education agility)
AI can decelerate personal agility in specific scenarios, despite its perceived ability to accelerate it. For example:
Time management: AI assistance in software development can sometimes increase the time required for tasks, as developers grapple with understanding the tool and integrating its output, leading to a perceived but not always actual productivity gain. Cerebral agility come in handy here.
Meaningful adaptation: AI-driven algorithms on social media can trap users in their own personalized feeds, fostering passive consumption and hindering their ability to adapt to new information, thus decelerating personal agility. Using Change agility in this scenario will pave the right path.
Enabling integration: AI's impact on agility is dependent on context. The integration and human interaction with AI are key. How effectively individuals learn to use and collaborate with AI tools can determine whether it supports or hinders their personal agility. Learning agility is key here.
In the end, personal agility is a human skill set, while AI is a technical creation. Keeping that in mind the Outcomes agility in the PALHTM model serve to better enhance every walk of life when tread with caution when it comes to AI and personal agility.
Related: Illuminating Pathways: A Journey in Leadership Towards the Personal Agility Lighthouse