During my teaching at the Asia Pacific ESSEC Master in Management on the vibrant Singapore campus, we delved into a pivotal discussion about the intersection of AI and sustainability. It was in this forum that we unpacked the necessity of demystifying technology to see AI for its true capabilities—nothing more, nothing less.

Consider the insights of Harvard Business School’s own Karim Lakhani, who eloquently states, “The human-like responses are a statistical illusion.” Lakhani peels back the veneer, revealing that what appears as sentient interaction is nothing but “a statistical or computational illusion,” a mimicry born from extensive digestion of our human texts and videos[1]. This resonates with my longstanding perspective: AI, when harnessed with finesse, is not a usurper of roles but a powerful ally to human capability[2].

Yet, we must tread with caution. The very advancement that promises augmentation can, if left unchecked, pose significant repercussions for the burgeoning minds of future generations. The task at hand is not to shy away from these tools of incredible potential but to engage with them intelligently, ensuring that we steer the helm of AI towards augmenting human potential, not diminishing it.

As the digital age accelerates, AI’s burgeoning role in business uncovers an urgent need for a radical reimagining of intern and junior training. The advent of Large Language Models (LLMs) offers a stark warning—let’s not render our juniors obsolete. Consider this: these LLMs, the sprightly interns of the virtual realm, are already commandeering tasks once reserved for human neophytes. They draft memos, spruce up presentations, and never clock out, all while consuming only the ‘token money’ of computing resources. They’re dazzling in their efficiency, but let’s be clear: they are no substitute for the human intellect’s seasoning—the logic, reasoning, and creativity that only humans can provide.

In the bustling ecosystem of corporate growth, where nurturing newbies is akin to fostering delicate saplings in a forest of towering oaks, the intern’s role is pivotal. They’re the sponge, absorbing not just the technical know-how but also the nuanced dance of corporate culture. It’s in these early career days that the bedrock of their professional journey is laid, shaping the trajectory of their growth.

Yet, this indispensable induction faces a threat from AI, which can effortlessly automate the errands and even the analytics once reserved for the wide-eyed interns. If LLMs, which mimic human dialogue with the ease of a Jane Austen protagonist, can manage what was once an intern’s proving ground, how do we adapt? Google and its ilk have pioneered training programs that attempt to bridge the gap, but the real transformation lies in morphing the initial career years into a live-fire exercise—an ‘execution classroom’ where learning is doing, and doing begets learning.

Herein lies the crux: the narrative of technology as a harbinger of doom for jobs is not entirely accurate. The fear that AI will supplant human roles is as overcooked as the notion that LLMs possess boundless wisdom. While it’s true they can generate responses that uncannily resemble human banter, the reality is they’re adept at stitching words together, nothing more. They’re not the sages of Silicon Valley; they’re the algorithmic illusionists, capable of making data dance but still falling short of human sapience.

This brings us to a dichotomy in our expectations. We impose on machines the lofty standards of Asimov’s first law of robotics—to cause no harm—while simultaneously forgiving the LLMs for their errors, enchanted by their conversational prowess. We scorn the rare slip-up of an autonomous vehicle but chuckle at the eccentricities of a chatbot’s flawed poetry.

So, what’s the call to action? As we integrate AI into our businesses, we must revisit the intern playbook. We must infuse our training with humanity, nurture patience, and offer a scaffolding of experiences that no algorithm could replicate. Our goal? To arm our interns with the skills to thrive alongside AI, ensuring that as the corporate ladder evolves, it remains a climb towards enlightenment, not a chute into irrelevance.

In conclusion, while I debunk AI myths in my lectures—clarifying that LLMs are sophisticated but not infallible and that AI is a tool for augmentation rather than replacement—I emphasize a deeper message. We must evolve our corporate education, not as a knee-jerk reaction to technology but as a strategic embrace of it, ensuring that our juniors become the resilient architects of tomorrow’s enterprise and not its casualties. Bots may take the coffee runs, but the boardroom seats? Let’s reserve those for the humans who’ve learned to dance with the machines.

References

[1] Lakhani, Karim. “AI Won’t Replace Humans — But Humans With AI Will Replace Humans Without AI.” Interview by Adi Ignatius. Harvard Business Review, August 4, 2023. https://hbr.org/2023/08/ai-wont-replace-humans-but-humans-with-ai-will-replace-humans-without-ai. 

[2] Dell’Acqua, Fabrizio and McFowland, Edward and Mollick, Ethan R. and Lifshitz-Assaf, Hila and Kellogg, Katherine and Rajendran, Saran and Krayer, Lisa and Candelon, François and Lakhani, Karim R., Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality (September 15, 2023). Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-013, Available at SSRN: https://ssrn.com/abstract=4573321 or http://dx.doi.org/10.2139/ssrn.4573321
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