Have you ever wondered what drives us to innovate and take risks?
The saying “Curiosity killed the cat” warns of the dangers of unchecked curiosity, but in the realm of AI and personal growth, curiosity is a double-edged sword. Let’s explore how balancing curiosity with caution can lead to remarkable achievements and sustainable progress.
I could have failed. But I didn’t. Stepping into my first CEO role, I faced one of the most transformative periods of my life. With a mix of corporate wisdom and a startup mindset, I founded a cash flow-positive company, Lead a group of super talented people, representing with giants like Nintendo and LEGO. Navigating daily management challenges—from COVID-19 shutdowns to the fast-paced political climate of Israel—was no small feat. Yet, through it all, I made it!
After resigning, my journey was fueled by a relentless curiosity about AI. Despite sleepless nights and intensive learning about automation, I pursued knowledge out of genuine interest, not necessity. Rather than chasing quick profits, I created and trained AI workshops for free, supported different teams with content created using AI and my personal experience creating business plans and projects, focusing on deep learning and community engagement.
The AI SummerCamp, for instance, attracted tens of thousands of viewers without any positive financial transactions, proving the power of a dedicated and curious mind and two weeks of spare time 🙂
The path was fraught with challenges. On top of time and daily focus (100% of it) Overspending on AI-related subscriptions and tools—with some months getting up to $1,500—meant prioritizing education over immediate financial stability. This choice brought financial pressure and the constant juggle between passion-driven learning and fiscal prudence. Yet, the fulfillment and expertise I gained far outweighed the financial strains.
Just like testing new AI tools in your organization, sandbox some ideas, curiosity-driven exploration can lead to breakthroughs but also comes with risks. Just as my financial pressures impacted my family, AI systems can produce unintended, sometimes harmful outcomes. These issues can stem from security risks, biased training data, unforeseen system interactions, or misapplication in unanticipated contexts.
Many traditional businesses overlook ethical considerations in AI, seeing them as isolated IT issues or someone that other will set for them. Education system, government or the software company that sold them the service. However, we know employees often share confidential data with AI systems, inadvertently teaching them sensitive information. I’ve heard business owners dismiss AI’s impact, only to face internal security incidents that necessitated hiring a Chief Information Security Officer (CISO).
Ethical Frameworks and Continuous Monitoring
Business leaders must focus on ethical frameworks for AI, much like digital transformation, this should be part of the company values, tone, DNA. This is an ongoing process, not a one-time upgrade. Continuous monitoring is essential to detect and rectify unintended behaviors, mitigating risks and ensuring systems operate as intended.
Balancing Innovation and Caution
The balance between innovation and caution often shifts towards public discussion and regulatory scrutiny after significant crises.
In business history we saw examples of Kodak and IBM being extremely cautious with innovation
- Kodak developed the first digital camera in the 1970s but didn’t pursue it, fearing it would cannibalize its profitable film business. This strategic misstep led to Kodak’s bankruptcy in 2012 when digital photography became mainstream.
- IBM pioneered personal computers but lost its lead by focusing on mainframes, allowing competitors like Microsoft and Apple to dominate the market.
And we witness crises as a global community to later regulate innovation like;
“Curiosity killed the cat” is a reminder that while curiosity drives innovation, it must be balanced with caution to avoid unintended consequences. By adopting rigorous testing, ethical frameworks, and continuous monitoring, business leaders can harness AI’s benefits while minimizing risks, ensuring their innovations contribute positively to their companies.
- Nuclear Energy Post-World War II The devastating impact of nuclear weapons led to international treaties and regulatory frameworks promoting the peaceful use of nuclear technology.
- Disasters like the Bhopal gas tragedy and the Exxon Valdez oil spill prompted stricter environmental regulations and heightened public awareness of sustainable practices and corporate accountability.
- Financial Regulations Post-2008 Crisis: The crisis led to significant regulatory increasing transparency and reducing systemic risks.
As a high school dropout who believes in the transformative power of knowledge, I urge you not to wait for the next crisis. Embrace continuous learning and ethical innovation to drive success.
My free internal innovation sprint checklist / facilitator book for AI usage in business launching soon
DM me if you’re interested in joining this journey.