Building trust starts with leaders asking the right questions about AI and how it can be used
Imagine sitting in a room with some of the greatest minds of our time – Alan Turing, Sheryl Sandberg, Steve Jobs and Elon Musk. These are the people who have shaped our digital world, pioneers whose work laid the foundation for the technology we use every day. Turing would delve into his insatiable curiosity about mathematics and cryptography, a curiosity that cracked codes and saved lives during World War II. Sandberg, the former chief operating officer of Meta, might share how her curiosity about leadership and social networks helped her steer one of the most influential companies of our era. Jobs might tell you how his curiosity led him to explore calligraphy, which ultimately influenced the beautiful fonts we use on our devices today. Musk, known for his curiosity about space, electric cars and sustainable energy, might discuss how his relentless pursuit of knowledge and innovation continues to push the boundaries of technology.
These leaders share a common thread: their relentless curiosity pushed them to explore, innovate, and ultimately, shape the world as we know it. But as we look to the future, it’s crucial to understand that the strategies and solutions that brought past successes might not be enough to navigate the challenges ahead, particularly in the rapidly evolving field of artificial intelligence (AI). Relying on past achievements can lead to a dangerous complacency – a status-quo mindset that stifles innovation and prevents organizations from adapting to new realities.
The perils of relying on past successes
In today’s fast-paced world, what worked yesterday may not work tomorrow. The business environment is constantly shifting, driven by technological advancements, changes in consumer behaviors, and global competition. Companies that cling to past successes risk falling into the trap of status-quo behaviors, which can kill innovation and leave them vulnerable to disruption.
Consider the case of Research In Motion (RIM), the company behind the once-iconic BlackBerry. At the height of its success, BlackBerry was the go-to smartphone for professionals, boasting unparalleled security and a physical keyboard that users loved. But as Apple introduced the iPhone with its innovative touchscreen and app ecosystem, RIM’s reliance on its past successes became its downfall. The company failed to adapt to the changing market, clinging to its keyboard design and business model. Apple’s relentless curiosity and willingness to explore new possibilities allowed it to dominate the smartphone market, while BlackBerry faded into irrelevance.
Similarly, in the fashion industry, traditional retailers long relied on seasonal trends and instinct to stock their shelves. Then companies like
Stitch Fix disrupted the model by using data science and algorithms to predict and personalize clothing selections for each customer. Stitch Fix’s success lies in its curiosity-driven approach, constantly refining its algorithms to better understand and meet customer needs. Retailers that failed to innovate have struggled to keep pace in a market increasingly driven by personalization and technology.
These examples highlight the danger of relying too heavily on what has worked in the past. Innovation requires a willingness to question the status quo, explore new ideas, and embrace uncertainty – qualities that are deeply rooted in curiosity. Curiosity drives innovation and fosters trust: it encourages continuous learning, transparency, and adaptability, ensuring that both employees and customers have confidence in the organization’s ability to navigate change and deliver reliable, forward-thinking solutions.
Unleashing curiosity
To build a culture of curiosity that embraces AI and drives future success, we must first understand what inhibits curiosity. Through my years of research, as detailed in the Curiosity Code Index (CCI) assessment and my most recent book, Curiosity Unleashed, I’ve identified four primary factors – fear, assumptions, technology, and environment – known as Fate.
These factors can significantly hinder curiosity and, by extension, the ability to innovate and effectively implement AI. Overcoming these inhibitors is key to fostering curiosity and building trust in AI.
Overcoming fear
Fear is one of the key factors that can inhibit curiosity. In the context of AI, fear often stems from uncertainty about the technology’s implications – fear of the unknown, fear of making mistakes, or fear of being replaced by machines. This fear can prevent leaders and teams from fully engaging with AI and exploring its possibilities.
Consider Netflix’s journey with its recommendation algorithm. Early on, there was significant apprehension about whether an AI could accurately predict what movies people wanted to watch. Would it replace human judgment? Could it alienate viewers? Instead of succumbing to these fears, Netflix leaned into curiosity. They experimented, tested and refined their algorithm, ultimately creating one of the most trusted and effective AI systems in the world. This approach not only alleviated fear, but also built consumer trust in the platform.
Leaders who foster a culture of curiosity create an environment where fear is not a barrier, but a motivator for exploration. They encourage their teams to ask questions, take risks and view failures as learning opportunities rather than setbacks. This mindset is essential for building trust in AI, as it allows organizations to continually refine and improve their AI systems in response to real-world challenges.
Challenging assumptions
Assumptions can be another major barrier to curiosity. When we assume that we already know the answers, we stop asking questions. This complacency can be particularly dangerous in the development and deployment of AI, where unchallenged assumptions can lead to misguided trust or overlooked flaws.
Amazon’s approach to its AI-driven recommendation engine exemplifies the power of challenging assumptions. Rather than assuming their initial algorithm was flawless, Amazon continually questioned its effectiveness. They regularly gathered data, tested new models, and refined their approach to ensure the AI remained accurate and reliable. By challenging assumptions, Amazon built an AI system that customers trust to deliver personalized, relevant recommendations.
In contrast, consider what might happen if assumptions go unchallenged. If a company assumes that its AI system is infallible, it might miss critical errors or biases embedded in the algorithm. These oversights can lead to a loss of trust among users and, ultimately, damage the company’s reputation. By fostering a culture of curiosity, organizations ensure that assumptions are regularly questioned and tested, leading to more robust and trustworthy AI systems.
Embracing technology
Technology – especially something as complex as AI – can be both a driver and an inhibitor of curiosity. The rapid pace of technological advancement can inspire exploration, but it can also be intimidating, causing some to shy away from fully engaging with the technology.
Of course, leaders who embrace curiosity don’t shy away from technology; they dive into it, seeking to understand its intricacies. Take Tesla. Elon Musk’s curiosity about AI and autonomous driving led him to push beyond the limits of existing technology, asking how it could be made better, safer and more reliable.
This relentless curiosity has not only advanced Tesla’s AI capabilities, but also built consumer trust in their self-driving cars. By embracing technology through curiosity, Tesla has established itself as a leader in innovation.
For organizations to build trust in AI, they must create a culture where curiosity about technology is encouraged. This involves providing opportunities for employees to learn about AI, experiment with new tools, and ask questions about how the technology works. When employees feel confident in their understanding of AI, they are more likely to trust the technology and advocate for its use within the organization.
Creating an environment that fosters curiosity
The environment in which we work plays a crucial role in either fostering or stifling curiosity. A supportive environment encourages questions, experimentation, and open dialogue – elements that are essential for building trust in AI.
Google’s ‘20% time’ policy is a prime example of fostering an environment of curiosity. By allowing employees to spend 20% of their time on projects that interest them, Google has cultivated a culture of innovation. This environment has led to some of Google’s most successful products, including Gmail and Google News. In the context of AI, such an environment encourages exploration, continuous learning, and the questioning of AI’s outputs, leading to more trusted and innovative systems.
A curious environment is one where employees feel safe to express their ideas, challenge assumptions, and explore new possibilities without fear of judgment. Leaders play a critical role in creating this environment by modeling curiosity in their actions – asking questions, seeking feedback, and being open to new ideas. When employees see their leaders embracing curiosity, they are more likely to do the same, creating a culture where trust in AI can flourish.
Overcoming distrust through curiosity
One of the most significant challenges in deploying AI is overcoming the distrust that many people feel towards the technology. This often stems from fears about AI’s potential to replace human jobs, make biased decisions, or operate in ways that are not transparent. However, curiosity can be the antidote.
By fostering a culture of curiosity, organizations can encourage employees and stakeholders to engage with AI in a meaningful way. This means asking critical questions about how AI systems are developed, how they make decisions, and how they impact people. For example, leaders might ask: How does this AI algorithm make its decisions? What data is it using, and how is that data selected and processed? What potential biases might be embedded within the AI system?
When these questions are asked openly and answered transparently, it helps to demystify AI and build trust. People are more likely to trust AI systems when they understand how they work and when they see that those systems are designed with fairness, ethics and transparency in mind.
Ultimately, curiosity plays a crucial role in how we interact with AI systems. The better our questions, the better the AI’s output, which in turn enhances our ability to trust the information it provides. The process of refining prompts through curiosity helps to ensure that the AI’s responses are aligned with our goals and ethical standards, which is a critical step in building trust.
A crucial capability
The future of AI depends not only on technological advancements but on the human capacity for curiosity. Just as Turing, Sandberg, Jobs, and Musk used curiosity to build the systems that shape our world, so we too must embrace curiosity to ensure that AI develops in ways that are both innovative and trustworthy.
Curiosity enables us to explore the unknown, challenge the status quo, and build systems that earn trust by being transparent, ethical, and effective. By fostering a culture of curiosity, organizations can confidently navigate the complexities of AI, ensuring that this powerful technology serves us all with integrity.
As AI continues to evolve, those who dare to ask, explore, and innovate will lead the way, building a future where trust and technology go hand in hand – just as the great minds of the past have shown us is possible.
Diane Hamilton is founder and chief executive of Tonerra, and a Duke CE educator
