Guardians of AI: Herman DeBoard Of Huvr On How AI Leaders Are Keeping AI Safe, Ethical, Responsible, and True
Why it matters: AI systems should be transparent so that users and developers understand how decisions are made. Transparency helps avoid the “black box” effect, where AI operates without a clear explanation, leading to skepticism and misuse.
As AI technology rapidly advances, ensuring its responsible development and deployment has become more critical than ever. How are today’s AI leaders addressing safety, fairness, and accountability in AI systems? What practices are they implementing to maintain transparency and align AI with human values? To address these questions, we had the pleasure of interviewing Herman DeBoard.
Herman C. DeBoard III is the CEO and Founder of Huvr Inc., a technology company with products that focus on video and fiber optics using AI and machine vision capabilities for both marketing and security purposes. As a speaker, author, and successful entrepreneur, Herman draws on his diverse experiences, including his decorated service in the United States Air Force, to inspire others to pursue success regardless of their current circumstances. His motivational life stories and innovative approach to business have earned him features in MarTech, Forbes, The Tech Tribune, Cynthia Corsetti’s Leadership Podcast, Marketscale, FoxLiveNOW, and more.
Thank you so much for your time! I know that you are a very busy person. Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?
I’d be happy to. My journey into AI and technology is rooted in my passion for entrepreneurship and solving real-world problems. I’ve been building and scaling businesses for over two decades, starting with nothing and learning along the way. My experience as a Gulf War veteran helped shape my resilience, adaptability, and leadership style, which I applied to every business I started.
After leaving the military, I focused on using my background in communication studies to launch companies that would use technology to improve lives and make businesses more efficient. The idea of using AI to solve complex business challenges became clear as I built Huvr and AURA — both of which use advanced technology to enhance operations, decision-making, and customer experiences.
Over the years, I’ve learned that success isn’t just about technology; it’s about creating solutions that genuinely improve people’s lives. This principle guided me as I ventured into AI, and it continues to drive my work today, ensuring that the products I help develop are ethical, innovative, and impactful.
None of us can achieve success without some help along the way. Is there a particular person who you are grateful for, who helped get you to where you are? Can you share a story?
There have been many people who played a pivotal role in shaping who I am today, and I’m deeply grateful for each of them. From an early age, I had the support of teachers like Debbie Brisker, who saw potential in me when no one else did, and coaches like Jimmy Whitby and Rick Handley, who recognized my competitive spirit and pushed me to be the best version of myself.
In the military, Chief Master Sergeant John J. Lemier was instrumental in setting me on the true leadership path. His guidance was invaluable in shaping my approach to leadership, discipline, and resilience. Later, at Marshall University, I had the privilege of studying under Dr. Robert Bookwalter, whose insights into the importance of communication — both in life and academia — taught me how crucial it is to understand people, connect with them, and communicate effectively.
Finally, I must mention Ray McElhaney, a business leader who mentored me in the early stages of my entrepreneurial journey. Ray taught me the ins and outs of building and selling businesses, providing me with the practical knowledge and insight I needed to launch and grow successful ventures.
Each of these individuals, along with countless others along the way, helped shape my path, and I wouldn’t be where I am today without their guidance and belief in me.
You are a successful business leader. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?
As a business leader, I’ve found that certain character traits have been absolutely crucial to my success. The three traits I believe have been most instrumental are resilience, adaptability, and integrity.
Resilience has been key in overcoming the inevitable challenges that come with building and scaling businesses. One story that comes to mind is the early days of Huvr. There were many obstacles — technical failures, financial setbacks, and moments when it felt like the company might not survive. It was my resilience and ability to get back up after each setback that pushed me to find solutions and keep moving forward. Each time we encountered a failure, we used it as an opportunity to learn and improve, ultimately leading to the success we enjoy today.
Adaptability has been just as essential. As an entrepreneur, you can’t rely solely on your original plan because the business world is constantly changing. One instance of this was when we first launched AURA. The market for AI technology was still emerging, and we had to quickly adapt to the needs of businesses that were unfamiliar with AI and hesitant to adopt new technologies. Rather than sticking rigidly to our initial concept, we listened to feedback, adjusted our approach, and tailored our offerings to solve the specific problems our clients faced. This flexibility helped us gain traction and build a strong foundation for the company.
Lastly, integrity has been the foundation of everything I’ve done. I’ve always believed that running a business with integrity is non-negotiable, especially when you’re building long-term relationships. A key moment for me was when I was negotiating deals early on in my career. There were many opportunities to take shortcuts or engage in practices that might have been profitable in the short term but compromised my values. Instead, I chose to prioritize honesty and transparency with partners, clients, and employees, even if it meant losing a deal. Over time, this earned me a reputation for trustworthiness, and it became one of the most valuable assets to my success in business.
Thank you for all that. Let’s now turn to the main focus of our discussion about how AI leaders are keeping AI safe and responsible. To begin, can you list three things that most excite you about the current state of the AI industry?
The current state of the AI industry is incredibly exciting for several reasons. First and foremost, I am excited by AI’s potential to tackle complex, real-world challenges in ways we could only imagine a few years ago. At AURA, we’re using AI to improve business efficiency, automate processes, and enable smarter decision-making. But beyond business, AI has the potential to solve global issues like climate change, healthcare access, and resource distribution, making it a tool for social good.
Second, I am amazed at the speed at which machine learning models are advancing. It’s astounding. With more refined algorithms, AI can now deliver hyper-personalized experiences that weren’t possible before. For example, AI is increasingly capable of predicting customer preferences and providing tailored solutions, which not only benefits businesses but also enhances the customer experience. I’m excited to be part of this evolution, as AI-driven personalization helps create more meaningful interactions between businesses and customers.
Another exciting aspect is the growing focus on ethical AI. As an AI leader, I’m thrilled to see more attention being paid to the responsible use of AI technologies. At AURA, we’re prioritizing transparency, fairness, and accountability in our AI systems. The industry’s collective effort to ensure that AI serves the greater good, not just business interests, is something I’m deeply passionate about. As AI continues to evolve, I’m excited to contribute to ensuring that it remains safe, ethical, and beneficial to society.
Conversely, can you tell us three things that most concern you about the industry? What must be done to alleviate those concerns?
While I’m incredibly excited about the future of AI, there are also several concerns that need to be addressed to ensure the industry evolves in a responsible and beneficial way.
One of the most concerning issues is the potential for AI systems to perpetuate bias and inequality. AI models are only as good as the data they’re trained on, and if that data is flawed or biased, the results can reinforce harmful stereotypes or unfair practices. To alleviate this, it’s crucial that AI developers, including us at AURA, take proactive steps to ensure diverse datasets and continuously audit AI systems for biases. Collaboration with ethicists, sociologists, and diverse communities can help ensure that AI is fair and representative.
Another issue is the “black box” nature of many AI models, where decisions made by the system are not fully understandable to humans. This lack of transparency can erode trust and make it difficult to hold AI systems accountable for their actions. To address this concern, the industry must prioritize developing AI models that are explainable and transparent. At AURA, we focus on creating AI systems that allow for clarity and interpretability so decision-makers can understand how conclusions are reached and ensure accountability.
Finally, with the rapid growth of AI, there’s also the risk of AI being used maliciously or irresponsibly — whether it’s for cyberattacks, deepfakes, or manipulating public opinion. AI systems can be vulnerable to exploitation, and ensuring their security is paramount. We need stronger regulations, ongoing testing, and enhanced cybersecurity measures to mitigate this risk.
At Huvr, we implement rigorous security protocols and ensure our AI systems are built with robust safeguards to prevent misuse. There also needs to be a broader industry-wide commitment to ethical AI development that incorporates security and responsibility into the design and deployment of AI systems.
As a CEO leading an AI-driven organization, how do you embed ethical principles into your company’s overall vision and long-term strategy? What specific executive-level decisions have you made to ensure your company stays ahead in developing safe, transparent, and responsible AI technologies?
As the CEO of AI-driven companies like Huvr and AURA, embedding ethical principles into our overall vision and strategy is a top priority. From the outset, I’ve made it clear that the responsible development of AI is not just a technical issue — it’s a moral one that impacts businesses, societies, and individuals. Our strategy reflects this commitment at every level, ensuring that ethical considerations are integrated into our decision-making processes.
- Clear Ethical Guidelines and Company Values
To ensure that ethics are at the heart of our work, we’ve established a set of core values that guide our AI development: transparency, fairness, accountability, and safety. These values are embedded into our organizational culture and inform everything from product development to employee training. By creating a foundation of ethical principles, we’ve made it clear to every team member — from engineers to leaders — that responsible AI development is non-negotiable. - Ethical Auditing and Continuous Evaluation
One of the specific executive-level decisions I made was to implement a regular internal and external ethical audit of our AI systems. We work with third-party experts to review our algorithms and data models for bias, fairness, and transparency. Additionally, our teams are trained to assess and mitigate the risks of AI misuse before products are deployed. This continuous evaluation process ensures that we stay ahead of emerging risks and maintain trust with our customers and stakeholders. - Investment in Explainable AI
Transparency and explainability are core to ethical AI. Early on, I made the decision to prioritize the development of explainable AI systems within both AURA and Huvr. By focusing on creating AI that can be understood and trusted by both end-users and decision-makers, we help prevent AI from becoming a “black box” where decisions are made without human comprehension. This has been crucial in maintaining accountability and ensuring that AI systems operate in ways that align with ethical standards. - Data Privacy and Security Commitment
Data privacy is another pillar of ethical AI. At Huvr and AURA, I’ve ensured that our AI technologies are built with stringent data privacy measures. We comply with global data protection regulations and are proactive in adopting best practices for data security. We’ve also implemented internal protocols for transparency in how data is collected, stored, and used to train our AI models. This commitment to security ensures that we protect users’ rights while enabling innovation. - Ethical Leadership and Long-Term Responsibility
Finally, I make it a priority to foster a leadership team that deeply understands the ethical dimensions of AI. Our leadership regularly engages with ethicists, legal experts, and community stakeholders to ensure our AI products align with the broader social good. We also allocate resources to R&D focused not just on performance but on ensuring the technology we create positively impacts society.
By embedding ethics into the very fabric of our strategy, we’ve created a company that doesn’t just build AI products for profit but for the greater good, always ensuring our technologies are transparent, safe, and responsible. Leading with this long-term vision is how we stay ahead of the curve in developing AI that serves humanity’s best interests.
Have you ever faced a challenging ethical dilemma related to AI development or deployment? How did you navigate the situation while balancing business goals and ethical responsibility?
Yes, as a leader of AURA, an AI-driven company, we’ve faced ethical dilemmas, particularly around the collection and use of sensitive data. One specific challenge revolved around AURA’s ability to use AI to “hear” and “see” things through sensors that gather real-time data to make decisions or trigger actions. This technology is incredibly powerful — it can detect sounds, read visual data, and sense other inputs that provide critical insights. However, the ability to capture this kind of sensory data comes with significant privacy concerns.
The challenge was balancing AURA’s business goals of innovation, efficiency, and client success with the ethical responsibility of protecting individual privacy. We recognized that while the technology could enhance operational effectiveness for businesses, there was the potential for misuse or violation of privacy if not carefully managed. We faced the ethical dilemma of whether to move forward with this technology or pause and reevaluate its ethical implications.
To navigate this, we took several proactive steps. First, we established strict privacy protocols. Every piece of data collected through the sensory AI technology, whether visual or auditory, is anonymized and processed in compliance with global data protection laws. We only collect data that is necessary for the intended purpose and make it clear to customers how the data will be used. Transparency became a core part of the process.
We also established an internal ethics committee to continuously monitor the use and deployment of sensory AI technologies. This committee, composed of legal experts, ethicists, and engineers, reviews each use case to ensure that we’re not infringing on people’s privacy or going beyond the intended use of the technology. The committee helps us strike a balance between pushing the boundaries of AI and ensuring that we are not compromising ethical responsibility.
Another important decision was to engage with customers, privacy advocates, and regulatory bodies. We openly communicated our concerns and sought feedback on how to improve our AI’s deployment. By working with these groups, we addressed concerns early, making adjustments to technology and policies before issues arose.
We also implemented a clear consent process for users of AURA’s technology. This process ensures that anyone who interacts with or is affected by the AI’s sensory capabilities understands how their data is being used and has the choice to opt in or opt out. In addition to transparency, this empowered individuals to take control of their own data.
Ultimately, we chose to proceed with the technology, but only after putting safeguards in place to protect privacy. We maintained the balance between pursuing business innovation and upholding our ethical responsibility. Our mission is to be a company that creates powerful AI solutions and does so with integrity.
Many people are worried about the potential for AI to harm humans. What must be done to ensure that AI stays safe?
AI has the potential to drastically improve many aspects of our lives, but it also raises safety concerns, especially when its capabilities are misunderstood or misused. To ensure that AI stays safe, several critical steps need to be taken at every level of development and deployment.
One of the most important factors in AI safety is ensuring transparency in how AI systems work. Developers must design AI systems that are explainable and understandable to both technical and non-technical stakeholders. At AURA, we prioritize creating models that can be interpreted and understood, allowing decision-makers to know precisely how and why an AI system is making a decision. This transparency ensures accountability, helping to prevent AI from being used in harmful ways and ensuring we can trace any issues back to their root cause.
Before any AI system is deployed, it must undergo extensive testing to identify potential risks and failures. At Huvr and AURA, we follow a strict testing process that includes simulations of extreme conditions and unintended consequences. We don’t just test the AI for performance but also for its ability to handle unexpected situations responsibly.
As AI leaders, it’s our responsibility to establish a dedicated ethics board or internal oversight team on every project. This group should assess ethical concerns, including biases, fairness, and the potential for AI systems to unintentionally harm individuals or communities. We must be proactive (not reactive) when addressing these concerns. At AURA, we engage regularly with external ethicists, stakeholders, and legal experts to ensure that we are fully aware of the societal impact of the technologies we build.
AI systems evolve as they learn. To ensure they remain safe, we also need continuous monitoring and frequent updates. This means setting up systems to continually audit AI performance, looking for biases, performance issues, and unintended outcomes. AURA and Huvr regularly review our systems and make updates to ensure they remain safe and aligned with ethical principles.
Ensuring AI safety requires collaboration across industries, governments, and academia. We need clear regulations and standards for AI safety and ethics. Participating in the global conversation about AI safety is key, and AURA actively participates in forums and groups dedicated to shaping the future of safe, responsible AI.
Lastly, AI safety involves educating the public and fostering understanding. Misunderstanding and fear often result from a lack of knowledge. By being transparent and educating both consumers and businesses, we can create an informed society that can help guide responsible use of the technology.
Despite huge advances, AIs still confidently hallucinate, giving incorrect answers. In addition, AIs will produce incorrect results if they are trained on untrue or biased information. What can be done to ensure that AI produces accurate and transparent results?
These are serious challenges that the industry must tackle head-on. The foundation of any AI system is the data it is trained on. To avoid hallucinations and biases, we must ensure that AI is trained on high-quality, diverse, and accurate data. This means prioritizing diverse datasets that reflect a wide range of perspectives and experiences and continually auditing the data for errors or biases. At AURA, we take extra precautions to ensure that the data we use is thoroughly vetted, validated, and free from harmful biases that could skew the results. The more representative and accurate the data, the less likely the AI will produce erroneous results.
Another key solution to ensuring accurate AI results is improving the explainability of AI models. When AI systems are built with transparency in mind, it becomes easier to understand why they produce specific results. This means not just having “black box” systems but designing models that allow users to trace how decisions or outputs were derived. At AURA, we focus on developing explainable AI, ensuring that our models provide not just results but also clear reasoning behind them. This allows users to better trust the AI’s decisions and identify areas where errors or biases may have crept in.
To combat hallucination and inaccuracy, AI systems must undergo extensive testing and auditing, not just before deployment but continuously throughout their life cycle. This includes simulated tests and real-world trials to identify any areas where the AI may go astray. We conduct regular audits of our systems to ensure that AI is performing as expected and consistently producing accurate, unbiased results. These audits involve reviewing the underlying data, algorithms, and output to ensure everything aligns with ethical and factual standards.
In addition, bias detection and mitigation are critical to ensuring that AI systems produce fair and accurate results. At Huvr and AURA, we’ve implemented advanced bias detection algorithms that flag any inconsistencies or biases in our models during the development phase. We also work with external experts to conduct independent audits of our systems to ensure they remain unbiased and ethical. By actively addressing biases in our training data and continuously monitoring model outputs, we can improve the reliability and fairness of AI-generated results.
Despite the advances in AI, humans still play a critical role in ensuring accuracy and transparency. Implementing a “human-in-the-loop” approach means that AI-generated results are reviewed by humans who can verify their accuracy and intervene if necessary. This is especially important in high-stakes applications where precision is essential. By incorporating human oversight, we can correct errors, reduce hallucinations, and ensure that AI systems operate within a framework of accountability.
And finally, AI systems must be capable of continuous learning and improvement. By establishing feedback loops where AI is constantly updated with new, verified information, we reduce the likelihood of hallucinations and errors. At AURA, we ensure that our AI models are capable of learning from real-world data and feedback, refining their outputs based on verified information to continuously improve accuracy over time.
Based on your experience and success, what are your “Five Things Needed to Keep AI Safe, Ethical, Responsible, and True”?
Based on my experience in leading AI-driven companies like AURA and Huvr, here are the five things I consider essential.
- Transparency in AI Systems
Early in our work with AURA, we developed an AI model designed to improve decision-making for businesses by analyzing vast amounts of data. However, we quickly realized that the more complex the model became, the harder it was to explain how decisions were made. This created concerns about trust, both internally and with our customers. To address this, we prioritized making our AI models explainable. We developed tools that provided clear, understandable insights into how the AI arrived at its conclusions. This transparency fostered trust among our clients and allowed us to proactively address any concerns about how data was being interpreted and used. - Why it matters: AI systems should be transparent so that users and developers understand how decisions are made. Transparency helps avoid the “black box” effect, where AI operates without a clear explanation, leading to skepticism and misuse.
- Bias Mitigation in Data and Algorithms
In one of our early projects, we trained an AI model to analyze customer data and make recommendations. During testing, we discovered that the model disproportionately favored certain demographic groups over others, reflecting biases in the training data. This was a critical moment for us at AURA. We immediately paused the deployment, audited the data, and worked with external experts to adjust the training process to ensure fairness. By diversifying the data sources and employing specific bias detection algorithms, we were able to correct the model and build a more ethical and inclusive AI system. - Why it matters: AI systems are only as good as the data they’re trained on. If the data is biased, the results will be biased as well. Continuous monitoring and efforts to mitigate bias are crucial to ensuring AI behaves fairly and ethically.
- Accountability and Ethical Oversight
One of the toughest decisions we faced at Huvr was implementing AI-driven surveillance for security purposes. We understood that while AI could enhance security, it also raised significant privacy concerns. To navigate this, we created an internal ethics board consisting of legal experts, ethicists, and privacy advocates to review the implications of deploying our AI systems in sensitive areas. This board evaluated the ethical ramifications, provided feedback, and ensured we were not violating privacy or misusing data. As a result, we implemented strict data privacy policies and transparency guidelines for how our AI systems were used. - Why it matters: Accountability ensures that AI development is aligned with ethical principles and that any mistakes or issues can be addressed. An external or internal ethics board can play a critical role in overseeing AI deployments and ensuring that AI systems remain accountable for their actions.
- Security and Safeguards Against Misuse
With the growing use of AI, we knew that security was paramount, especially in areas like data privacy and AI misuse. At AURA, we implemented advanced security measures, including encryption and multi-factor authentication, to protect data used in AI systems. We also conducted regular vulnerability assessments and partnered with cybersecurity experts to ensure our systems were robust and protected from malicious actors. This commitment to security not only protected our clients but also ensured that our AI systems could not be hijacked for unethical purposes, such as deepfakes or cyberattacks.
Why it matters: AI systems can be vulnerable to cyberattacks, manipulation, and misuse. Strong security protocols are necessary to prevent unauthorized access and misuse, ensuring that AI remains a positive and safe technology for all.
- Continuous Monitoring and Feedback Loops
The deployment of AI doesn’t stop once it’s out the door. At Huvr, we established continuous monitoring processes to track the performance of our AI systems and ensure they were working as intended. This included setting up a feedback loop where clients could report issues or concerns with the AI’s behavior, allowing us to make adjustments in real time. For instance, when we deployed AI-based customer service bots, we continuously monitored their interactions and gathered user feedback to fine-tune responses. This proactive approach allowed us to catch issues before they became larger problems and kept our AI systems aligned with customer needs and ethical standards. - Why it matters: AI models need continuous monitoring and updating. The world evolves, and so should AI. Regular audits, feedback loops, and continuous improvement ensure AI remains relevant, accurate, and ethical in dynamic environments.
Looking ahead, what changes do you hope to see in industry-wide AI governance over the next decade?
One of the most significant shifts I hope to see is the development and widespread adoption of global standards for ethical AI. Right now, there’s a patchwork of regulations across different regions, and many countries are still working to catch up with the rapid pace of AI innovation. In the next decade, I believe we’ll see more harmonized international standards that govern AI’s ethical implications. These standards should address issues like transparency, fairness, accountability, and privacy, creating a more unified approach to responsible AI across the globe.
Next, I envision a future where industries and companies implement AI ethics boards and oversight committees as standard practice, not just as an afterthought. These boards should consist of diverse stakeholders, including ethicists, legal experts, sociologists, and technologists, to ensure AI is developed with a broad understanding of its impact on society. I believe these committees will become more deeply integrated into AI development, providing a layer of checks and balances to guide businesses in making responsible decisions when deploying AI systems.
Third, I hope to see a significant shift toward more inclusive representation in AI development teams over the next decade. Currently, the development of AI systems often lacks diverse representation, which can lead to biased systems and solutions that don’t fully serve all people. This includes not just gender and racial diversity but also a broader range of perspectives from different industries, backgrounds, and life experiences. A more diverse team will be better equipped to create AI systems that are more universally applicable and fair.
Fourth, I would like to see stronger privacy and data protection laws globally, particularly regarding the use of AI in data analytics and decision-making processes. These laws should not only ensure that data is handled responsibly but also give individuals greater control over their own personal data. Companies like AURA that use AI will need to be even more transparent in how they collect, store, and use data, ensuring that AI systems respect personal privacy while still providing value.
Lastly, I hope to see a major push for increased public education and engagement around AI because there’s still a significant knowledge gap about what AI is, how it works, and its potential impacts. Over the next decade, I believe we’ll see greater efforts to educate the public about AI’s benefits and risks, making it more accessible to everyone. This will help individuals understand the implications of AI in their daily lives and contribute to a more informed and empowered society. Additionally, this will foster greater collaboration between businesses, governments, and citizens in shaping AI governance.
What do you think will be the biggest challenge for AI over the next decade, and how should the industry prepare?
The biggest challenge for AI over the next decade will likely be balancing the pace of technological advancement with the need for responsible and ethical oversight. As AI continues to evolve rapidly, there’s a growing risk that its deployment could outpace the development of regulatory frameworks, ethical guidelines, and safety protocols. This gap could lead to unintended consequences, such as exacerbating social inequalities, violating privacy, or even causing harm through the misuse of AI systems.
One of the most pressing needs is the creation of strong, adaptive regulatory frameworks that evolve alongside AI technology. Governments, industry leaders, and academic experts must collaborate to establish clear, globally consistent regulations that address AI’s ethical, legal, and social implications. These frameworks should focus not only on protecting privacy and data but also on ensuring AI is used responsibly and safely in diverse contexts, from healthcare to autonomous vehicles.
As AI systems become more integrated into everyday life, it’s also crucial that the industry regularly assesses the societal impacts of its technologies. Companies need to implement continuous ethical audits, ensuring that AI models are free from bias, promote fairness, and are transparent in how they make decisions. At AURA, we’ve already implemented ongoing reviews of our AI systems, and this will be even more important in the coming decade to ensure we stay aligned with ethical principles and societal needs.
The next decade will require AI to be more human-centric, designed to complement and enhance human capabilities rather than replace them. This involves ensuring that AI systems are built with empathy, fairness, and accessibility at their core. AI developers must prioritize understanding the human context in which their systems operate — whether it’s a recommendation engine, medical diagnostic tool, or autonomous vehicle — and create AI that benefits all individuals, not just those with access to advanced technologies.
The increasing complexity of AI models, particularly deep learning systems, presents another challenge — ensuring these systems are explainable and transparent. Many AI systems, especially those used in critical applications like healthcare, criminal justice, or finance, operate as “black boxes,” where users cannot easily understand how decisions are made. The industry must prioritize building AI systems that are not only accurate but also interpretable, allowing both users and regulators to trust and understand how and why decisions are being made. This transparency is key to avoiding mistakes and maintaining accountability.
Lastly, as AI continues to shape more aspects of daily life, public education will be essential in fostering a more informed and engaged society. The average person must understand how AI works, what data it uses, and its potential implications. By empowering the public with knowledge, we can ensure that AI is used ethically and responsibly and that individuals have the tools to question and challenge its applications when necessary.
You are a person of great influence. If you could inspire a movement that would bring the most good to the most people, what would that be? You never know what your idea can trigger. 🙂
If I could inspire a movement, it would be one that empowers people to reconnect with their true selves, independent of the identities that brands, trends, or external forces try to impose on them. In a world where consumerism and marketing are deeply embedded in our daily lives, many people unknowingly tie their sense of self-worth and identity to external labels, whether it’s the latest tech gadget, fashion brand, or even social media trends. This movement would help people understand that their identity should not be defined by brands or societal expectations but by their authentic values, beliefs, and actions.
The movement would focus on cultivating self-awareness, helping individuals understand who they truly are, what they stand for, and how they can express themselves confidently in a way that resonates with their true essence. This involves practicing emotional and verbal intelligence, enabling people to communicate with others in a way that’s rooted in authenticity. The ability to articulate one’s true self is powerful and can foster meaningful, genuine connections in both personal and professional relationships.
By empowering people to express their authentic selves, we break free from the influence of external pressures and become leaders of our own lives. The more individuals who embrace their unique identities, the more we can collectively shift away from superficial labels and instead build a society based on genuine human connection.
Imagine a world where we stop measuring success by the brands we wear, the cars we drive, or the labels we follow. Instead, success is measured by how well we communicate who we truly are, how much we embrace our individuality, and how much we contribute to making the world a better place. That’s the kind of movement I’d like to inspire: one that brings people back to their authentic selves and allows them to shine through their true identity, not one created by external forces.
How can our readers follow your work online?
I am on social media.
- LinkedIn — https://www.linkedin.com/in/hermandeboard/
- Instagram — https://www.instagram.com/hermandeboard/
- X — @hermandeboard
Or my personal website at hermandeboard.com
Thank you so much for joining us. This was very inspirational.
Guardians of AI: Herman DeBoard Of Huvr On How AI Leaders Are Keeping AI Safe, Ethical… was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.