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Dr Seth Dobrin

Dr Seth Dobrin, CEO, Qantm AI

Describe your career to date

My career has been a journey through the evolving landscape of artificial intelligence (AI) and data science, marked by significant contributions across various sectors. I have consistently been at the forefront of technological innovation and ethical AI practices, from my pioneering work in agriculture at Monsanto to my transformative leadership in AI and data science initiatives at IBM and the visionary founding of Qantm AI.  

My multidisciplinary background, combining molecular and cellular biology expertise with extensive experience in diverse industries, has positioned me to influence the future of AI and technology.  

At Monsanto, I led a team that integrated data science into sustainable agriculture, revolutionizing farming practices with data-driven insights and precision agriculture. This period was characterized by groundbreaking advancements in agricultural technology and a strong emphasis on sustainability and stewardship.  

Moving to IBM, I became the company’s first-ever Global Chief AI Officer, playing a pivotal role in integrating AI development and governance across the organization. He was instrumental in aligning AI initiatives with ethical standards and business objectives, ensuring responsible and advanced AI technologies.  

Under my leadership, the IBM Data Science Elite Team was formed, rapidly growing and working on numerous AI, data science, and machine learning projects across various sectors. This team became a model for responsible AI development and diversity in the tech industry. I then founded Qantm AI where I have emphasized a human-focused approach to AI, tailoring solutions to meet each client’s unique needs and challenges.  

Throughout my career, I have been a vocal advocate against technological colonialism, recognizing the risks of deploying global AI technologies without considering different regions’ cultural and ethical contexts. My efforts ensure that AI development is sensitive to cultural diversity and does not impose a one-size-fits-all solution.  

Additionally, I champion diversity in tech, supporting organizations like Women Leaders in Data and AI (WLDA) and Wonder Women Tech, playing an instrumental role as a board member.  

What challenges do you see for data in the year ahead that will have an impact on you and on the industry as a whole?  

Integrating foundational AI models, such as GPT, Gemini, and more within the frameworks of complex regulations (GDPR, CCPA, EU AI Act) poses a significant challenge. This complexity is magnified by the ambiguity surrounding these regulations, demanding a nuanced approach to compliance.  

We are witnessing a pivotal moment where traditional data pipelines, architectures, infrastructures, and governance paradigms are being rethought. The rise of generative AI (genAI) necessitates new frameworks capable of supporting these technologies effectively. However, the industry’s prevailing technology-first approach, rather than a strategy-first methodology, introduces many challenges, underscoring the need for a strategic realignment.  

In this evolving landscape, data and model observability become increasingly critical. As we navigate the complexities of deploying AI in a compliant and ethical manner, the ability to monitor, understand, and manage the performance of AI models in real-time and act on these observations becomes indispensable. Observability allows us to ensure that AI systems operate as intended, maintain compliance with evolving regulations, and quickly address any issues. The path forward requires a concerted effort to balance technological innovation with strategic foresight.  

By championing data and model observability, we can not only navigate the regulatory complexities but also drive AI initiatives aligned with organizational goals, ensuring that our deployment of AI technologies is effective and compliant. This approach is essential for realizing the full potential of AI in a responsible and value-driven manner. 

How do you see data literacy developing across a) your network and b) the data industry generally? 

Putting this question in the context that you have no AI (genAI or otherwise) without data. Across my personal network, the rise of genAI is pushing for an advanced understanding of AI and genAI principles, their applications, and ethical considerations. Initiatives are focused on educating teams about genAI’s capabilities and ethical use, aiming to blend innovation with responsibility. This involves integrating genAI literacy into professional development, emphasizing the importance of ethical standards and the interpretability of AI insights. This has led to an entire offering for my business providing education for senior leaders on this topic.  

Across the data industry there is a recognition for broader data literacy encompassing genAI. This includes the technical skills to operate genAI tools and critical thinking to assess their outputs. There’s a push for education on AI ethics, bias recognition, and the transparency of AI models as crucial elements of data literacy. The objective is to prepare professionals to navigate genAI’s complexities, ensuring its responsible and effective use across various sectors. This focus on expanding data literacy to include genAI competencies reflects a commitment to harnessing the technology’s potential while navigating its challenges responsibly. 

How do you see the industry preparing for AI adoption and change management? 

Organizations engage firms like mine for guidance when at various stages of their AI journey. The process begins by evaluating the organization’s readiness for AI, a crucial first step that sets the foundation. Subsequent strategy discussions focus on essential queries: determining how the organization’s business strategy can be propelled by technology, including data and AI; identifying governance principles to uphold and the necessary policies and structures to support them; and assessing whether the organization possesses the requisite knowledge and skills for success in these initiatives. This holistic approach ensures that AI integration is aligned with strategic goals, governed by clear principles, and executed by a capable and informed team. 

Dr Seth Dobrin
Dr Seth Dobrin
has been included in:
  • 100 Influencers 2023 (USA)
  • 100 Influencers 2024 (USA)

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