Greenbook Future List Spotlight: Josh Seltzer

Editor’s Note: The following interview features a 2024 Greenbook Future List honoree, Josh Seltzer. The Greenbook Future List recognizes leadership, professional growth, personal integrity, passion, and excellence in the next generation of consumer insights and marketing professionals within the first 10 years of their careers.

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Josh Seltzer, CTO at Nexxt Intelligence, leads research in Language Models and NLP for market research solutions. His pioneering R&D work has elevated the company's status in the industry, driving innovation through strategic partnerships. Josh's mentorship cultivates a culture of continuous growth in market research.

Josh, driven by a passion for cognitive science and social dynamics, aims to shape sustainable futures. His expertise in AI and market research fuels his mission to advance technology ethically. Engaged in LLM research and conservation efforts, Josh co-authored publications on leveraging tech for ecological studies. Pioneering AI integration in market research, he introduced "conversations-as-a-service" via the inca SmartProbe API, democratizing AI for researchers. Educating the industry on AI ethics, Josh's initiatives have enhanced market research practices responsibly.

Outside of insights, what are your passions and interests?

In my last year of university I had the privilege of visiting the Tiputini Biodiversity Station in the Ecuadorean Amazon, where I was enamored by the richness and diversity of life among the seemingly magical trails and rivers of the rainforest. Around the same time I was learning about exciting new innovations in machine learning, and to my surprise I ended up writing my thesis on the use of computer vision for automatically identifying animal species in photos from “camera traps” (motion- and heat-sensing cameras mounted in various ecosystems with the goal of monitoring animal populations).

Since then, I have been drawn into the world of conservation tech (a disparate set of hardware, software, and AI solutions for monitoring and ultimately protecting wildlife and their ecosystems). Technology is far from a panacea, but I’ve seen how helpful these tools can be to support individuals and communities who act as stewards for their land. It’s also just incredibly fun: aside from using AI to monitor animals in diverse ways, I’ve had the joy of climbing trees, flying drones, and searching for monkeys in the dark. Conservation tech has grown immensely in the last few years, and I’m ecstatic to see the new opportunities and brilliant people who have dedicated themselves to understanding and protecting the beauty of life around us.

If you could go back in time to when you first started your career, what advice would you give to your younger self?

Just get involved! The tech world is large and can be overwhelming, but the best way to figure out what you truly enjoy and where you excel is by diving into various projects and communities. Participate in hackathons, engage with open source projects, attend tech meetups, and contribute to the growing plethora of open research initiatives, especially in burgeoning fields such as large language models (LLMs) and applied research. This exposure will not only sharpen your technical skills but also build a network of peers and mentors whose support and guidance can be invaluable. And don't forget the importance of soft skills; the ability to communicate and work with a team will probably get you even further in tech than it will elsewhere.

For those who find themselves drawn to the startup world or decide to found one, remember that it's a marathon, not a sprint. Popular media tends to glamorize the rapid success stories, but the reality is that they're the exception rather than the rule. Building a company is a long-term endeavor filled with highs and lows. When things go wrong—and they inevitably will—it's not the end of the world but a really valuable learning experience. Stay steady, keep your vision in focus, and take care of your health and relationships. These are the pillars that will sustain you through the long journey ahead.

What do you think the key characteristics or qualities of a leader are? How does this play into MRX?

Respect, responsibility, and resilience are three key characteristics that I believe are essential for any leader, and they are particularly relevant in the MRX industry.

Respect is foundational. As a leader, you must have a deep respect for the people you work with, the clients you serve, and the research participants who provide the data that is the lifeblood of our industry. This means listening actively, valuing diverse perspectives, and fostering an inclusive environment where everyone feels valued and heard. In MRX, where understanding human behaviour and perspectives is central, respect ensures that we approach our work with the empathy and patience necessary to gain true insight.

Responsibility is about being accountable for your decisions and their impact on your team, your clients, and the broader industry. In MRX, this means upholding the highest standards of data privacy and ethical research practices. It also means being transparent with clients and taking ownership of both successes and failures. As a leader, you set the tone for how your organization navigates the complex balance between commercial success and ethical considerations.

Resilience is crucial, and doubly so for a tech startup. There is constant evolution with new technologies and methodologies, and leaders must be able to adapt and guide their teams through change. There will inevitably be painful challenges and failures: this requires a willingness to learn from mistakes and to stay cool-headed. In MRX, resilience enables leaders to push the boundaries of what's possible in research, driving innovation while maintaining the integrity of the insights we deliver.

Where do you see the future of insights heading in the next 10 years?

Qualitative research at scale, driven by conversational AI.

While we’re already seeing an industry-wide embrace of AI-powered research tools, we’re still in the very early stages of a new era of insights which will give us qualitative insights at quantitative scale. The building blocks for this braided methodology are rapidly emerging: powerful multimodal models to analyze and generate images, videos, and text; peripheral tools such as recent advances in brain-computer interfaces (check out MinD-Vis!); and my own area of specialty, conversational AI, which leverages language as the single most expressive lens into human understanding. Perhaps AI will also help take us to the next frontier—modeling societal dynamics with the use of multi-agent systems—but only time will tell.

I’ve also got my eyes on the emergence of ‘synthetic data’. My take is that, if used appropriately it will surely richen our toolbox for understanding humans, but it’s not fundamentally that different from the traditional statistical outputs that we use: it is a distilled and probabilistic representation of human behavior with certain biases and limitations, and one which must be calibrated with real humans and applied with expert judgment. I don’t see it superseding the primacy of qualitative research as a means of understanding individuals, at least not in the next 10 years!