Ahead of Dreamforce 2024, taking place Sept. 17-19, five event speakers and leaders of the artificial intelligence industry share their thoughts on the most important priorities for the near future.

Edward Norton, Co-Founder and Chief Strategy Officer of Zeck

From a high level, we need something akin to the medical Hippocratic oath, which governs doctors to do no harm. It’s for others to decide whether that’s regulation or something else, but we need a framing commitment. 

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I often come at things from a narrative place, and I’ve always been struck by writer Isaac Asimov’s Robot series, in which he weaves meditations around how societal principles and protections are included in the laws of robotics on an almost engineered basis. Similarly, we need someone to assert a foundational principle for all of us that AI shouldn’t do harm.

On balance, at the phase we’re in right now, I see far more benefits than any actual realized negatives. I think what’s going on in medicine alone should give people a lot of enthusiasm for the positive potential in AI. That’s the field in which I’ve seen things I think are truly astonishing, and are going to lead to real revolutions in human health and quality of life for a lot of people. 

Even just AI in radiology: the capacity of AI and machine learning to just do a much, much better job than human interpretation of cancer screening. And instead of turning to treatments that have low efficacy because we’re throwing a dart at the wall, we’re starting to see the capacity of AI to create bespoke, curated, data-driven conclusions about what will benefit an individual person vs. a population. 

The diagnostic potential in AI, or the interface between diagnosis and treatments that will have efficacy, combined with genetics—it just really starts to get into a world that, to me, is really positive.

But we need an ethical baseplate to do no harm. How that gets actually structured and expressed, both on an engineered, technological level and a societal, governing level, is going to be one of the really big questions and challenges of the next few decades.

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Jack Hidary, CEO of Sandbox AQ

For the past 20 months, generative AI and large language models (LLMs) have dominated the mindshare of leaders and driven countless innovations. However, C-suite execs and AI experts need to start looking beyond the capabilities—and limitations—of LLMs and explore the larger, more profound impact that large quantitative models (LQMs) will have on their organization and industry.

While LLMs are centered on our digital world—creating ­content or deriving insights from textual or visual data—LQMs drive impact on the physical world and the financial-­services sector. LQMs leverage physics-based first principles to generate new products in sectors such as biopharma, chemicals, energy, automotive, and aerospace. They can also analyze large volumes of complex numerical data to optimize investment portfolios and manage risk exposure for financial companies. 

With LQMs, breakthroughs that were seemingly impossible 24 months ago are now bearing fruit, transforming industries and pushing the boundaries of what is possible with AI. 

Enterprises are realizing they need to implement LQMs and LLMs in order to extract maximum benefits. If CEOs focus solely on LLM-powered AI solutions for customer service, marketing, document creation, digital assistants, etc., they will likely fall behind competitors who are leveraging LQMs to transform processes, create innovative new products, or solve computationally complex problems.

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Cristóbal Valenzuela, Co-Founder and CEO of Runway

Over the course of the next year, our industry needs to reset the way we talk about AI to both manage expectations of what progress looks like and bring bright, creative minds with us along the way. 

This will require a collective effort to communicate our vision clearly and maintain transparency around our advancements, and it will be important to do this in a way that does not create fears or make these products out to be more than just that—products.

At Runway, we’re building significantly more advanced, accessible, and intuitive technologies and tools for our millions of creative users around the world. Our successes and future growth are driven by the strong community we’ve built through our work with artists and creatives—understanding their needs and how they approach their crafts will always be the priority.

You can see this manifested through initiatives like our annual AI Film Festival, our Gen:48 short-film competition, and our new Research and Art (RNA) community Q&A sessions.

These have all provided a platform for artists, which in turn has driven our growth and mission of empowering these artists.

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Sasha Luccioni, AI and climate lead of Hugging Face

I think that we should be focusing on transparency and accountability, and communicating AI’s impacts on the planet, so that both customers and members of the community can make more informed choices. 

We don’t really have good ways of measuring the sustainability or the labor impact of AI. And what would be useful is to develop new ways of reflecting on how switching from one type of AI tool or approach to another changes the environmental impact.

For example, Google switched from good old-fashioned AI to generative AI summaries for web search. I think that’s where customers really want more information. They want to know: What do these AI summaries represent in terms of societal and planetary impacts? In my research, we found that switching from extractive AI to generative AI actually comes with 10 to 20 times more energy usage for the same request. 

We can’t opt out of new technology—and yet we don’t know how many more computers are needed; how much more energy or water is needed; how many more data centers they have to build in order for people to be able to get these AI summaries that they didn’t really ask for in the first place.

That’s where the transparency is missing because for a lot of people, they are mindful of the climate. And so I think that companies have a responsibility to their customers to say, “This is how much more energy you’re using.”

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Robert Wolfe, Co-founder of Zeck

AI has the potential to transform efficiency: it gives us the opportunity to both save people time and help create audience-specific content.

I am seeing it firsthand across several companies that I’ve been lucky to work with. For example, think about a GoFundMe campaign. If AI can help you generate your narrative in a way that makes your audience more passionate about your cause, that could be monumental for someone raising money for their neighbor. 

The No. 1 angst amongst our customers at Zeck is creating infographics, charts, and graphs. Such a pain. There is not a single person in the world who likes creating charts and graphs. But Zeck AI looks at your table or data and suggests, “This may look good as a pie chart,” and creates that pie chart for you. You can choose to accept it, iterate on it, or decline it. And Zeck AI will come up with red flags as you build your narrative that you wouldn’t have thought of. Just imagine the time savings for someone who typically spends hours upon hours building everything from scratch. Now it takes minutes. Mindblowing.

I am certainly not saying that AI should replace people, but AI will definitely make everyone more efficient.