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Generative AI will improve efficiencies and spark creativity in the workplace

The possibilities and capabilities of generative AI are yet to be fully understood — and as with anything, they will no doubt continue to evolve. 

Still, Fidelity VP for AI and ML Sarah Hoffman described “three levers” of the technology: It can support efficiency, creativity and learning. 

To the first point, “generative AI can definitely take efficiency to the next level,” Hoffman said in a fireside chat at today’s VentureBeat Transform 2023. 

For instance, in a large company like Fidelity, it can be difficult to share information, but gen AI can make collaboration much easier. Similarly, in terms of workflows, interfaces could envision text boxes instead of a “web page with lots and lots of tabs.”

Furthermore, the technology could create emails that financial advisors could send to clients, that humans could then edit to retain a semblance of human authority. “This is where creativity and efficiency come together,” said Hoffman. 

When it comes to brainstorming or any other creative task, Hoffman called generative AI “the perfect technology to use.”

In brainstorming, so-called hallucinations aren’t as much of an issue, she pointed out, because if something comes back that is untrue, it doesn’t go out into the world. An untrue or half-true statement could even spark creativity and help humans to come up with ideas that they may not have otherwise. 

For instance, Hoffman said, she was researching generative AI in healthcare, and asked ChatGPT what she could be missing. The chatbot came back with examples where generative AI could be used in mental health scenarios (something she hadn’t considered). 

“Any type of brainstorming you’re doing, it’s good to look at this technology,” she said.

There are two distinct camps when it comes to AI in the workplace: It will take over human jobs; or it will augment them. Hoffman is of the latter persuasion. 

“I love it for learning,” she said. “I use it maybe not every day, but almost every day.” 

The technology can be critical in industries like financial services where there can be a lot of complex jargon, she said, and also for corporate and personalized new-hire training. In those cases, the technology could be used to help understand a person’s existing skill set, then direct them to new learning areas. 

>>Follow all our VentureBeat Transform 2023 coverage<<

In the personal realm, she shared an anecdote about her mother, who recently had surgery. In analyzing the MRI results, Hoffman turned to ChatGPT and asked for explanations of medical terms and context for the findings. From there, she was able to go to the doctor and have a much better conversation.

“It’s a great way to gain info,” she said.

Also, with generative AI, “there’s no shame, there’s no judgment.” You can ask a system a question four times and four different ways if you don’t understand the answer fully (whereas doing so with a human might cause frustration or irritation). Or, we can ask AI to explain something to use as if we were a fourth grader.

Hoffman added that she dislikes the use of anthropomorphizing terms such as “hallucination” — when in the case of other software or technologies, such inaccuracies are referred to as “bugs.” 

“It’s not a bug, it’s a feature,” she said, emphasizing that it’s important to know not to trust generative AI completely. 

Hoffman, who is on the research team of the Fidelity Center for Applied Technology, emphasized the importance of having an internal AI and technology research team. She explores technology and socio-cultural trends looking roughly three to five years out, then uses those insights to make recommendations and predictions across the company. 

For instance, she began to grow excited about generative AI in 2021, she explained. Around that time, Fidelity hosted a company-wide no-code challenge to allow workers to tinker with the technology. 

“This was before everyone was talking about generative AI,” she said. 

As far as truly looking three to five years out, Hoffman joked that the way AI is accelerating, “we’re happy if we’re one year ahead.”

She predicted that gen AI and other technologies will be combined to help fill existing gaps in a way that will be “remarkable.” As of yet, it would be irresponsible to not run generative AI outputs by humans — particularly in healthcare or the financial industry — but there may be a day when some AI will no longer need human authority.

Still, she said, that’s a ways off, and “it’s really dependent on cases and how good the technology gets.”

Join top executives in San Francisco on July 11-12 and learn how business leaders are getting ahead of the generative AI revolution. Learn More


The possibilities and capabilities of generative AI are yet to be fully understood — and as with anything, they will no doubt continue to evolve. 

Still, Fidelity VP for AI and ML Sarah Hoffman described “three levers” of the technology: It can support efficiency, creativity and learning. 

To the first point, “generative AI can definitely take efficiency to the next level,” Hoffman said in a fireside chat at today’s VentureBeat Transform 2023. 

For instance, in a large company like Fidelity, it can be difficult to share information, but gen AI can make collaboration much easier. Similarly, in terms of workflows, interfaces could envision text boxes instead of a “web page with lots and lots of tabs.”

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Furthermore, the technology could create emails that financial advisors could send to clients, that humans could then edit to retain a semblance of human authority. “This is where creativity and efficiency come together,” said Hoffman. 

The perfect technology for creativity

When it comes to brainstorming or any other creative task, Hoffman called generative AI “the perfect technology to use.”

In brainstorming, so-called hallucinations aren’t as much of an issue, she pointed out, because if something comes back that is untrue, it doesn’t go out into the world. An untrue or half-true statement could even spark creativity and help humans to come up with ideas that they may not have otherwise. 

For instance, Hoffman said, she was researching generative AI in healthcare, and asked ChatGPT what she could be missing. The chatbot came back with examples where generative AI could be used in mental health scenarios (something she hadn’t considered). 

“Any type of brainstorming you’re doing, it’s good to look at this technology,” she said.

A critical learning tool

There are two distinct camps when it comes to AI in the workplace: It will take over human jobs; or it will augment them. Hoffman is of the latter persuasion. 

“I love it for learning,” she said. “I use it maybe not every day, but almost every day.” 

The technology can be critical in industries like financial services where there can be a lot of complex jargon, she said, and also for corporate and personalized new-hire training. In those cases, the technology could be used to help understand a person’s existing skill set, then direct them to new learning areas. 

>>Follow all our VentureBeat Transform 2023 coverage<<

In the personal realm, she shared an anecdote about her mother, who recently had surgery. In analyzing the MRI results, Hoffman turned to ChatGPT and asked for explanations of medical terms and context for the findings. From there, she was able to go to the doctor and have a much better conversation.

“It’s a great way to gain info,” she said.

Also, with generative AI, “there’s no shame, there’s no judgment.” You can ask a system a question four times and four different ways if you don’t understand the answer fully (whereas doing so with a human might cause frustration or irritation). Or, we can ask AI to explain something to use as if we were a fourth grader.

Hoffman added that she dislikes the use of anthropomorphizing terms such as “hallucination” — when in the case of other software or technologies, such inaccuracies are referred to as “bugs.” 

“It’s not a bug, it’s a feature,” she said, emphasizing that it’s important to know not to trust generative AI completely. 

Waves beyond generative AI

Hoffman, who is on the research team of the Fidelity Center for Applied Technology, emphasized the importance of having an internal AI and technology research team. She explores technology and socio-cultural trends looking roughly three to five years out, then uses those insights to make recommendations and predictions across the company. 

For instance, she began to grow excited about generative AI in 2021, she explained. Around that time, Fidelity hosted a company-wide no-code challenge to allow workers to tinker with the technology. 

“This was before everyone was talking about generative AI,” she said. 

As far as truly looking three to five years out, Hoffman joked that the way AI is accelerating, “we’re happy if we’re one year ahead.”

She predicted that gen AI and other technologies will be combined to help fill existing gaps in a way that will be “remarkable.” As of yet, it would be irresponsible to not run generative AI outputs by humans — particularly in healthcare or the financial industry — but there may be a day when some AI will no longer need human authority.

Still, she said, that’s a ways off, and “it’s really dependent on cases and how good the technology gets.”

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Author: Taryn Plumb
Source: Venturebeat

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