DefinedCrowd CEO Daniela Braga. (Dário Branco Photo)

Artificial intelligence is the fourth industrial revolution and women had better play a prominent role in its development, says Daniela Braga, CEO of Seattle startup DefinedCrowd.

“We left the code era to men over the last 30 years and look at where it got us,” Braga told attendees of the recent Women in Data Science global conference. “Ladies … let’s lead the world to a better future together.”

Technology has of course led to amazing advancements in health, communications, education and entertainment, but it has also created a more polarized and extremist society, spread dangerous misinformation and excluded swaths of the population from participation. A 2018 study by Element AI found that only 13% of U.S. AI researchers were women.

Braga thinks we can do better. She is a co-founder of DefinedCrowd, an AI training data technology platform that launched in December 2015. Braga took over as CEO in mid-2016. The company is ranked No. 21 on the GeekWire 200, our list of top Pacific Northwest tech startups, and has reeled in $63.6 million in venture capital, including a $50 million round raised last year.

We caught up with Braga after the conference to learn how AI is usurping coding; the need to impose ethics and regulations on where it takes us; and the need for more women in the industry and in AI leadership. Here are some key takeaways:

Data is king (or maybe queen)

We spent five centuries in the print era, 30 years in software and now AI is on a path to supplant software, Braga said. And while coding and programmers drove software development, it’s data and data scientists that produce AI.

“You don’t program rules, you teach AI with data that is structured and [there’s] a lot of it,” Braga said. The data “allows us to train a brain, an artificial brain, in a week instead of what it used to take us months to code.”

And it’s so much more powerful. Traditional coding, which is essentially built from “if then” decision making rules, isn’t capable of controlling complex tasks like self-driving cars or virtual assistants that require subtle assessments and decision making.

The cautionary tale of Tay

We’re still at the dawn of AI, Braga said, or what’s called narrow AI. In these early days, the field needs to be incorporating rules and standards to make sure that AI is used in ways that are ethical, unbiased and protect privacy. Oversight is needed at an international level that brings in a diversity of voices.

“We need an alliance, almost like a United Nations for AI,” she said.

The data used to train AI needs to be high quality, which for Braga means it’s accurate, representative or unbiased. It also should be monitored, anonymized so it can’t be traced to its sources, and people are consenting in providing their information. Braga admittedly has a vested interest in this matter, as her company’s business it to provide the data that companies use to train their AI. DefinedCrowd’s focus is speech and natural language processing.

In an infamous case of what can happen when AI is trained on bad data, Microsoft’s AI chatbot named Tay was quickly corrupted in 2016 when online users fed it racist, misogynistic language and conspiracy theories that the personal assistant parroted back to the public.

Where is AI headed

While we’re in narrow AI now, next steps are general AI and super AI, Braga said. As the technology matures, the different AI systems will be able to communicate with each other. Navigation, for example, will mix with voice interaction combined with text messaging. Home and work AI domains will talk together.

“There are some people who say when you start interlinking so many things you will have an AI that may become sentient,” Braga said, creating technology such as the personal assistant in the movie “Her” who is so lifelike and charming that the protagonist falls in love.

“The super AI is when AI is smarter, thinking faster, thinking better than humans,” Braga said. “So that is the part that is science fiction, where the machine will take over the world. We’re very far from that.”

Why women in AI

“Women bring emotional intelligence that technology should have,” Braga said. “It’s just that emotional intelligence component, that creativity, that warmth, that should resemble more a human — that aspect does not come through built by men alone.”

Data science is different from traditional software engineering. While the latter focused on programming languages, math and statistics, work in AI incorporates linguistics, psychology and ethics to a greater degree.

Wanted: Female AI execs

DefinedCrowd is trying to build a diverse workforce and has an office in Portugal, where Braga was born and raised. The company’s staff is about 32% female, but it’s difficult to recruit qualified women, particularly for senior roles. What’s even tougher, Braga said, is finding women at her level for mentoring and support.

There are a handful of founder/CEOs at AI-focused companies, including Daphne Koller of insitro and Rana el Kaliouby of Affectiva. And only 22 women who hold the title of founder/CEO have taken their companies public among thousands of IPOs over the decades, according to Business Insider.

“I always have a super hard time finding women to look up to because it just doesn’t exist. I’m basically paving my way by myself. I don’t have role models,” Braga said. “It’s really hard to not have a way to bounce ideas within a safe circle.”





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